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

Size: px
Start display at page:

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

Transcription

1 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 the performance of wreless ad hoc networs. Generally t s dffcult to acheve both hgh throughput and low pacet delay. In ths proect, the obectve s to acheve hgh throughput whle eepng the pacet delay under certan threshold. We wll frst loo at the throughput capacty theoretcally n moble ad hoc networs. Gupta and Kumar [1] show the average avalable throughput per node decreases as 1 / n or 1 / n lg n n a statc ad hoc networ, where n s the number of nodes. That means, the total networ capacty ncreases as at most n. Furthermore, Grossglauser and Tse [2] show moblty can mprove the capacty. However, delay s not guaranteed n ther schemes. Actually delay wll ncrease due to possbly more hops or queueng n order to ncrease the throughput. Bansal and Lu [3] show t s possble to acheve close-to optmal capacty whle eepng the delay small. In ther model, each sender can acheve an average throughput of W mn( m, n) c, where W s the maxmum avalable bandwdth, wth the pacet delay at 3 nlog n 2 d most, where d s the dameter of the networ and v s the velocty of the moble nodes. v Based on ths fact, the authors propose a routng algorthm that acheves the obectve through explotng the patterns n the moblty of nodes. The throughput acheved by ths algorthm s only a poly-logarthmc factor off from the optmal.

2 1. Introducton Wreless networ s becomng more and more popular n nowadays. Comparng to the tradtonal wred networ, wreless networ set up the connectons through wreless channel. Generally there are two nds of wreless networs. One has a wred bacbone networ n whch the base statons are the boundary nodes, and the extended connectons between moble users and the base staton are wreless channels. Ths one-hop wreless networ s very popular currently,.e., the cellular networs and WLANs. The other s wreless ad hoc networ, whch has more than one hop wreless channels n the connecton. Ths nd of topology s not wdely mplemented yet, but t s useful sometmes, especally n mltary applcatons and sensor networs. In our proect, we wll focus on the latter topology, the wreless ad hoc networ, wthout consderng any wred lns. As an extenson to the bacbone networ, wreless ad hoc networ conssts of nodes that communcate wth each other through wreless channels only. We can descrbe the system as follows. Our system conssts of only wreless nodes, n whch all nodes can communcate wth other nodes n the range of rado transmsson through wreless channel. Each wreless node can act as a sender, a recever or a router. As a sender, the node can send message to the specfed destnaton node through some route. As a recever, t can receve the message from other nodes. As a router, t can relay the pacet to the destnaton or next router n the route f necessary. Each node can buffer pacets when the pacets need to wat for transmsson. We are nterested n the capacty and delay of such nd of networ. In general these two parameters are the most mportant performance measurement for any wreless networ systems. The capacty represents the throughput (bts per second) of the whole system ncludng all nodes, and the delay represents the average tme duraton of a pacet transmttng n the networ from a source to the destnaton. As n any other queueng system, there are tradeoffs between the capacty and the delay. Intutvely n order to ncrease the capacty, we need to eep all nodes busy wth transmttng or recevng pacets durng all the tme, whch means the queue of each node s always nonempty, obvously ths wll lead to a longer delay. On the other hand, n order to reduce the delay, the optmal stuaton s, all nodes along the route can transmt the pacet mmedately to the next node untl t reaches the destnaton, whch means there s no pacet competng for transmssons n the queues, surely ths causes very low throughput. We wll see ths tradeoff n wreless ad hoc networs n the report. Furthermore, our obectve s to fnd a way that the networ can acheve a hgh throughput whle eepng the delay under certan threshold. Ths report wll address the problem. In the followng, secton 2 wll descrbe the methodology to model the problem step by step, secton 3 wll gve out the man results n the papers and explan ther meanngs to the capacty and the pacet delay, based on these a routng algorthm s proposed to reach our obectve. Fnally n secton 4 we conclude the capacty and delay n wreless ad hoc networs.

3 2. Methodology In ths part, we wll show the methodology to solve the problem step by step. Recall that our obectve s to acheve hgh capacty n wreless ad hoc networs wth eepng the pacet delay under a small threshold. We wll model the networs from smple to complex, from general to specfc step by step. In each model, we wll descrbe the scenaro, the transmsson model and the measurement metrcs n detals. Frst of all, we develop the models for wreless ad hoc networs wth statc nodes. Gupta and Kumar [1] propose two models for such nd of networ. For smplcty, the models scale the space so that n nodes are located n a regon of area 1 m 2. Each node can transmt at W bts per second over a common wreless channel. The channel s dvded to several sub-channels, each wth capacty W 1, W2, m, WM bts per second, where M m= 1 W m = W. 2.1 Model 1 (model of arbtrary networs n [1]) Frst we defne the scenaros. In the networ the nodes and traffc patterns are arbtrarly located. Say, n nodes are arbtrarly located n a ds of unt area n the plane. Each node arbtrarly chooses a destnaton to send message at an arbtrary rate, and also arbtrarly choose a transmsson range or power level. Then we use two models to ndcate successful recepton of a transmsson over one hop: the protocol model and the physcal model. In the protocol model, let denote the th locaton of a node, and suppose node transmts over the m sub-channel to a node. Ths transmsson causes a successful recepton by node f ( 1 + ) for any other node same sub-channel. On the other hand, n the physcal model, let { ; Τ} smultaneously transmttng over the be the subset of nodes smultaneously transmttng over a certan sub-channel. Assume node transmts wth power P, for successful recepton by node Τ. The transmsson from a node, P f the nequalty N + Τ P Τ causes a β s satsfed, where β s a threshold of sgnal-to-nterference rato (SIR) for successful receptons, N s the ambent nose power level, and > 2 ndcates the sgnal power decay wth dstance 1. r

4 Fnally n the model we need to defne the measurement metrcs. We defne bt-meter as the product of the number of bts and the dstances over whch the bts are carred. Accordng to ths, the capacty s defned as the sum of all bt-meter n the networ. From Model 1, we can compute the upper bound and lower bound of the capacty, thus get some nowledge about the actual capactes, whch s descrbe n detals n secton 3.1. Whle ths model s qute general, a further model wth more nformaton on the locaton and traffc pattern of the nodes wll gve us more useful results. 2.2 Model 2 (model of random networs n [1]) Smlarly frst we descrbe the scenaros. There are some tny dfferences from Model 1. n nodes are ndependently and unformly dstrbuted on the surface S 2 of a threedmensonal sphere of area 1 m 2. We adopt ths change n order to elmnate the boundary effects. Each node randomly and ndependently chooses a destnaton to send λ n bts per second. message wth the rate of ( ) Then for the transmsson model we adopt both a protocol model and a physcal model for ndcatng the successful recepton, ust le what we do n Model 1. The only dfference s that we ntroduce a common range r for all transmssons and the nequalty n the protocol model changes to r and ( 1 + )r. Fnally n order to compute the throughput of the networ, we defne a throughput of λ ( n) bts per second for each node s feasble f there s a spatal and temporal scheme for schedulng transmssons, such that every node can send λ ( n) bts per second on average to ts chosen destnaton node through the ntermedate nodes and some bufferng strategy n the ntermedate nodes. Based on ths model, smlarly we can calculate a lower bound and an upper bound of the capacty. However, because node relayng and bufferng are ntroduced, t s possble that some pacets wll have long delays. Furthermore, n both models we only consder the networ conssts of statc nodes. As we now, one of the bggest advantages of wreless networs s the moblty. In the next we wll extend the model to nclude moble nodes. Grossglauser and Tse [2] study nfluence of moblty on the capacty of wreless networs. 2.3 Model 3 (model wth moble nodes n [2]) Frst we descrbe the scenaros. The networ stll conssts of n nodes lyng n the ds of unt area, but dfferent from Model 1 and 2, all the nodes are moble. Denote the locaton of the th user at tme t as () t. Assume the traectores of dfferent users are ndependent and dentcally dstrbuted, and each node s both a source node for one sesson and a destnaton node for another sesson. Let d () represent the destnaton node of node. Durng the transmsson, we assume that each source node has nfnte

5 number of pacets to send to ts destnaton. Furthermore, ths S-D assocaton does not change wth tme no matter how the nodes move. We wll use the same physcal model as n Model 1 and 2 for transmsson. Furthermore, n order to ensure a hgh long-term throughput for each S-D par, a scheduler s ntroduced to determne whch nodes wll transmt pacets, whch pacets they wll transmt, and at whch power levels P () t the pacets wll be transmtted from node. As a measurement metrc, the throughput ( n) λ s a random quantty dependng on the random locatons and movements of the nodes. The capacty of the networ s consdered as the total throughput to all S-D pars. Based on ths model wth moblty, we can compute the theoretcal results for the capacty n case of ether wthout relayng nodes or wth relayng nodes, whch are dscussed n detals n secton 3.3. Untl now we have satsfactory models for the wreless ad hoc networs wth both statc and moble nodes. However, as we have seen, n Model 1, 2 and 3, we only consder the capacty of the networs wthout any consderatons on the delay. In order to acheve hgh capacty, we assume pacets can be relayed and buffered n the ntermedate nodes, ths mght cause very large delay when the buffer length s long and the number of ntermedate nodes s large. So t s necessary and mportant to get some deas on the pacet delay n the networs. Bansal and Lu [3] set up a model to address ths problem, wth more assumptons on the moblty pattern and traffc pattern. 2.4 Model 4 (delay model n [3]) Frst, the ad hoc networ conssts of n statc nodes and m moble nodes lyng n a ds of unt area. The statc nodes are unformly dstrbuted over the unt crcular ds and never move. The moble nodes are randomly dstrbuted n the ds ntally, later they wll change postons and veloctes wth a moblty model. There are many models to do so, here a unform moblty model s used. Intally each moble node moves at speed v nsde the unt crcular ds. The drectons of movement are ndependent and unformly dstrbuted n [ 0,2π ). At subsequent tme the node pcs a drecton unformly dstrbuted n ( 0,2π ] and moves n that drecton for a dstance d at speed v, where d s an exponentally dstrbuted random varable wth mean µ. And so on. When the node reaches the boundary of the ds, t s reflected bac to the ds agan. Smlarly we use the physcal model for transmsson wth mnor modfcatons. At tme t, let S 1, S 2, m, S m be the senders wth postons 1, 2,, m and let R be the recever wth poston 0. If S use power P () t for transmsson, t causes a successful recepton by node R f N + P () t P () t 0 0 β.

6 The same performance metrc s used as n the frst 3 models. But besdes capacty, the pacet delay s also consdered. From ths model, Bansal and Lu proves t s possble to acheve a hgh throughput whle eepng the delay under some threshold, furthermore, a routng protocol s proposed to mplement the obectve, whch s descrbed n secton 3.4. Wth studyng the evoluton of the models of wreless ad hoc networs, we almost solve our proposed problem by addng more and more assumptons to the smple model. Ths s a very mportant methodology to do research. 3. Man Results We have descrbed the models to solve the problem step by step. In ths secton we wll lst the man results for dfferent models and explan the mportance n desgnng a wreless ad hoc networs. We won t go through the dervatons of those results, the readers can refer to the papers ([1], [2], [3]) f nterested n the detals. 3.1 Model 1 (model of arbtrary networs n [1]) Result 1 (man result 1 n [1]) Wth the transmsson model of Protocol Model, the transport capacty of networs n Model 1 s Θ ( W n ) bt-meters per second gven that the nodes are optmally placed, the traffc pattern s optmally allocated, and the range of transmsson s optmally chosen. Result 2 (man result 2 n [1]) Wth the transmsson model of Physcal Model, cw n / whle c ' Wn 1 bt-meters per seconds s not feasble for approprate c, 1 Wn Specfcally, 1 2 n + 8π / β bt-meters per second s feasble, ' c. bt-meters per second (n a multple of 4) s feasble when the networ s approprately desgned, wth an upper bound of β + 2 Wn bt-meters per second. π β From these results, we can drectly conclude that for arbtrary networ model, the Θ W n. If the total capacty s capacty of wreless ad hoc networ s n the order of ( ) W equally dvded among all the nodes, then each node can acheve the capacty of Θ n bt-meters per second. Furthermore, consder each source node transmts to the

7 destnaton about the same dstance of 1m apart, each node can obtan a capacty of W Θ bts per second. n 3.2 Model 2 (model of random networs n [1]) Result 3 (man result 3 n [1]) In case of both the surface of the sphere and a planar ds, the order of the throughput capacty s ( ) W λ n = Θ bts per second for the Protocol Model. The upper bound nlog n ' can be ndcated by the fact that for some c, lm Pr ' W ob λ ( n) = c s feasble = 0. n log n n Specfcally, there exsts constants c '' ''', c ndependent on n, or W, such that '' ''' c W c W λ ( n) = bts per second s feasble, and λ( n) = bts per 2 2 ( 1+ ) n log n nlog n second s not feasble, wth the probablty approachng one as n. Result 4 (man result 4 n [1]) Wth the transmsson model of Physcal Model, a throughput of ( ) cw λ n = Θ bts nlog n ' c W per second s feasble, whle λ( n) = bts per second s not feasble, for approprate c, n ' c, wth probablty approachng one as n. Specfcally, there exsts constants '' ''' c and c ndependent on n, N,, β or W, such that '' c W λ( n) = bts per second s feasble wth 1 2 n log n ''' c β probablty approachng one as n. If L s the mean dstance between two ponts ndependently and unformly dstrbuted n the doman (ether surface of sphere or planar ds of unt area), then there s a determnstc sequence ε ( n) 0, ndependent on 8 W 1+ ε ( n) N,, β or W, such that bt-meters per second s not feasble 1 / π L( β 1) n wth probablty approachng one as n.

8 From these results, we can see for random networ model, the capacty s n the order of ( ) W λ n = Θ, less than the capacty n the arbtrary networ mode. That s nlog n because we add some lmtatons on the traffc pattern. Furthermore, from result 3, we can get some nsghts on what lmts the capacty. In the case of a ds on the plane, the nodes lyng n the center wll have more possbltes to relay pacets, so-called hot spots, but the order of throughput capacty s the same as on the surface of the sphere. That shows the cause of the throughput constrcton s not the formaton of hot spots, but s the pervasve need for all nodes to share the channel locally wth other nodes. 3.3 Model 3 (model wth moble nodes n [2]) Result 5 (Theorem III-3 n [2]) Consder a schedulng polcy that s only allowed to schedule drect transmsson between the source and destnaton nodes. Say, no relayng s permtted. If c s any 1/ ( 1+ / 2) 2 / 2 β + L constant satsfyng c > π β, ( ) then Pr{ ( ) 1/ 1= / 2 λ n = cn R s feasble} = 0 for suffcently large n. From ths result, we can see the capacty per S-D par goes to 0 as n f no relayng s permtted n the networs. That s because n each source node, hgh power s requred to transmt the pacets drectly to the destnaton node, whch leads to hgh nterference and lmts the capacty. It s possble to gan hgher capacty f we schedule nodes to communcate only wth close neghbors and relay pacets for destnaton nodes far away. Result 6 (Theorem III-4 & Theorem III-5 n [2]) Consder a schedulng polcy π allowng relayng nodes. For a gven S-D par, there s one drect route and n-2 two-hop routes that go through one relay node. The networ can acheve a throughput of Θ () 1 per S-D par,.e., there exsts a constant c > 0 such that lm Pr λ n = cr s feasble = 1 n { ( ) }. Comparng Result 5, 6 wth Result 1, 2 and Result 3, 4, we can see mmedately that f relayng s permtted n the networs, moblty can dramatcally mprove the capacty n from Θ ( n ) or Θ to Θ ( n). lg n

9 3.4 Model 4 (delay model n [3]) Result 7 (man result n [3]) In the wreless ad hoc networ wth n statc nodes and m moble nodes, whch are characterzed n Model 4, there exsts a constant c > 0, such that each sender can W mn( m, n) acheve an average throughput of c, where W s the maxmum avalable 3 nlog n 2 d bandwdth, whle the pacet delay s at most, where d s the dameter of the networ v and v s the velocty of the moble nodes. Ths result solve our problems proposed at the begnnng, n the followng a routng algorthm s descrbed to acheve ths obectve. Result 8 (routng algorthm n [3]) Step 1. Local leader electon A local lead s elected among the statc nodes wthn each regon of sze 1 / m 1/ m. Ths leader wll be responsble for communcatng all the messages of the statc nodes n ts regon wth the moble nodes. Step 2. Statc to moble phase A statc node S1 wantng to send messages to destnaton R frst transfers ts message to ts local leader S. S stores the message and wats for a moble node M1 such that M1 s close enough to S and movng approxmately along the drecton of R. when such a node s avalable S hands over the data from S1 to M1. Step 3. Moble to moble phase The moble nodes relay the pacets towards R amongst all possble moble nodes such that the pacet moves closer and closer to the destnaton. Step 4. Statc to statc phase When the moble node carryng the pacet s close enough to the destnaton, t hands off the pacet to some leader node. Ths pacet s then relayed among the statc leader nodes towards the correct leader node, whch can transmt the pacet to the destnaton node drectly. Wth ths routng algorthm, the wreless ad hoc networ can acheve close-to optmal capacty whle eepng the pacet delay small. Ths algorthm explots the moblty patterns of the nodes to provde guarantees on the pacet delay. The readers can refer to [3] f nterested n the detaled operatons and arguments of the algorthm.

10 4. Concluson In ths proect, we explore the throughput and delay n wreless ad hoc networs. Our obectve s to acheve hgh throughput whle eepng the pacet delay relatvely small. In order to solve ths problem, we start from the smplest model, compute the capacty only, then add more assumptons step by step, and fnally fnd out a routng algorthm whch can acheve our obectves. Ths s a very mportant methodology for any nd of research. W For wreless ad hoc networs wth only statc nodes, the capacty per node s Θ n bts per second for Arbtrary Networ model, and W Θ for Random Networ n lg n model. If moblty s consdered n the networ, the capacty can be dramatcally mproved to Θ () 1 per S-D par. Furthermore, f more assumptons on the traffc pattern and moblty pattern are ntroduced, the proposed routng algorthm can guarantee the pacet delay and acheve a close-to optmal capacty, whch s only a poly-logarthmc factor off from the optmal algorthm. Note that we have no consderatons on the energy lmtaton of the nodes n the networ, whch s another mportant constrant actually exstng n the wreless ad hoc networs. References: [1] Pyush Gupta and P. R. Kumar, The Capacty of Wreless Networs, IEEE Transactons on Informaton Theory, Vol. 46, No. 2, March [2] Matthas Grossglauser and Davd Tse, Moblty Increases the Capacty of Ad Hoc Wreless Networs, IEEE/ACM Transactons on Networng, Vol. 10, No. 4, August [3] Nhl Bansal and Zhen Lu, Capacty, Delay and Moblty n Wreless Ad-Hoc Networs INFOCOM 2003; Twenty-Second Annual Jont Conference of the IEEE Computer and Communcatons Socetes, IEEE, Volume: 2, 30 March - 3 Aprl 2003.

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

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

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

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

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

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

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

Priv-Code: Preserving Privacy Against Traffic Analysis through Network Coding for Multihop Wireless Networks

Priv-Code: Preserving Privacy Against Traffic Analysis through Network Coding for Multihop Wireless Networks Prv-Code: Preservng Prvacy Aganst Traffc Analyss through Networ Codng for Multhop Wreless Networs Zhguo Wan, Ka Xng, Yunhao Lu MOE Key Lab for Informaton System Securty, School of Software, Tsnghua Natonal

More information

Efficient On-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks

Efficient On-Demand Data Service Delivery to High-Speed Trains in Cellular/Infostation Integrated Networks IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. XX, NO. XX, MONTH 2XX 1 Effcent On-Demand Data Servce Delvery to Hgh-Speed Trans n Cellular/Infostaton Integrated Networks Hao Lang, Student Member,

More information

Luby s Alg. for Maximal Independent Sets using Pairwise Independence

Luby s Alg. for Maximal Independent Sets using Pairwise Independence Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent

More information

Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures

Minimal Coding Network With Combinatorial Structure For Instantaneous Recovery From Edge Failures Mnmal Codng Network Wth Combnatoral Structure For Instantaneous Recovery From Edge Falures Ashly Joseph 1, Mr.M.Sadsh Sendl 2, Dr.S.Karthk 3 1 Fnal Year ME CSE Student Department of Computer Scence Engneerng

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

An Adaptive and Distributed Clustering Scheme for Wireless Sensor Networks

An Adaptive and Distributed Clustering Scheme for Wireless Sensor Networks 2007 Internatonal Conference on Convergence Informaton Technology An Adaptve and Dstrbuted Clusterng Scheme for Wreless Sensor Networs Xnguo Wang, Xnmng Zhang, Guolang Chen, Shuang Tan Department of Computer

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

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

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

1 Example 1: Axis-aligned rectangles

1 Example 1: Axis-aligned rectangles COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture # 6 Scrbe: Aaron Schld February 21, 2013 Last class, we dscussed an analogue for Occam s Razor for nfnte hypothess spaces that, n conjuncton

More information

Wireless Inter-Session Network Coding - An Approach Using Virtual Multicasts

Wireless Inter-Session Network Coding - An Approach Using Virtual Multicasts Wreless Inter-Sesson Network Codng - An Approach Usng Vrtual Multcasts Mchael Hendlmaer,DesmondS.Lun,DanalTraskov,andMurelMédard Insttute for Communcatons Engneerng CCIB RLE Technsche Unverstät München

More information

An Ad Hoc Network Load Balancing Energy- Efficient Multipath Routing Protocol

An Ad Hoc Network Load Balancing Energy- Efficient Multipath Routing Protocol 246 JOURNA OF SOFTWAR, VO. 9, NO. 1, JANUARY 2014 An Ad Hoc Network oad alancng nergy- ffcent Multpath Routng Protocol De-jn Kong Shanx Fnance and Taxaton College, Tayuan, Chna mal: dejnkong@163.com Xao-lng

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

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

Economic-Robust Transmission Opportunity Auction in Multi-hop Wireless Networks

Economic-Robust Transmission Opportunity Auction in Multi-hop Wireless Networks Economc-Robust Transmsson Opportunty Aucton n Mult-hop Wreless Networks Mng L, Pan L, Mao Pan, and Jnyuan Sun Department of Electrcal and Computer Engneerng, Msssspp State Unversty, Msssspp State, MS 39762

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

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

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

Relay Secrecy in Wireless Networks with Eavesdropper

Relay Secrecy in Wireless Networks with Eavesdropper Relay Secrecy n Wreless Networks wth Eavesdropper Parvathnathan Venktasubramanam, Tng He and Lang Tong School of Electrcal and Computer Engneerng Cornell Unversty, Ithaca, NY 14853 Emal : {pv45, th255,

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

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

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

Formulating & Solving Integer Problems Chapter 11 289

Formulating & Solving Integer Problems Chapter 11 289 Formulatng & Solvng Integer Problems Chapter 11 289 The Optonal Stop TSP If we drop the requrement that every stop must be vsted, we then get the optonal stop TSP. Ths mght correspond to a ob sequencng

More information

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

Sangam - Efficient Cellular-WiFi CDN-P2P Group Framework for File Sharing Service

Sangam - Efficient Cellular-WiFi CDN-P2P Group Framework for File Sharing Service Sangam - Effcent Cellular-WF CDN-P2P Group Framework for Fle Sharng Servce Anjal Srdhar Unversty of Illnos, Urbana-Champagn Urbana, USA srdhar3@llnos.edu Klara Nahrstedt Unversty of Illnos, Urbana-Champagn

More information

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP) 6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes

More information

Calculation of Sampling Weights

Calculation of Sampling Weights Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a two-stage stratfed cluster desgn. 1 The frst stage conssted of a sample

More information

Enabling P2P One-view Multi-party Video Conferencing

Enabling P2P One-view Multi-party Video Conferencing Enablng P2P One-vew Mult-party Vdeo Conferencng Yongxang Zhao, Yong Lu, Changja Chen, and JanYn Zhang Abstract Mult-Party Vdeo Conferencng (MPVC) facltates realtme group nteracton between users. Whle P2P

More information

On Secrecy Capacity Scaling in Wireless Networks

On Secrecy Capacity Scaling in Wireless Networks On Secrecy Capacty Scalng n Wreless Networks O. Ozan Koyluoglu, Student Member, IEEE, C. Emre Koksal, Member, IEEE, and esham El Gamal, Fellow, IEEE arxv:0908.0898v [cs.it] 0 Apr 00 Abstract Ths work studes

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

Master s Thesis. Configuring robust virtual wireless sensor networks for Internet of Things inspired by brain functional networks

Master s Thesis. Configuring robust virtual wireless sensor networks for Internet of Things inspired by brain functional networks Master s Thess Ttle Confgurng robust vrtual wreless sensor networks for Internet of Thngs nspred by bran functonal networks Supervsor Professor Masayuk Murata Author Shnya Toyonaga February 10th, 2014

More information

Implementation of Deutsch's Algorithm Using Mathcad

Implementation of Deutsch's Algorithm Using Mathcad Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages - n "Machnes, Logc and Quantum Physcs"

More information

DISTRIBUTED storage systems have been becoming increasingly

DISTRIBUTED storage systems have been becoming increasingly 268 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 28, NO. 2, FEBRUARY 2010 Cooperatve Recovery of Dstrbuted Storage Systems from Multple Losses wth Network Codng Yuchong Hu, Ynlong Xu, Xaozhao

More information

Forecasting the Direction and Strength of Stock Market Movement

Forecasting the Direction and Strength of Stock Market Movement Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems

More information

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

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

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

An Efficient Recovery Algorithm for Coverage Hole in WSNs

An Efficient Recovery Algorithm for Coverage Hole in WSNs An Effcent Recover Algorthm for Coverage Hole n WSNs Song Ja 1,*, Wang Balng 1, Peng Xuan 1 School of Informaton an Electrcal Engneerng Harbn Insttute of Technolog at Weha, Shanong, Chna Automatc Test

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

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

"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

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

RequIn, a tool for fast web traffic inference

RequIn, a tool for fast web traffic inference RequIn, a tool for fast web traffc nference Olver aul, Jean Etenne Kba GET/INT, LOR Department 9 rue Charles Fourer 90 Evry, France Olver.aul@nt-evry.fr, Jean-Etenne.Kba@nt-evry.fr Abstract As networked

More information

Network Aware Load-Balancing via Parallel VM Migration for Data Centers

Network Aware Load-Balancing via Parallel VM Migration for Data Centers Network Aware Load-Balancng va Parallel VM Mgraton for Data Centers Kun-Tng Chen 2, Chen Chen 12, Po-Hsang Wang 2 1 Informaton Technology Servce Center, 2 Department of Computer Scence Natonal Chao Tung

More information

VoIP over Multiple IEEE 802.11 Wireless LANs

VoIP over Multiple IEEE 802.11 Wireless LANs SUBMITTED TO IEEE TRANSACTIONS ON MOBILE COMPUTING 1 VoIP over Multple IEEE 80.11 Wreless LANs An Chan, Graduate Student Member, IEEE, Soung Chang Lew, Senor Member, IEEE Abstract IEEE 80.11 WLAN has hgh

More information

Secure Walking GPS: A Secure Localization and Key Distribution Scheme for Wireless Sensor Networks

Secure Walking GPS: A Secure Localization and Key Distribution Scheme for Wireless Sensor Networks Secure Walkng GPS: A Secure Localzaton and Key Dstrbuton Scheme for Wreless Sensor Networks Q M, John A. Stankovc, Radu Stoleru 2 Department of Computer Scence, Unversty of Vrgna, USA 2 Department of Computer

More information

One-Shot Games for Spectrum Sharing among Co-Located Radio Access Networks

One-Shot Games for Spectrum Sharing among Co-Located Radio Access Networks One-Shot Games for Spectrum Sharng among Co-Located Rado Access etwors Sofonas Halu, Alexs A. Dowhuszo, Olav Tronen and Lu We Department of Communcatons and etworng, Aalto Unversty, P.O. Box 3000, FI-00076

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

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

Packet Dispersion and the Quality of Voice over IP Applications in IP networks

Packet Dispersion and the Quality of Voice over IP Applications in IP networks acet Dsperson and the Qualty of Voce over I Applcatons n I networs Ham Zlatorlov, Hanoch Levy School of Computer Scence Tel Avv Unversty Tel Avv, Israel Abstract- Next Generaton Networs (NGN and the mgraton

More information

Mobility Control with Local Views of Neighborhood in Mobile Networks

Mobility Control with Local Views of Neighborhood in Mobile Networks Moblty Control wth Local Vews of Neghborhood n Moble Networks Zhen Jang Je W Robert Klne Dept. of Compter Scence Dept. of Compter Sc. and Eng. Dept. of Compter Scence West Chester Unversty Florda Atlantc

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

Load Balanced Rendezvous Data Collection in Wireless Sensor Networks

Load Balanced Rendezvous Data Collection in Wireless Sensor Networks 2011 Eghth IEEE Internatonal Conference on Moble Ad-Hoc and ensor ystems Load Balanced endezvous Data Collecton n Wreless ensor Networks Luo Ma 1, Longfe hangguan 1, Chao Lang 1, Junzhao Du 1, Hu Lu 1,

More information

A Dynamic Load Balancing Algorithm in Heterogeneous Network

A Dynamic Load Balancing Algorithm in Heterogeneous Network 06 7th Internatonal Conference on Intellgent Systems Modellng and Smulaton A Dynamc Load Balancng Algorthm n Heterogeneous etwork Zhxong Dng Xngjun Wang and Wenmng Yang Shenzhen Key Lab of Informaton Securty

More information

On the Interaction between Load Balancing and Speed Scaling

On the Interaction between Load Balancing and Speed Scaling On the Interacton between Load Balancng and Speed Scalng Ljun Chen, Na L and Steven H. Low Engneerng & Appled Scence Dvson, Calforna Insttute of Technology, USA Abstract Speed scalng has been wdely adopted

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

Schedulability Bound of Weighted Round Robin Schedulers for Hard Real-Time Systems

Schedulability Bound of Weighted Round Robin Schedulers for Hard Real-Time Systems Schedulablty Bound of Weghted Round Robn Schedulers for Hard Real-Tme Systems Janja Wu, Jyh-Charn Lu, and We Zhao Department of Computer Scence, Texas A&M Unversty {janjaw, lu, zhao}@cs.tamu.edu Abstract

More information

Ad-Hoc Games and Packet Forwardng Networks

Ad-Hoc Games and Packet Forwardng Networks 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

An Enhanced Super-Resolution System with Improved Image Registration, Automatic Image Selection, and Image Enhancement

An Enhanced Super-Resolution System with Improved Image Registration, Automatic Image Selection, and Image Enhancement An Enhanced Super-Resoluton System wth Improved Image Regstraton, Automatc Image Selecton, and Image Enhancement Yu-Chuan Kuo ( ), Chen-Yu Chen ( ), and Chou-Shann Fuh ( ) Department of Computer Scence

More information

Joint Scheduling of Processing and Shuffle Phases in MapReduce Systems

Joint Scheduling of Processing and Shuffle Phases in MapReduce Systems Jont Schedulng of Processng and Shuffle Phases n MapReduce Systems Fangfe Chen, Mural Kodalam, T. V. Lakshman Department of Computer Scence and Engneerng, The Penn State Unversty Bell Laboratores, Alcatel-Lucent

More information

Downlink Power Allocation for Multi-class. Wireless Systems

Downlink Power Allocation for Multi-class. Wireless Systems Downlnk Power Allocaton for Mult-class 1 Wreless Systems Jang-Won Lee, Rav R. Mazumdar, and Ness B. Shroff School of Electrcal and Computer Engneerng Purdue Unversty West Lafayette, IN 47907, USA {lee46,

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

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

How To Improve Delay Throughput In Wireless Networks With Multipath Routing And Channel Codeing

How To Improve Delay Throughput In Wireless Networks With Multipath Routing And Channel Codeing Delay-Throughput Enhancement n Wreless Networs wth Mult-path Routng and Channel Codng Kevan Ronas, Student Member, IEEE, Amr-Hamed Mohsenan-Rad, Member, IEEE, Vncent W.S. Wong, Senor Member, IEEE, Sathsh

More information

How To Understand The Results Of The German Meris Cloud And Water Vapour Product

How To Understand The Results Of The German Meris Cloud And Water Vapour Product 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 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

Optimization of network mesh topologies and link capacities for congestion relief

Optimization of network mesh topologies and link capacities for congestion relief Optmzaton of networ mesh topologes and ln capactes for congeston relef D. de Vllers * J.M. Hattngh School of Computer-, Statstcal- and Mathematcal Scences Potchefstroom Unversty for CHE * E-mal: rwddv@pu.ac.za

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

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed

More information

On File Delay Minimization for Content Uploading to Media Cloud via Collaborative Wireless Network

On File Delay Minimization for Content Uploading to Media Cloud via Collaborative Wireless Network On Fle Delay Mnmzaton for Content Uploadng to Meda Cloud va Collaboratve Wreless Network Ge Zhang and Yonggang Wen School of Computer Engneerng Nanyang Technologcal Unversty Sngapore Emal: {zh0001ge, ygwen}@ntu.edu.sg

More information

An MILP model for planning of batch plants operating in a campaign-mode

An MILP model for planning of batch plants operating in a campaign-mode An MILP model for plannng of batch plants operatng n a campagn-mode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafe-concet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño

More information

Self-Motivated Relay Selection for a Generalized Power Line Monitoring Network

Self-Motivated Relay Selection for a Generalized Power Line Monitoring Network Self-Motvated Relay Selecton for a Generalzed Power Lne Montorng Network Jose Cordova and Xn Wang 1, Dong-Lang Xe 2, Le Zuo 3 1 Department of Electrcal and Computer Engneerng, State Unversty of New York

More information

Computer Networks 55 (2011) 3503 3516. Contents lists available at ScienceDirect. Computer Networks. journal homepage: www.elsevier.

Computer Networks 55 (2011) 3503 3516. Contents lists available at ScienceDirect. Computer Networks. journal homepage: www.elsevier. Computer Networks 55 (2011) 3503 3516 Contents lsts avalable at ScenceDrect Computer Networks journal homepage: www.elsever.com/locate/comnet Bonded defct round robn schedulng for mult-channel networks

More information

The Greedy Method. Introduction. 0/1 Knapsack Problem

The Greedy Method. Introduction. 0/1 Knapsack Problem The Greedy Method Introducton We have completed data structures. We now are gong to look at algorthm desgn methods. Often we are lookng at optmzaton problems whose performance s exponental. For an optmzaton

More information

How To Solve A Problem In A Powerline (Powerline) With A Powerbook (Powerbook)

How To Solve A Problem In A Powerline (Powerline) With A Powerbook (Powerbook) MIT 8.996: Topc n TCS: Internet Research Problems Sprng 2002 Lecture 7 March 20, 2002 Lecturer: Bran Dean Global Load Balancng Scrbe: John Kogel, Ben Leong In today s lecture, we dscuss global load balancng

More information

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.

To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently. Corporate Polces & Procedures Human Resources - Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:

More information

Inter-Ing 2007. INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 15-16 November 2007.

Inter-Ing 2007. INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 15-16 November 2007. Inter-Ing 2007 INTERDISCIPLINARITY IN ENGINEERING SCIENTIFIC INTERNATIONAL CONFERENCE, TG. MUREŞ ROMÂNIA, 15-16 November 2007. UNCERTAINTY REGION SIMULATION FOR A SERIAL ROBOT STRUCTURE MARIUS SEBASTIAN

More information

Demographic and Health Surveys Methodology

Demographic and Health Surveys Methodology samplng and household lstng manual Demographc and Health Surveys Methodology Ths document s part of the Demographc and Health Survey s DHS Toolkt of methodology for the MEASURE DHS Phase III project, mplemented

More information

Evaluation of Coordination Strategies for Heterogeneous Sensor Networks Aiming at Surveillance Applications

Evaluation of Coordination Strategies for Heterogeneous Sensor Networks Aiming at Surveillance Applications Evaluaton of Coordnaton Strateges for Heterogeneous Sensor Networs Amng at Survellance Applcatons Edson Pgnaton de Fretas, *, Tales Hemfarth*, Carlos Eduardo Perera*, Armando Morado Ferrera, Flávo Rech

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

Software project management with GAs

Software project management with GAs Informaton Scences 177 (27) 238 241 www.elsever.com/locate/ns Software project management wth GAs Enrque Alba *, J. Francsco Chcano Unversty of Málaga, Grupo GISUM, Departamento de Lenguajes y Cencas de

More information

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School

Robust Design of Public Storage Warehouses. Yeming (Yale) Gong EMLYON Business School Robust Desgn of Publc Storage Warehouses Yemng (Yale) Gong EMLYON Busness School Rene de Koster Rotterdam school of management, Erasmus Unversty Abstract We apply robust optmzaton and revenue management

More information

Extending Probabilistic Dynamic Epistemic Logic

Extending Probabilistic Dynamic Epistemic Logic Extendng Probablstc Dynamc Epstemc Logc Joshua Sack May 29, 2008 Probablty Space Defnton A probablty space s a tuple (S, A, µ), where 1 S s a set called the sample space. 2 A P(S) s a σ-algebra: a set

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

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

Distributed Optimal Contention Window Control for Elastic Traffic in Wireless LANs

Distributed Optimal Contention Window Control for Elastic Traffic in Wireless LANs Dstrbuted Optmal Contenton Wndow Control for Elastc Traffc n Wreless LANs Yalng Yang, Jun Wang and Robn Kravets Unversty of Illnos at Urbana-Champagn { yyang8, junwang3, rhk@cs.uuc.edu} Abstract Ths paper

More information

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts

Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts Power-of-wo Polces for Sngle- Warehouse Mult-Retaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)

More information

Hybrid Log-based Fault Tolerant scheme for Mobile Computing System Yongning Zhai1, a, Zhenpeng Xu1, b, Weini Zeng1, c

Hybrid Log-based Fault Tolerant scheme for Mobile Computing System Yongning Zhai1, a, Zhenpeng Xu1, b, Weini Zeng1, c 2nd Internatonal Conference on Advances n Mechancal Engneerng and Industral Informatcs (AMEII 2016) Hybrd Log-based Fault Tolerant scheme for Moble Computng System Yongnng Zha1, a, Zhenpeng Xu1, b, Wen

More information

2008/8. An integrated model for warehouse and inventory planning. Géraldine Strack and Yves Pochet

2008/8. An integrated model for warehouse and inventory planning. Géraldine Strack and Yves Pochet 2008/8 An ntegrated model for warehouse and nventory plannng Géraldne Strack and Yves Pochet CORE Voe du Roman Pays 34 B-1348 Louvan-la-Neuve, Belgum. Tel (32 10) 47 43 04 Fax (32 10) 47 43 01 E-mal: corestat-lbrary@uclouvan.be

More information

A User-Centric Approach for Dynamic Resource Allocation in CDMA systems based on Hopfield Neural Networks

A User-Centric Approach for Dynamic Resource Allocation in CDMA systems based on Hopfield Neural Networks A User-Centrc Approach for Dynamc esource Allocaton n CDA systems based on Hopfeld eural etworks. García. Agustí J. érez-omero Unverstat ompeu Fabra (UF) Unverstat oltècnca de Catalunya (UC) Barcelona

More information

On the Interaction between Load Balancing and Speed Scaling

On the Interaction between Load Balancing and Speed Scaling On the Interacton between Load Balancng and Speed Scalng Ljun Chen and Na L Abstract Speed scalng has been wdely adopted n computer and communcaton systems, n partcular, to reduce energy consumpton. An

More information

Period and Deadline Selection for Schedulability in Real-Time Systems

Period and Deadline Selection for Schedulability in Real-Time Systems Perod and Deadlne Selecton for Schedulablty n Real-Tme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information