Trust Evaluation and Dynamic Routing Decision Based on Fuzzy Theory for MANETs

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1 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER Trus Evaluao ad yamc Roug ecso Based o Fuzzy Theory for ANETs Hogu a, Zhpg Ja ad Zhwe Q School of Compuer Scece ad Techology, Shadog Uversy, Ja, Cha.P.R. Emal: {dahog, zp}@sdu.edu.c, qzw@mal.sdu.edu.c Absrac As a kd of ypcal embedded sysem, ANET s a mul-hop self-cofgurg ework wh he opology chages dyamcally. To model of he secury, mobly, ad dyamc chages of ANET, rus s used as a ovel cocep recely. I hs paper, based o he classc fuzzy heory, he rus evaluao ad he dyamc roug proocols for ANET are represeed, o gve he modelg of ANET wh he fuzzy ferece rules, ad o mprove he roug proocols wh fuzzy dyamc programmg. The expermes wh OPNET show ha he ovel fuzzy rused SR proocols ca reduce he Packe rop Rao ad ehace he hroughpu wh he accepable Ed o Ed elay ANET. Idex Terms embedded sysem, rus roug of ANET, fuzzy rus evaluao, rus modelg wh fuzzy logc, fuzzy dyamc programmg, fuzzy rused SR I. INTROUCTION As a kd of ypcal embedded sysem, he moble adhoc ework (ANET) [2] s a self-cofgurg ework of he moble devces coeced by wreless lks, whch cosss of a lo of low power wreless devces. Each devce (called ode) a ANET s free o move ay dreco depedely, whch exchages he daa ad lk formao wh each oher frequely, o maa he sa commucao by co-operag durg he esablshme of roues forwardg packes o he desao. Usually, he odes ca commucae whou use of ay fxed frasrucure, ad hey are performed hrough he mul-hop roug. For he secury ad varably, curre ypcal roug proocols, such as SR, AOV, LAR [3], have o be horoughly desged ad aalyzed erm of her co-operaos wh each oher, proposed rapd respose well copg wh he usable opology. Sce he ework opology chages dyamcally due o he arbrary mobly of odes ad he odes ca parcpae or whdraw from ANET a ay me, s dffcul o measure he secury ad sably of he dyamcal roug raffc formao. All odes behave as he rouers o ake par he processes of he roug auscrp receved November 12, 2008; revsed July 1, 2009; acceped July 15, Ths work was suppored par by he Naural Scece Foudao of Cha (No ), he Cha Naoal 863 Proec (No. 2007AA01Z105-05) ad he Cha Posdocoral Scece Foudao (No ). dscovery ad maeace o oher odes a he same me, whch eed o share he formao ad he daa saly. Furhermore, as he self-orgazed mul-hop ework, meas wo odes may be ou of drec commucao rage, whch requres he er-medae odes o rasm he messages. Frequely, he odes serve as hos ad rouer smulaeously, so ANET s effce o deal wh he malcous odes aacks, whch usually reles o he dvdual secury soluos wh each ode. All hese are cocluded as he ework facors. O he oher had, each ode s a ypcal embedded sysem, whch sll faces he challeges from s ow characers, such as lmed physcal secury, flexble ode mobly, low maufacurg prce, ad lmed sysem resources (.e., processor, power, sze, sorage). efely, hese hardware/sofware cosras of he ode are crcal o keep he ework safe ad sable, so here s he creasg cocer abou he odes sysem secury ad usably ANET because he odes may be deeply affeced by he real complex evromes ad he malcous aacks ca also am o hese odes. All hese are cocluded as he ode facors. Obvously, s ecessary o keep he odes ad he ework acve wh hese wo facors, bu radoally, hey belogs o ework research ad embedded sysem research separaely, s very dffcul o calculae boh ode facors ad ework facors as a holsc modelg ad aalyss. Recely, rus s carred ou as a se of ew heory ad has bee used o ANET o measure hese egraed facors. I he huma socey, rus s oe of he mos commo coceps, whle rus depeds o a hos of facors whch ca be easly modeled by he compuaoal mehods. I he areas of compuer scece, rus has bee used may felds o mea may dffere hgs. For example, s a descrpor of secury ad ecrypo; a ame for auhecao mehods or dgal sgaures; a measure of he qualy of a peer P2P sysems; a facor game heory; a model for age eracos; a gauge of aackressace; a compoe of ubquous ad dsrbued compug; a foudao for eracos age sysems; or a movao for ole eraco ad recommeders sysems [4]. I ANET, Trus ca be defed ha he curre age has followed he rused age s wllgess ad has he capably o delver a muually agreed servce a gve coex [5]. For example, whe a ode requess he rasmsso servce from s eghbors, he eghbor 2009 ACAEY PUBLISHER do: /sw

2 1092 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER 2009 ode may have behaved o be damaged, overloaded or compromsed malcously, ad leads s dffcul o ge he correc daa or formao by he requesg ode. I hs case, rus ca be used o measure he ework codos ad exeral evromes, ad also o ge he opmal soluos furher [24]. There have bee some algorhms o evaluae he rus of ANET, such as graph heory [6, 7], arkov Cha [8], Bayesa model [9]. Besdes, as a fac ha he uceray exss mos of he facors, fuzzy heory s suable for modelg ad evaluao of he uceray ad boudary ANET. Frs, fuzzy logc ca be used for he rus modelg of ANET. I uses qualave erms ad lgusc labels o represe rus as a fuzzy cocep, ad he membershp fucos descrbe he degree of a peer whch ca be labeled as rusworhy or urusworhy. Fuzzy logc also provdes he rules o reaso wh fuzzy measures. I he modelg of he rus, coceps such as rusworhess, hoesy, ad accuracy, are eeded o be defed ad quafed wh he mahemacal mehods a erval, fuzzy logc ca be used o hadle he uceray ad he mprecso. Secod, he calculaed rusworhy value he ca be used o he roug proocols for he praccal purpose. Accordg o he fuzzy ad dyamc feaures of ANET ad he ucera facors roug dscovery, fuzzy dyamc programmg (FP) [10] ca be used o he opmzao of he roug proocols. FP s developed as a process o accep preprocessed pus ad has he oupus whch are furher de-fuzzy for acual applcaos. Because he calculao ad measureme of rus hs usupervsed ad-hoc evrome volves complex aspecs such as credbly rag for opos delvered by a ode, he hoesy of recommedaos provded by a moble ode, or he assessme of pas expereces wh he ode oe o erac wh. The use of FP algorhms ad models exeds fuzzy logc o develop a rus model based o he fuzzy recommedao o solve roug problems. I hs paper, as he exeso of he research [1], based o he classc fuzzy heory, he rus evaluao modelg ad he dyamc roug proocols for ANETs are roduced. Frs, rus evaluao wh fuzzy logc s gve, drecly modelg he odes wh he mahemacal formula, he fuzzy modelg he ma aspecs of ANET wh he fuzzy ferece rules. Secod, he roug decso wh fuzzy dyamc programmg s dscussed, whch cludes he seps ad process o esablsh he fuzzy rused roug, o mpleme he mproved SR proocols (FTSR), ad o ake some useful opmzaos. The expermes have show ha FTSR proocols ca reduce he packe drop rao, ehace he hroughpu wh he accepable ed o ed delay. The res of he paper s orgazed as follows. A overvew of relaed work s gve Seco II. I Seco III, he fuzzy rus evaluao model abou each ode s roduced, cludg drec rus evaluao accordg o he feaures of he ode ad rus evaluao wh fuzzy logc o model he ode, he ework ad he evrome. I Seco IV, how o make he roug decso wh FP s dscussed deal, from he basc rus absraco based o FP, o ge he rused roug model wh FP, ad he abou he opmal equao soluos for rused roug model. I Seco V, he praccal rus roug algorhm wh FP s gve, focus o each sep of he algorhm, o how o make he mul-sage decso, he represes he process o esablsh he fuzzy rused SR, gves wo useful opmzao mehods for FTSR. The smulaos ad expermes wh OPNET are descrbed ad aalyzed Seco VI. The coclusos are gve Seco VII. II. RELATE WORKS Trus s a absrac maer he everyday lfe, bu s releva research o compuer scece s a ew subec. Ths causes a lack of coherece s defos bewee dffere felds compuer scece. Geerally, he oo of rus used hroughou hs paper s defed as: rus s he degree of belef abou he fuure behavor of oher ees, s calculao s based o he pas experece wh ad he observao of he ohers relaed acos [11]. For ANET, rus s erpreed as a relao amog ees ha parcpae varous proocols [12]. os sudes of rus value maageme [13-15] have proposed several rus maageme approaches. [16, 17] proposed he collaborave repuao mechasms o esablsh repuao rags for odes. [18] proposed a sraegy-proof rus maageme from a ode s prevous hoor. Alhough he maageme brgs low overhead, he hoor defo for chagg rus values has o bee defed. [19] preseed a auhecao servce o acheve ework secury by dscoverg ad solag dshoes users, bu he rules of chagg a ode s rus sae bewee good ad bad rus values ware o well defed. I [20, 21], several rus relaoshps are defed for a coex-aware maageme proocol, bu hey may cause error rus relaoshp. [22] proposed a mehod o maage mulcas key rees ha mach he ework opology ad hus reduced he commucao overhead of rekeyg. However, he mpac facors of he key maageme server were o cosdered due o ode mobly. [23] proposed a wo-sep secure auhecao approach for mulcas ANETs wh arkov cha. A ode s rus value s aalyzed from s prevous rus maer ha was performed hs group. The proposed rus model s prove as a couous-me arkov cha model. By moorg he rasmsso behavor, several rus based secury roug algorhms have bee proposed o evaluag ode s repuao. [25] proposed a Secure ad Obecve Repuaobased Iceve (SORI) scheme o ecourage packe forwardg ad dscple selfsh behavor. The scheme, however, does o preve a malcous ode from selecvely forwardg packes or from oher malcous behavor. Toke-based mechasm [26] s a ufed ework layer secury soluo ANETs. I hs scheme, each ode carres a oke order o parcpae 2009 ACAEY PUBLISHER

3 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER ework operaos, ad s local eghbors moor ay msbehavor roug or daa packe forwardg fucos. Spre [27] s a smple, chea-proof, credbased sysem for ANETs, whch uses cred o provde ceves for moble odes o cooperae ad repor acos hoesly. As a exeso o SR, [17] proposed a ew secury roug proocol-confiant. Smlarly wh he Wachdog Pah-raer (WP) mechasm, frsly roduces a moor o ge rusee s rasmsso sae, wh he help of repuao sysem ad rus maager compoe, he mplemes he evaluao ad updae of he rus rag. However, whe he me expres, he ode wll aga ur o be a legmae parcpa, whch may coue s msbehavor. Wha s more, roducg recommedao rus wll make he rus evaluao mecosumg ad cause much more overhead, whch also crease s complexy. [29] gave a rus evaluao scheme dyamcally based o roug model (Trus SR). Fve roug seleco sraeges have bee proposed, whch are based o he rus evaluao of he rasmsso lks. Because s roug seleco s lmed o he roues ha obaed from sadard SR, he ulmae seleced roue s o ecessarly he mos rused oe. Some research has used fuzzy heory o rus evaluao ad roug decso for ANET. RFSTrus [30], a rus model based o fuzzy recommedao smlary, s proposed o quafy ad o evaluae he rusworhess of odes. Fuzzy logc provdes a aural framework o deal wh uceray ad he olerace of mprecse daa pus for he subecve asks of rus evaluao, packe forwardg revew ad credbly adusme. [31] proposed a Fuzzy based Ad hoc Odemad sace Vecor (FAOV) Roug Proocol. The auhors used Fuzzy Logc a rus evaluao ad seup a Threshold Trus Value (TTV) for rus verfcao. Fuzzy Logc based rus evaluao ca gve a raoal predco of rus value ad gve a accurae defcao of malcous behavor based o fuzzy ferece rules. However, he FAOV model oly gves he proeco mehod agas modfcao aacks ad he rus evaluao process oly moors he ode s behavor for roug dscovery bu o for he rasmsso of daa packes. Above all, alhough here have bee some research abou rus modelg, rus evaluao ad rus roug proocols, he research combed fuzzy heory ad rus ANET s sll a ew opc. To ge more rused roug algorhms, s feasble o use FP o rus compug felds oo. III. FUZZY TRUST EVALUATION I ANETs, rus s represeed by he relaoshps eraced wh each oher. Ths ca be absraced as he assocaos bewee a rusg ode ad a rused ode. Trus relaoshps are deermed by he rules o evaluae he evdece wh a quaave way, geeraed by he prevous behavors of a ode. Accordgly, fuzzy logc s he process o formulae he mappg from a gve pu o a logcal oupu, whch provdes he bass from he decsos made, or he paers dscered. Because of he mobly of he odes ad he me-varyg of he wreless chaels, he rus ANET has he aural uceray ad compleeess, he he evaluao models of rus focus o he colleco ad he quazao of he dyamc formao. The rus assocaos bewee wo odes ca be classfed o hree caegores: drec eraco, assocao hrough oher odes recommedaos (drec assocao), ad revew hrough he hsory records. A. rec Trus Evaluao Le T prese he drec rus value from ode o ode, he T ca be go from he hsory records ad coex formao bewee he wo odes. Accordg o [9, 31], a smple formula ca be cocluded as F.3-1. I 1 S k k E 1 T (1 ) I 2 N k 1 k Cq p 3-1 S k preses durg he rece I mes eracos, he real oal servce cou a he kh me bewee ode ad ode. N k preses he expeced servce cou of ode a he kh me. Node ofe makes observao a dffere me saces. Le S k deoe he me whe ode make observao of ode. A me k, ode observes ha ode performs he aco mes upo he reques of performg he aco mes. Obvously, N k S k. These hsory facors descrbe ha he observao has bee made for a perod of me, ad should carry less mporace ha he observao made recely. E p, C q, preses he ode formao a he curre me. E p s he eergy cosumpo formao, whch represes he power resources as he moble embedded sysem; C q s he processor ulzao perceage, whch represes he calculao resources; s he memory ulzao perceage, whch represes he sorage resources. α, β ad γ are all posve egers, whch represes he wegh values of he hree aspecs.ρ [0,1], s he varable coeffce. The proporo of he hsory records ad he ode codo ca be ued wh o le he formula more praccal. B. Trus Evaluao wh Fuzzy Logc Whe ode ask ode for he packe rasmsso of he daa or lk formao, ode has he dffculy o evaluae wheher ode ca provde he servce a ha me or wheher he servce provded by ode s secury ad rusworhy. The, hs suao ca be udged ad moored by ode from he hsory eraco records of ode. Le C() represes he capably of he requesed ode (ode ) o provdg packes rasfer servces a me, whch cludes he rema ulzao rao of baery, local memory, CPU cycle, ad badwdh a ha po. Le H() represes a me, he hsory behavors o offer cera servces bewee he pas me ervals, such as packe-drop rao. Le TL(+1) refers o he ode s rus 2009 ACAEY PUBLISHER

4 1094 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER 2009 level a me +1. Assume he fuzzy member fuco of C() cosss of hree fuzzy ses: LOW(L), edal() ad Hgh(H). The fuzzy membershp fuco of H() ad TL(+1) cosss of four dffere levels of fuzzy ses: LOW(L), edal(), Hgh(H) ad VeryHgh(VH). Accordg o he socal corol heory [28], he fuzzy ferece rules are gve Table I. TABLE I. FUZZY RULES ON TRUST LEVEL TL(T+1) H () L H VH C () L L L H H L H VH The rules Table I esablsh a mappg from H C o TL. I s based o he aalyss of he ode s curre codo ad hsorc behavors. Whe a overloaded ode lacks he CPU cycles, buffer space or avalable ework badwdh o forward packes, wll be also urusworhy ex me erval because of such a low capably level, eve f s hsorc rus level s very hgh. Ths s oly he frs basc rule Table I, ad he he ferece relaoshp ca be cocluded wh R l : R l H C TL ad for h H, c C, u TL, R l ( h, c, H ( h) C( c) TL( 3-3 For all he rules we have he fuzzy ferece relaoshp as F R( h, c, ( h, c, R l l1 For each par of gve pu H * ad C *, use he geeral oal relaoshp R, he oupu ca be calculaed: * * * TL ( H C ) R 3-5 The, wh he maxmal membershp degree approach, he rus value u * [0,1], ca be calculaed wh he defuzzy mehods. Ths s he basc models wh wo aspecs C() ad H().Whle he real world, he evromes of he ANET are also he mpora facors. Le E() represe Iems C() H() E() TABLE II. AIN FACTORS WITH TRUST EVALUATION Coes Power supply Baery codo CPU cycle Local memory Backup of mpora daa Safe sysem checkg aa recovery mechasm Ecrypo Secury of sysem sofware Sysem operao log Commucao badwdh Chael frequecy Ecrypo Roue able maeace Real-me roue dscovery Roue backup log Temperaure osure Lghg A-lghg Error-proof seg he evrome facors, such as emperaure, mosure, ad lghg, mos of hese facors have bee classfed Table II. Respecvely, he mproved resuls ca be modeled ad calculaed wh he smlar process ad he smlar formula above. IV. FUZZY YNAIC ROUTING ECISION Trus s a aural fuzzy cocep, whch poses a fuzzy cosra o he rused roug decso-makg, so he dffere odes mgh provde dverse rougs abou he same odes,.e., dffere odes would have he dffere ad eve oppose rus evaluaos oward a same ode. Based o fuzzy model, each ode ca calculae he rus value for s eghbors ad maa s eghbor roue able. mal values for rus ca occur as a resul of more malcous behavor ha legmae behavor of a eghborg ode. As he rused roug process s also fuzzy, FP s proposed o make he rus roug decso ANET. A. Trus Absraco based o FP I he usual dyamc programmg (P), he soluos of he gve quesos are absraced as he decso processes, he hs process s dvded o several assocaed phases ad here have bee several desged feasble plas each phase. The obecve of he decso s o selec he mos suable plas each phase, o ge he bes overall effec of he whole decso process. I FP, as he exeso of P, he decso s cofed wh fuzzy cosras each phase durg he process o solve he quesos. Because he rus evaluao of each ode has he aural fuzzy feaures, he process of roug dscovery s suable for FP accordgly. Based o FP, The decso model ANET ca be descrbed as: (1) urg he whole decso process, he sysem may appear o be dffere saes. Suppose he oal cou s l, he he sae se s E={e 1,e 2, e l } (2) The sysem should receve he exeral pus o be cofgured or corolled, ad he he curre saes are adused o approach he pre-deermed obec. Suppose he pu se s U={u 1,u 2, u m } (3) Suppose he whole decso process s fulflled he perod of [0, T], a umber of momes are sered o dvde he whole decso process o several phases. For example, he oal of he mome s -1(0= 0 < 1 < < -1 < =T), so he oal of he phases s ad each phase, he me perod s ( k-1, k ] (k=1,2, ). Suppose a he k(0<k<=) phase, he sysem pu s k ) U. (4) suppose a he k-1 mome (ha s a he ed of ( k-2, k-1 ]), he sysem sae s e( k-1 ) ad a he k mome (ha s ( k-1, k ]), he sysem has receved he pu k ), he a he ed of he k mome, he sysem sae e( k ) oly has relaos wh e( k-1 ) ad k ), ha s e( k ) f ( e( k 1 ), k )), k 1,2,..., ACAEY PUBLISHER

5 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER Suppose he sae mgrao has o relao wh he evrome of he curre mome, s allocaed wh a mgrao marx: S11 S12... S1 m S 21 S S 2m S( Sl1 Sl 2... Slm (5) I he marx, S E. S meas f he sysem s he sae e E, f here s he pu u U, he he sysem has he mgrao o S. Tha s: S f ( e, u )( 1,2,..., l; 1,2,..., m) 4-2 If he al sae of he sysem s e( 0 ), he obecve of he FP s a fuzzy se of E, ha s he mome =T, B F(E). Suppose a he phase ( k-1, k ], he acual sysem pu s u, he he acual fuzzy cosra se based o U s C k F(U). Accordg o he gve codos above, he FP ca be descrbed as: Gve e( 0 ), he U * { u u ( 1), 2),..., Of course, U * ca be calculaed wh ), e( ))} e( 1) f ( e( 0), 1)), e( 2) f ( e( 1), 2))..., e( ) f ( e( 1), )) Le F(U * ), f u=( 1 ), 2 ),, 1 ), e( )), he ( C1( 1)) C2 ( 2 ))... C ( )) B ( e( )) So he FP ca be absraced o fdk u * U *, for he resul of ( u * ) ( 4-3 * uu ad u * =(u * ( 1 ), u * ( 2 ),, u * ( 1 ), e * ( )) s he opmal equao soluo. B. Trused Roug odel wh FP sgushed from he radoal roug model LAN eworks, ANET s regarded as a me-vara fe-sae deermsc sysem uder he defe corol. Each ode has a cera sae from he delvered packes perspecve ad he mgrao bewee wo saes ca be coceved from wo odes eraco. The pu corol varables for each sae are he oupu lks wh eghbor odes, ad he he process of roug dscovery equals a mul-sage sae mgrao from al sae o ermae sae. The resul s o ge a rusworhy crcal pah from source ode o desao ode. I order o model he rused roug such evromes, hree basc defos are gve below: efo 1. Sae Se X= { 1, 2,..., l, l 1,..., }, where, =1,2,, represes ode a ad hoc ework wh he scale, s a fe se. efo 2. Goal Se T= { l 1,..., }, whch s a specfed o-fuzzy subse of X, represes he desao s eghbor saes. efo 3. Ipu Se U= { 1,..., m }, where, =1,2, m, equals o m lks he ework. Because he rus codo of he lks s fuzzy by aure, se U s a fuzzy se. Le x be he sae of he packe beg delvered a me, =0,1,2,, whch rages over X, ad le u, =0,1,2,, be he pu corol varable a me, whch rages over U. efe he emporal evoluo of he sysem o be a sae formula F.4-4. x 1 f ( x, u ) 4-4 where =0,1,2,, ad f s a gve fuzzy fuco from X U o X, whch meas ha whe he packe a me arrves a sae x, wh he choosey pu u, he he sae wll be rasferred o sae x +1. Because he pu u s a alerave from he fuzzy se U, ad we assume he fal goal G s o duce he sysem sae o goal se T, so he dscovery of rused roug urs ou o fd a opmal decso by decso makg a fuzzy evrome. Suppose he decso process sars from he al sae 1 ad eds wh, accordg o he defo of goal se T, he process acually would fsh oce he sysem eers T, he ed me ca be gve by: x T, wh x T For <N, where N s he hop-cou. Wh hese codos, fuzzy decso s defed as a erseco of he gve goals ad cosras, whle he fuzzy logc has preseed he malcous behavors based o rus evaluao model, whch cosues he fuzzy cosras as pu varables o hs model. C. Opmal Equao Soluos Accordg o he feaures of he ANET opology ad he mobly of he wreless commucao, a udreced graph ca be used o absrac he ode relaos. As he models descrbed above, he sae mgrao graph ca be cocluded as Fg.1, whch ca be coceved as a ypcal fuzzy sysem. I he sae mgrao graph, a rused rasfer pah s eeded o be foud from al sae S o desao. The ermedae saes amog hem ca rasfer muually accordg o he esablshed mgrao graph. Take sae 4 ad sae 5 as a example, sae 4 may mgrae o sae 2, 3, 5, 6 ad 7, whle sae 5 may mgrae o sae 1, 2, 4, 7 ad 8. oreover, whe sae 4 s mgraed o sae 5, wll be cosraed by s rus degree o sae 5 wh he gve value 0.8 (suppose 0 represes complee dsrus, 2009 ACAEY PUBLISHER

6 1096 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER Fgure1. Par of a sae mgrao graph wh 8 odes. ad 1 represes absolue rus he comg me erval). Whe he sae mgrao process reaches sae 4, wll make a decso o choose whch sae ca be he successor uder he cosra C ad he geeral rus goal G. Accordg o he fuzzy dyamc programmg heory [10], hs fuzzy sysem, for each decso a he cera sage, s membershp fuco could ge s ( ) correspodg maxmal value. Le deoes he h compoe of he opmal goal aame vecor, ad C ( ) s he value of he membershp fuco of he cosra C sae for pu, wh C ( ) =1 for =l+1,,; ad he he decso ca be made as he followg equao: ( ) ( C ( ) ( f (, ))) where =1,2, ; =1,2, m. Also accordg o [10], a opmal polcy mus exs he fe polcy space wh l sages, modfyg from he radoal backward erao algorhm. V. FUZZY ROUTING ALGORITH Fuzzy roug proocols cosder much ucera ework saus as he facor makg roug decsos. The fuzzy roug algorhm moors he cogeso saus of acve rougs ad feeds he ework saus o he fuzzy logc coroller order o make he bes roug decso. A. Trus Roug Algorhm wh FP The mproved roug algorhm s preseed as Trus Roug algorhm based o FP, whch s descrbed Fg.2. B. ulsage ecso akg The backward erao process aes from he desao sae. Each sae volved each decso sage besdes he desao ca be dvded o hree sub-saes. As s show Fg.3, whe he ermedae saes receve he ROUTE ECISION (RE) packe ha Assumpos: each ode he ework maas a rus able abou s eghbor s rus values Ipu: each sae s rus able N( ), X, T Oupu: opmal polcy ( 1 ) from 1 o 1 ( ) 1; ( m ) 0; m 1,2,..., 1. 2 =1; A T; 3 desao broadcass opmal goal value ( ) ; 4 whle (<) 5 {for all X { 6 f ( be rggered && ( f (, )) 0 ) 7 {calculae: ( ) ( C ( ) ( f (, coas he opmal goal value ( x ) from he presage saes, wll be rasferred from Sleep (S) sub-sae o ecso () sub-sae. If he receved value s larger ha he opmal goal value of pre-sage, he sae wll eer he Ready (R) sub-sae, oherwse wll reur o Sleep(S). Afer a broadcas of he ew RE packe, he Ready(R) sub-sae wll also ur o Sleep(S), wag for ew arrval RE packes. Because oe sae always has several eghbors, a sae eed o make a erao decso ul obas he bes choce. Take sae 4 ad sae 5 Fg.1 as a example, suppose a me, boh of hem ges her opmal values, he hey wll broadcas correspodg RE packes o her eghbor saes. Saes 2 ad 7 wll receve wo RE packes; moreover, sae 4 ad 5 wll exchage her RE packes muually. Ths may cause wo problems: a) Tme sychrozao ad asychrozao I order o avod he message coflco problem, we adop he sychroous decso ad asychroous delvery mechasm. A he ed me of a sage, all saes se A make decsos smulaeously ad wh ))); 8 f ( ( ) <= ( ( 1) ) ) delee from A; 9 else sore: ( ) u *, where makes he maxmum value ( ), sae s roue able; add o A;}} /*ed f, ed for*/ 10 f (A ) { 11 all he saes A broadcas her correspodg opmal goal value; =+1; } 12 else { 13 f ( ( 1 ) 0 ; 14 else ) o rused roug o he sae ( ) (, f (, u ), f ( f (, u ), u ),..., ); * * * break;}} /*ed whle*/ 16 reur ( 1 ) ; Fgure2. Seps of Trus Roug algorhm based o FP 2009 ACAEY PUBLISHER

7 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER Fgure3. Sub-sae mgrao graph cera me erval (TI) he decso saes wll broadcas her opmal goal value oe afer aoher o s eghbors, a sae whch receves a RE packe wll wa a cera me TI ul ge eough RE packes from oher eghbor saes ad he make a egraed decso. b) Roue cycle problem I Fg.1, suppose sae 4 s successor s sae 7, sae 7 s successor s 5, he ca be cocluded ha (4) (7), (7) (5), whch dcaes (4) (5). If sae 5 s successor s 4, mus f he equao (5) (4), hs codo ca work oly he precodo (4) (5), however, accordg o he algorhm, f (4) (5), he RE packe wll be dropped. So s uable o form a roug cycle. oreover, he desero of he packes wh equal opmal goal values ca decrease he vald messages he ework ad reduce he overhead of ework odes. C. Esablsh Fuzzy Trused SR Accordg o he Trus Roug Algorhm wh FP descrbed above, he process o esablsh a fuzzy rused ANET proocol s geerally as he followg, wh a abbrevao FTSR. Assumpos: (1) The lks bewee wo odes are bdrecoal; hs assumpo s ofe vald [32]. (2) Besdes he roue able eeded sadard SR proocol, each ode our model addoally ows a rus able wh ems defed as follows: N_I() s he defcao (I) of ode s eghbor; T_IN() s he rus value ha he eghbor ode ges abou ode ; T_OUT() s he rus value ha ode has abou s eghbors. All he rus values are obaed from he rus evaluao model show seco III. (3) The packes ha coa he rus values are kep from modfed by malcous odes, us lke he RE packe. The roug esablshme process maly cludes roug dscovery ad roug maeace. FP s maly used for he dscovery process, ad o much chage should be made for he maeace of SR. Roug dscovery: Sep 1: Source ode S aes a roug dscovery by broadcasg a ROUTE REQUEST (RRQ) packe ha coas he desao address o s eghbors. The eghbors ur apped her ow addresses o he RRQ packe ad rebroadcas. Ths process coues ul a RRQ packe reaches. Sep 2: Termae ode aes he decso process backwards wh he rus roug algorhm wh FP (as descrbed Fg.2). Curre saes selec ex-hop sae wh he curre rus able ems ad sore he chose sae her roue ables. Afer fshg he process of he algorhm, each sae obas s opmal roue ad he roug dscovery s compleely mplemeed. Roue maeace: Roue maeace assures he roue s egraed ad vald a cera me erval (TI); a lk-broke eve wll rgger a ew rus evaluao process ad rus roueupdae process. Also, whe a roue able em overwhelms he maxmum vald me, a ew roug dscovery wll also resar.. Two Opmzao mehods for FTSR Bascally, FTSR s a more complex process ha he commo roug algorhms such as SR, AOV. Whle he roug decso should be rapd eough ad fulfll he hroughou requremes, so some opmzao could be ake o ge more praccal usably. Of course, here s cera performace loss afer he opmzao ad hey should be used o dffere codos. Two geeral opmzao algorhms are carred here. a) Avod secod decso-makg I FTSR, here s a ecessary verse erao process (as he de-fuzzy process) o ge he roug pah. Because of he asymmerc feaures bewee wo eghbor odes, he rus value from ode o ode may o equal he rus value from ode o ode. Ths causes useful o re-calculae ad re-acvae he odes whch have prevously fshed he roug decso, ad o make he secod decso. I a complex ANET wh may (.e., more ha 100) odes, hs may happe frequely because so may odes ca commucae each oher drecly. Alhough hs secod decso-makg process s more accurae o fd he mos rusworhy pah, brgs much more pressure o he -me decso ad he huge hroughou processg. Noe ha oly le 6 ad le 7 make he chages, add he fuco ecso_flag() o avod he secod decso. 6 f ( be rggered && ( f (, )) 0 && ecso_flag( )==0 ) 7 {calculae: ( ) ( C ( ) ( f (, ))); ecso_flag( )=1; Fgure4. Algorhm Chages FTSR-I 2009 ACAEY PUBLISHER

8 1098 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER 2009 So he approach o avod he secod decso-makg s a useful way o accelerae he decso respose. Use a flag fuco o mark he odes wheher has made he decsos, oly few chages s made o he algorhm Fg.2 ad Fg.4 shows he mproved process. Ths mproveme s amed as FTSR-I. b) Heursc decso wh hreshold value whe he ode s he sae of calculao ad decso, amog all of he succeedg odes whch have passed rus value us ow, here are may be more ha oe ode have he same rus values, he oe ode s seleced whou ay decso FTSR, us show as α Le 9, Fg.2. To be more rusworhy, he odes, wh he bgges rus value (he ode wh he bgges μ c ) he posve roug drecos, ca be seleced as he ex-hop from he curre ode. Compared wh FTSR, hs ca mprove he rus value he each separae hop, whch meas he rus value he crcal roug pah ca be more average ad sable. I he mplemeao, he chages for he algorhm Fg.2 are maly added he seps o make a maxmal comparso. Ths s show Fg.5, amed as FTSR-II respecvely. Noe ha from le8, aoher brach saeme s added ad he maxmum pah s seleced 8 f ( ( ) <= ( ( 1) ) ) delee from A; else 9 IF more ha oe could sasfy he opmal goal ( ); 10 sore: * ( ) u k k max( C ( k )) sae s roue able; add else 11 sore: ( ) u *, where makes he maxmum value ( ), sae s roue able; add o A;}} /*ed f, ed for*/ TABLE III. SIULATION PARAETERS Parameer Value Smulaor OPNET AC layer Frequecy of operao 2.4GHz Number of moble odes 20 obly model Radom waypo Terra rage m 2 Trasmsso rage 250m Chael badwdh 1 bps oveme speed 1m/s Applcao raffc CBR(UP) Smulao me 100s Propagao mode Free space Packe sze 512 Byes axmum coeco 10 axmum malcous odes 7(35%) Type of aack Coordaed aack FTSR-I, FTSR-II), he performace s compared wh SR ad TSR [29], from he aspecs of Packe rop Rao, Ed o Ed elay ad Throughpu. All daa ca be go from he smulaor drecly ad he red s show he followg fgures. A. Packe rop Rao The packe drop rao dcaes he daa rasmsso performace of he ANET roug proocols. The basc characer of he malcous odes s o ake he aack by droppg packes delberaely or forcedly whe hey are overloaded. Fg.6 shows he experme resuls of he packes drop rao uder SR, TSR, FTSR, FTSR-I, ad FTSR-II respecvely. Fgure5. Algorhm Chages FTSR-II VI. SIULATIONS AN EXPERIENTS I he expermes, OPNET s used o perform he smulaos. A moble ad hoc ework wh 20 odes s dsrbued radomly he rage of 1000m 1000m area. Each ode has he cosa moveme speed of 1 m/s ad he drec rado rasmsso rage of each ode s se o be 250m. The smulao coues for 100s each me. The deals of he smulao parameers are show Table III. To ge he dffere level of he performace, varous umbers of he malcous odes are se o ru he smulaos. I he expermes, s assumed ha he malcous odes perceage s 12% (2 malcous odes, some odes may be ou of he commucao rage), 25%, ad 35% respecvely. Afer he mplemeao of he proocols hrough FTSR famly (cludg FTSR, Fgure6. Packe drop rao wh varous malcous odes I ca be foud ha FTSR proocol maas a lower drop rao ad he curve flucuaes smooher ha ohers. Ths s maly because he radoal SR proocol oly cosders he hop cou as he source for roug seleco, ad TSR chooses he opmal rused roue lmed o SR. Whle FTSR has used he FP algorhm a rus evaluao ad roug decso process, hs ca elmae malcous odes fluece ad mgae he aack caused by packe-drop. Take he cases wh 12% malcous odes as a example, he packe drop rao of FTSR s 17%, TSR s 37.5% ad SR s 60%. Whe he malcous odes crease from 25% o 35%, he packes dropped by FTSR crease oly 4% whle SR crease 15% ACAEY PUBLISHER

9 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER Compared wh FTSR famly, he resuls also have show ha FTSR-II s more rusworhy ha FTSR, whle FTSR-I has he rus loss ha FTSR. B. Ed o Ed elay Ed o Ed elay (ETE elay) refers o he me ake for a packe o be rasmed across a ework from source o desao. I order o choose he mos rused pah, he uque backward decso process FTSR s mplemeed whch s more complex ha SR ad TSR. Furhermore, he mos rused roue s o always he shores pah. The ed o ed laecy of FTSR urs o be averagely 26% loger ha SR ad TSR. Ad because FTSR-I has avoded he secod-decso makg process, s delay s less ha FTSR. Whle he calculao FTSR-II s more complex ha ha FTSR, so s delay s loger geerally.fg.7 shows he resul. Fgure8. Throughpu wh 12% malcous odes Fgure9. Throughpu wh 25% malcous odes Fgure7. Ed o Ed elay he dffere algorhms C. Throughpu I ANET, hroughpu s he average rae of successful message delvery over a commucao chael. These daa may be delvered over a physcal or logcal lk, or pass hrough a cera ework ode. The hroughpu s usually he sum of he daa raes ha are delvered o all ermals a ework, whch ca be aalyzed mahemacally by meas of queug heory, where he load packes per me u. I hs experme, he pah s me-average hroughpu he desao ode s gve he sascs, whch s measured packes per secod. Fg.8, Fg.9 ad Fg.10 show he hroughpu o he desao uder he codos of 12%, 25%, ad 35% malcous odes respecvely. Accordg o he dsrbuo values each fgure, ca be foud ha FTSR ca ge a obvous hgher hroughpu ha SR ad TSR. Take fg.8 as a example, he ed of he smulao, he hroughpu of TSR s 0.14 packe per secod, ad FTSR s 0.22 packe per secod, FTSR mproves he hroughpu by 57%. Because FTSR-II has more cosderao abou he sably of he rus value, ca geerally ge he hgher hroughpu ha FTSR. VII. CONCLUSIONS Fgure10. Throughpu wh 35% malcous odes ANET s a mul-hop self-cofgurg ework whou ay fxed frasrucure o commucae. Is opology chages dyamcally ad each ode faces challeges from s processor, power, sze, sorage ec. Because he uceray exss all of he evaluao facors, fuzzy heory s suable for he evaluao of he uceray ad he boudary. I hs paper, based o he classc fuzzy heory, he rus evaluao modelg ad he dyamc roug proocols for ANET are roduced ad verfed. Frs, has roduced he fuzzy rus evaluao model abou each ANET ode, cludg drec rus evaluao accordg o he feaures of he ode ad rus evaluao wh fuzzy logc o model he ode, he ework ad he evrome. Secod, he roug decso wh fuzzy dyamc programmg s dscussed, focus o each sep of 2009 ACAEY PUBLISHER

10 1100 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER 2009 he algorhm ad how o make he mul-sage decso, he represes he process o esablsh he fuzzy rused SR, ad gves wo opmzao mehods for FTSR. The expermes use OPNET o smulae a ANET evrome. The resul has show ha FTSR proocols ca mprove he ework secury, reduce he Packe rop Rao, ad ehace he hroughpu wh he accepable Ed o Ed elay. I he fuure work, more opmzao should be doe o mprove he effcecy of he FP for he beer use he real ANET evromes. REFERENCES [1] Q. Zhwe, J. Zhpg, ad C. Xhu, "Fuzzy yamc Programmg Based Trused Roug ecso oble Ad Hoc Neworks," Embedded Compug, SEC '08. Ffh IEEE Ieraoal Symposum o, 2008, pp [2]. Co ad S. Gordao, "ulhop Ad Hoc Neworkg: The Theory," Commucaos agaze, IEEE, vol. 45, pp , [3] A. Boukerche, "Performace comparso ad aalyss of ad hoc roug algorhms," Performace, Compug, ad Commucaos, IEEE Ieraoal Coferece o., 2001, pp [4] Chag. E, llo T, ad Hussa. F, Trus ad repuao for servce oreed evrome, Joh Wley ad Sos, [5] J. Golbeck, "Compug wh Trus: efo, Properes, ad Algorhms," Securecomm ad Workshops, 2006, 2006, pp [6] U. aurer, odelg a publc key frasrucure, Proc. Eur. Symp. Res. Compu. Secury, vol. 1146, Lecure Noes Compuer Scece, 1996, pp [7]. K. Reer ad S. G. Subblebe, Resle auhecao usg pah depedece, IEEE Tras. Compu., vol. 47, o. 12, pp , ec [8] C. Be-Jye ad K. Szu-Lag, "arkov Cha Trus odel for Trus-Value Aalyss ad Key aageme srbued ulcas ANETs," Vehcular Techology, IEEE Trasacos o, vol. 58, pp , [9] S. Gaerwal ad. B. Srvasava, Repuao-based framework for hgh egry sesor eworks, Proc. AC Secury for Ad-Hoc ad Sesor New., 2004, pp [10]. Alka, A.. Erkme, ad I. Erkme, Fuzzy dyamc programmg, Elecroechcal Coferece, Proceedgs., 7h ederraea, 1994, pp vol.2. [11] A. Boukerch, L. Xu, ad K. El-Khab, Trus-based secury for wreless ad hoc ad sesor eworks, Compuer Commucaos, vol. 30, pp , [12] G. Theodorakopoulos, ad J. Baras, Trus evaluao ad-hoc eworks, Proceedgs of AC workshop o Wreless secury, USA, 2004, pp [13] G. Suryaarayaa,. H. allo, J. R. Erekraz, ad R. N. Taylor, Archecural suppor for rus models deceralzed applcaos, Proc. 28h I. Cof. Sofw. Eg., ay 2006, pp [14] L. Xog ad L. Lu, Buldg rus deceralzed peer o peer elecroc commues, Proc. 5h I. Cof. Elecro. Commerce Res., Oc. 2002, pp [15] E. Kosovos ad A. Wllams, BambooTrus: Praccal scalable rus maageme for global publc compug, Proc. AC Symp. Appl. Compu., Apr. 2006, pp [16] G. Zachara ad P. aes, Trus maageme hrough repuao mechasms, Appl. Arf. Iell., vol. 14, o. 9, pp , Oc [17] S. Buchegger ad J. L. Boudec, Performace aalyss of he cofda proocol: Cooperao of odes-faress dyamc ad hoc eworks, Proc. AC I. Symp. oble Ad Hoc New. Compu., Ju. 2002, pp [18] H. Su ad J. Sog, Sraegy proof rus maageme wreless ad hoc ework, Proc. Ca. Cof. Elec. Compu. Eg., ay 2004, vol. 3, pp [19] E. C. H. Nga,. R. Lyu, ad R. T. Ch, A auhecao servce agas dshoes users moble ad hoc eworks, Proc. IEEE Aerosp. Cof., ar. 2004, vol. 2, pp [20] C. Cadol ad H. H. Kar, srbug complee rus wreless ad hoc eworks, Proc. IEEE Souheas Cof., Apr. 2003, pp [21]. K. Chu, C. Wag, H.-F. Leug, I. Kafeza, ad E. Kafeza, Supporg he legal dees of coracg ages wh a age auhorzao plaform, Proc. I. Cof. Elecro. Commerce, Aug. 2005, vol. 113, pp [22] Y. Su, W. Trappe, ad K. J. Ray, A scalable mulcas key maageme scheme for heerogeeous wreless eworks, IEEE/AC Tras. New., vol. 12, o. 4, pp , Aug [23] A. A. Przada ad C. coald, Trus esablshme pure ad hoc eworks, Wrel. Pers. Commu., vol. 37, o. 1/2, pp , Apr [24] A. Boukerche ad Y. Re, "A rus-based secury sysem for ubquous ad pervasve compug evromes," Compuer Commucaos, vol. 31, pp , [25] Q. He,. Wu, ad P. Khosla, Sor: a secure ad obecve repuao-based ceve scheme for ad-hoc eworks, Wreless Commucaos ad Neworkg Coferece 2004 WCNC 2004, arch 2004, vol. 2, IEEE, pp [26] H. Yag, J. Shu, X. eg, ad S. Lu, Sca: selforgazed ework-layer secury moble ad hoc eworks, IEEE J. Seleced Areas Commu.24 (2) (2006) [27] S. Zhog, J. Che, ad Y.Yag, Spre: a smple, cheaproof, cred-based sysem for moble ad-hoc eworks, INFOCO 2003, Twey-Secod Aual Jo Coferece of he IEEE Compuer ad Commucaos Socees, 30 arch 3 Aprl 2003, vol. 3, IEEE, pp [28]. A. Caloyades, "Ole moorg: secury or socal corol?," Secury & Prvacy, IEEE, vol. 2, pp , [29] Guo We, Xog Zhogwe, ad L Zhag, yamc rus evaluao based roug model for ad hoc eworks, Proc. of he Wreless Commucaos, Neworkg ad oble Compug 2005, Sep.2005, Vol.2, pp [30] J. Luo, X. Lu, ad. Fa, A rus model based o fuzzy recommedao for moble ad-hoc eworks, Compuer Neworks, vol. I Press, Correced Proof, [31] ackam, J. ar Leo, ad Shamugavel. S, Fuzzy based rused ad hoc o-demad dsace vecor roug proocol for ANET, Advaced Compug ad Commucaos 2007, ec.2007, pp [32] Khayaa R.E., Pug C.., Zweg J., A dsrbued medum access proocol for wreless LANs, Sgals, Sysems ad Compuers 1994, Nov.1994, Vol.1, pp ACAEY PUBLISHER

11 JOURNAL OF SOFTWARE, VOL. 4, NO. 10, ECEBER Hogu a receved he B.S. degree compuer scece ad echology ad he PH. degree compuer applcao from Zheag Uversy of Cha 2002 ad 2007, respecvely. He s currely a Full Lecurer a he School of Compuer Scece ad Techology, Shadog Uversy, Ja, Cha. Hs research eress clude compoe-based sofware, mul-core compuer archecure, ad rus compug for embedded sysems ad ANETs. Zhpg Ja receved he B.S. degree ad he.s. degree compuer echology from Shadog Idusry Uversy of Cha 1989 ad 1992 respecvely, ad he PH. degree corol heory ad egeerg from Shadog Uversy of Cha He s currely a Full Professor a he School of Compuer Scece ad Techology, Shadog Uversy, Ja, Cha. Hs research eress clude corol egeerg, embedded sysem, realme sysem, dsrbued compug, ad rus compug. Zhwe Q receved he B.S. degree compuer scece ad echology from Shadog Normal Uversy of Cha 2004, ad receved he.s. degree compuer archecure from Shadog Uversy of Cha He s currely a PH. Caddae of eparme of Compug a he Hog Kog Polyechc Uversy, Cha. Hs research eress clude mul-core embedded sofware ad sysems, rus compug for ANETs ACAEY PUBLISHER