Cost-Effective Lifetime Prediction Based Routing Protocol for Mobile Ad Hoc Network

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Cost-Effectve Lfetme Predcton Based Routng Protocol for Moble Ad Hoc Network ABU MD. ZAFOR ALAM, MUHAMMAD ARIFUR RAHMAN, M. LUTFAR RAHMAN 1 Faculty of Scence and Informaton Technology, Daffodl Internatonal Unversty, Dhaka 10, BANGLADESH Abstract: Moble Ad hoc Networkng (MANET) s the most mpressve technology n today s Wreless communcatons. Cost reducton and proper utlzaton of battery power becomes the prmary concerns for varous type of routng. Cost effectve lfetme predcton based routng protocol for wreless network gves an optmum path based on both cost and the lfetme of the moble network. Ths paper represents an mprovement algorthm for the routng protocol of Moble Ad Hoc Network. Due to the lmted battery power of moble devces, recent research n moble ad hoc routng s motvated towards selecton of a path that maxmzes the network lfetme. Another approach for the routng protocol n moble devce to select the mnmum path length. Ths algorthm selects a path that consders both the path cost and the battery power of the moble network. For the stablty of the whole network of the MANET, the most concern thng s that, a low power node/devce has to transfer nformaton very earler for the better mprovement of the network. Otherwse the network may damage. The graphcal and smulaton results of the paper gve a clear dea that how can we mprove our network stablty for the moble ad hoc network. Keywords: Moble Ad Hoc Networks, Lfetme Predcton, Routng Protocol, Wreless Networks, Dstrbuted Systems. 1 Introducton Ad hoc networks are networks that are desgned to dynamcally connect remote devces such as cell phones, laptops, and PDAs. These networks are termed ad hoc because of ther shftng network topologes. Whereas WLANs use a fxed network nfrastructure, ad hoc networks mantan random network confguratons, relyng on a master-slave system connected by wreless lnks to enable devces to communcate. As devces move about n an unpredctable fashon, these networks must be reconfgured on the fly to handle the dynamc topology. Fgure 1 shows a smple moble ad hoc network. A Moble ad hoc Network (MANET) s composed of a group of moble wreless nodes that form a network ndependently of any centralzed admnstraton, whle forwardng packets to each other n a mult-hop fashon. Snce those moble devces are battery operated and extendng the battery lfetme has become an mportant objectve, researchers and practtoners have recently started to consder power-aware desgn of network protocols for the Ad hoc networkng envronment [1]-[]. As each moble node n a MANET performs the routng functon for establshng communcaton among dfferent nodes the death of even a few of the nodes due to energy exhauston mght cause dsrupton of servce n the entre network. In a conventonal routng algorthm for ad hoc network, whch s unaware of energy budget, connectons between two nodes are establshed between nodes through the shortest path routes. Ths algorthm may however result n a quck depleton of the battery energy of the nodes along the most heavly used routes n the network. We must consder both the lfe tme of the battery of the moble devces and the dstance that the routes takes. Moble Ad Hoc Network (MANET) s an autonomous system wth moble hosts connected by wreless lnks and work ndependent of any common central control. Routng n MANETs has been the subject of ntense research efforts over the past few years; these efforts have resulted n numerous proposals for routng protocols. Typcally n moble ad hoc networks, t s assumed that all the devces that make up the network are cooperatve n partcular they are wllng to act as ntermedate nodes n a routng path by forwardng data for other network nodes. These hosts are self-adaptve n that f there are changes n the network they also have to change ther won routng tables to reflect the changes of the network.

Ad Hoc LAN Fg 1: A Smple Moble Ad Hoc Network The lmtaton of fnte energy supply of wreless devces rases concerns about the tradtonal belef that nodes n ad hoc network wll always relay packets for each other. Energy effcency s a key objectve n many routng protocols. An energy effcent routng protocol ensures that a packet from a source node to a destnaton gets routed along the most energy effcent path possble va ntermedate nodes. Falure of some nodes n the network mght result n lack of connectvty between nodes that are stll alve. Hence we should consder the proper utlzaton of the lmted power of a node of wreless network. Selecton of the least power cost route may possess a harmful mpact on the network stablty. Thus t s better to use a routng soluton that avods usng nodes havng small amount of remanng battery energy. The remander of ths paper s organzed as follows. In next secton we dscuss the problem of routng n moble networks and provde the metrcs we used for performance evaluaton. Secton 3 contans revew of some recent related research works. Secton 4 descrbes the Djkstra algorthm wth proposed necessary modfcaton. Secton descrbes the ratonale and detals of the proposed cost-effectve lfetme based algorthm. Secton 6 elaborates on the smulaton envronment, the mplementaton and expermental results comparng Cost Effectve Lfetme Predcton (CELP) wth Lfetme Predcton Routng (LPR), Demand Source Routng (DSR) and power-aware routng. At last, Secton concludes ths paper. Metrcs We encounter two conflctng goals: on the one sde, n order to optmze cost, least cost or shortesthop routng should be used, whle on the other sde, use of shortest-hop route means that nodes wth hgher degree mght de soon snce they are used n most cases. An nterestng property of usng least-cost routng s that packet delay does not ncrease. The cost of forwardng messages could be defned and determned n varous ways takng nto account factors such as cost of energy used to forward messages, hop count, delay, lnk qualty as well as other factors. Another metrcs used s the lfetme of nodes, whch s a functon of the remanng battery energy. As n [1], lfetme of a node s predcted based on the resdual battery capacty and the rate of energy dscharge. Our routng algorthm s a reactve routng protocol, whch only takes acton and starts computng routng paths when a network ntates a sesson. It uses a DSR-lke route dscovery protocol and channels all nformaton regardng cost and lfetme to the destnaton node. The destnaton node computes the cost and lfetme of each path and sends ths nformaton back to the source. 3 Related work Some researchers have tred energy effcent broadcast / multcast algorthm [6] []. One major approach for energy conservaton s to route a communcaton sesson along the route whch requres the lowest total energy consumpton [8][]. Ths optmzaton problem s referred to as Mnmum-Energy Routng [10]. Whle the mnmum-energy uncast routng problem can be solved n polynomal tme by shortest-path algorthms, t remans open whether the mnmumenergy broadcast routng problem can be solved n polynomal tme, despte the NP-hardness of ts general graph verson. Recently three greedy heurstcs were proposed n [11] MST (Mnmum Spannng Tree), SPT (Shortest-Path Tree), and BIP (Broadcastng Incremental Power). They have been evaluated through smulatons n [1], It has recently been recognzed that medum access control (MAC) schemes can sgnfcantly ncrease the energy effcently of moble batteres [13]. If moble devce A transmts data to another moble devce B, neghborng mobles do not lsten to the data from moble A snce lstenng causes unnecessary moble power consumpton. Another energy effcent MAC scheme has been proposed n [14]. The man dsadvantage of power aware routng [1] technques s that t always selects the least

power cost routes. As a result, there s a large possblty of selectng a node, whch has a very lttle lfetme; hence t would de early. So the network wll get dsconnected and the network lfetme wll be adversely affected. Besdes, n these technques a partcular node may become a vctm because of ts poston at such a place that makes t selected frequently and hence de early. Ths s doubly harmful snce the node that de early s precsely the one that s needed most to mantan the network connectvty. Therefore, t wll be better to use a hgher power cost route f ths routng soluton avods usng nodes that have a small lfetme. Keepng t n mnd, [1] proposes a lfetme predcton based routng algorthm. Lfetme predcton routng s an on demand source routng protocol that uses battery lfetme predcton. The objectve of ths routng protocol s to extend the servce lfe of wth dynamc topology. Ths protocol favors the path whose lfetme s maxmum. The authors calculated the lfetme of a route wth the followng equaton. MaxT ( t) = Mn( T ( t)) π π επ Where: T π (t): lfetme of path π T (t): predcted lfetme of node n path π In ths algorthm lfetme of a path s predcted by the mnmum lfetme of all nodes along the path. That path s selected whch has maxmum value of calculated mnmum lfetmes. The man objectve of LPR s to mnmze the varance n the remanng energes of all the nodes and thereby prolong the network lfetme. Although, LPR ncreases the stablty of the network, ths technque has totally overlooked the cost of routng. To acheve best performance we propose a routng algorthm that combnes the best features of the two above-mentoned technques. 4 Development of Algorthm Vrtually all packet-swtchng networks and all nternets base ther routng on some form of leastcost crteron. Most least-cost routng algorthms n use are varatons of one of two common algorthms, known as Djkstra s Algorthm and the Bellman-Ford algorthm. To mplement our project proposal, we have used Djkstra s Algorthm and modfed t where necessary. Djkstra s algorthm can be stated as follows- Fnd the shortest paths from a gven source node to all other nodes, by developng the paths n order of ncreasng path length. The algorthm proceeds n stage, the shortest paths to the k nodes closest to (least cost away from) the source node have been determned; these nodes are n a set T. At stage (k+1), the node not n T that has the shortest path from the source node s added to T. As each node s added to T, ts path from the source s defned. The algorthm can be formally descrbed as follows. N = Set of nodes n the network. s = Source node. T = Set of nodes so far ncorporated by the algorthm. W(,j)= lnk cost from node to node j; w(,j)=0; w(,j)=, f the two nodes are not drectly connected; w(,j) 0 f the two nodes are drectly connected. L(n)= cost of the least cost path from node s to node n that s currently known to the algorthm; at termnaton, ths t s the cost of the least-cost path n the graph from s to n. The algorthm has three steps; step and 3 are repeated untl T=N. That s step and 3 are repeated untl fnal paths have been assgned to all node n the network. The steps are as follows: Step 1: [Intalzaton] T = {s}.e. the set of nodes so far ncorporated conssts of only the source node. L(n) = w(,j) for n s.e. the ntal path cost to neghborng nodes are smply the lnk cost. Step : [Get Next Node] Fnd the neghborng node not n T that has the least-cost path from node s and ncorporate that node nto T: also ncorporate the edge that s ncdent on that node and a node n T that contrbutes to the path. Ths can be expressed as- Fnd x T such that L(n) = mn L(j) j T Step 3: [Update Least-Cost Path] L(n) = mn[l(n), L(x) + w(x,n)] for all n M If the latter term s the mnmum, the path from s to n s now the path from s to x concatenated wth the edge from x to n. The algorthm termnates when all nodes have been added to T. At termnaton, the value L(x) assocated wth each node x s the cost (length) of

the least-cost path from s to x. In addton, T defnes the least-cost path from s to each other node. On teraton of the step and step 3 adds one new node to T and defnes the least-cost path from s to that node. That path passes only through nodes that are n T. To see ths, let us consder ths followng lne of reasonng: After K teratons, there are K nodes n T, and the least-cost path from s to each of these nodes has been defned. Let us now consder all possble paths from s to nodes not n T. Among those paths, there s one of least cost that passes exclusvely through nodes n T, endng wth a drect lnk from some node n T to a node not n T. Ths node s added to T and the assocated path s defned as the least cost path from that node. 4.1 Modfed developed algorthm 1. Durng the tme of fndng the shortest-path (least-cost path) the man calculaton nvolves the steps and 3, that s. Fnd x T such that L(n) = mn L(j) j T 3. L(n) = mn[l(n), L(x) + w(x,n)] for all n M We have used these two concepts n three dfferent ways. They are: Frstly, we have used the algorthm as t s provded to calculate the least-cost path through the network. Secondly, we have consdered the lfetme of the battery of the moble devce as the path weght to mplement the concept that the path wll consst only wth the hgh powered nodes on the way from the source to the destnaton. In order to mantan the ntegrty of the algorthm, we have just negated the battery power that facltated us wth the concept of least-cost path. For example, f x s an nteger greater than all other ntegers n a set, negaton of x (.e. x ) wll change t to the smallest nteger of the set. Thrdly, to mplement our proposed method we have frstly calculated the value of the functon composed of lterals (.e. scalng factor ξ, path selectng parameter β and cost of path Ĝ) that we have proposed. We have used the value of ths functon to compute the desred route. Proposed Model A network N=(V,E, ω) conssts of a set of nodes V={v 1,.,v n } that represent moble devces, a set E V x V of drected edges (v, v j ) that connect two nodes, and a weght functon ω:e R (Ratonal number) for each edge (v, v j ) that ndcates the cost of transmttng a data packet from node v to v j. Each node has a unque dentfcaton number, but t s not a pror known whch nodes are currently n the network, nor s edge set E or weght functon ω known. A node can not control the drecton n whch t sends data, and thus data are broadcast to all nodes nsde ts transmsson range. Nodes can move and the edge cost between any two nodes can change over tme. Also the lfetme of any node can change over tme. However, for the ease of presentaton, we assume a statc network durng the route dscovery phase..1 Cost-Effectve Lfetme Predcton based routng (CELP) Our objectve s to select a cost effectve route, whch affects less on the stablty of the network. Routng cost and lfetme of nodes are used as the selectng parameters of a path. In power-aware routng algorthms the selected path of transmsson s the most cost-effectve whereas n lfetme predctve routng algorthms selects a path wth maxmum lfetme and hence results stablty of the network. Power-aware routng algorthms suffer from poor stablty and lfetme predcaton based routng algorthms suffer from poor cost effectveness. Our proposed CLPR algorthm s more stable than that of power-aware routng and also has less cost than that of lfetme predcton routng. Let us assume the possble lfetme of any node s up to L and the possble transfer cost between any two nodes s up to C. We defne a scalng factor ξ as the rato of the two parameters. L ξ = C Let there be n paths (π 1, π,..π n ) from source to destnaton. Then lfetme of a path π s τ = MnT j (t) jε and the cost of a path π s ς = π m 1 cπ j, j + 1 j= 1 ( t) where π m s number of nodes n path π and c j,j+1 s the cost between node j and j+1. Our path selectng parameter β s represented by τ β = ξς

The algorthm selects a path, whch has the largest β. If more than one path havng hghest β s found, the path wth hghest hop count wll be selected. 0 S 8 E C 100 A 6 40 40 Fg : A network wth 8 moble nodes wth ther battery lfetmes (Network 1). As an example, consder the scenaro shown n fgure. Here from source (S) to destnaton (D) there are sx paths. They are: Path 1: S A B D Path : S A B C F G D Path 3: S E F C B D Path 4: S E F G D Path : S C F G D and Path 6: S C B D. If we calculate the total cost along each path and select the path wth mnmum cost among them, as done n cost-effectve routng, we get the path 1: S A B D havng cost 1 and lfetme 100s. Whle n LPR the path 4: S E F G D s chosen havng lfetme 40s and cost. For our CELP algorthm let us assume maxmum cost (C) between any two nodes s 1 and maxmum lfetme (L) of any node s 600. So the scalng factor ξ becomes 40. Hence, usng CELP algorthm the selectng parameter β for the path- 1, path-, path- 3, path- 4, path- and path- 6 are 0.1316, 0.068, 0.8, 0.38, 0.304 and 0.44 respectvely. So the selected path s path 6: S C B D havng cost and lfetme. As another example, consder the scenaro shown n fgure 3. Here from source (A) to 10 00 6 3 B 10 4 J 300 0 F 1 1 30 A D G 30 3 00 E 6 I H F 00 B 0 G 46 8 D destnaton (J) there are twelve paths to reach from source to destnaton. Fg 3: A network wth 10 moble nodes wth ther battery lfetmes (Network ). Those paths are: Path 1: A B C F J Path : A D F J Path 3: A D C F J Path 4: A E H I J Path : A E H D F J Path 6: A E H D C F J Path : A E H G J Path 8: A E H G F J Path : A D H I J Path 10: A D H G J Path 11: A B C D F J and Path 1: A B C D H I J. If we calculate the total cost along each path and select the path wth mnmum cost among them, as done n cost-effectve routng, we get the path-, havng cost 11 and lfetme 0s. Whle n LPR the route path-4 s chosen havng lfetme 30s and cost 3. So the selected path for our proposed CELP based method s path-: A E H G J havng cost 1 and lfetme 30. Now we wll consder another network shown n fgure 4. Here we have 13 nodes. Let the Source s A and the destnaton s M. If we use Cost-Effectve Routng then the path wll be- path 1: A B E I M, If we use Lfetme Predcton Routng then the path wll be- path 14: A D H G K M and f we use our proposed Cost Effectve Lfetme Predcton then the path wll be- path 1: A D H L M. 30 B D 3 0 6 A C 10 F 100 E 300 4 G 0 10 I 30 J 30 H 00 K M 0 8 L 30

Fg 4: A network wth 13 moble nodes wth ther battery lfetmes (Network 3). The paths are: Path 1: A B E I M Path : A B F E I M Path 3: A B F J M Path 4: A B F J K M Path : A B F J K G H L M Path 6: A C G K J F B E I M Path : A C G K J F E I M Path 8: A C G K J M Path : A C G K M Path 10: A C G H L M Path 11: A D H G K J F B E I M Path 1: A D H G K J F E I M Path 13: A D H G K J M Path 14: A D H G K M and Path 1: A D H L M Here s a comparson tables for the path-cost and network lfetme for the three methods for the above three networks. COST-EFF. LPR CELP Network 1 1 Network 11 3 1 Network 3 13 40 30 Table 1: Path-Costs for dfferent Networks COST-EFF. LPR CELP Network 1 40 600 Network 0 30 30 Network 3 0 30 Table : Network-Lfetmes for dfferent Networks The followng two charts fgure and fgure 6 wll graphcally show the comparsons of path-cost and network lfetme for the exstng two protocols and wth our proposed one for those three networks. Cost Lfetme 4 40 3 30 0 1 10 0 00 600 00 300 00 100 0 Comparson Chart for Path Cost Network 1 Network Network 3 Routng Protocols Fg : A Comparson of Path Cost for dfferent Routng protocols. Comparson Chart for Network Lfetme Network 1 Network Network 3 Routng Protocols Cost-Eff. LPR CELP Cost-Eff. LPR CELP Fg 6: A Comparson of Network lfetme for dfferent Routng protocols. We fnd that CELP s better than CLP n cost perspectve and also better than cost-effectve routng n stablty perspectve. Although CELP may selects a path wth cost lttle hgher than a path wth least cost and a path havng lttle less of lfetme than a path havng hghest lfetme, ths s acceptable consderng both the stablty and the cost-effectveness of the route. Smulaton In our dscrete event drven smulaton we used up to 0 nodes. The lfetme of a node may vary between 1 and 00 whle the transmsson to neghborng nodes may vary between 1 and 0.

Random connectons were establshed where each node has chance to connect wth every other nodes. The smulaton was run for 000 tme unt. Nodes followed random vewpont moblty model. Each packet relayed or transmtted has a cost factor and ths cost s consdered as the cost at the transmtter node. 6 Concluson A cost effectve lfetme predcton (CELP) based routng protocol for moble ad hoc networks that ncrease the network lfetme and performance, was presented n ths paper. Smulaton results show that the proposed "Cost Effectve Lfetme Predcton (CELP)" protocol can ncrease the network lfetme more than 0%. In the prevous works, whle they are tryng to ncrease the lfetme of the network, they just consdered the battery power of the moble devsed. They ddn t consder the dstance that the selected route covered. So most of the tme, t has chosen the longest path to maxmze the network lfetme. Here securty may be hampered due to the longest dstance from the source to the destnaton. Our proposed method has cut the dstance short whle ncreasng network lfetme. References: [1] M. Malek, K. Dantu and M. Perdram, Lfetme Predcton Routng n Moble Ad- Hoc Networks, proc. Of IEEE Wreless Communcaton and Networkng Conf., Mar, 003. [] Davd B. Johnson, Davd A. Maltz, Yh-Chun Hu and Jorjeta G. Jetcheva. The Dynamc Source Routng for Moble Ad Hoc Wreless Networks, http://www.etf.org/nternetdrafts/draftetf-manet-dsr-06.txt, IETF Internet Draft, Nov. 001. [3] S. Lndsey, K. Svalngam and C.S. Raghavendra, Power Aware Routng and MAC protocols for Wreless and Moble Networks, n Wley Handbook on Wreless Networks and Moble Computng; Ivan Stojmenvc, Ed., John Wley & Sons, 001 [4] Stojmenovc and X. Ln, Power-aware localzed routng n wreless networks. Proc. IEEE IPDPS, Cancun, Mexco, May 000. [] S. Sngh, M.Woo and C.S. Raghavendra, Power-Aware Routng n Moble Ad hoc Networks, Proceedngs of Mobcom 8. [6] J. E. Weselther, G. D. Nguyen and A. Ephremdes, On the Constructon of Energy- Effcent Broadcast and Multcast Trees n Wreless Networks, Proc. of IEEE Infocom 000, March 000. [] J. E. Weselther, G. D. Nguyen and A. Ephremdes, Energy-Effcent Broadcast and Multcast Trees n Wreless Networks, Moble Networks and Applcatons archve, Vol., Issue 6. Dec. 00, pp- 481 4. [8] J. H. Chang and L. Tassulas, Energy Conservng Routng n Wreless Ad Hoc Networks, Proc. of Infocom 000, March 000. [] A. Mchal and A. Ephremdes, Energy Effcency Routng for Connecton-Orented Traffc n Ad Hoc Wreless Networks, Proc. of the 11th IEEE Internatonal Symposum on Personal, Indoor and Moble Rado Communcaton (PIMRC), 000. [10] J. Wan, G. C. Alnescu, and O. Freder, Mnmum-Energy Broadcastng n Statc Ad Hoc Wreless Networks,Wreless Networks 8, 00. [11] C. Olvera, J. Km, and T. Suda, An Adaptve Bandwdth Reservaton Scheme for Hgh Speed Multmeda Wreless Net-works, IEEE J. Select. Areas n Commun., Vol. 16, Aug. 18, pp. 88-83. [1] J.E. Weselther, G.D. Nguyen and A. Ephremdes, On the constructon of energyeffcent broadcast and multcast trees n wreless networks, Proc. of IEEE Infocom 000, March 000. [13] H. Woesner, J. Evert, M. Schlager, and A. Wolsz, Power-savng mechansms n emergng standards for Wreless LANs: the MAC level perspectve, IEEE Pers. Commun, 18, (3). [14] K. Jn and D. Cho, A MAC algorthm for energy-lmted ad-hoc networks,ieee Vehcular Technology Socety, Fall Vtc 00, vol. 1, Boston, Sep. 000. [1] S. Sngh, M. Woo, and C. Raghavendra, "Power-aware routng n moble ad hoc networks," proc. 4th Annual ACM/IEEE Int. Conf. Moble Computng Networkng, Oct. 18.