A GENERIC HANDOVER DECISION MANAGEMENT FRAMEWORK FOR NEXT GENERATION NETWORKS

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "A GENERIC HANDOVER DECISION MANAGEMENT FRAMEWORK FOR NEXT GENERATION NETWORKS"

Transcription

1 A GENERIC HANDOVER DECISION MANAGEMENT FRAMEWORK FOR NEXT GENERATION NETWORKS Shanthy Menezes 1 and S. Venkatesan 2 1 Department of Computer Scence, Unversty of Texas at Dallas, Rchardson, TX, USA 1 2 ABSTRACT Next generaton networks are defned to be packet based networks that provde telecommuncaton servces to users by utlzng dfferent transport technologes, wred and wreless. In ths paper we provde a generc framework for handover decson management n next generaton networks. We show that any handover decson algorthm can utlze our framework. We show the feasblty of applyng our framework through an mplementaton example. One of the man features of NGNs s applcaton adaptablty; the applcatons desgned for NGN systems have to be adaptable to dfferent networks and dfferent devces. We propose a handover decson algorthm that utlzes our generc framework and selects the network for handover such that the qualty of experence of the user s near optmal. Through smulatons we show that our algorthm reduces unnecessary handovers and also satsfes the handover requrements. KEYWORDS Next Generaton Network, Wreless Network, Moblty, Handover Decson 1. INTRODUCTION Next generaton networks (NGNs) are expected to support a varety of the exstng wred/wreless access network technologes as well as new wreless access technologes to support hgh data rates up to 1Gbps. The network envronment envsoned for NGN s made up of the varous wred and wreless access networks connected to a common NGN core network. Fgure 1 shows a typcal settng of a NGN. Snce the evoluton towards NGNs s drven by the ever ncreasng moble subscrber base and the set of moble applcatons, moblty management (MM) s an essental requrement for NGN users. Hence the Telecommuncaton Standardzaton Sector (ITU-T) has descrbed ffteen general moblty management requrements for NGNs [1]. One of the requrements s to support polcy-based and dynamc network selecton. Network selecton s the process of choosng the access network to connect to. The network selecton process s done ntally at the tme of startng a servce (applcaton) that requres network connecton and durng handover of the servce to a new network. Durng handover, the selecton process s known as the handover decson process; that s, decdng whether to dsconnect from the current network and decdng whch network to handover to. Durng handover n NGN, the moble devce has the opton of handng over to the access network whch s of the same rado access technology (RAT) as ts current network (horzontal handover) or to an access network of a dfferent RAT (vertcal handover). Tradtonally a handover s performed when the current network does not meet the requrements of the moble devce. In the case of NGNs the handover process poses a varety of challenges due to the dfferent set of applcatons used, networks avalable, qualty of servce (QoS) avalable, and devces used. In ths envronment handover can be performed not only because the current DOI : /cnc

2 network does not meet the requrements, but also due to the avalablty of a better network or devce. Servces and applcatons Cellular 2.5G New RAT NGN Core Wred xdsl WMax Cellular 3G Cellular 4G WLAN BlueTooth Fgure 1. Archtecture of Next Generaton Networks The requrements of horzontal handovers were prmarly confned to the rado lnk requrements such as rado sgnal strength and bt error rate of the channel. In the NGN scenaro, the varety of access networks avalable dffer n QoS provson, securty schemes offered, cost of servce etc. The capabltes of the moble devces also vary n many aspects such as power consumpton, applcaton support and so forth. The key goal for NGNs s to enhance the user experence. Ths requres the provson of the most sutable rado access network for any gven user. Thus the handover decson has to be managed such that the requrements of the user are satsfed optmally. In ths paper we propose a generc framework for handover decson management whch has an extensve lst of requrements for handover that optmze the moble user experence. We elaborate on actual mplementaton of our framework by utlzng the IEEE meda ndependent handover standard. In NGNs, n order to be able to offer servces anywhere and anytme the servces and applcatons have to be desgned such that they are adaptable to the multtude of access networks avalable. We propose a handover decson algorthm that takes nto consderaton the needs of adaptable applcatons and also provdes flexblty n specfyng the user and network requrements. Through smulatons we show that our algorthm satsfes user requrements and also reduces unnecessary handovers. The rest of the paper s organzed as follows. Secton 2 dscusses related work n the area of handover decson algorthms and framework sutable for NGNs. In secton3 we present our generc framework for handover decson management. In secton 4 we show how our framework can be used to represent any exstng or future handover decson algorthm through three examples consstng of a decson algorthm for horzontal handover and two of the most cted decson algorthms for vertcal handover. Secton 5 presents our proposed generc handover decson algorthm. In secton 6 we present an example mplementaton of our generc framework and handover decson algorthm. Secton 7 provdes the smulaton detals and analyzes the smulaton results. Fnally secton 8 provdes the summary of the paper. 52

3 2. RELATED WORK Varous solutons [2,3,5,7,8,9,12,13,14,15] for handover management n heterogeneous network envronment have been proposed n the lterature. Several solutons [2, 3, 14, 15] utlze the servces provded by the IEEE standard [4] to facltate a handover decson. The framework can provde the parameters requred for a handover decson; an actual handover decson management module s not specfed n the standard. Cacace and Vollero [2] provde a detaled moblty management framework that uses the standard to provde servces to the applcatons to adapt to the new networks avalable. Ther soluton provdes nput to the moble IPv6 protocol to mplement a handover wthout any packet loss. The moblty management frameworks provded n [2,3,5] do not address the handover decson that decdes the lnk layer handover. Yungkyu and Cho [6] provde solutons for handover between and networks that maxmze the energy usage and mnmze the cost requred. These solutons are not unversally applcable snce not all the obectves for heterogeneous handovers are consdered. A varety of approaches [7,8,9] based on the theory of mult-attrbute decson makng (MADM) are generc n nature. We elaborate on these algorthms n secton.4 and also compare them to our handover decson algorthm usng smulatons. An extensve framework for handover decson management s not provded n these solutons [7,8,9]. Any of the exstng handover decson algorthms can be represented by our proposed framework. In secton 4 we gve examples of a horzontal handover decson algorthm and the two most cted vertcal handover decson algorthms [7,9], and demonstrate how any handover decson algorthm can be represented usng our generc framework. Due to the vast number of choces for access networks, a large dscrepancy between the values offered by dfferent networks s a defnte possblty. The handover decson algorthm presented here addresses ths ssue wth the ad of the framework provded. Our algorthm also prevents unnecessary handovers, unlke the other generc vertcal handover algorthms. 3. HANDOVER DECISION MANAGEMENT FRAMEWORK We present a handover decson management framework as shown n Fgure 2. Any handover decson algorthm, whether for horzontal handover or vertcal can be bult upon our generc management framework. The vtal part of our framework s a handover decson algorthm. The other parts of the framework are elements that affect the handover decson, used as nputs by the handover decson algorthm. The most nfluental of these nputs are the Parameters. Parameter values are nfluenced by the handover decson, namely the access network chosen. The parameters portray the obectves set by varous enttes that get affected by handover. The enttes specfy the requrements for the parameters n terms of weghts and thresholds. The weghts specfy the mportance of the parameters to the entty. The thresholds specfy the condtons to be met for the parameters. The exstng handover decson algorthms only consder one type of threshold that affects the handover decson, whch we term mandatory threshold. In order to consder the adaptve nature of the servces offered by NGNs, we consder another threshold for each parameter called the preferred threshold. The other feature of the framework s the values offered by the varous networks for each of the parameters specfed. The bass of any handover decson algorthm s a comparson of these offered values to the parameter requrements. Also as part of the framework, are the parameters used by handover decson algorthms to avod unnecessary handovers. In the next secton we show that our framework can be used by any exstng handover decson algorthm and we llustrate the utlty through examples. If, due to future enhancements or restrctons to the NGNs the handover decson module requres nputs not represented by our framework, our framework can be expanded to nclude these nputs termed as future nputs. 53

4 Fgure 2. Handover Decson Management Framework Our framework can be represented n vector form as follows: 3.1. Enttes The enttes that provde the parameters are denoted by the vector <E 1,,E M > Parameter Requrements The parameters are denoted by <O 1,O 2,,O P >. Parameter requrements are gven n terms of weghts and thresholds. Weghts: The weghts specfy the prortes gven to each parameter. The hgher the weght of the parameter, the larger s ts nfluence n the handover decson. Each entty provdes weghts for ts own parameters by prortzng them, these weghts are called local weghts. The handover decson algorthm can prortze the enttes by provdng weghts to the enttes. The global weghts used by the algorthms are the products of the local weghts and the weghts of the respectve enttes. For example let <W 1,,W m > be the local weghts of the m parameters set by entty and <W 1,,W n > be the local weghts of the n parameters set by entty. If the weghts of and are W and W respectvely, then the global weghts are <W 1 *W,,W m *W,W 1 *W,,W n *W >. We denote the global weghts of the parameter as W = < W 1,W 2,,W P > Thresholds: In most of the handover decson algorthms n lterature [7,8,9], the threshold values of the parameters are only consdered n elmnatng networks durng the decson process. That s, f the network s offered value for a parameter does not meet a threshold, then t s not consdered for handover. Snce some of the requrements such as user requrements and servce requrements are adaptable, a sngle threshold s not applcable n the case of handover n NGN networks. We propose the use of two types of threshold values: 1. Mandatory Thresholds: For a network to be elgble for selecton, the network s offered value for a partcular parameter should satsfy these thresholds. The mandatory thresholds are represented by the vector µ=<µ 1,µ 2,,µ P >. These values could be lower sded, upper sded or exact dependng on whether the value of the parameter should be,, or equal to the threshold. 54

5 2. Preferred Thresholds: The preferred thresholds represent the values desred by users and servces for ther best performance. The preferred thresholds are ether lower sded or upper sded. These may not be specfed for all parameters. These are represented as vector π=<π 1, π 2,,π P > 3.3 Parameter Values The values offered for each of the parameters by the access networks specfes the contrbuton of the network for each of these parameters. The values offered by an access network s denoted as the vector R = <R 1,R 2,,R P >. From the parameter values offered by the networks, we form two sets of vectors: (1) hghest offered value H = <H 1,H 2,,H P > denotng the best offered value, and (2) lowest offered value L = <L 1,L 2,,L P > denotng the worst offered. If parameter O has a lower sded threshold, then H = max R and L = mn R. If O has an upper sded threshold then H = mn R and L = max R, otherwse H = L = R. 3.4 System Parameters for Unnecessary Handover Avodance If the handover decson s not mplemented effcently, t can result n unnecessary handovers that can also lead to the png-pong effect. Hysterss value and dwell tmers are two such parameters utlzed n horzontal handover decson algorthms. We represent the set of these system parameters by Σ. 4. UTILITY OF THE FRAMEWORK Most handover decson algorthms can be dvded nto two phases () part of the algorthm that makes the decson to perform a handover and () part of the algorthm that chooses the network to handover to. The frst phase s referred to as the handover ntaton algorthm and the second phases s referred to as the network selecton algorthm. In ths secton we lst some of the exstng handover decson algorthms and show how they can be represented as functons of our framework. Horzontal handover algorthm: One of the ntal handover decson algorthms used for horzontal handover part of The North Amercan Personal Access Communcaton Systems (PACS) combnes a hysteress value wth dwell tmer to reduce the number of unnecessary handovers [10]. Ths basc algorthm can be splt nto ntaton algorthm and network selecton algorthm. Intaton algorthm: If R c1 µ 1 and R c2 µ 2 for T amount of tme then handover to the network selected by the network selecton algorthm. The ntaton algorthm can be represented as f(r c1, R c2, T, µ 1, µ 2 ), where c represents the current network, R c1 s the RSS measured and R c2 s the bt error rate measured. Network selecton: For the network selecton, the mandatory thresholds are computed as µ 1 = R c1 + δ 1 and µ 2 = R c2 + δ 2, δ 1 and δ 2 are hysteress values used to avod unnecessary handover. If R 1 µ 1 and R 2 µ 2, for any detected neghborng network, then handover to network. The network selecton algorthm can be represented as f(r, µ 1, µ 2, Σ) Smple addtve weghng (SAW) algorthm: Varous vertcal handover algorthms are proposed n lterature based on SAW [8]. SAW s a network selecton algorthm. Accordng to SAW the selected network s the one satsfyng max M P = 1 W R, where M s the set of all elgble networks, W s weght of parameter, and R s the value offered by network for parameter. Ths algorthm can be represented as f(w,r). 55

6 Multservce vertcal handover: A varaton of SAW proposed by Zhu and McNar [7] s to s use the cost functon for each network gve by: C =, where C s the cost ncurred by choosng network for servce s and s gven as C s s = W s C η ( R ). The functon η s used to normalze the values offered. Only those R values that satsfy the mandatory thresholds µ are consdered. Whenever a new network s detected, the cost functon s evaluated for all networks and the network wth the mnmum cost s selected. Hence the handover selecton s done whenever a new low cost network s detected. The authors also present a per servce handover algorthm. The servces are prortzed, and each servce n the order of the prortes s handed off to the network wth the least cost. The assumpton here s that the moble devce s communcatng usng multple rado nterfaces smultaneously. Ths algorthm can be represented as f(µ, W, R). Gray relatonal analyss (GRA) algorthm: The GRA algorthm presented by Song and Jamalpour [9] lsted n Fgure 3 s based on grey relatonal analyss (GRA). GRA s used to analyze relatonshp between dfferent dscrete vectors. A grey relatonal coeffcent (GRC) s computed between each of the vectors and a reference vector known as the deal vector. The vector wth the largest GRC s selected. GRA Algorthm (µ, W, R, H, L) 1 Normalze the vectors R nto a vector =( 1,, ) 2 Calculate the GRC for each network as = 3 Select the network wth mnmum GRC Fgure 3 GRA Algorthm 1 = Here R * R = H L L f parameter O has a lower sded threshold and network selecton algorthm can be represented as f(µ,w,r,h,l). R * = L L R H. Ths 5. GENERIC HANDOVER DECISION ALGORITHM Clearkt no decson algorthm consders the preferred threshold values of adaptable parameter requrements. In ths secton we descrbe a handover ntaton and network selecton algorthm that can optmze the user qualty of experence by consderng the requrements for the best operaton of the applcaton/servce used. 5.1 Defntons For a network, and a parameter, we quantfy dgresson from preferred threshold as D : D = 0 f preferred threshold s satsfed,.e f R π or R π dependng on whether the threshold s lower sded or upper sded respectvely. If the preferred threshold s not satsfed then the dgresson s gven as: D = (π - R )/π, f threshold s lower sded. D = (R - π )/π, f threshold s upper sded. 56

7 The dgresson for a network s gven by D = D Algorthm Our handover decson algorthm conssts of two phases, as descrbed n Fgure 4. P = 1 Fgure 4 Handover Decson Algorthm Phase I: Handover Intaton Algorthm Handover s ntated f one of the two condtons s met: Condton 1: The current network has not met the threshold requrements for T. That s: there exsts at least one parameter (1 P), such that R c < π or R c > π for lower sded or upper sded mandatory threshold respectvely for at least T amount of tme. Condton 2: Condton 1 s not true, but one or more new networks are detected and for at least one of the new networks, D < D c, where D c s the newly calculated dgresson for the current network Phase II: Network Selecton Algorthm Calculate D for each of the detected networks and select the network wth the mnmum D value. If handover was ntated due to condton 2 n phase I, then handover to the network wth mnmum D value only f the dgresson for current network D c < D. We also propose a varaton of the handover decson algorthm descrbed above, whch ncorporate the weghts of parameters n calculatng D. Each parameter has a weght 57

8 assocated wth t. Usng the weghts the dgresson for network s computed as: D = P = 1 W D. 6. FRAMEWORK IMPLEMENTATION In ths secton we provde an example mplementaton of our framework. Fgure 5 depcts ths example. The handover decson algorthm resdes n the moble devce n ths partcular example, but t s possble to have the handover decson algorthm n a network element n the case of a network controlled handover. In ths example we utlze ze the IEEE standard [4] known as Meda Independent Handover (MIH). Ths s the standard for optmzaton of handovers between IEEE 802 systems and cellular systems. Fgure 5 Framework Implementaton Example The enttes provdng the parameters for the handover decson are: MAC and PHY layer: The PHY layer parameters used are sgnal-to-nose nose rato (SNR), BER, and receved sgnal strength (RSS). Only the mandatory thresholds are consdered for the PHY layer. The MAC layer (lnk layer) parameters specfy the parameters measured by the MAC layers, such as the peak rate, packet error rate, tter, etc. The mandatory and preferred thresholds set for these parameters are dependent on the applcaton used. Due to the dfferent access networks supported, the MAC and PHY layer are specfc to the access technology (AT) of the networks, such as or rado access technologes such as , or UMTS. Applcaton: The applcaton entty provdes the parameters that affect the performance of the applcaton/servce used by the moble devce. In ths example we use the followng applcaton parameters: QoS Requrements: The mplementaton can utlze the QoS parameters specfed n the standard: data rate, mnmum packet transfer delay, maxmum packet transfer delay, tter, 58

9 packet loss rate, and packet error rate [4]. An applcaton requres all or a subset of these parameters. The applcaton provdes thresholds and weghts for each of the parameters t specfes. We consder both mandatory and preferred thresholds for these parameters n ths example. User: The user provdes a profle that ncludes the parameters of: Cost: Ths requrement specfes the monetary cost that the user s ready to ncur due to a connecton. Securty: Wth ths requrement the user specfes the authentcaton related requrements. For example, the authentcaton requrements can be gven as dfferent levels where level 0 ndcates open authentcaton, level 1 ndcates a shared key based authentcaton wth no encrypton, and level 2 may ndcate shared key based authentcaton wth encrypton etc. Now, we elaborate on the operaton of the handover decson algorthm usng ths example framework. Fgures 6a and 6b show handover ntaton due to the PHY layer mandatory thresholds not satsfed and due to the applcaton QoS requrements not met. The handover decson algorthm s notfed that the PHY layer mandatory thresholds are not met through the event servce provded by the MIHF. A protocol that wshes to use the MIH event servce sends the message MIH_Event_Subscrbe.request [13] to the MIHF as shown n Fgure 6a. In the case of the PHY layer mandatory thresholds, ths s acheved by subscrbng to the predctve event Lnk_Gong_Down of the current lnk. Ths event s trggered by the current MAC and PHY layer, whenever the mandatory thresholds of PHY layer parameters of ths lnk are not met. Fgure 6a. Notfcaton of PHY layer Performance In order to get notfed whenever the mandatory thresholds of the QoS requrements are not satsfed, we utlze the MIH_Lnk_Confgure_Thresholds command [4] as shown n fgure 6b. The standard provdes the mappng of the specfed QoS parameters to AT specfc parameters. When the MIHF receves the MIH_Lnk_Confgure_Thresholds request, t maps the QoS parameter thresholds to the current lnk layer parameters, and sends the command Lnk_Confgure_Thresholds to the current lnk layer. Ths results n the lnk layer notfyng the MIHF usng Lnk_Parameters_Report event whenever the specfed thresholds are not met. 59

10 Fgure 6b Notfcaton of Applcaton QoS Deteroraton In Fgure 7, we show when the network selecton algorthm s trggered and how t acqures the network offered values. When the moble node (MN) frst connects to any network, t acqures nformaton about neghbor networks through the MIH_Get_Informaton.request message of the meda ndependent nformaton servce (MIIS). The standard specfes a MIIS server that serves a group of neghborng networks and has statc knowledge of the network parameters such as the network dentfcaton, cost of servce, and securty offered. The MIIS server responds to the nformaton request from the MIHF of the MN wth ths nformaton. Ths provdes the values offered for cost and securty parameters. As descrbed n secton 5.2, one of the condtons for handover ntaton s that a neghborng network s detected. Ths s acheved n the example through the MIHF event Lnk_detected. The other condton to ntate handover s whenever the mandatory thresholds of any parameters are not satsfed. As descrbed above the events Lnk_gong_down and Lnk_Parameters_Report notfy that the mandatory thresholds of the PHY layer parameters and the applcaton QoS parameters respectvely are not met. When handover s ntated, the handover decson algorthm acqures the network offered values of all the avalable lnks for the specfed parameters through the request MIH_HO_Canddate_Query to the MIHF. The MIHF n turn requests the nformaton from the current network whch n turn requests the nformaton from the gven neghborng networks. Wth ths nformaton, the network selecton algorthm has all the requred values to calculate the dgresson of all the neghborng networks and select a network to handover to. 60

11 7. SIMULATION AND RESULTS Fgure 7 Network Selecton Procedure We smulated our handover decson algorthm and the SAW algorthm as used by Zhu and McNar [7] and the GRA algorthm as gven by Song and Jamalpour [9] Smulaton Model For our smulatons, we used a dscrete event smulator developed by us usng the Mcrosoft Vsual Studo.Net C++ to smulate moblty and handovers. We have used a network area of 2000 square meters populated by three dfferent access networks (ANs) as shown n Fgure 8.We use shadow fadng wth 6dB standard devaton to calculate the RSS at the moble node. The specfcatons of the three ANs for ths calculaton are gven n Table 1. Table 1. Network Specfcatons for RSS Calculaton AN 1 AN 2 AN 3 Frequency (MHz) Transmt Power (dbm) Coverage Radus (meters)

12 Fgure 8 Smulaton Network Model The parameters used for handover decson are the receved sgnal strength (RSS), data rate offered, and the cost of AN. Only the mandatory threshold s consdered for the RSS parameter; for the data rate and cost parameters both mandatory and preferred thresholds are consdered. Whle the RSS value s dynamc and changes wth the locaton of the moble node, data rate and cost are statc parameters. We have used the random waypont moblty model [11], where ntally the moble node s at a random poston wthn the smulaton area. Subsequently, the MN randomly chooses a new locaton and moves to ths locaton wth a speed of 5m/s. The smulaton s done for two scenaros:. In the frst scenaro there s a large dscrepancy between the values offered by the three access networks and only one network satsfes the preferred threshold hold for the cost parameter. Table 3 shows the values offered by the networks. We can see that n the frst scenaro the dfference between the data rate offered by the networks AN 1 and AN 3 s vastly hgher than the data rate of 8Mbps offered by AN 2. Only AN 2 satsfes the preferred threshold of 0.3 for cost n ths scenaro.. In the second scenaro the dscrepancy between the values offered s less and two of the three avalable networks satsfy the preferred threshold. As can be seen from Table 3, n ths scenaro the data rates offered by the three networks dffer at most by 150 Mbps and access networks 1 and 2 both satsfy the preferred thresholds for both data rate and cost. We provde the detals of the requrements for the parameters and the values offered by the networks for each of the scenaros n Tables 2 and 3. Cost s gven as a normalzed value usng the hghest cost charged by a network. For example f the hghest cost charged s by a network s $100, then the cost value for AN 1 s 0.6 f ths network charges $60. 62

13 Table 2. Parameter Requrements. Mandatory Threshold Preferred Threshold Data rate Cost Data rate Cost Scenaro 1 4Mbps 0.6 8Mbps 0.3 Scenaro 2 25Mbps Mbps 3 Data Rate Table 3. Parameter Values Cost AN 1 AN 2 AN 3 AN 1 AN 2 AN 3 Scenaro Mbps 8 Mbps 200 Mbps Scenaro Mbps 50 Mbps 200 Mbps Results and Analyss We present the results for both the scenaros n terms of the number of handovers occurred and the percentage of handovers that satsfes the preferred thresholds. In the results gven below we are only recordng those handovers that occurred when more than one AN was avalable for selecton, and when AN 2 was one of those networks. Ths s done n order to evaluate the behavor of the algorthms at tmes when a network satsfyng preferred thresholds s avalable. Fgure 9 compares the total number of handovers and Fgure 10 gves the percentage of tmes the preferred thresholds were met after the handovers. 90 T o t a l H a n d o v e r s Our algorthm SAW algorthm GRA algorthm 0 Scenaro 1 Scenaro 2 Fgure 9 Smulaton Results: Total Handovers 63

14 The results show that by consderng the preferred thresholds, our algorthm avods unnecessary handovers. In Fgure 9, we observe ths for both the scenaros, even though n the second scenaro both networks AN 1 and AN 2 satsfy the preferred thresholds. Ths s due to the fact that the MN executes handover only f the current network does not satsfy the preferred thresholds. Hence by utlzng preferred thresholds for parameters we reduce the handovers by more than 25%. Handover executon not only requres resources of the user devce and networks, but also the bandwdth whch s lmted for wreless access networks. Hence, by reducng the unnecessary handovers through our handover decson algorthm, we have acheved resource effcency. 120 S a t s f e d R e q u e s t s % Our algorthm SAW algorthm GRA algorthm 0 Scenaro 1 Scenaro 2 Fgure 10. Percentage of Preferred Requests Satsfed In the frst scenaro, only AN 1 can satsfy the preferred thresholds of all parameters. The preferred thresholds are satsfed durng hundred percent of the handovers when our algorthm s used as shown n Fgure 10. Ths s due to the fact that by usng dgresson our algorthm always chooses the network that most satsfes the preferred thresholds. In the second scenaro where the two networks AN2 and AN3 satsfy the preferred thresholds, SAW based algorthm also satsfes the preferred thresholds. Avalablty of dfferent access networks offerng values that dffer largely s a defnte possblty n NGNs. We have shown that n such scenaros our algorthm satsfes the parameter requrements whenever possble. 8. CONCLUSIONS The goal of the next generaton networks s to provde servces to users utlzng a packet based core network whch s able to ntegrate a varety of transport technologes, wred and wreless. The ITU-T standardzaton body has publshed requrements for the NGNs. In ths paper we have consdered the handover decson problem, whch s complex due to the avalablty of dfferent access networks. Next generaton networks not only offer the choce of a varety of access networks but also a myrad of applcatons to users. A key feature of the applcatons desgned for NGNs s ther adaptablty to the dverse networks offered. The overall user experence depends not only on the performance of the applcatons, but also on the cost benefts and the devce performance. We have presented a generc framework for handover decson n NGNs usng the concept of preferred thresholds for the requrements of parameters that affect the handover. Through examples we showed that our framework can be utlzed by any exstng handover decson algorthm for horzontal or vertcal handover. 64

15 We have presented a handover decson algorthm that utlzes the concept of preferred thresholds and hence represents the adaptve nature of the NGN servces. Through smulatons we have compared our algorthm wth the vertcal handover decson algorthms based on SAW [25] and GRA [27]. We observe that our algorthm s able to satsfy the user requrements and, n scenaros where there s a consderable dscrepancy n the values offered by networks for the dfferent parameters, only our algorthm pcks the network that most satsfes the user preference durng all handovers. The results showed that n all scenaros we reduce handovers by more than 25%, thus mprovng resource effcency. REFERENCES [1] ITU-T Recommendaton Q.1706 Next Generaton Networks: Generalzed Moblty Internatonal Telecommuncaton Unon, 2006 [2] F. Cacace and L. Vollero, Managng Moblty and Adaptaton n Upcomng Enabled Devces, Proc. 4th Int l. Wksp. Wreless Moble Apps. and Servces on WLAN Hotspots, 2006 [3] G. Lampropoulos, A. Salkntzs, and N. Passas, Meda Independent Handover for Seamless Servce Provson n Heterogeneous Networks, IEEE Commun. Mag., vol.46, no. 1, Jan [4] IEEE Std IEEE standard for Local and metropoltan area networks- Part 21: Meda Independent Handover [5] 3gPP TS v 6.9.0, General packet rado servce. 3GPP specfcatons [6] Y. Cho and S. Cho, Servce charge and energy-aware vertcal handoff n ntegrated IEEE e/ networks, Proc. IEEE INFOCOM, 2007, pp [7] Fang, Z., McNar, J.: Multservce Vertcal Handoff Decson Algorthms. EURASIP Journal on Wreless Communcatons and Networkng 2006(2), (2006) [8] Ram T, O. Salazar, Guy P. Vertcal Handoff Decson Scheme Usng MADM for Wreless Networks. In IEEE WCNC 2008 [9] Q. Song and A. Jamalpour, A network selecton mechansm for next generaton networks, n Proc. IEEE ICC, Seoul, Korea, May 2005, pp [10] G. Polln, Trends n handover desgn, IEEE Commun. Mag., vol. 34, no. 3, pp , Mar [11] J. Broch, D. A. Maltz, D. B. Johnson, Y. Hu, and J. G. Jetcheva. A Performance Comparson of Mult-Hop Wreless Ad Hoc Network Routng Protocols. In MobCom'98, Proceedngs of the Fourth Annual ACM/IEEE Internatonal Conference on Moble Computng and Networkng, pp [12] Pen-ho Chang and Tsan-Pn Wang (2009) Desgn and Implementaton of an Integrated RFID and VOIP System for Supportng Personal Moblty Internatonal Journal of Computer Networks & Communcatons (IJCNC) October 2009 vol 1, no. 3. [13] Yee YC, et al. (2007) "SIP-based proactve and adaptve moblty management framework for heterogeneous networks", Journal of Network and Computer Applcatons. [14] Dutta et al. 2005) Seamless Handover across Heterogeneous Networks An IEEE Centrc Approach Proceedngs of the nternatonal wreless submt-wreless personal multmeda communcatons (WPMC) [15] Srcharan, M.S.; Vadeh, V.; Arun, P.P. (2006) An actvty based moblty predcton strategy for next generaton wreless networks Proceedngs of IFIP Internatonal Conference on Wreless and Optcal Communcatons Networks,

16 Authors Shanthy Menezes receved the M.S. and Ph. D degrees n Computer Scence from the Unversty of Texas at Dallas n 2000 and 2010 respectvely. Her research nterests nclude wreless networks, moblty management n next generaton heterogeneous networks, and network smulaton. S. Venkatesan receved the M.S. and Ph.D. degrees from the Unversty of Pttsburgh n 1985 and 1989, respectvely and has been a faculty member n the Computer Scence Department at the Unversty of Texas at Dallas snce then. Hs nterests are n telecommuncaton networks, varous ssues n the desgn and operaton of wreless networks, dstrbuted algorthms, fault-tolerance and network forenscs and securty. Hs work has been funded by the federal, state and ndustral sponsors n the past. 66

An Interest-Oriented Network Evolution Mechanism for Online Communities

An Interest-Oriented Network Evolution Mechanism for Online Communities An Interest-Orented Network Evoluton Mechansm for Onlne Communtes Cahong Sun and Xaopng Yang School of Informaton, Renmn Unversty of Chna, Bejng 100872, P.R. Chna {chsun,yang}@ruc.edu.cn Abstract. Onlne

More information

M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS

M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS M3S MULTIMEDIA MOBILITY MANAGEMENT AND LOAD BALANCING IN WIRELESS BROADCAST NETWORKS Bogdan Cubotaru, Gabrel-Mro Muntean Performance Engneerng Laboratory, RINCE School of Electronc Engneerng Dubln Cty

More information

VERTICAL HANDOFF IN WIRELESS OVERLAPPING NETWORKS

VERTICAL HANDOFF IN WIRELESS OVERLAPPING NETWORKS VERTICAL HANDOFF IN IRELESS OVERLAPPING NETORKS Andres Marquez (Unversty of South Florda, Tampa, FL, US; amarquez@mal.usf.edu) Lus Martnez (Unversty of South Florda, Tampa, FL, US; lgmartn@mal.usf.edu)

More information

A Replication-Based and Fault Tolerant Allocation Algorithm for Cloud Computing

A Replication-Based and Fault Tolerant Allocation Algorithm for Cloud Computing A Replcaton-Based and Fault Tolerant Allocaton Algorthm for Cloud Computng Tork Altameem Dept of Computer Scence, RCC, Kng Saud Unversty, PO Box: 28095 11437 Ryadh-Saud Araba Abstract The very large nfrastructure

More information

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho

More information

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS

INVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMA-HDR NETWORKS 21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech-2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS

More information

Efficient Bandwidth Management in Broadband Wireless Access Systems Using CAC-based Dynamic Pricing

Efficient Bandwidth Management in Broadband Wireless Access Systems Using CAC-based Dynamic Pricing Effcent Bandwdth Management n Broadband Wreless Access Systems Usng CAC-based Dynamc Prcng Bader Al-Manthar, Ndal Nasser 2, Najah Abu Al 3, Hossam Hassanen Telecommuncatons Research Laboratory School of

More information

Communication Networks II Contents

Communication Networks II Contents 8 / 1 -- Communcaton Networs II (Görg) -- www.comnets.un-bremen.de Communcaton Networs II Contents 1 Fundamentals of probablty theory 2 Traffc n communcaton networs 3 Stochastc & Marovan Processes (SP

More information

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application

Performance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdo-dong,

More information

taposh_kuet20@yahoo.comcsedchan@cityu.edu.hk rajib_csedept@yahoo.co.uk, alam_shihabul@yahoo.com

taposh_kuet20@yahoo.comcsedchan@cityu.edu.hk rajib_csedept@yahoo.co.uk, alam_shihabul@yahoo.com G. G. Md. Nawaz Al 1,2, Rajb Chakraborty 2, Md. Shhabul Alam 2 and Edward Chan 1 1 Cty Unversty of Hong Kong, Hong Kong, Chna taposh_kuet20@yahoo.comcsedchan@ctyu.edu.hk 2 Khulna Unversty of Engneerng

More information

A Secure Password-Authenticated Key Agreement Using Smart Cards

A Secure Password-Authenticated Key Agreement Using Smart Cards A Secure Password-Authentcated Key Agreement Usng Smart Cards Ka Chan 1, Wen-Chung Kuo 2 and Jn-Chou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,

More information

Cooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing

Cooperative Load Balancing in IEEE 802.11 Networks with Cell Breathing Cooperatve Load Balancng n IEEE 82.11 Networks wth Cell Breathng Eduard Garca Rafael Vdal Josep Paradells Wreless Networks Group - Techncal Unversty of Catalona (UPC) {eduardg, rvdal, teljpa}@entel.upc.edu;

More information

A Dynamic Energy-Efficiency Mechanism for Data Center Networks

A Dynamic Energy-Efficiency Mechanism for Data Center Networks A Dynamc Energy-Effcency Mechansm for Data Center Networks Sun Lang, Zhang Jnfang, Huang Daochao, Yang Dong, Qn Yajuan A Dynamc Energy-Effcency Mechansm for Data Center Networks 1 Sun Lang, 1 Zhang Jnfang,

More information

An RFID Distance Bounding Protocol

An RFID Distance Bounding Protocol An RFID Dstance Boundng Protocol Gerhard P. Hancke and Markus G. Kuhn May 22, 2006 An RFID Dstance Boundng Protocol p. 1 Dstance boundng Verfer d Prover Places an upper bound on physcal dstance Does not

More information

PAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign

PAS: A Packet Accounting System to Limit the Effects of DoS & DDoS. Debish Fesehaye & Klara Naherstedt University of Illinois-Urbana Champaign PAS: A Packet Accountng System to Lmt the Effects of DoS & DDoS Debsh Fesehaye & Klara Naherstedt Unversty of Illnos-Urbana Champagn DoS and DDoS DDoS attacks are ncreasng threats to our dgtal world. Exstng

More information

Survey on Virtual Machine Placement Techniques in Cloud Computing Environment

Survey on Virtual Machine Placement Techniques in Cloud Computing Environment Survey on Vrtual Machne Placement Technques n Cloud Computng Envronment Rajeev Kumar Gupta and R. K. Paterya Department of Computer Scence & Engneerng, MANIT, Bhopal, Inda ABSTRACT In tradtonal data center

More information

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING

ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, 610-519-4390,

More information

What is Candidate Sampling

What is Candidate Sampling What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

More information

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1

Open Access A Load Balancing Strategy with Bandwidth Constraint in Cloud Computing. Jing Deng 1,*, Ping Guo 2, Qi Li 3, Haizhu Chen 1 Send Orders for Reprnts to reprnts@benthamscence.ae The Open Cybernetcs & Systemcs Journal, 2014, 8, 115-121 115 Open Access A Load Balancng Strategy wth Bandwdth Constrant n Cloud Computng Jng Deng 1,*,

More information

A Novel Auction Mechanism for Selling Time-Sensitive E-Services

A Novel Auction Mechanism for Selling Time-Sensitive E-Services A ovel Aucton Mechansm for Sellng Tme-Senstve E-Servces Juong-Sk Lee and Boleslaw K. Szymansk Optmaret Inc. and Department of Computer Scence Rensselaer Polytechnc Insttute 110 8 th Street, Troy, Y 12180,

More information

Dimming Cellular Networks

Dimming Cellular Networks Dmmng Cellular Networks Davd Tpper, Abdelmounaam Rezgu, Prashant Krshnamurthy, and Peera Pacharntanakul Graduate Telecommuncatons and Networkng Program, Unversty of Pttsburgh, Pttsburgh, PA 1526, Unted

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

Fault tolerance in cloud technologies presented as a service

Fault tolerance in cloud technologies presented as a service Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance

More information

On the Complexity of Always Best Connected in 4G Mobile Networks

On the Complexity of Always Best Connected in 4G Mobile Networks On the Complexty of Always Best Connected n 4G Moble etworks Vangels Gazs, kos Houssos, ancy Alonstot, Lazaros Merakos Communcaton etworks Laboratory, Department of Informatcs & Telecommuncatons, Unversty

More information

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika.

VRT012 User s guide V0.1. Address: Žirmūnų g. 27, Vilnius LT-09105, Phone: (370-5) 2127472, Fax: (370-5) 276 1380, Email: info@teltonika. VRT012 User s gude V0.1 Thank you for purchasng our product. We hope ths user-frendly devce wll be helpful n realsng your deas and brngng comfort to your lfe. Please take few mnutes to read ths manual

More information

QoS-based Scheduling of Workflow Applications on Service Grids

QoS-based Scheduling of Workflow Applications on Service Grids QoS-based Schedulng of Workflow Applcatons on Servce Grds Ja Yu, Rakumar Buyya and Chen Khong Tham Grd Computng and Dstrbuted System Laboratory Dept. of Computer Scence and Software Engneerng The Unversty

More information

Project Networks With Mixed-Time Constraints

Project Networks With Mixed-Time Constraints Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa

More information

iavenue iavenue i i i iavenue iavenue iavenue

iavenue iavenue i i i iavenue iavenue iavenue Saratoga Systems' enterprse-wde Avenue CRM system s a comprehensve web-enabled software soluton. Ths next generaton system enables you to effectvely manage and enhance your customer relatonshps n both

More information

On the Optimal Control of a Cascade of Hydro-Electric Power Stations

On the Optimal Control of a Cascade of Hydro-Electric Power Stations On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE

AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE Yu-L Huang Industral Engneerng Department New Mexco State Unversty Las Cruces, New Mexco 88003, U.S.A. Abstract Patent

More information

Joint Dynamic Radio Resource Allocation and Mobility Load Balancing in 3GPP LTE Multi-Cell Network

Joint Dynamic Radio Resource Allocation and Mobility Load Balancing in 3GPP LTE Multi-Cell Network 288 FENG LI, LINA GENG, SHIHUA ZHU, JOINT DYNAMIC RADIO RESOURCE ALLOCATION AND MOBILITY LOAD BALANCING Jont Dynamc Rado Resource Allocaton and Moblty Load Balancng n 3GPP LTE Mult-Cell Networ Feng LI,

More information

A Dynamic Load Balancing for Massive Multiplayer Online Game Server

A Dynamic Load Balancing for Massive Multiplayer Online Game Server A Dynamc Load Balancng for Massve Multplayer Onlne Game Server Jungyoul Lm, Jaeyong Chung, Jnryong Km and Kwanghyun Shm Dgtal Content Research Dvson Electroncs and Telecommuncatons Research Insttute Daejeon,

More information

A Hierarchical Reliability Model of Service-Based Software System

A Hierarchical Reliability Model of Service-Based Software System 2009 33rd Annual IEEE Internatonal Computer Software and Applcatons Conference A Herarchcal Relablty Model of Servce-Based Software System Lun Wang, Xaoyng Ba, Lzhu Zhou Department of Computer Scence and

More information

Complex Service Provisioning in Collaborative Cloud Markets

Complex Service Provisioning in Collaborative Cloud Markets Melane Sebenhaar, Ulrch Lampe, Tm Lehrg, Sebastan Zöller, Stefan Schulte, Ralf Stenmetz: Complex Servce Provsonng n Collaboratve Cloud Markets. In: W. Abramowcz et al. (Eds.): Proceedngs of the 4th European

More information

VoIP Playout Buffer Adjustment using Adaptive Estimation of Network Delays

VoIP Playout Buffer Adjustment using Adaptive Estimation of Network Delays VoIP Playout Buffer Adjustment usng Adaptve Estmaton of Network Delays Mroslaw Narbutt and Lam Murphy* Department of Computer Scence Unversty College Dubln, Belfeld, Dubln, IRELAND Abstract The poor qualty

More information

A role based access in a hierarchical sensor network architecture to provide multilevel security

A role based access in a hierarchical sensor network architecture to provide multilevel security 1 A role based access n a herarchcal sensor network archtecture to provde multlevel securty Bswajt Panja a Sanjay Kumar Madra b and Bharat Bhargava c a Department of Computer Scenc Morehead State Unversty

More information

DEFINING %COMPLETE IN MICROSOFT PROJECT

DEFINING %COMPLETE IN MICROSOFT PROJECT CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMI-SP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,

More information

Reinforcement Learning for Quality of Service in Mobile Ad Hoc Network (MANET)

Reinforcement Learning for Quality of Service in Mobile Ad Hoc Network (MANET) Renforcement Learnng for Qualty of Servce n Moble Ad Hoc Network (MANET) *T.KUMANAN AND **K.DURAISWAMY *Meenaksh College of Engneerng West K.K Nagar, Cheena-78 **Dean/academc,K.S.R College of Technology,Truchengode

More information

A Novel Adaptive Load Balancing Routing Algorithm in Ad hoc Networks

A Novel Adaptive Load Balancing Routing Algorithm in Ad hoc Networks Journal of Convergence Informaton Technology A Novel Adaptve Load Balancng Routng Algorthm n Ad hoc Networks Zhu Bn, Zeng Xao-png, Xong Xan-sheng, Chen Qan, Fan Wen-yan, We Geng College of Communcaton

More information

Data Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network *

Data Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network * JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819-840 (2008) Data Broadcast on a Mult-System Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,

More information

Performance Analysis and Comparison of QoS Provisioning Mechanisms for CBR Traffic in Noisy IEEE 802.11e WLANs Environments

Performance Analysis and Comparison of QoS Provisioning Mechanisms for CBR Traffic in Noisy IEEE 802.11e WLANs Environments Tamkang Journal of Scence and Engneerng, Vol. 12, No. 2, pp. 143149 (2008) 143 Performance Analyss and Comparson of QoS Provsonng Mechansms for CBR Traffc n Nosy IEEE 802.11e WLANs Envronments Der-Junn

More information

Energy Conserving Routing in Wireless Ad-hoc Networks

Energy Conserving Routing in Wireless Ad-hoc Networks Energy Conservng Routng n Wreless Ad-hoc Networks Jae-Hwan Chang and Leandros Tassulas Department of Electrcal and Computer Engneerng & Insttute for Systems Research Unversty of Maryland at College ark

More information

MAPP. MERIS level 3 cloud and water vapour products. Issue: 1. Revision: 0. Date: 9.12.1998. Function Name Organisation Signature Date

MAPP. MERIS level 3 cloud and water vapour products. Issue: 1. Revision: 0. Date: 9.12.1998. Function Name Organisation Signature Date Ttel: Project: Doc. No.: MERIS level 3 cloud and water vapour products MAPP MAPP-ATBD-ClWVL3 Issue: 1 Revson: 0 Date: 9.12.1998 Functon Name Organsaton Sgnature Date Author: Bennartz FUB Preusker FUB Schüller

More information

A FRAMEWORK FOR EFFICIENT BANDWIDTH MANAGEMENT IN BROADBAND WIRELESS ACCESS SYSTEMS

A FRAMEWORK FOR EFFICIENT BANDWIDTH MANAGEMENT IN BROADBAND WIRELESS ACCESS SYSTEMS A FRAMEWORK FOR EFFICIENT BANDWIDTH MANAGEMENT IN BROADBAND WIRELESS ACCESS SYSTEMS BY BADER S. AL-MANTHARI A thess submtted to the School of Computng n conformty wth the requrements for the degree of

More information

A Design Method of High-availability and Low-optical-loss Optical Aggregation Network Architecture

A Design Method of High-availability and Low-optical-loss Optical Aggregation Network Architecture A Desgn Method of Hgh-avalablty and Low-optcal-loss Optcal Aggregaton Network Archtecture Takehro Sato, Kuntaka Ashzawa, Kazumasa Tokuhash, Dasuke Ish, Satoru Okamoto and Naoak Yamanaka Dept. of Informaton

More information

Analysis of Energy-Conserving Access Protocols for Wireless Identification Networks

Analysis of Energy-Conserving Access Protocols for Wireless Identification Networks From the Proceedngs of Internatonal Conference on Telecommuncaton Systems (ITC-97), March 2-23, 1997. 1 Analyss of Energy-Conservng Access Protocols for Wreless Identfcaton etworks Imrch Chlamtac a, Chara

More information

Energy Efficient Routing in Ad Hoc Disaster Recovery Networks

Energy Efficient Routing in Ad Hoc Disaster Recovery Networks Energy Effcent Routng n Ad Hoc Dsaster Recovery Networks Gl Zussman and Adran Segall Department of Electrcal Engneerng Technon Israel Insttute of Technology Hafa 32000, Israel {glz@tx, segall@ee}.technon.ac.l

More information

A Performance Analysis of View Maintenance Techniques for Data Warehouses

A Performance Analysis of View Maintenance Techniques for Data Warehouses A Performance Analyss of Vew Mantenance Technques for Data Warehouses Xng Wang Dell Computer Corporaton Round Roc, Texas Le Gruenwald The nversty of Olahoma School of Computer Scence orman, OK 739 Guangtao

More information

An Adaptive Cross-layer Bandwidth Scheduling Strategy for the Speed-Sensitive Strategy in Hierarchical Cellular Networks

An Adaptive Cross-layer Bandwidth Scheduling Strategy for the Speed-Sensitive Strategy in Hierarchical Cellular Networks An Adaptve Cross-layer Bandwdth Schedulng Strategy for the Speed-Senstve Strategy n erarchcal Cellular Networks Jong-Shn Chen #1, Me-Wen #2 Department of Informaton and Communcaton Engneerng ChaoYang Unversty

More information

Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters

Frequency Selective IQ Phase and IQ Amplitude Imbalance Adjustments for OFDM Direct Conversion Transmitters Frequency Selectve IQ Phase and IQ Ampltude Imbalance Adjustments for OFDM Drect Converson ransmtters Edmund Coersmeer, Ernst Zelnsk Noka, Meesmannstrasse 103, 44807 Bochum, Germany edmund.coersmeer@noka.com,

More information

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña

A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION

More information

QoS in the Linux Operating System. Technical Report

QoS in the Linux Operating System. Technical Report Unverstät Karlsruhe (H) Insttut für elematk QoS n the Lnux Operatng System echncal Report Marc Bechler and Hartmut Rtter Insttut für elematk Fakultät für Informatk Unverstät Karlsruhe (H) E-Mal: [mbechler

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

Cost Minimization using Renewable Cooling and Thermal Energy Storage in CDNs

Cost Minimization using Renewable Cooling and Thermal Energy Storage in CDNs Cost Mnmzaton usng Renewable Coolng and Thermal Energy Storage n CDNs Stephen Lee College of Informaton and Computer Scences UMass, Amherst stephenlee@cs.umass.edu Rahul Urgaonkar IBM Research rurgaon@us.bm.com

More information

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure

More information

An Integrated Approach of AHP-GP and Visualization for Software Architecture Optimization: A case-study for selection of architecture style

An Integrated Approach of AHP-GP and Visualization for Software Architecture Optimization: A case-study for selection of architecture style Internatonal Journal of Scentfc & Engneerng Research Volume 2, Issue 7, July-20 An Integrated Approach of AHP-GP and Vsualzaton for Software Archtecture Optmzaton: A case-study for selecton of archtecture

More information

J. Parallel Distrib. Comput. Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers

J. Parallel Distrib. Comput. Environment-conscious scheduling of HPC applications on distributed Cloud-oriented data centers J. Parallel Dstrb. Comput. 71 (2011) 732 749 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. ournal homepage: www.elsever.com/locate/pdc Envronment-conscous schedulng of HPC applcatons

More information

A 2 -MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks

A 2 -MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks : An Adaptve, Anycast MAC Protocol for Wreless Sensor Networks Hwee-Xan Tan and Mun Choon Chan Department of Computer Scence, School of Computng, Natonal Unversty of Sngapore {hweexan, chanmc}@comp.nus.edu.sg

More information

Politecnico di Torino. Porto Institutional Repository

Politecnico di Torino. Porto Institutional Repository Poltecnco d Torno Porto Insttutonal Repostory [Artcle] A cost-effectve cloud computng framework for acceleratng multmeda communcaton smulatons Orgnal Ctaton: D. Angel, E. Masala (2012). A cost-effectve

More information

Traffic State Estimation in the Traffic Management Center of Berlin

Traffic State Estimation in the Traffic Management Center of Berlin Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,

More information

An ILP Formulation for Task Mapping and Scheduling on Multi-core Architectures

An ILP Formulation for Task Mapping and Scheduling on Multi-core Architectures An ILP Formulaton for Task Mappng and Schedulng on Mult-core Archtectures Yng Y, We Han, Xn Zhao, Ahmet T. Erdogan and Tughrul Arslan Unversty of Ednburgh, The Kng's Buldngs, Mayfeld Road, Ednburgh, EH9

More information

An Alternative Way to Measure Private Equity Performance

An Alternative Way to Measure Private Equity Performance An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

More information

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo

More information

A Game-Theoretic Approach for Minimizing Security Risks in the Internet-of-Things

A Game-Theoretic Approach for Minimizing Security Risks in the Internet-of-Things A Game-Theoretc Approach for Mnmzng Securty Rsks n the Internet-of-Thngs George Rontds, Emmanoul Panaouss, Aron Laszka, Tasos Daguklas, Pasquale Malacara, and Tansu Alpcan Hellenc Open Unversty, Greece

More information

Control Charts for Means (Simulation)

Control Charts for Means (Simulation) Chapter 290 Control Charts for Means (Smulaton) Introducton Ths procedure allows you to study the run length dstrbuton of Shewhart (Xbar), Cusum, FIR Cusum, and EWMA process control charts for means usng

More information

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node

denote the location of a node, and suppose node X . This transmission causes a successful reception by node X for any other node Fnal Report of EE359 Class Proect Throughput and Delay n Wreless Ad Hoc Networs Changhua He changhua@stanford.edu Abstract: Networ throughput and pacet delay are the two most mportant parameters to evaluate

More information

Load Balancing Based on Clustering Methods for LTE Networks

Load Balancing Based on Clustering Methods for LTE Networks Cyber Journals: Multdscplnary Journals n Scence and Technology Journal of Selected Areas n Telecommuncatons (JSAT) February Edton 2013 Volume 3 Issue 2 Load Balancng Based on Clusterng Methods for LTE

More information

Learning the Best K-th Channel for QoS Provisioning in Cognitive Networks

Learning the Best K-th Channel for QoS Provisioning in Cognitive Networks 000 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050

More information

IWFMS: An Internal Workflow Management System/Optimizer for Hadoop

IWFMS: An Internal Workflow Management System/Optimizer for Hadoop IWFMS: An Internal Workflow Management System/Optmzer for Hadoop Lan Lu, Yao Shen Department of Computer Scence and Engneerng Shangha JaoTong Unversty Shangha, Chna lustrve@gmal.com, yshen@cs.sjtu.edu.cn

More information

A New Paradigm for Load Balancing in Wireless Mesh Networks

A New Paradigm for Load Balancing in Wireless Mesh Networks A New Paradgm for Load Balancng n Wreless Mesh Networks Abstract: Obtanng maxmum throughput across a network or a mesh through optmal load balancng s known to be an NP-hard problem. Desgnng effcent load

More information

AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION

AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION The Medterranean Journal of Computers and Networks, Vol. 2, No. 1, 2006 57 AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION L. Bada 1,*, M. Zorz 2 1 Department of Engneerng,

More information

FOURTH Generation (4G) Wireless Networks are developed

FOURTH Generation (4G) Wireless Networks are developed 2600 IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, VOL. 9, NO. 8, AUGUST 2010 Congeston-Based Prcng Resource Management n Broadband Wreless Networks Najah AbuAl, Mohammad Hayajneh, and Hossam Hassanen

More information

Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks

Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks Rapd Estmaton ethod for Data Capacty and Spectrum Effcency n Cellular Networs C.F. Ball, E. Humburg, K. Ivanov, R. üllner Semens AG, Communcatons oble Networs unch, Germany carsten.ball@semens.com Abstract

More information

"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *

Research Note APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES * Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789-794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC

More information

Brigid Mullany, Ph.D University of North Carolina, Charlotte

Brigid Mullany, Ph.D University of North Carolina, Charlotte Evaluaton And Comparson Of The Dfferent Standards Used To Defne The Postonal Accuracy And Repeatablty Of Numercally Controlled Machnng Center Axes Brgd Mullany, Ph.D Unversty of North Carolna, Charlotte

More information

ABSTRACT. Categories and Subject Descriptors. General Terms. Keywords

ABSTRACT. Categories and Subject Descriptors. General Terms. Keywords On Desgnng Incentve-Compatble Routng and Forwardng Protocols n Wreless Ad-Hoc Networks An Integrated Approach Usng Game Theoretcal and Cryptographc Technques Sheng Zhong L (Erran) L Yanbn Grace Lu Yang

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

Availability-Based Path Selection and Network Vulnerability Assessment

Availability-Based Path Selection and Network Vulnerability Assessment Avalablty-Based Path Selecton and Network Vulnerablty Assessment Song Yang, Stojan Trajanovsk and Fernando A. Kupers Delft Unversty of Technology, The Netherlands {S.Yang, S.Trajanovsk, F.A.Kupers}@tudelft.nl

More information

Optimization of Resource Allocation in Wireless Systems Based on Game Theory

Optimization of Resource Allocation in Wireless Systems Based on Game Theory Internatonal Journal of Computer Scences and Engneerng Open Access Research Paper Volume-4, Issue-1 E-ISSN: 347-693 Optmzaton of Resource Allocaton n Wreless Systems Based on Game Theory Sara Rah 1*, Al

More information

Research of Network System Reconfigurable Model Based on the Finite State Automation

Research of Network System Reconfigurable Model Based on the Finite State Automation JOURNAL OF NETWORKS, VOL., NO. 5, MAY 24 237 Research of Network System Reconfgurable Model Based on the Fnte State Automaton Shenghan Zhou and Wenbng Chang School of Relablty and System Engneerng, Behang

More information

Enterprise Master Patient Index

Enterprise Master Patient Index Enterprse Master Patent Index Healthcare data are captured n many dfferent settngs such as hosptals, clncs, labs, and physcan offces. Accordng to a report by the CDC, patents n the Unted States made an

More information

The OC Curve of Attribute Acceptance Plans

The OC Curve of Attribute Acceptance Plans The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4

More information

Optimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm

Optimization Model of Reliable Data Storage in Cloud Environment Using Genetic Algorithm Internatonal Journal of Grd Dstrbuton Computng, pp.175-190 http://dx.do.org/10.14257/gdc.2014.7.6.14 Optmzaton odel of Relable Data Storage n Cloud Envronment Usng Genetc Algorthm Feng Lu 1,2,3, Hatao

More information

Efficient Project Portfolio as a tool for Enterprise Risk Management

Efficient Project Portfolio as a tool for Enterprise Risk Management Effcent Proect Portfolo as a tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company January 5, 27 Effcent Proect Portfolo as a tool for Enterprse

More information

Resource Scheduling in Desktop Grid by Grid-JQA

Resource Scheduling in Desktop Grid by Grid-JQA The 3rd Internatonal Conference on Grd and Pervasve Computng - Worshops esource Schedulng n Destop Grd by Grd-JQA L. Mohammad Khanl M. Analou Assstant professor Assstant professor C.S. Dept.Tabrz Unversty

More information

Network-Wide Load Balancing Routing With Performance Guarantees

Network-Wide Load Balancing Routing With Performance Guarantees Network-Wde Load Balancng Routng Wth Performance Guarantees Kartk Gopalan Tz-cker Chueh Yow-Jan Ln Florda State Unversty Stony Brook Unversty Telcorda Research kartk@cs.fsu.edu chueh@cs.sunysb.edu yjln@research.telcorda.com

More information

Dynamic Resource Allocation and Power Management in Virtualized Data Centers

Dynamic Resource Allocation and Power Management in Virtualized Data Centers Dynamc Resource Allocaton and Power Management n Vrtualzed Data Centers Rahul Urgaonkar, Ulas C. Kozat, Ken Igarash, Mchael J. Neely urgaonka@usc.edu, {kozat, garash}@docomolabs-usa.com, mjneely@usc.edu

More information

A New Task Scheduling Algorithm Based on Improved Genetic Algorithm

A New Task Scheduling Algorithm Based on Improved Genetic Algorithm A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng Envronment Congcong Xong, Long Feng, Lxan Chen A New Task Schedulng Algorthm Based on Improved Genetc Algorthm n Cloud Computng

More information

Cloud-based Social Application Deployment using Local Processing and Global Distribution

Cloud-based Social Application Deployment using Local Processing and Global Distribution Cloud-based Socal Applcaton Deployment usng Local Processng and Global Dstrbuton Zh Wang *, Baochun L, Lfeng Sun *, and Shqang Yang * * Bejng Key Laboratory of Networked Multmeda Department of Computer

More information

Sensitivity Analysis in a Generic Multi-Attribute Decision Support System

Sensitivity Analysis in a Generic Multi-Attribute Decision Support System Senstvty Analyss n a Generc Mult-Attrbute Decson Support System Sxto Ríos-Insua, Antono Jménez and Alfonso Mateos Department of Artfcal Intellgence, Madrd Techncal Unversty Campus de Montegancedo s/n,

More information

Multi-Source Video Multicast in Peer-to-Peer Networks

Multi-Source Video Multicast in Peer-to-Peer Networks ult-source Vdeo ultcast n Peer-to-Peer Networks Francsco de Asís López-Fuentes*, Eckehard Stenbach Technsche Unverstät ünchen Insttute of Communcaton Networks, eda Technology Group 80333 ünchen, Germany

More information

Network Services Definition and Deployment in a Differentiated Services Architecture

Network Services Definition and Deployment in a Differentiated Services Architecture etwork Servces Defnton and Deployment n a Dfferentated Servces Archtecture E. kolouzou, S. Manats, P. Sampatakos,. Tsetsekas, I. S. Veners atonal Techncal Unversty of Athens, Department of Electrcal and

More information

Load Balancing Algorithm of Switched Dynamic Iteration

Load Balancing Algorithm of Switched Dynamic Iteration Send Orders for Reprnts to reprnts@benthamscence.ae 236 The Open Cybernetcs Systemcs Journal, 2015, 9, 236-242 Load Balancng Algorthm of Swtched Dynamc Iteraton Open Access Chen Yansheng 1,3,* Wu Zhongkun

More information

Data security in Intelligent Transport Systems

Data security in Intelligent Transport Systems Data securty n Intellgent Transport Systems Tomas ZELINKA Czech Techncal Unversty n rague, FTS 110 00 raha 1, Czech Republc Mroslav SVITEK Czech Techncal Unversty n rague, FTS 110 00 raha 1, Czech Republc

More information

An Introduction to 3G Monte-Carlo simulations within ProMan

An Introduction to 3G Monte-Carlo simulations within ProMan An Introducton to 3G Monte-Carlo smulatons wthn ProMan responsble edtor: Hermann Buddendck AWE Communcatons GmbH Otto-Llenthal-Str. 36 D-71034 Böblngen Phone: +49 70 31 71 49 7-16 Fax: +49 70 31 71 49

More information

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

More information

Mining Multiple Large Data Sources

Mining Multiple Large Data Sources The Internatonal Arab Journal of Informaton Technology, Vol. 7, No. 3, July 2 24 Mnng Multple Large Data Sources Anmesh Adhkar, Pralhad Ramachandrarao 2, Bhanu Prasad 3, and Jhml Adhkar 4 Department of

More information

Traffic-light a stress test for life insurance provisions

Traffic-light a stress test for life insurance provisions MEMORANDUM Date 006-09-7 Authors Bengt von Bahr, Göran Ronge Traffc-lght a stress test for lfe nsurance provsons Fnansnspetonen P.O. Box 6750 SE-113 85 Stocholm [Sveavägen 167] Tel +46 8 787 80 00 Fax

More information

OPTIMIZATION OF VERTICAL HANDOFF DECISION PROCESS FOR HETEROGENEOUS WIRELESS NETWORKS

OPTIMIZATION OF VERTICAL HANDOFF DECISION PROCESS FOR HETEROGENEOUS WIRELESS NETWORKS OPTIMIZATION OF VERTICAL HANDOFF DECISION PROCESS FOR HETEROGENEOUS WIRELESS NETWORKS 1 T.VELMURUGAN, 2 Dr.SIBARAM KHARA 1 School of Electroncs Engneerng, VIT Unversty, Vellore. 2 School of Electroncs

More information