Mobile Agents in Telecommunications Networks A Simulative Approach to Load Balancing
|
|
- Julius Wade
- 8 years ago
- Views:
Transcription
1 Moble Agets Telecommucatos Networks A Smulatve Approach to Load Balacg Steffe Lpperts Departmet of Computer Scece (4), Uversty of Techology Aache Aache, 52056, Germay Ad Brgt Kreller Corporate Techology Departmet, Semes AG Much, 8730, Germay ABSTRACT Networks today are growg cotuously complex, wth ew kds of servces beg cluded ad heterogeeous etworks terworkg as a whole. Telecommucatos etworks partcular have become truly global etworks, cosstg of a varety of atoal ad regoal etworks, both wred ad wreless. Cosequetly, the maagemet of telecommucatos etworks s becomg a creasgly complex task, as sze ad complexty costtute crtcal requremets that have to be met. Decetralzed approaches to etwork maagemet are curretly beg dscussed, as s has become evdet that cetral solutos caot cope wth scalablty ssues. Moble aget techology partcular s beg examed as a ew dstrbuted system ad etwork paradgm. Oe vtal ssue telecommucatos etworks maagemet s load balacg, as t allows to effcetly use the etwork to capacty ad avod overload stuatos. I ths paper, we wll exame swarmg tellgece of moble agets as a bass for the developmet of a decetralzed load balacg mechasm telecommucatos etworks. Varous strateges for swarmg tellgece wll be evaluated ad compared to covetoal approaches wth a smulatve approach. Keywords: Moble Agets, Smulato, Load Balacg, Telecommucatos Networks, Swarmg Itellgece.. INTRODUCTION Telecommucatos etworks today are volatle commucato etworks whch cosst of heterogeeous, very ofte compatble, mult-vedor evromets. Crcumstaces such as these cause the maagemet of telecommucatos etworks to be complex ad to cota operator-tesve tasks that eed cosderable huma volvemet. Legacy etwork maagemet systems [,2], however, follow a cetralzed approach whch causes a umber of problems. The maagemet formato to be processed threates to excess the capabltes of the huma maagers. Moreover, the maagemet solutos are sestve to the rapdly chagg etwork codtos ad addto caot effcetly cope wth the growg scale of the etworks. I order to avod the formato overload, decetralzed approaches to etwork maagemet are curretly beg examed [3,4], wth moble aget techology [5,6] playg a crucal role may of these approaches [7,8]. Ths paper focuses o a moble aget based approach to load balacg telecommucatos etworks. Load balacg ams at evely dstrbutg the load over a etwork, thus leavg o routers dle ad prevetg overloads for others. If o load balacg mechasms are appled, etwork cogestos ca occur eve f may of the etwork s odes are ot used to capacty at all. Cetralzed approaches to load balacg, whch wll be dscussed more detal secto 4, suffer from the same problems as other cetralzed maagemet solutos. Therefore, ths paper we preset a dstrbuted approach whch s motvated by bologcal pheomea. I ature, several examples ca be observed where a tellget ad effcet behavor of a overall system results from the terworkg of autoomous dvduals obeyg smple rules, e.g. sect swarms, fsh schools, ad brd flocks. Ths behavor s beg examed by Artfcal Lfe [9], a research area whch forms part of the Artfcal Itellgece (AI) work. Artfcal Lfe tres to determe whch way the smple rules ad behavoral patters result a overall system executo. For ths, the autoomous dvdual staces ad the rules drectg ther local teracto ad goal-drected behavor are beg examed. It has bee foud out that there s o behavoral cotrol o a global level, whch s called localty of the system. It s rather a property called emergece whch causes the complex, dyamc, ad structured behavor o system level. Emergece s the crucal property Artfcal Lfe ad deotes the occurrece of a system property drawg from the teracto of dvdual compoets, wthout havg bee specfed explctly or beg drectly deductble [0]. The term self-orgazato ths cotext descrbes the emergece of a mproved system structure, e.g. wth regard to stablty or fault-tolerace. Apart from the autoomy of the compoets, ther localty, ad emergece, there are a umber of addtoal characterstcs of such systems. Sce all of the compoets act autoomously ad locally, they have a hgh degree of parallelsm. Ths parallel dyamsm dffers from the predomatly sequetal mode of executo whch s gve tradtoal computer ad etwork archtectures. Trasferrg results of Artfcal Lfe to computers ad etworks therefore
2 troduces a ew problem solvg approach whch wll be dscussed detal the followg. Aother property of Artfcal Lfe models s called temporal varace of the compoets,.e. these compoets have a predefed lfecycle. They are created ad the rema uchaged, whle able to multply, ad evetually are termated. The latter ca be trggered by the stace tself or by aother compoet. Ths lfecycle s ofte exteded by moblty,.e. the compoets are able to move through the system autoomously. Together wth the gve lfecycle, especally the ablty to multply, the populato of the system thus ca dyamcally adapt to a chagg evromet. I the followg secto, we wll descrbe swarmg tellgece whch deals wth the emergece of group behavor ad show how t tegrates wth Artfcal Lfe. We wll the pot out how moble agets ca be regarded as a challegg techology for swarmg tellgece strateges. Secto three troduces a swarmg tellgece archtecture for load balacg telecommucatos etworks whch s based o moble agets. Secto four descrbes dfferet strateges for the load balacg process whch ca be mplemeted wth moble agets. The developmet of a smulatve tool for the evaluato of these strateges ad the results are preseted secto fve. The fal secto cocludes wth a summary ad a outlook o future work. 2. SWARMING INTELLIGENCE I the frst secto, Artfcal Lfe has bee troduced as a ew problem solvg paradgm for complex dstrbuted systems ad etworks. Research Artfcal Lfe ca be dstgushed two categores. Frst, work s beg executed to aalyze ad mtate bologcal ad socal mechasms. Secod, the applcato ad adaptato of models for lfelke behavor basg o bologcal systems to artfcal systems s amed at. I order to acheve the latter, partcular to apply Artfcal Lfe models to computer ad commucato etworks, moble agets costtute a promsg techology, as ther characterstcs ca be mapped drectly to the prcples outled above. moble aget creato ad cofgurato take both ther code ad status alog ad trasfer themselves to aother host ad cotue executo there, thus fulfllg the moblty property. The ablty to mgrate also eables the meetg cocept where moble agets frst meet at a commo locato ad the teract locally, thus addressg the localty property. Fally, as moble agets act autoomously ad addto are parallel processes, they ca be take as a bass to trasfer Artfcal Lfe models to computer ad commucato etworks. I ths paper, moble agets techology s used for a decetralzed load balacg of telecommucatos etworks. The problem solvg techque appled s a swarmg tellgece method,.e. based o depedet, autoomous agets wth the overall system behavor drawg from the emergece of ther teracto. Fgure 2 shows how swarmg tellgece ca be classfed as part of Artfcal Lfe. Swarmg tellgece solutos offer a umber of advatages f appled dstrbuted system ad etworkg ssues. Frst of all, cotrast to cetralzed approaches, there s o problem wth scalablty, as a swarm of depedet agets costtutes a etrely decetralzed soluto whch ca adopt to the sze of a system by reproducto ad mgrato. I addto, swarmg tellgece provdes hghly adaptve systems, as the agets lfecycle ad ther ablty to mgrate allows to dyamcally adopt to chagg system requremets. Therefore, swarmg tellgece s partcularly sutable for large ad hghly dyamc systems. Moreover, wth agets beg autoomous,.e. able to execute wthout relyg o other agets, the overall system based o depedet agets s robust ad fault tolerat. Whle the crash of a cetral compoet a cetralzed approach wll cause the etre system to fal, the termato of a group of agets ca cause a system to act less effcetly, but t wll ot cause the etre system to halt. Cellular Robotc System Decetralsed Robotc System Sesor-Based Behavour Group Itellgece Emergece of Orgazato/Socety Emergece of Group Behavour Coloy of Socal Isect Socety of Huma Begs Ats Fsh School Swarmg Itellgece Flock mgratg executg suspeded Collectve Itellgece Bees Emergece of Idvduals returg home Reforcemet Learg Cellular Automato L-System Artfcal Neural Network Geetc Algorthms dyg Fgure : The Moble Aget Lfecycle Model As show fgure, moble agets adhere to a lfecycle whch s detcal to the property of temporal varace. Equally mportatly, moble agets are able to mgrate,.e. to Fgure 2: Swarmg Itellgece Artfcal Lfe Last but ot least, cocevg a problem soluto based o dvdual ad self-cotaed compoets results hghly modular ad clearly structured systems, thus mprovg mateace ad updates. Bearg these potetal beefts md, the ext secto explas how moble aget techology ca be deployed for a swarmg tellgece the load balacg process of a telecommucatos etwork.
3 3. A MOBILE AGENT BASED ARCHITECTURE FOR LOAD BALANCING A vtal ssue telecommucatos etworks s the avalablty of les ad servces. Frst of all, t must be esured that the umber of calls whch are blocked or lost are kept to a mmum. At frst sght, t mght therefore be a straghtforward soluto to geerously provde capactes to avod stuatos of hgh load. Ths, however, s ether effcet or ecoomcally feasble. It must rather be amed at utlzg the avalable capactes to a maxmum degree. Load balacg addresses the topc of dstrbutg load over the odes of a etwork. As a cosequece, a hgher umber of calls wll the be allowed to go through ad co-exst. Recet research demostrates the geeral applcablty of moble aget techology for etwork maagemet ad ts potetal beefts [7,8,], especally f the moble agets form a swarmg tellgece [2,3]. Examatos of swarmg tellgece specfc areas of etwork maagemet cover cofgurato maagemet [4] ad fault maagemet [5]. I the followg, we wll focus o swarmg tellgece wth moble agets for load balacg telecommucatos etworks ad preset a decetralzed archtecture whch suts ths purpose. As dscussed later ths paper, t wll serve as a eablg techology for the load balacg strateges. I accordace wth the approach troduced [6], two classes of moble agets are defed by the archtecture depcted fgure 3, load agets ad strategy agets. Load agets operate o the lowest layer of the archtecture. If a load aget s emtted to the etwork, t wll determe the paths offerg the largest free capacty from the curret ode to each of the other odes the etwork ad the modfy the routg tables accordgly, makg use of ts ablty to mgrate to the other odes. The algorthm of Djkstra [7] s appled, ad the moblty of agets allows a straghtforward realzato of ths algorthm. Whle the detals of the algorthm are omtted here, t s mportat to ote that the updates of the routg tables have to be made reverse order,.e. startg from the target ode, order to avod loops. Strategy Maager Compoet Dstrbuted Strategy Maager Strategy Maager Compoet Strategy Maager Compoet The remag capacty of a etre path s set by the coecto elemet wth the mmum free capacty. Hece, the determato of the path offerg the maxmum free capacty requres a examato of all avalable paths ad ther elemets ad the selecto of the path wth the maxmum value. I ths process, both the lks ad the odes of a etwork ca be take to accout, because ether of these ca form a bottleeck for a coecto. Hece, wth gve odes ad lks of varyg capactes, dfferet paths ca be selected accordg to the selecto crtera. A example s gve fgure 4. The umbers dcate the free capacty of the lks ad odes. Takg oly the values of the lks to accout wll result a selecto of path A, whlst regardg the odes or both lks ad odes wll result selecto of path B. The fgure thus also expresses that depedg o the selecto crtera, the path whch s selected eed ot be the shortest coecto, as there s also a drect coecto betwee the two odes avalable. The selecto of loger paths wll result a creased load of the overall etwork. Therefore, load agets ca also be structed to prortze short paths. Deployg moble agets to execute the updates of the routg tables allows to easly modfy the selecto crtera. It s doe smply by emttg the correspodg agets whch wll do the requred modfcatos of the routg tables whle cosderg a gve subset of the crtera. Hece, a chage of the crtera ca eve be doe at rutme by emttg agets wth a modfed set of crtera. Ths s a dcato of the flexblty of the moble aget approach, addto the modularty of the archtecture gve by the fact that the modfcatos of the load agets are etrely trasparet to strategy agets whch operate o top of them. Aalogously, the operato ad modfcato of strategy agets s depedet of the uderlyg load agets Path A Path B Strategy Agets Load Agets Fgure 3: Outle of the Load Balacg Archtecture Fgure 4: Selecto of the Optmal Path Strategy agets are resposble for the populato of load agets,.e. ther creato ad termato, ad for delegatg tasks to them. Sce o cetral stace s gve the moble aget approach for load balacg, strategy agets wll move aroud the etwork radomly ad gather formato about the lks ad odes, such as the curret load ad the umber of
4 calls orgatg from a ode. Comparg the curret values of the load to the mea values of former vsts, the strategy agets ca detect chages of the traffc ad the etwork tself ad the decde o emttg load agets accordgly. What umber of load agets to be created ad whch ode to select for ther emsso, these factors are determed by the strategy appled by the strategy aget. These strateges are preseted detal chapter 4. Accordg to the resposbltes of the strategy agets, they operate two dfferet modes. The frst mode s a purely observg oe, where formato about the evromet s beg collected. If a rregularty or overload stuato has bee detected, the strategy aget wll swtch to the secod mode where t wll emt load agets ad thus start fxg the stuato, f o other strategy aget has already started ths process. Accordg to these two modes, strategy agets wll mutually fluece ther route. A strategy aget wll move to aother ode, f the curret ode s already beg observed by a predefed umber of agets, f aother aget s already workg o that ode, or f there already s a suffcet umber of load agets updatg the routg tables the etwork. Ths two-layered archtecture offers the advatages of load balacg whch were dscussed secto 2, e.g. scalablty ad adaptablty. Drect ter-aget commucato, a mportat research ssue for eablg moble aget deploymet may applcato domas, s a crtcal factor for moble aget solutos. It s curretly beg addressed by stadardzato [8,9] ad research [20,2,22]. Based o swarmg tellgece, the archtecture preseted here s etrely based drect commucato of agets,.e. both load ad strategy agets leave marks for ther peers ad other agets to be foud. Ths avods problems of aget sychrozato ad also equps the archtecture wth addtoal robustess. What s stll eeded, however, s a addtoal layer for the maagemet of the strategy agets, whch wll allow operatos such as motorg, chage of strateges etc. The thrd layer s a Dstrbuted Strategy Maager, depcted fgure 3, whch cossts of dstrbuted Strategy Maagemet Compoets. The Dstrbuted Strategy Maager thus adheres to the de-cetralzed approach ad offers vsualzato ad steerg facltes to the huma maager. For example, f a chage of strategy s to be carred out, the Strategy Maagemet Compoets wll be told to termate all strategy agets followg the expred strategy ad replace them wth ew oes. If a strategy aget has crashed, a ew strategy aget wll be created by a Strategy Maagemet Compoet. Addtoal strategy agets wll be created, f a etwork error s mmet ad error detecto ad recovery s to be stregtheed. Tmestamps ca be deployed to determe falure of agets ad also the curret aget populato of the system. For detals o tmestamp usage, see [6]. A archtecture based o reactve moble agets as preseted ths chapter allows dfferet strateges for load balacg telecommucatos etworks. I the followg chapter, detals of these strateges are dscussed order to expla ther mode of operato, before ther effcecy s aalyzed secto LOAD BALANCING STRATEGIES The edeavor to optmze the usage of etworks ad partcular telecommucatos etworks has lead to tese vestgatos of dstrbutg load over the avalable odes. Accordg to the effort made to balace the load of a etwork, three ma groups of routg strateges ca be dstgushed: statc strateges, dyamc strateges, ad swarmg tellgece strateges wth moble agets. I the begg, oly statc routg was appled. I these approaches, specfc routg tables were geerated before a etwork was take to operato. These routg tables were depedet of tme ad load stuatos. Methods belogg to ths category are for stace FIX (Fxed Routg) ad FAR (Fxed Alterate Routg). I the FIX strategy, all routg tables are set up to cota oly the shortest path to the destato odes. Cosequetly, o load balacg s doe, sce all coectos betwee odes are predetermed. Wth the etwork s load growg, however, t s obvous that these paths soo wll overload ad calls wll be lost, as there s o adaptato to ths stuato. Therefore, the FARx strategy, x alteratve paths to a destato ode are memorzed a ordered lst. If the capacty of the optmal route s low or suffcet, the followup route wll be chose from ths ordered lst of paths. Although ths approach allows to avod overload stuatos through a frst, yet very rgd load balacg, t stll does ot adapt to the actual load of the etwork. I recet years, dyamc strateges have come up whch allow a adaptato of the routg tables at rutme, depedg o the gve etwork load. The best kow strateges of ths category are DAR (Dyamc Alterate Routg) from Brtsh Telecom [23], ADR (Adaptve Dyamc Routg) from Norther Telecom [24,25], ad DNHR (Dyamc No- Herarchcal Routg) from AT&T [26]. All of the dyamc strateges determe a umber of alteratve paths from source odes to destato odes, but cotrast to statc strateges, the curret load of the odes ad lks are take to cosderato whe ths lst of paths s frequetly updated. Ths guaratees that stuatos of hgh load o a gve path, the alteratve path whch meets the curret stuato of the etwork best wll be selected. A ew category of strateges s establshed whe evaluatg the applcablty ad effcecy of moble aget based swarmg solutos for load balacg, whch would provde the beefts descrbed secto 2. I the remader of ths paper, we wll preset fve strateges of ths kd [27] whch are realzed wth the archtecture descrbed secto 3. Ther performace wll be compared to fve strateges represetg the frst two groups, amely statc, mult-path ad alteratve routg, wth a specfcally developed smulato tool. Two statc strateges (amed strategy 0 ad ) have bee examed. They dffer the umber of alteratve paths avalable for coectg source ad destato odes. I strategy 0, the optmal path accordg to the algorthm of Djkstra for coectg each source ode to the destato odes s calculated advace ad wrtte to the routg tables, ad o load balacg s doe at rutme. Strategy, however, selects a predefed umber of low-cost paths from the set of all possble paths. Sce there mght be a huge overall umber of paths, a restrcto of the legth of the paths to be selected ca be troduced va a hop cout. I the smulato preseted secto 5, the load strategy wll be evely dstrbuted over all of these low-cost paths. Three strateges (amed strategy 2, 3, ad 4) represetg the class of dyamc strateges have bee smulated. Strategy 2 s a decetralzed alteratve routg, where all alteratve paths (possbly restrcted by a hop cout) are determed advace. O etwork operato, each of the odes wll exame ts
5 curret load fxed tervals ad wll select the most sutable path from the predefed set, depedg o ths local formato. Strategy 3 s also decetralzed, but does ot operate o a gve set of alteratve paths. It rather calculates the optmal path to destato odes o the fly, usg the Djkstra algorthm. Ths calculato process s trggered parallel o all odes gve tervals. A varato of ths approach s gve wth strategy 4. I order to avod the massve computato requred strategy 3, the process of applyg the Djkstra algorthm s here started o the odes of a etwork a sequetal order, also gve tervals. The strateges based o the swarmg tellgece archtecture preseted above are amed strategy 5 to 9. They operate o routg tables whch are tally set to the optmal paths betwee odes (oly strategy 9 holds a lst of alteratve paths) ad dyamcally ad adaptvely modfy these routg tables durg etwork executo through the load agets. The strateges dffer from each other the appled method to determe the locato for emttg the load agets to the etwork. I strategy 5, the strategy agets select the ode for lauchg a load aget from of a lst cotag the te most recetly vsted odes. From ths lst, the ode s selected where most calls orgate from,.e. the oe wth the hghest source rate. Load agets strategy 6, however, wll be started o a ode ext to the oe whch curretly holds the largest source rate. Ths ams at freeg capacty at the overloaded ode wthout addg the addtoal computato overhead for the route calculato to the ode tself. Smlarly, strategy 7 starts load agets o all eghborg odes of the overloaded ode, order to maxmze the amout of traffc take away from t. Strategy 8 s smlar to strategy 5, but here threshold values are troduced to avod stabltes. These stabltes have emerged wth strategy 5 ad were caused by a cotuous re-routg of the load. Fally, strategy 9 s a modfcato of the alteratve routg gve strategy, as all possble paths from oe ode to aother are computed advace. Load agets here are emtted aalogy to strategy 5, but they operate oly of the predefed set of alteratve paths,.e. f a strategy aget detects a overloaded ode, a load aget wll be emtted to the ode wth the maxmum source rate. It wll the determe the path offerg the largest free capacty from the set of kow paths. Ths holds the advatage that the computato effort s reduced, but t also eglects eve better paths whch are ot cotaed the set. The followg secto presets the aalytcal codtos ad the results of the smulatos for the dvdual strateges ad thus dcates, whch way moble aget based swarmg tellgece ca cotrbute to load balacg of telecommucatos etworks. 5. SIMULATION RESULTS The am of load balacg mechasms s to evely dstrbute load over a etwork, thus leavg o odes dle ad prevetg overload of others. I other words, the varace of the load over all odes wth a etwork s to be mmzed. I order to formally specfy ths property, the load of a etwork has to be examed more detal. Let s (t) be the overall load caused at ode by outgog calls whch termate at ode k,.e. s ( t) = (I) A k k= Aalogously, let r (t) be the overall load of comg calls at ode, amely r ( t) = (II) A k k= Addtoal load at ode results from paths from ode j to ode k that use ths ode. Ths load s gve by u ( t) = j, k= j k A jk (III) Wth (I-III), the etre load L (t) curretly gve at a ode ca therefore be determed as L (t) = s (t) + u (t) + r (t), where s, u, r 0 (IV) Gve the load of the dvdual odes of the etwork, the mmum varace of the loads the etwork ca be expressed wth the followg optmzato fucto: MIN = t 2 k= t = L t) L ( ) t dt = k ( t 2 t = k= k L ( ) ( ) t Lk t dt (V) Bascally, what s descrbed here s a summato of the load of all odes whch s the dvded by the umber of odes the etwork. Ths wll result the mea load the etwork at tme t. Gve ths mea value, the absolute value of each ode s load varyg from the average load s determed. The summato of these values ad ther tegrato gves the varace of the load the etwork. load uts Frot to back: Strategy 5 (swarmg) Strategy 8 (swarmg) Strategy 9 (swarmg) Strategy 4 (dyamc) Strategy 3 (dyamc) tme/hour Strategy 6 (swarmg) Strategy 7 (swarmg) Strategy 2 (dyamc) Strategy 0 (statc) Strategy (statc) Fgure 5: Comparso of the Mea Varace of all Strateges
6 Ths formula has bee take as a bass for realzg a smulatve tool, whch helps to compare the load balacg strateges preseted above. For a gve etwork, the tool frst talzes the routg tables of the odes accordg to the requremets of the curret strategy ad assgs a tal load to the odes. Durg the smulato of the etwork operato, the load of the dvdual odes s frequetly updated,.e. for each ew coecto ad for each termated coecto, the load of the odes volved s modfed accordgly. The umber of calls to be tated ad termated s take from probablty curves deotg the call frequecy at each tme of the day. These curves ca be adapted to sut the dstrbuto of calls over a perod of tme, e.g. to reflect that durg busess hours, a hgher umber of calls s establshed tha at ght. I parallel to the load dstrbuto, the load balacg processes are smulated, wth the moblty of moble agets take to cosderato case of swarmg tellgece strateges. Smulatos have bee made for each of the te strateges. The mea varace of the strateges, whch allows to compare ther overall effectveess, s show fgure 5. It ca be see that the strategy dsplayg the lowest varace ad thus the hghest effectveess s strategy 5, the swarmg tellgece soluto usg the lst of most recetly vsted odes to determe the locato to start the load agets. The hgh adaptablty of ths strategy s depcted more detal fgure 6. The progress of the load dstrbuto over the selected odes very quckly adapts to a creased ad decreased load of the etwork. Ths s a dcato of the load agets takg specfc actos, wth the overall effect beg ot oly a evely dstrbuted load, but also a very stable operato of the etwork, as the mmedate adaptato mmses temporary mbalaces. load uts tme/hour Kote 5 Kote Fgure 6: Load Dstrbuto over the Nodes for Strategy 5 Comparg the swarmg tellgece strateges to the statc ad dyamc oes, fgure 5 also shows that swarmg tellgece offers very effcet solutos. The three most effcet strateges are all swarmg tellgece based. Merely strateges 6 ad 7 perform worse tha some dyamc strateges. Ths dcates that startg load agets o eghborg odes to avod addtoal usage of hghly loaded odes does ot have a suffcet effect o the traffc of the target ode. Fally, t ca be see, that statc strateges are much less successful provdg etwork robustess ad use to capacty. Kote 9 6. CONCLUSION AND OUTLOOK I ths paper, we have evaluated the deploymet of moble agets form of swarmg tellgece for load balacg telecommucatos etworks. Havg troduced swarmg tellgece characterstcs ad beefts, we have preseted a archtecture deployg layers of moble agets whch serves a robust, flexble, scalable, ad adaptve load balacg. The effcecy of strateges based o ths archtecture has bee show a smulatve approach, usg a specfcally developed tool. For ths tool, we have made a aalytcal model of the load dstrbuto a etwork, whch resulted the defto of a formula deotg the varace of the load telecommucatos etworks. As a ma result, t ca be stated that deploymet of autoomous moble agets, whch s beg dscussed for dfferet applcato areas, especally e-commerce, user maagemet, ad etwork maagemet, has prove to offer beefts for etwork maagemet, specfcally load balacg. Future work cocerg load balacg wll focus o equppg the agets wth oe addtoal characterstc, amely the ablty to lear. Ths wll allow the defto of actve agets, rather tha the purely reactve oes deployed here. Agets wll the be capable to uderstad recurrg traffc patters ad to take precautoary actos. For example, they ca be able to foresee stuatos of hgh load ad act e.g. by adjustg the umber of load agets advace. 7. ACKNOWLEDGMENTS Ths work was partally fuded by the Germa Research Coucl (DFG) uder SFB IMPROVE ad GRK 85/ REFERENCES [] Rama, L.: OSI System ad Network Maagemet. I: IEEE Commucatos: Maagemet of Heterogeeous Networks, vol.36, o.3, March 998 [2] Stallgs, W.: SNMP ad SNMPv2: The Ifrastructure for Network Maagemet. I: IEEE Commucatos: Maagemet of Heterogeeous Networks, vol.36, o.3, March 998 [3] Goldszmdt, G.; Yem, Y.: Delegated Agets for Network Maagemet. I: IEEE Commucatos: Maagemet of Heterogeeous Networks, Vol.36, No.3, March 998 [4] Pavo, J.; Tomas, J.: CORBA for Network ad Servce Maagemet the TINA Framework. I: IEEE Commucatos: Maagemet of Heterogeeous Networks, Vol.36, No.3, March 998 [5] Harrso, C.; Chess, D.; Kershebaum, A.: Moble Agets: Are they a good dea? Techcal Report RC 9887, IBM Res., March 995 [6] Pham, A.; Karmouch, A.: Moble Software Agets: A Overvew. I: IEEE Commucatos Magaze, July 998 [7] Bald, M.; Ga, S.; Pcco, G.: Explotg Code Moblty Decetralsed ad Flexble Network Maagemet. I: Proceedgs of Frst Iteratoal Workshop Moble Agets '97, Berl, Germay, Aprl 997
7 [8] Beszczad, A.; Pagurek, B.; Whte, T.: Moble Agets for Network Maagemet. I: IEEE Commucatos Surveys, September 998 [9] Lagto, C.: Artfcal Lfe. Proceedgs of a Iterdscplary Workshop o the Sythess ad Smulato of Lvg Thgs, Los Alamos, New Mexco, 987 [0] Forrest, St.: Emerget Computato: Self-Orgasg, Collectve ad Co-Operatve Pheomea Natural ad Artfcal Computg Networks. I: Emerget Computato. MIT Press, 99 [] Saha, A.; Mor, C.: Eablg a Moble Network Maager (MNM) Through Moble Agets. I: Proceedgs of Secod Iteratoal Workshop Moble Agets '98, Stuttgart, Germay, 998 [2] Whte, T.; Pagurek, B.: Towards Mult-Swarm Problem Solvg Networks. I: Proceedgs of the 3rd Iteratoal Coferece o Mult-Aget Systems (ICMAS '98), July, 998 [3] Whte, T.; Pagurek, B; Oppacher, F.: ASGA: Improvg the At System by Itegrato wth Geetc Algorthms. I: Proceedgs of the 3rd Coferece o Geetc Programmg (GP/SGA'98), July 998 [4] Pagurek, B.; L, Y.; Beszczad, A. et al.: Network Cofgurato Maagemet Heterogeeous ATM Evromets. I: Proceedgs of the 3rd Iteratoal Workshop o Agets Telecommucatos Applcatos IATA'98, Aget-World'98, Pars, Frace, July 998 [5] Whte, T.; Beszczad, A.; Pagurek, B.: Dstrbuted Fault Locato Networks Usg Moble Agets. I: Proceedgs of the 3rd Iteratoal Workshop o Agets Telecommucatos Applcatos IATA'98, AgetWorld'98, Pars, Frace, July 998 [6] Appleby, S.; Steward, S.: Moble Software Agets for Cotrol Telecommucato Networks. I: BT Techology Joural, Aprl 994 [7] Djkstra, E.W.: A Note o Two Problems Coecto wth Graphs. I: Numerc Mathematcs, p , 959 [8] Foudato for Itellget Physcal Agets: Aget Commucato Laguage. Geeva, Swtzerlad, October 997 [9] GMD Fokus: Moble Aget System Iteroperablty Facltes Specfcato. Jot Submsso, November 997 [20] Bauma, J.; Hohl, F.; Radoukls, N. et al.: Commucato Cocepts for Moble Aget Systems. I: Proceedgs of Frst Iteratoal Workshop Moble Agets '97, Berl, Germay, Aprl 997 [2] Dömel, P.; Lgau, A.; Drobk, O.: Moble Aget Iteracto Heterogeeous Evromets. I: Proceedgs of Frst Iteratoal Workshop Moble Agets '97, Berl, Germay, Aprl 997 [22] Lpperts, S.: CORBA for Iter-Aget Commucato of Maagemet Iformato. I: 5th Iteratoal Workshop o Moble Multmeda Com-mu--ca-to, Berl, Germay, October 998 [23] Stacey, R.; Soghurst, D.: Dyamc Alteratve Routg the Brtsh Telecom Trk Network. I: Iteratoal Swtchg Symposum ISS87, Phoex, USA, 987 [24] Chemul, P.; Gauther, P.: Adaptve Traffc Routg Telephoe Networks. I: L Echo de Recherches, Eglsh Issue, 990 [25] Reger, J.; Camero, W.: State-Depedet Dyamc Traffc Maagemet for Telephoe Networks. I: IEEE Commucatos Magaze, October 990 [26] Ash, G.; Cardwell, R.; Murray, R.: Desg ad Optmsato of Networks wth Dyamc Routg. I: Bell System Techcal Joural, vol.60, 98 [27] Kreller, B.: Moble Agets for the Effcet Load Balacg Maagemet Telecommucato Networks. Otto-v.-Guercke-Uverstät Magdeburg, 996
6.7 Network analysis. 6.7.1 Introduction. References - Network analysis. Topological analysis
6.7 Network aalyss Le data that explctly store topologcal formato are called etwork data. Besdes spatal operatos, several methods of spatal aalyss are applcable to etwork data. Fgure: Network data Refereces
More informationIDENTIFICATION OF THE DYNAMICS OF THE GOOGLE S RANKING ALGORITHM. A. Khaki Sedigh, Mehdi Roudaki
IDENIFICAION OF HE DYNAMICS OF HE GOOGLE S RANKING ALGORIHM A. Khak Sedgh, Mehd Roudak Cotrol Dvso, Departmet of Electrcal Egeerg, K.N.oos Uversty of echology P. O. Box: 16315-1355, ehra, Ira sedgh@eetd.ktu.ac.r,
More informationNumerical Methods with MS Excel
TMME, vol4, o.1, p.84 Numercal Methods wth MS Excel M. El-Gebely & B. Yushau 1 Departmet of Mathematcal Sceces Kg Fahd Uversty of Petroleum & Merals. Dhahra, Saud Araba. Abstract: I ths ote we show how
More informationThe impact of service-oriented architecture on the scheduling algorithm in cloud computing
Iteratoal Research Joural of Appled ad Basc Sceces 2015 Avalable ole at www.rjabs.com ISSN 2251-838X / Vol, 9 (3): 387-392 Scece Explorer Publcatos The mpact of servce-oreted archtecture o the schedulg
More informationMaintenance Scheduling of Distribution System with Optimal Economy and Reliability
Egeerg, 203, 5, 4-8 http://dx.do.org/0.4236/eg.203.59b003 Publshed Ole September 203 (http://www.scrp.org/joural/eg) Mateace Schedulg of Dstrbuto System wth Optmal Ecoomy ad Relablty Syua Hog, Hafeg L,
More informationGreen Master based on MapReduce Cluster
Gree Master based o MapReduce Cluster Mg-Zh Wu, Yu-Chag L, We-Tsog Lee, Yu-Su L, Fog-Hao Lu Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of Electrcal Egeerg Tamkag Uversty, Tawa, ROC Dept of
More informationRESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL CLOUD APPLICATIONS
Joural of Theoretcal ad Appled Iformato Techology 3 st October 22. Vol. 44 No.2 25-22 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 RESEARCH ON PERFORMANCE MODELING OF TRANSACTIONAL
More informationLoad Balancing Algorithm based Virtual Machine Dynamic Migration Scheme for Datacenter Application with Optical Networks
0 7th Iteratoal ICST Coferece o Commucatos ad Networkg Cha (CHINACOM) Load Balacg Algorthm based Vrtual Mache Dyamc Mgrato Scheme for Dataceter Applcato wth Optcal Networks Xyu Zhag, Yogl Zhao, X Su, Ruyg
More informationAgent-based modeling and simulation of multiproject
Aget-based modelg ad smulato of multproject schedulg José Alberto Araúzo, Javer Pajares, Adolfo Lopez- Paredes Socal Systems Egeerg Cetre (INSISOC) Uversty of Valladold Valladold (Spa) {arauzo,pajares,adolfo}ssoc.es
More informationChapter 3. AMORTIZATION OF LOAN. SINKING FUNDS R =
Chapter 3. AMORTIZATION OF LOAN. SINKING FUNDS Objectves of the Topc: Beg able to formalse ad solve practcal ad mathematcal problems, whch the subjects of loa amortsato ad maagemet of cumulatve fuds are
More informationCyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), January Edition, 2011
Cyber Jourals: Multdscplary Jourals cece ad Techology, Joural of elected Areas Telecommucatos (JAT), Jauary dto, 2011 A ovel rtual etwork Mappg Algorthm for Cost Mmzg ZHAG hu-l, QIU Xue-sog tate Key Laboratory
More informationProjection model for Computer Network Security Evaluation with interval-valued intuitionistic fuzzy information. Qingxiang Li
Iteratoal Joural of Scece Vol No7 05 ISSN: 83-4890 Proecto model for Computer Network Securty Evaluato wth terval-valued tutostc fuzzy formato Qgxag L School of Software Egeerg Chogqg Uversty of rts ad
More informationA New Bayesian Network Method for Computing Bottom Event's Structural Importance Degree using Jointree
, pp.277-288 http://dx.do.org/10.14257/juesst.2015.8.1.25 A New Bayesa Network Method for Computg Bottom Evet's Structural Importace Degree usg Jotree Wag Yao ad Su Q School of Aeroautcs, Northwester Polytechcal
More informationRQM: A new rate-based active queue management algorithm
: A ew rate-based actve queue maagemet algorthm Jeff Edmods, Suprakash Datta, Patrck Dymod, Kashf Al Computer Scece ad Egeerg Departmet, York Uversty, Toroto, Caada Abstract I ths paper, we propose a ew
More informationEfficient Traceback of DoS Attacks using Small Worlds in MANET
Effcet Traceback of DoS Attacks usg Small Worlds MANET Yog Km, Vshal Sakhla, Ahmed Helmy Departmet. of Electrcal Egeerg, Uversty of Souther Calfora, U.S.A {yogkm, sakhla, helmy}@ceg.usc.edu Abstract Moble
More informationImpact of Mobility Prediction on the Temporal Stability of MANET Clustering Algorithms *
Impact of Moblty Predcto o the Temporal Stablty of MANET Clusterg Algorthms * Aravdha Vekateswara, Vekatesh Saraga, Nataraa Gautam 1, Ra Acharya Departmet of Comp. Sc. & Egr. Pesylvaa State Uversty Uversty
More information10.5 Future Value and Present Value of a General Annuity Due
Chapter 10 Autes 371 5. Thomas leases a car worth $4,000 at.99% compouded mothly. He agrees to make 36 lease paymets of $330 each at the begg of every moth. What s the buyout prce (resdual value of the
More informationA Parallel Transmission Remote Backup System
2012 2d Iteratoal Coferece o Idustral Techology ad Maagemet (ICITM 2012) IPCSIT vol 49 (2012) (2012) IACSIT Press, Sgapore DOI: 107763/IPCSIT2012V495 2 A Parallel Trasmsso Remote Backup System Che Yu College
More informationAPPENDIX III THE ENVELOPE PROPERTY
Apped III APPENDIX III THE ENVELOPE PROPERTY Optmzato mposes a very strog structure o the problem cosdered Ths s the reaso why eoclasscal ecoomcs whch assumes optmzg behavour has bee the most successful
More informationECONOMIC CHOICE OF OPTIMUM FEEDER CABLE CONSIDERING RISK ANALYSIS. University of Brasilia (UnB) and The Brazilian Regulatory Agency (ANEEL), Brazil
ECONOMIC CHOICE OF OPTIMUM FEEDER CABE CONSIDERING RISK ANAYSIS I Camargo, F Fgueredo, M De Olvera Uversty of Brasla (UB) ad The Brazla Regulatory Agecy (ANEE), Brazl The choce of the approprate cable
More informationProactive Detection of DDoS Attacks Utilizing k-nn Classifier in an Anti-DDos Framework
World Academy of Scece, Egeerg ad Techology Iteratoal Joural of Computer, Electrcal, Automato, Cotrol ad Iformato Egeerg Vol:4, No:3, 2010 Proactve Detecto of DDoS Attacks Utlzg k-nn Classfer a At-DDos
More informationA DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS
L et al.: A Dstrbuted Reputato Broker Framework for Web Servce Applcatos A DISTRIBUTED REPUTATION BROKER FRAMEWORK FOR WEB SERVICE APPLICATIONS Kwe-Jay L Departmet of Electrcal Egeerg ad Computer Scece
More informationUsing Phase Swapping to Solve Load Phase Balancing by ADSCHNN in LV Distribution Network
Iteratoal Joural of Cotrol ad Automato Vol.7, No.7 (204), pp.-4 http://dx.do.org/0.4257/jca.204.7.7.0 Usg Phase Swappg to Solve Load Phase Balacg by ADSCHNN LV Dstrbuto Network Chu-guo Fe ad Ru Wag College
More informationANOVA Notes Page 1. Analysis of Variance for a One-Way Classification of Data
ANOVA Notes Page Aalss of Varace for a Oe-Wa Classfcato of Data Cosder a sgle factor or treatmet doe at levels (e, there are,, 3, dfferet varatos o the prescrbed treatmet) Wth a gve treatmet level there
More informationof the relationship between time and the value of money.
TIME AND THE VALUE OF MONEY Most agrbusess maagers are famlar wth the terms compoudg, dscoutg, auty, ad captalzato. That s, most agrbusess maagers have a tutve uderstadg that each term mples some relatoshp
More informationApplications of Support Vector Machine Based on Boolean Kernel to Spam Filtering
Moder Appled Scece October, 2009 Applcatos of Support Vector Mache Based o Boolea Kerel to Spam Flterg Shugag Lu & Keb Cu School of Computer scece ad techology, North Cha Electrc Power Uversty Hebe 071003,
More informationModels for Selecting an ERP System with Intuitionistic Trapezoidal Fuzzy Information
JOURNAL OF SOFWARE, VOL 5, NO 3, MARCH 00 75 Models for Selectg a ERP System wth Itutostc rapezodal Fuzzy Iformato Guwu We, Ru L Departmet of Ecoomcs ad Maagemet, Chogqg Uversty of Arts ad Sceces, Yogchua,
More informationOptimal Packetization Interval for VoIP Applications Over IEEE 802.16 Networks
Optmal Packetzato Iterval for VoIP Applcatos Over IEEE 802.16 Networks Sheha Perera Harsha Srsea Krzysztof Pawlkowsk Departmet of Electrcal & Computer Egeerg Uversty of Caterbury New Zealad sheha@elec.caterbury.ac.z
More informationOnline Appendix: Measured Aggregate Gains from International Trade
Ole Appedx: Measured Aggregate Gas from Iteratoal Trade Arel Burste UCLA ad NBER Javer Cravo Uversty of Mchga March 3, 2014 I ths ole appedx we derve addtoal results dscussed the paper. I the frst secto,
More informationNetwork dimensioning for elastic traffic based on flow-level QoS
Network dmesog for elastc traffc based o flow-level QoS 1(10) Network dmesog for elastc traffc based o flow-level QoS Pas Lassla ad Jorma Vrtamo Networkg Laboratory Helsk Uversty of Techology Itroducto
More informationAbraham Zaks. Technion I.I.T. Haifa ISRAEL. and. University of Haifa, Haifa ISRAEL. Abstract
Preset Value of Autes Uder Radom Rates of Iterest By Abraham Zas Techo I.I.T. Hafa ISRAEL ad Uversty of Hafa, Hafa ISRAEL Abstract Some attempts were made to evaluate the future value (FV) of the expected
More informationAnySee: Peer-to-Peer Live Streaming
ysee: Peer-to-Peer Lve Streamg School of Computer Scece ad Techology Huazhog Uversty of Scece ad Techology Wuha, 40074, Cha {xflao, hj, dfdeg }@hust.edu.c Xaofe Lao, Ha J, *Yuhao Lu, *Loel M. N, ad afu
More informationSHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN
SHAPIRO-WILK TEST FOR NORMALITY WITH KNOWN MEAN Wojcech Zelńsk Departmet of Ecoometrcs ad Statstcs Warsaw Uversty of Lfe Sceces Nowoursyowska 66, -787 Warszawa e-mal: wojtekzelsk@statystykafo Zofa Hausz,
More informationAN ALGORITHM ABOUT PARTNER SELECTION PROBLEM ON CLOUD SERVICE PROVIDER BASED ON GENETIC
Joural of Theoretcal ad Appled Iformato Techology 0 th Aprl 204. Vol. 62 No. 2005-204 JATIT & LLS. All rghts reserved. ISSN: 992-8645 www.jatt.org E-ISSN: 87-395 AN ALGORITHM ABOUT PARTNER SELECTION PROBLEM
More informationThe Analysis of Development of Insurance Contract Premiums of General Liability Insurance in the Business Insurance Risk
The Aalyss of Developmet of Isurace Cotract Premums of Geeral Lablty Isurace the Busess Isurace Rsk the Frame of the Czech Isurace Market 1998 011 Scetfc Coferece Jue, 10. - 14. 013 Pavla Kubová Departmet
More informationAutomated Event Registration System in Corporation
teratoal Joural of Advaces Computer Scece ad Techology JACST), Vol., No., Pages : 0-0 0) Specal ssue of CACST 0 - Held durg 09-0 May, 0 Malaysa Automated Evet Regstrato System Corporato Zafer Al-Makhadmee
More informationStudy on prediction of network security situation based on fuzzy neutral network
Avalable ole www.ocpr.com Joural of Chemcal ad Pharmaceutcal Research, 04, 6(6):00-06 Research Artcle ISS : 0975-7384 CODE(USA) : JCPRC5 Study o predcto of etwork securty stuato based o fuzzy eutral etwork
More informationDiscrete-Event Simulation of Network Systems Using Distributed Object Computing
Dscrete-Evet Smulato of Network Systems Usg Dstrbuted Object Computg Welog Hu Arzoa Ceter for Itegratve M&S Computer Scece & Egeerg Dept. Fulto School of Egeerg Arzoa State Uversty, Tempe, Arzoa, 85281-8809
More informationA particle swarm optimization to vehicle routing problem with fuzzy demands
A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg, Ye-me Qa A partcle swarm optmzato to vehcle routg problem wth fuzzy demads Yag Peg 1,Ye-me Qa 1 School of computer ad formato
More informationA particle Swarm Optimization-based Framework for Agile Software Effort Estimation
The Iteratoal Joural Of Egeerg Ad Scece (IJES) olume 3 Issue 6 Pages 30-36 204 ISSN (e): 239 83 ISSN (p): 239 805 A partcle Swarm Optmzato-based Framework for Agle Software Effort Estmato Maga I, & 2 Blamah
More informationResearch on Cloud Computing and Its Application in Big Data Processing of Railway Passenger Flow
325 A publcato of CHEMICAL ENGINEERING TRANSACTIONS VOL. 46, 2015 Guest Edtors: Peyu Re, Yacag L, Hupg Sog Copyrght 2015, AIDIC Servz S.r.l., ISBN 978-88-95608-37-2; ISSN 2283-9216 The Itala Assocato of
More informationHow To Balance Load On A Weght-Based Metadata Server Cluster
WLBS: A Weght-based Metadata Server Cluster Load Balacg Strategy J-L Zhag, We Qa, Xag-Hua Xu *, Ja Wa, Yu-Yu Y, Yog-Ja Re School of Computer Scece ad Techology Hagzhou Daz Uversty, Cha * Correspodg author:xhxu@hdu.edu.c
More informationThe analysis of annuities relies on the formula for geometric sums: r k = rn+1 1 r 1. (2.1) k=0
Chapter 2 Autes ad loas A auty s a sequece of paymets wth fxed frequecy. The term auty orgally referred to aual paymets (hece the ame), but t s ow also used for paymets wth ay frequecy. Autes appear may
More informationDynamic Service and Data Migration in the Clouds
2009 33rd Aual IEEE Iteratoal Computer Software ad Applcatos Coferece Dyamc Servce ad Data Mgrato the Clouds We Hao Departmet of Computer Scece Norther Ketucky Uversty haow1@ku.edu Abstract Cloud computg
More informationAverage Price Ratios
Average Prce Ratos Morgstar Methodology Paper August 3, 2005 2005 Morgstar, Ic. All rghts reserved. The formato ths documet s the property of Morgstar, Ic. Reproducto or trascrpto by ay meas, whole or
More informationTESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION
TESTING AND SECURITY IN DISTRIBUTED ECONOMETRIC APPLICATIONS REENGINEERING VIA SOFTWARE EVOLUTION Cosm TOMOZEI 1 Assstat-Lecturer, PhD C. Vasle Alecsadr Uversty of Bacău, Romaa Departmet of Mathematcs
More informationHow To Make A Supply Chain System Work
Iteratoal Joural of Iformato Techology ad Kowledge Maagemet July-December 200, Volume 2, No. 2, pp. 3-35 LATERAL TRANSHIPMENT-A TECHNIQUE FOR INVENTORY CONTROL IN MULTI RETAILER SUPPLY CHAIN SYSTEM Dharamvr
More informationDynamic Two-phase Truncated Rayleigh Model for Release Date Prediction of Software
J. Software Egeerg & Applcatos 3 63-69 do:.436/jsea..367 Publshed Ole Jue (http://www.scrp.org/joural/jsea) Dyamc Two-phase Trucated Raylegh Model for Release Date Predcto of Software Lafe Qa Qgchua Yao
More informationIntegrating Production Scheduling and Maintenance: Practical Implications
Proceedgs of the 2012 Iteratoal Coferece o Idustral Egeerg ad Operatos Maagemet Istabul, Turkey, uly 3 6, 2012 Itegratg Producto Schedulg ad Mateace: Practcal Implcatos Lath A. Hadd ad Umar M. Al-Turk
More informationCredibility Premium Calculation in Motor Third-Party Liability Insurance
Advaces Mathematcal ad Computatoal Methods Credblty remum Calculato Motor Thrd-arty Lablty Isurace BOHA LIA, JAA KUBAOVÁ epartmet of Mathematcs ad Quattatve Methods Uversty of ardubce Studetská 95, 53
More informationBanking (Early Repayment of Housing Loans) Order, 5762 2002 1
akg (Early Repaymet of Housg Loas) Order, 5762 2002 y vrtue of the power vested me uder Secto 3 of the akg Ordace 94 (hereafter, the Ordace ), followg cosultato wth the Commttee, ad wth the approval of
More informationApplication of Grey Relational Analysis in Computer Communication
Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato Jgcha J Applcato of Grey Relatoal Aalyss Computer Commucato Network Securty Evaluato *1 Jgcha J *1, Frst ad Correspodg Author
More informationDynamic Provisioning Modeling for Virtualized Multi-tier Applications in Cloud Data Center
200 IEEE 3rd Iteratoal Coferece o Cloud Computg Dyamc Provsog Modelg for Vrtualzed Mult-ter Applcatos Cloud Data Ceter Jg B 3 Zhlag Zhu 2 Ruxog Ta 3 Qgbo Wag 3 School of Iformato Scece ad Egeerg College
More informationADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN
Colloquum Bometrcum 4 ADAPTATION OF SHAPIRO-WILK TEST TO THE CASE OF KNOWN MEAN Zofa Hausz, Joaa Tarasńska Departmet of Appled Mathematcs ad Computer Scece Uversty of Lfe Sceces Lubl Akademcka 3, -95 Lubl
More informationAn Approach to Evaluating the Computer Network Security with Hesitant Fuzzy Information
A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog A Approach to Evaluatg the Computer Network Securty wth Hestat Fuzzy Iformato Jafeg Dog, Frst ad Correspodg Author
More informationChapter Eight. f : R R
Chapter Eght f : R R 8. Itroducto We shall ow tur our atteto to the very mportat specal case of fuctos that are real, or scalar, valued. These are sometmes called scalar felds. I the very, but mportat,
More informationSuspicious Transaction Detection for Anti-Money Laundering
Vol.8, No. (014), pp.157-166 http://dx.do.org/10.1457/jsa.014.8..16 Suspcous Trasacto Detecto for At-Moey Lauderg Xgrog Luo Vocatoal ad techcal college Esh Esh, Hube, Cha es_lxr@16.com Abstract Moey lauderg
More informationA Study of Unrelated Parallel-Machine Scheduling with Deteriorating Maintenance Activities to Minimize the Total Completion Time
Joural of Na Ka, Vol. 0, No., pp.5-9 (20) 5 A Study of Urelated Parallel-Mache Schedulg wth Deteroratg Mateace Actvtes to Mze the Total Copleto Te Suh-Jeq Yag, Ja-Yuar Guo, Hs-Tao Lee Departet of Idustral
More informationModeling of Router-based Request Redirection for Content Distribution Network
Iteratoal Joural of Computer Applcatos (0975 8887) Modelg of Router-based Request Redrecto for Cotet Dstrbuto Network Erw Harahap, Jaaka Wjekoo, Rajtha Teekoo, Fumto Yamaguch, Shch Ishda, Hroak Nsh Hroak
More informationAn Evaluation of Naïve Bayesian Anti-Spam Filtering Techniques
Proceedgs of the 2007 IEEE Workshop o Iformato Assurace Uted tates Mltary Academy, West Pot, Y 20-22 Jue 2007 A Evaluato of aïve Bayesa At-pam Flterg Techques Vkas P. Deshpade, Robert F. Erbacher, ad Chrs
More informationCommercial Pension Insurance Program Design and Estimated of Tax Incentives---- Based on Analysis of Enterprise Annuity Tax Incentives
Iteratoal Joural of Busess ad Socal Scece Vol 5, No ; October 204 Commercal Peso Isurace Program Desg ad Estmated of Tax Icetves---- Based o Aalyss of Eterprse Auty Tax Icetves Huag Xue, Lu Yatg School
More informationT = 1/freq, T = 2/freq, T = i/freq, T = n (number of cash flows = freq n) are :
Bullets bods Let s descrbe frst a fxed rate bod wthout amortzg a more geeral way : Let s ote : C the aual fxed rate t s a percetage N the otoal freq ( 2 4 ) the umber of coupo per year R the redempto of
More informationOptimization Model in Human Resource Management for Job Allocation in ICT Project
Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Optmzato Model Huma Resource Maagemet for Job Allocato ICT Project Saghamtra Mohaty Malaya Kumar Nayak 2 2 Professor ad Head Research
More informationA Security-Oriented Task Scheduler for Heterogeneous Distributed Systems
A Securty-Oreted Tas Scheduler for Heterogeeous Dstrbuted Systems Tao Xe 1 ad Xao Q 2 1 Departmet of Computer Scece, Sa Dego State Uversty, Sa Dego, CA 92182, USA xe@cs.sdsu.edu 2 Departmet of Computer
More informationAn Effectiveness of Integrated Portfolio in Bancassurance
A Effectveess of Itegrated Portfolo Bacassurace Taea Karya Research Ceter for Facal Egeerg Isttute of Ecoomc Research Kyoto versty Sayouu Kyoto 606-850 Japa arya@eryoto-uacp Itroducto As s well ow the
More informationCapacitated Production Planning and Inventory Control when Demand is Unpredictable for Most Items: The No B/C Strategy
SCHOOL OF OPERATIONS RESEARCH AND INDUSTRIAL ENGINEERING COLLEGE OF ENGINEERING CORNELL UNIVERSITY ITHACA, NY 4853-380 TECHNICAL REPORT Jue 200 Capactated Producto Plag ad Ivetory Cotrol whe Demad s Upredctable
More informationImpact of Interference on the GPRS Multislot Link Level Performance
Impact of Iterferece o the GPRS Multslot Lk Level Performace Javer Gozalvez ad Joh Dulop Uversty of Strathclyde - Departmet of Electroc ad Electrcal Egeerg - George St - Glasgow G-XW- Scotlad Ph.: + 8
More informationAlgorithm Optimization of Resources Scheduling Based on Cloud Computing
JOURNAL OF MULTIMEDIA, VOL. 9, NO. 7, JULY 014 977 Algorm Optmzato of Resources Schedulg Based o Cloud Computg Zhogl Lu, Hagu Zhou, Sha Fu, ad Chaoqu Lu Departmet of Iformato Maagemet, Hua Uversty of Face
More information1. The Time Value of Money
Corporate Face [00-0345]. The Tme Value of Moey. Compoudg ad Dscoutg Captalzato (compoudg, fdg future values) s a process of movg a value forward tme. It yelds the future value gve the relevat compoudg
More informationResearch on the Evaluation of Information Security Management under Intuitionisitc Fuzzy Environment
Iteratoal Joural of Securty ad Its Applcatos, pp. 43-54 http://dx.do.org/10.14257/sa.2015.9.5.04 Research o the Evaluato of Iformato Securty Maagemet uder Itutostc Fuzzy Evromet LI Feg-Qua College of techology,
More informationA Novel Resource Pricing Mechanism based on Multi-Player Gaming Model in Cloud Environments
1574 JOURNAL OF SOFTWARE, VOL. 9, NO. 6, JUNE 2014 A Novel Resource Prcg Mechasm based o Mult-Player Gamg Model Cloud Evromets Tea Zhag, Peg Xao School of Computer ad Commucato, Hua Isttute of Egeerg,
More informationSecurity Analysis of RAPP: An RFID Authentication Protocol based on Permutation
Securty Aalyss of RAPP: A RFID Authetcato Protocol based o Permutato Wag Shao-hu,,, Ha Zhje,, Lu Sujua,, Che Da-we, {College of Computer, Najg Uversty of Posts ad Telecommucatos, Najg 004, Cha Jagsu Hgh
More informationDECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT
ESTYLF08, Cuecas Meras (Meres - Lagreo), 7-9 de Septembre de 2008 DECISION MAKING WITH THE OWA OPERATOR IN SPORT MANAGEMENT José M. Mergó Aa M. Gl-Lafuete Departmet of Busess Admstrato, Uversty of Barceloa
More informationThe Gompertz-Makeham distribution. Fredrik Norström. Supervisor: Yuri Belyaev
The Gompertz-Makeham dstrbuto by Fredrk Norström Master s thess Mathematcal Statstcs, Umeå Uversty, 997 Supervsor: Yur Belyaev Abstract Ths work s about the Gompertz-Makeham dstrbuto. The dstrbuto has
More informationThe Time Value of Money
The Tme Value of Moey 1 Iversemet Optos Year: 1624 Property Traded: Mahatta Islad Prce : $24.00, FV of $24 @ 6%: FV = $24 (1+0.06) 388 = $158.08 bllo Opto 1 0 1 2 3 4 5 t ($519.37) 0 0 0 0 $1,000 Opto
More informationCompressive Sensing over Strongly Connected Digraph and Its Application in Traffic Monitoring
Compressve Sesg over Strogly Coected Dgraph ad Its Applcato Traffc Motorg Xao Q, Yogca Wag, Yuexua Wag, Lwe Xu Isttute for Iterdscplary Iformato Sceces, Tsghua Uversty, Bejg, Cha {qxao3, kyo.c}@gmal.com,
More informationClassic Problems at a Glance using the TVM Solver
C H A P T E R 2 Classc Problems at a Glace usg the TVM Solver The table below llustrates the most commo types of classc face problems. The formulas are gve for each calculato. A bref troducto to usg the
More informationCHAPTER 2. Time Value of Money 6-1
CHAPTER 2 Tme Value of Moey 6- Tme Value of Moey (TVM) Tme Les Future value & Preset value Rates of retur Autes & Perpetutes Ueve cash Flow Streams Amortzato 6-2 Tme les 0 2 3 % CF 0 CF CF 2 CF 3 Show
More informationPreprocess a planar map S. Given a query point p, report the face of S containing p. Goal: O(n)-size data structure that enables O(log n) query time.
Computatoal Geometry Chapter 6 Pot Locato 1 Problem Defto Preprocess a plaar map S. Gve a query pot p, report the face of S cotag p. S Goal: O()-sze data structure that eables O(log ) query tme. C p E
More informationLoad Balancing Control for Parallel Systems
Proc IEEE Med Symposum o New drectos Cotrol ad Automato, Chaa (Grèce),994, pp66-73 Load Balacg Cotrol for Parallel Systems Jea-Claude Heet LAAS-CNRS, 7 aveue du Coloel Roche, 3077 Toulouse, Frace E-mal
More informationReport 52 Fixed Maturity EUR Industrial Bond Funds
Rep52, Computed & Prted: 17/06/2015 11:53 Report 52 Fxed Maturty EUR Idustral Bod Fuds From Dec 2008 to Dec 2014 31/12/2008 31 December 1999 31/12/2014 Bechmark Noe Defto of the frm ad geeral formato:
More informationSpeeding up k-means Clustering by Bootstrap Averaging
Speedg up -meas Clusterg by Bootstrap Averagg Ia Davdso ad Ashw Satyaarayaa Computer Scece Dept, SUNY Albay, NY, USA,. {davdso, ashw}@cs.albay.edu Abstract K-meas clusterg s oe of the most popular clusterg
More informationFault Tree Analysis of Software Reliability Allocation
Fault Tree Aalyss of Software Relablty Allocato Jawe XIANG, Kokch FUTATSUGI School of Iformato Scece, Japa Advaced Isttute of Scece ad Techology - Asahda, Tatsuokuch, Ishkawa, 92-292 Japa ad Yaxag HE Computer
More informationLow-Cost Side Channel Remote Traffic Analysis Attack in Packet Networks
Low-Cost Sde Chael Remote Traffc Aalyss Attack Packet Networks Sach Kadloor, Xu Gog, Negar Kyavash, Tolga Tezca, Nkta Borsov ECE Departmet ad Coordated Scece Lab. IESE Departmet ad Coordated Scece Lab.
More informationLoad and Resistance Factor Design (LRFD)
53:134 Structural Desg II Load ad Resstace Factor Desg (LRFD) Specfcatos ad Buldg Codes: Structural steel desg of buldgs the US s prcpally based o the specfcatos of the Amerca Isttute of Steel Costructo
More informationAnalysis of real underkeel clearance for Świnoujście Szczecin waterway in years 2009 2011
Scetfc Jourals Martme Uversty of Szczec Zeszyty Naukowe Akadema Morska w Szczece 2012, 32(104) z. 2 pp. 162 166 2012, 32(104) z. 2 s. 162 166 Aalyss of real uderkeel clearace for Śwoujśce Szczec waterway
More informationOn Error Detection with Block Codes
BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 9, No 3 Sofa 2009 O Error Detecto wth Block Codes Rostza Doduekova Chalmers Uversty of Techology ad the Uversty of Gotheburg,
More informationANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS. Janne Peisa Ericsson Research 02420 Jorvas, Finland. Michael Meyer Ericsson Research, Germany
ANALYTICAL MODEL FOR TCP FILE TRANSFERS OVER UMTS Jae Pesa Erco Research 4 Jorvas, Flad Mchael Meyer Erco Research, Germay Abstract Ths paper proposes a farly complex model to aalyze the performace of
More informationStatistical Pattern Recognition (CE-725) Department of Computer Engineering Sharif University of Technology
I The Name of God, The Compassoate, The ercful Name: Problems' eys Studet ID#:. Statstcal Patter Recogto (CE-725) Departmet of Computer Egeerg Sharf Uversty of Techology Fal Exam Soluto - Sprg 202 (50
More informationOptimal replacement and overhaul decisions with imperfect maintenance and warranty contracts
Optmal replacemet ad overhaul decsos wth mperfect mateace ad warraty cotracts R. Pascual Departmet of Mechacal Egeerg, Uversdad de Chle, Caslla 2777, Satago, Chle Phoe: +56-2-6784591 Fax:+56-2-689657 rpascual@g.uchle.cl
More informationUSEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT
USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT Radovaov Bors Faculty of Ecoomcs Subotca Segedsk put 9-11 Subotca 24000 E-mal: radovaovb@ef.us.ac.rs Marckć Aleksadra Faculty of Ecoomcs Subotca Segedsk
More informationSimple Linear Regression
Smple Lear Regresso Regresso equato a equato that descrbes the average relatoshp betwee a respose (depedet) ad a eplaator (depedet) varable. 6 8 Slope-tercept equato for a le m b (,6) slope. (,) 6 6 8
More informationSoftware Reliability Index Reasonable Allocation Based on UML
Sotware Relablty Idex Reasoable Allocato Based o UML esheg Hu, M.Zhao, Jaeg Yag, Guorog Ja Sotware Relablty Idex Reasoable Allocato Based o UML 1 esheg Hu, 2 M.Zhao, 3 Jaeg Yag, 4 Guorog Ja 1, Frst Author
More informationReinsurance and the distribution of term insurance claims
Resurace ad the dstrbuto of term surace clams By Rchard Bruyel FIAA, FNZSA Preseted to the NZ Socety of Actuares Coferece Queestow - November 006 1 1 Itroducto Ths paper vestgates the effect of resurace
More informationCH. V ME256 STATICS Center of Gravity, Centroid, and Moment of Inertia CENTER OF GRAVITY AND CENTROID
CH. ME56 STTICS Ceter of Gravt, Cetrod, ad Momet of Ierta CENTE OF GITY ND CENTOID 5. CENTE OF GITY ND CENTE OF MSS FO SYSTEM OF PTICES Ceter of Gravt. The ceter of gravt G s a pot whch locates the resultat
More informationAustralian Climate Change Adaptation Network for Settlements and Infrastructure. Discussion Paper February 2010
Australa Clmate Chage Adaptato Network for Settlemets ad Ifrastructure Dscusso Paper February 2010 The corporato of ucertaty assocated wth clmate chage to frastructure vestmet apprasal Davd G. Carmchael
More informationManaging Interdependent Information Security Risks: Cyberinsurance, Managed Security Services, and Risk Pooling Arrangements
Maagg Iterdepedet Iformato Securty Rsks: Cybersurace, Maaged Securty Servces, ad Rsk Poolg Arragemets Xa Zhao Assstat Professor Departmet of Iformato Systems ad Supply Cha Maagemet Brya School of Busess
More informationWeb Service Composition Optimization Based on Improved Artificial Bee Colony Algorithm
JOURNAL OF NETWORKS, VOL. 8, NO. 9, SEPTEMBER 2013 2143 Web Servce Composto Optmzato Based o Improved Artfcal Bee Coloy Algorthm Ju He The key laboratory, The Academy of Equpmet, Beg, Cha Emal: heu0123@sa.com
More informationA Real-time Visual Tracking System in the Robot Soccer Domain
Proceedgs of EUEL obotcs-, Salford, Eglad, th - th Aprl A eal-tme Vsual Trackg System the obot Soccer Doma Bo L, Edward Smth, Huosheg Hu, Lbor Spacek Departmet of Computer Scece, Uversty of Essex, Wvehoe
More informationM. Salahi, F. Mehrdoust, F. Piri. CVaR Robust Mean-CVaR Portfolio Optimization
M. Salah, F. Mehrdoust, F. Pr Uversty of Gula, Rasht, Ira CVaR Robust Mea-CVaR Portfolo Optmzato Abstract: Oe of the most mportat problems faced by every vestor s asset allocato. A vestor durg makg vestmet
More information