A Novel Fuzzy Stochastic Routing Protocol For Mobile AdHoc Network

Transcription

1 Avalable Onlne at Internatonal Journal of Computer Scence and Moble Computng A Monthly Journal of Computer Scence and Informaton Technology IJCSMC, Vol. 2, Issue. 0, October 203, pg RESEARCH ARTICLE ISSN X A Novel Fuzzy Stochastc Routng Protocol For Moble AdHoc Network M.M.Goswam, V. Rughwan 2, Mr. A. Anjkar 3 Rajv Gandh College of Engneerng & Research, Dept. of Informaton Technology, Nagpur, Inda 2 Om College of Engneerng, Wardha, Inda 3 Rajv Gandh College of Engneerng & Research, Nagpur, Inda E-mal: mm_gos@yahoo.com Abstract Conventonal routng algorthms for moble ad hoc networks such as AODV or DSR consder only one metrc, for example, hop count to select best path from source to destnaton. However due to specal characterstcs of MANET such as nodal moblty, unstable lnks and lmted resources, conventonal routng algorthm found to be unsutable for routng multmeda traffc or real tme applcatons whch requre optmzaton of more than one metrc. The paths chosen by conventonal routng algorthm devate far from optmal paths. In the proposed algorthm called Fuzzy Stochastc Routng (FSR) multple metrcs such as hop count, battery power, sgnal strength are consdered usng fuzzy logc to gve multple optmal paths. Nodes then forward data stochastcally on these multple paths resultng nto automatc load balancng and fault tolerance. Smulaton results show the great mprovements over the conventonal routng algorthm (AODV) n terms of varous parameters lke packet delvery rato, no of route dscoveres, delay, etc. Keywords- Moble Adhoc Networks; AODV; Fuzzy logc I. INTRODUCTION Moble ad hoc network conssts of a collecton of wreless moble nodes, whch dynamcally exchange data among themselves wthout the relance on a fxed base staton or carred backbone network []. Each moble node acts as a termnal or router and the control of the network actvty s dstrbuted to these nodes. Ths knd of network s very flexble and sutable for applcatons such as temporary nformaton sharng n conferences, mltary actons and dsaster rescues. However moble nodes have lower battery power and lower computaton ablty. Also, the network topology s generally dynamc because the connectvty among the nodes may change wth tme due to nodal moblty, the effect of rado communcaton and power lmtatons. These features of MANET have posed a lot of challenges n desgnng an effectve, relable and scalable routng protocol [2]. In order to facltate communcaton wthn the network, a routng protocol s used to dscover routes between nodes. The prmary goal of such an ad hoc network routng protocol s to provde correct and effcent route 203, IJCSMC All Rghts Reserved 98

2 establshment between par of nodes so that messages may be delvered n tme [3]. MANET routng protocols are manly clubbed nto two technques,.e. table-drven and on-demand routng. Table drven routng protocol requrements are perodc advertsement of the changes n the network and ts global dssemnaton of connectvty because of whch t s unsutable for large - szed networks. Protocols based on table-drven technque are Destnaton Sequence Dstance Vector (DSDV) routng [4], Cluster-head Gateway Swtch Routng (CGSR) [5], and Wreless Routng Protocol (WRP) [6]. On-demand routng protocols are effcent for routng n large - szed ad hoc networks because they mantan the routes that are currently needed, ntatng a path dscovery process whenever a route s needed for the message transfer [7]. Popular protocols based on on-demand scheme are ad-hoc on demand Dstance Vector (AODV) [8], Dynamc Source Routng (DSR) [9], Temporally Ordered Routng Algorthm (TORA) [0], Sgnal Stablty based Adaptve (SSA) [] routng and Assocatvty-Based Routng (ABR) [2]. However n these algorthms route s decded by choosng one or two selecton parameters wthout consderng the nterplays of dfferent selecton parameters. As mentoned above the topology of MANET s determned by many factors such as battery capacty, traffc pattern, lnk stablty and nodal moblty. All of these factors are correlated. Consderaton of only one or two factors s not suffcent for choosng an optmal path. For example f the shortest path s decded by the number of ntermedate hops and the algorthm s not power aware or moblty aware then the algorthm may select unstable routes or lead to shortenng the lfetme of a node whch can result n route falures n between actve communcaton sessons due to expraton of batteres of ntermedate nodes. Ths paper extends the dea of usng fuzzy logc n AODV to present a mult-objectve multpath routng algorthm for MANETs to fnd the most preferred route by evaluatng the alternatves aganst the multple objectves and selectng the routes whch best acheves the varous objectves. The dfferent routng metrcs are taken nto consderaton usng a fuzzy logc system to capture nterplay of varous metrcs whch return multple optmal paths. Routes selecton s then performed stochastcally and data s forwarded over optmal routes resultng nto dstrbuton of traffc whch allevate congeston and fault tolerance. Thus, ths probablstc routng strategy leads to data spreadng accordng to the estmated qualty of paths. The rest of the paper begns wth secton II that descrbes the bascs of AODV routng protocol snce proposed routng protocol FSR s nspred from AODV. Desgn of fuzzy logc system s dscussed n secton III. Secton IV presents proposed routng protocol. Then, n secton V, smulaton and results are gven and secton VI concludes the paper. II. AODV PROTOCOL Ad hoc on demand Dstance Vector routng protocol uses a broadcast route dscovery mechansm, and t reles on dynamcally establshed routng table entres at ntermedate nodes. The functons performed by AODV protocol nclude local connectvty management, route dscovery, route table management and path mantenance. Local connectvty management happens as follows. Nodes learn about ther neghbors by ether recevng or sendng broadcast packets from or to ther neghbors. Recevng the broadcast or HELLO from a new neghbor or falng to receve HELLO messages from a node that was prevously n the neghborhood, ndcates that the local connectvty has changed. The source node ntates path dscovery by broadcastng a RREQ route request packet to ts neghbors. When a node receves RREQ, n case t has routng nformaton, t sends the reply, RREP, packet back to the destnaton. Otherwse, t rebroadcasts RREQ packet further to ts neghbors. As the RREQ packet travels from the source to the destnaton t automatcally sets up the reverse path from all nodes back to the source. As the RREP travels back to the source, each node along the path sets up a forward ponter to the node from whch the RREP came and updates ts tmeout nformaton for route entres to the source and destnaton. For each destnaton of nterest a node mantans a sngle route table entry that contans the address of the destnaton, the next hop along the path to that destnaton, the number of hops to the destnaton, and other route related parameters. If a node s presented wth two dfferent routes to the destnaton t chooses the fresher route. If both routes were dscovered smultaneously, the route wth fewer hops s preferred. Path mantenance s performed as follows: When any node lyng along establshed path moves so that some of the nodes become unreachable, the specal ERROR message s sent to affected source nodes. Upon recevng notfcaton of a broken lnk, the source node restarts the path dscovery process, f t stll requres that route. 203, IJCSMC All Rghts Reserved 99

3 III. USE OF FUZZY LOGIC IN ROUTING Fuzzy control s a control technque based on the prncples of fuzzy set theory, and the control systems are desgned to mmc human control better than classcal control systems by ncorporatng expert knowledge and experence n the control process. Ths s acheved by usng lngustc varables n the control system to enable the desgner to nclude control rules that naturally follow human thought. A key feature of fuzzy logc s to handle uncertantes and non-lneartes, exstng n physcal systems. Fuzzy systems are used to approxmate functons. It s can be used to model any contnuous functon or system. The advantages of fuzzy logc are :- Conceptually easy to understand Flexble Tolerant of mprecse data Can model nonlnear functons of arbtrary complexty Can be bult on top of the experence of experts Can be blended wth conventonal control technques Based on natural language The nputs to the fuzzy controller to be desgned for routng are: () hop count,() remanng battery power and () sgnal stablty. These three selecton parameters reflect the network status and the node s ablty to relably delver network packets. The steps nvolved n use of fuzzy logc for routng n MANET are elaborated as follows: A. STEP I. Fuzzfcaton of nputs and outputs The three nput varables to be fuzzfed are the energy consumpton rate (B), the hop count (H) and the sgnal strength (SS). On the bass of exstng knowledge of MANET, the terms Low, Medum and Hgh are used to descrbe the energy consumpton rate and Less, Medum and Hgh to descrbe hop count. Strong, Medum and Weak are terms for representng the sgnal strength. Even though the choce and specfcaton of the membershp functons are wdely subjectve, there are several prncples for membershp functon selecton that can produce good adequate results. The trapezodal functons and trangular functons are chosen for nput and output respectvely as the membershp functons snce they have been extensvely used n real-tme applcatons due to ther smple formulas and computatonal effcency. We show these membershp functons n Fg.,2,3,4. We normalze the lngustc values of nputs and outputs n the range from 0 to. The output of FIS s a lnk cost, whch represents cost of node partcpatng n the route. The lnk cost from lowest to hghest are defned as VL (very low), L, M (Medum), H, VH (very hgh). W M S 0 Fgure. Fuzzy Membershp functon for sgnal strength(ss) L M H 0 Fgure 2. Fuzzy Membershp functon for battery capacty(b) 203, IJCSMC All Rghts Reserved 00

4 L M H 0 Fgure 3. Fuzzy Membershp functon for hop count(h) VL L M H VH Fgure 4. Fuzzy Membershp functon for lnk cost(lc) B. STEP 2. Inference engne and knowledge base The knowledge base s a set of rules developed usng expert knowledge. We desgn the knowledge based rules connectng the nputs and the output based on a thorough understandng of the system. The parameters and rules of our FLS are ntally set, nduced from many analytcal results of MANET routng. The fuzzy rules have IF-THEN structure. The nputs are then combned usng the AND operator. The followng s an example of rule, whch descrbes the nput output mappng. TABLE I. FUZZY RULES TABLE FOR WEAK SS B H Low Medum Hgh Less H M VL Medum H M L Hgh VH H H f battery power s medum(m) and no of hops are less(l) and sgnal strength s weak(w) then the lnk cost s medum(m). Table shows the fuzzy rules for the weak sgnal strength n fuzzy logc system. The fuzzy set parameters and rules of FSR are set by expert knowledge and heurstcs. Smlarly, fuzzy rule tables for medum and strong sgnal strength are formulated. C. STEP3. Defuzzfcaton Defuzzfcaton refers to the way a crsp value s extracted from a fuzzy set as a representaton value. There are many knds of defuzzfers. Here we take the centrod of area strategy for defuzzfcaton. 203, IJCSMC All Rghts Reserved 0

5 LC = AllRules AllRules x. ( x ) ( x ) Where LC s the lnk cost, x s the element and µ(x ) s ts membershp functon. Ths s the most wdely adopted defuzzfcaton strategy, whch s remnscent of the calculaton of the expected value of probablty dstrbutons. INPUT [hop count, sgnal strength, battery Fuzzfer Rule Base Fuzzy Inference System Membershp functons Defuzzfer OUTPUT [lnk_cost (LC)] Fgure 5. Computaton of lnk cost(lc) when RREQ vsts the node. IV. DESCRIPTION OF PROPOSED PROTOCOL The workng of FSR s smlar to AODV except the strategy for route selecton process usng fuzzy logc descrbed n ths secton n detal. As mentoned earler, the FSR utlzes three nput varables.e. hop count, sgnal strength and battery lfe of nodes. When a source wants to mantan a path to a destnaton, t broadcasts a RREQ packet throughout the network n order to fnd a path. When ntermedate node receves RREQ, t calculates ts lnk cost of partcpatng n the route and adds t to the sum of the lnk costs n the RREQ packet. Also the value of resultng sum s stored n the node. The ntermedate nodes as shown n fg. 5 make use of fuzzy logc to calculate the cost, whch s dependent on multple metrcs mentoned earler. In ths way as the RREQ packet travels through ts route, lnk cost gets accumulated at each ntermedate node. When the RREQ packet reaches the destnaton, RREP packet wll be generated and the total cost for whole path, TOTAL_COST, s calculated as shown n fg. 7, whch s carred n the RREP packet. When RREP s receved at ntermedate node whle travelng back to the source, the sum of lnk costs stored n the node earler wll be subtracted from the TOTAL_COST and follows the path n reverse. The result s route_cost of a path from ntermedate node at whch RREP s receved to destnaton gven by followng Eq.() t Route _ cos t LC () j, d l l l where t s the number of traversed routes(or lnks) n the path startng wth current node (l=) and fnshed wth node d (l=t) va neghbor node j. LC l l s the lnk cost between adjacent nodes l and l+. Routng cost table correspondng to the RREQ s destnaton s then updated as follows: 203, IJCSMC All Rghts Reserved 02

6 Route _ Cost j, d ( t ) ( ) Route _ Cost j, d ( t ) Route _ Cost j, d (2) where ρ s learnng rate and set to 0.7 and the probablty table s updated by usng (3) as follows: At node, For Destnaton d, the probablty s: / Route _ Cost j, d ( t) P j, d = l / Route _ Cost j, d ( t) (3) Where l neghbor () When RREP reaches fnally back to source node, the routng cost table and probablty table of the source node s updated. V. SIMULATION AND RESULTS We conducted experments to evaluate and compare the performance of the routng protocol FSR wth AODV. In these experments, we used network smulator, OMNET++ wth moblty framework, whch offers hgh fdelty n wreless ad hoc network smulaton by ncludng an accurate mplementaton of data lnk and physcal layers. Ffty moble nodes were moved accordng to the random waypont moblty model wthn a 500 m * 300 m area. Each node had a rado propagaton range of 250m and channel capacty was 2Mb/s. All smulatons were run for 600 seconds of smulated tme. We dd our experments wth movement patterns for 7 dfference pause tmes: 0, 00, 200, 300, 400, 500 and 600 seconds. Thrty moble nodes acted as traffc sources generatng 4 packets/second each, and data traffc was generated usng constant bt rate Control Packet receved RREQ Type RREP Compute the lnk cost as shown n fg. 5 Update the sum of lnk costs n RREQ by addng just computed Subtract the stored sum of lnk costs n a node from TOTAL_COST n the receved RREP to get Route_Cost. Update route_cost table & probablty Send RREQ to ts all Forward the RREP along the reverse entry Fgure 6. Response/Acton of ntermedate node when control packet (RREQ/RREP) s receved 203, IJCSMC All Rghts Reserved 03

7 LC 2 LC 2 +LC 23 LC 2+LC 23+LC Lnk cost gets added when RREQ vsts the node. The accumulated cost s stored n a node and also carred wth the RREQ Source 5 Destnaton TOTAL_COST= LC 2 +LC 23 +LC 34 +LC Fgure 7. Updaton of Lnk_Cost(LC) when RREQ vsts the node CBR) UDP traffc sources. The medum access control protocol was the IEEE 802. DCF. The sze of data packet was 52 bytes. The mnmum and the maxmum speeds were set constant to zero and 20m/s respectvely. Packet delvery rato s mportant as t descrbes the loss rate that wll be seen by the transport protocols, whch n turn affects the maxmum throughput that the network can support. Fg. 8 presents that packet delvery rato s hgher for FSR, whch s due to ts ablty to select a set of stable and least congested routes thus havng the lowest amount of congeston loss and very few route falures. Fgure 8. Packet delvery rato Fgure 9. End-to-end delay 203, IJCSMC All Rghts Reserved 04

8 Fgure 0. No. of route dscoveres The average end-to-end delay s the average elapsed tme to delver a packet from the source node to the destnaton node, and t ncludes all possble delays before data packets arrve at ther destnatons. The average endto-end delay for FSR s lower compared wth AODV (Fg. 9). It s obvous that AODV have the hgher delay because of hgh congeston. As the moblty decreases (ncreasng pause tme) the delay also decreases due to less route falures at low moblty. Route falures have an mpact on the delay, because route falures requre re-reroutng and storng of packets n the send buffer. Route redscovery s needed to locate an alternate route for the gven destnaton. It s an expensve task. So the less frequency of routng dscovery process means the less route dscovery latency and lower routng overhead. Fg. 0 shows that the frequency of route redscovery of FSR s lower among those of the compared routng protocols. Because FSR deals wth the uncertanty of MANET and consders the effects of dfferent correlated parameters on network performance, FSR decreases the route falures sgnfcantly. VI. CONCLUSION AND FUTURE WORK In ths paper correlaton of dfferent route selecton parameters that affect the network performance s captured by fuzzy logc. Also, stochastc routng over multple optmal paths result nto automatc load balancng and fault tolerance mprovng overall performance over conventonal routng protocol, AODV. Ths s acheved by equppng each node wth fuzzy logc system. The results show that fuzzy logc based multpath routng protocol s very promsng to take care of varous uncertantes of MANET effectvely. The result of ths research motvates the use of fuzzy logc routng protocol to select the best path stochastcally. It can be used to explore other areas of routng n MANET, for example, poston of node based routng. References [] Macker, J.P., Scott Corson, M. Moble ad-hoc networkng and the IETF n Mob. Comput. Commun. Rev. vol.2. ACM Press, New York, NY (998) 9-5. [2] M. Abolhasan, et al. A revew of routng protocols for moble ad hoc networks. Ad Hoc Networks 2 (2004) 22. [3] T.S. Rappaport, Wreless communcatons Prncples and Practce,Pearson edton, [4] C.E. Perkns and P. Bhagwat, Hghly Dynamc Destnaton-Sequenced Dstance-Vector Routng (DSDV) for Moble Computers, Proceedngs of ACM SIGCOMM 94, pp , 994. [5] C.-C. Chang, H.K. Wu, W. Lu and M.Gerla, Routng n Clustered Multhop, Moble Wreless Networks wth Fadng Channels, Proceedngs of IEEE SICOM 97, pp.97-2, 997. [6] S. Murthy and J.J. Garca-Luna-Aceves, An Effcent Routng Protocol for Wreless Networks, ACM Moble Networks and Applcatons Journal: Specal Issue on Routng n Moble Communcaton Networks, Vol., No. 2, pp , 996. [7]Y.-C. Hu and D.B.Johnson, Cachng Strateges n On-Demand Routng Protocols for Wreless Ad Hoc Networks, Proc. ACM Internatonal Conference on Moble Computng and Networks (MOBICOM), , IJCSMC All Rghts Reserved 05

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