Because the CPU is a very expensive resource in mobile ad hoc networks (MANETs), it is very important to consider the overhead introduced in a routing protocol. Many theories have been hypothesized with the aim of minimizing it. But how much is the energy consumption from a network node’s battery induced by the routing protocol overhead? In a previous work, we dealt with a routing protocol based on link stability (link duration observed in a time interval). In this work, we attempt to hypothesize a model for conserving the battery energy consumed by nodes in a MANET adopting the link stability routing protocol

DE BONIS M.

GALLO, CRESCENZIO

PERILLI M.

English

Archivio Istituzionale della Ricerca- Università degli Studi di Foggia

ISSN 0976-1438Current Development in Theory and Applicationsof Computer Science, Engineering andTechnologyReprintScientific Advances Publishers71/52 Bhusoli Tola, KhuldabadAllahabad 211 006 (INDIA)e-mail: atul@scientificadvances.orgCurrent Devdoptnetlt in Theory and Applications of Computer Science, Engineering and TechnologyVolume 4, Number 112,2011, Pages 1-11ENERGY SAVING IN LINK STABILITYROUTING PROTOCOLCRESCENZIO GALLO, MICHELE PERILLIand MICHELANGELO DE BONISDipartimento di Scienze EconomicheMatematiche e StatisticheUniversita di FoggiaLargo Papa Giovanni Paolo IIn.171121 FoggiaItalye-mail: c.gallo@ieee.orgAbstractBecause the CPU is a very expensive resource in mobile ad hoc networks(MANETs), it is very important to consider the overhead introduced in a routingprotocol. Many theories have been hypothesized with the aim of minimizing it.But how much is the energy consumption from a network node's battery inducedby the routing protocol overhead? In a previous work, we dealt with a routingprotocol based on link stability (link duration observed in a time interval). Inthis work, we attempt to hypothesize a model for conserving the battery energycon:-:,mmedby nodes in a :MANETadopting the link stability routing protocol.1. IntroductionThe problem of power consumption in mobile environments is acritical concept because of a continuous route path discovery due tofrequent topology changes. A consequence of the continuous path searchlimits the node's stand-by time, meanwhile increasing transmissions withKeywords and phrases: mobile ad hoc network, routing protocol, energy consumption.Received September 17, 2011© 2011 Scientific Advances Publishers2 CRESCENZIO GALLOet al.an obviously reduced battery lifetime (see Figure 1). This problem caneffectively limit the use and deployment of MANETs. In fact, networkoverhead is one of the main factors responsible for energy consumption. Itcan be seen from two points of view:• Algorithmic overhead. The intrinsic processing implied by therouting protocol, depend~ng on how it has been designed and works (e.g.,polling, synchronizing, etc.).• Data transmission overhead, The data bits added duringtransmission due to protocol rules (e.g" handshaking, transmissioncontrol, etc.).Figure 1. The network overhead in a mobile ad hoc network.From now on, we will deal with the term overhead from bothperspectives.ENERGY SAVIING IIN LINK STABIILITY ... 3In this article, we first present the state of the art on batteryconsumption saving related to existing mobile routing protocols, andparticularly to a recently introduced link stability routing protocol (see[4]). Then, we propose a simple way to save a node's energy consumptionby introducing a new value for the stability index respecting the conceptof energy saving.2. BackgroundIn most of the recently studied routing protocols, research aimed atfinding an efficient protocol minimizing the network overhead. Energyconsumption was not initially considered a real problem in protocolimplementation, But, if we consider a mobile node (such as a PDA), itsusage is strongly conditioned by its battery lifetime. The battery durationcan significantly change depending on transmitter circuits' working time.Some works were accomplished about an energy consumption model(see [1, 2, 3]). The most common routing protocols observed in the modelare dynamic source routing (DSRr and ad hoc on-demand distance vector(AODV). Research shows that energy consumption and bandwidthutilization are often antithetic concepts, So, a model was found toestimate a cost for every protocol situation, such as broadcast anddiscarding traffic. But no works were initiated to calculate and limit theenergy consumption in a real time way.3. Related WorkSome works concentrate on tendency to balance between performanceand energy consumption in a routing protocol. The idea is to estimate theenergy consumed in the first three ISOIOSI model layers: physical, data-link, network. In [6], some methods are presented to limit energyconsumption in the physical and data-link layers, focusing in particularon the third layer. Three different approaches are typically followed toselect the best path and in the same time to limit battery lifetime. Let usexamine them in detail.4 CRESCENZIO GALLOet al.MTPR (Minimal total transmission power routing). The concept ofreducing energy consumption is not devoted to one node, but distributedamong network nodes, so this model founds a way to reduce the totalenergy consumption, Starting from Dijkstra or Bellman-Ford algorithms,it introduces the conceptof power consumption. In this case, the best pathin Dijkstra ,algorithm is the best choice for the stability, because pathminimization maximizes route stability. In fact, in this model, the lowerthe number of nodes to be traversed, the greater the stability because ofnodes' high mobility.MBCR (Minimum battery cost routing). It is based on the conceptthat the energy contained in a battery directly influences the routingability of a node. So, the smaller the available battery energy of a node,the lower its ability to route. Because every node 'has a cost in the routepath (related to its battery level), the total route cost is calculated by asummarization of all node route costs.MMBCR (Min-max battery cost routing), The third approach is verysimilar, but the cost of a route is not a summarization, but the maximumcost value in the route. To make sure that no node will be overused, themost traversed node of a route is considered. Thus, for every route, wehave the most traversed node cost and we choose the minimum cost valueamong them,Another model is the GAF (geographical adaptive fidelity) algorithm[7], It conserves the energy consumption by identifying the importantnodes from a routing perspective, turning off unnecessary ones. Thisalgorithm is independent of the routing protocol, and consumes 40% to60% less energy than traditional ones. It has a limit due toradiolocalization and has been applied in simulation environments toAODVand DSR routing protocols, It starts from the GPS information forevery device, with the limit that we can find many situations, where noGPS signal is received due to physical obstacles,Another idea [5] of energy saving is to maintain the link qualityparameters (such as SIN ratio), when a new user asks for an entranceENERGY SAVIING lIN LINK STABlILITY ". 5into a stable-connected PDA group. The aim is to find the mInImUmtransmission power to satisfy a predefined minimum threshold for theentire group.4. Routing Stability and the Stability Index4.1.Link stabilityIn a previous work [4], we proposed a design for a mobile ad hocnetwork routing protocol based on the concept of stability of the linkbetween two nodes and the consequent stability of the entire route path,The link stability concept was based on the transmission signal's levelvariation measured by the receiving node.This level should not oscillate "too much" in a predefined"observation" time interval I'1T, This is accomplished by sampling sometransmission intensity values in this time interval and checking that(a) every sample does not overcome a percentage threshold of signalvariation with respect to the previous value and (b) it overcomes aminimum acceptable predefined signal value. In the routing protocoldesign, the best route path is chosen on a link stability basis,Finally, a stability index value s associated with every link isestablished, ranging from 0 (for a totally unstable link) to 1 (for acompletely stable link).4.2.Two antithetic concepts: best route and energy battery savingAll MANET routing protocols were studied with the only purpose tofind the best path maximizing throughput and the availability of route,with no consideration for battery life. But battery life reduction may leadusers to stop using mobile devices. A stable link generally implies astrong transmission signal, but this also implies a heavy energyconsumption.We present an idea to reduce battery draining while maintaining the"quality" of route, The idea comes from this question: Are we sure that6 CRESCENZIO GALLOet aLduring a transmission over a stable link we are not using an unnecessaryhigh signal level? This excessive signal level must be reduced and tuned,though respecting the stability of route.If we consider two nodes, the transmitter must use a sufficient powerto reach the receiving node. If PTX is the transmitter power, we can say(1)where d is the distance between two nodes and s is the stability index, Ifthe distance between nodes grows up or the stability index falls down(due to excessive interference or generally because of a too low SIN ratio),the transmitter rises up the transmission power.If we change the observation view on the receiver, we can also saythat the receiving signal level iss(2)where PRX is the intensity of signal detected by the receiving node (innegative value due to attenuation).Thus, referring to our previous algorithm scheme, for every link, wehave to estimate the distance in (2) storing it together with the stabilityindex.Corisequently, we can calculate the PTX value, But may it happen tobe too high? Can we lower it? How can we lower this value maintainingan acceptable stability index value?5.Our Proposal5.1.Transmission power and stability indexConsider a minimum threshold T s(O < T S ~ 1) for the stabilityindexes si detected at the various time intervals. We have to cut awayENERGY SAVIING lIN LINK STABIILITY ... 7the unnecessary transmission power to reduce the battery energyconsumption. To do so, we can decrease the transmission power used inthe i-th observation time interval! 1'l1i by a factor f:i (0 < f:i :5 1)if si ~ Ts,otherwise,(3)where PTX' 1 is the transmission power to be used in the next intervalt+I'lTi+l' if the current stability index si is greater than or equal to theminimum threshold T s' Otherwise. the transmission power remainsunchanged unless updated by a route discovery process, being it no moreacceptable because of a too low stability index. In this case, the routediscovery process has to be restarted in order to maintain the linkstability.In practice, it should be f:i < 1 in order to guarantee an effectivereduction in the transmission power (f:i = 1 means no reduction isapplied to the transmission power), while T s > 0 means we want to onlydeal with a "really stable" index for network links.5.2.How to exactly estimate the reduction factorThe reduction factor f:i depends on the context. In [4], we consideredthe average nodes' mobility rate µ (0:5 µ :5 1, where µ = 0 means nomobility and µ = 1 stands for a network with maximum nodes' mobilityrate). Now, we introduce the "attenuation" parameter a related to thesignal loss due to environmental obstacles (0:5 a :5 1, where a = 0means no attenuation, i.e., a fully open space with no obstacle and a = 1stands for total attenuation, i,e" full signal loss).1 The transmission power reduction can be expressed as a percentage of the previoustransmission power value.8 CRESCENZIO GALLOet aLThese parameters are strongly dependent on environmental aspectsas mobility of nodes and structural obstacles. In fact, if we consider animplementation in closed and highly mobile environments, such asshopping malls or factories, more obstacles are likely to be found withrespect to a relatively static and open environment, such as a sportsstadium.Besides, we consider (for the sake of generality) that the parametersµ and a are varying in time, so we will more precisely denote them byµi and ai·It seems reasonable to consider a direct relation between thecoefficient Ei and the two parameters µi and ai(4)where M is a "reasonable" lower bound for ai . µi.We can, for example, consider M = 0.1 in order to have a maximumreduction percentage of 10% so as to lower the transmission power by anorder of magnitude at the next iteration. We assume that if ai = 0and/or µi = 0, then Ei = M.5.3.Network simulationIn order to carry out an experimental validation of our idea, andstarting from the simulation environment developed in [4], we introducea casual behaviour for a link by randomly updating the parametersai, µi and - consequently -Ei'Table 1 summarizes the experimental results indicating the evolutionof the operating conditions of the sample link in 10 time intervals. Avalue of 0,60 is assumed for the threshold Ts and a missing value for Eimeans a new route discovery process started (at a standard transmissionpower of about 32mW) because of a too instable link.ENERGY SAVIING IIN LINK STABIILITY ... 9From this, it comes that our assumptions are supported by thesimulation here shown, which emphasizes the role of the reductioncoefficient E together with the stability index s. A particular attentionhat to be payed to the sporadic instability of the link, well managed bythe forced restarts related to the route discovery process.6. Conclusions and Future WorkIn most mobile ad hoc network routing protocols, the attention is onhow to quickly reorganize the network during mobility and how to findthe best route without increasing control overhead? However, because ofnodes' limited battery, ;3.dhoc mobile networks should pay more attentionon battery energy consumption in order to prolong network operationlifetime.Table 1. Simulated network's parameters µi, Ui' and Ei for the"observed" link, given Ts = 0.60, M = 0.50, and 10 observation timeintervalsi Distance PTX' PRXi s' U' µi E' E't t t t(in mts),(inmW) (indBm) (computed) (effective)1 47 31.66 - 58.69 0.85 ~ TS 0.05 0.78 0.04 0.502 4 15.83 - 40.30 0.37 < TS 0.39 0.55 0.21 ----3 9 31.66 - 44.33 0.17 < TS 0.68 0.21 0.14 ----4 33 31.66 - 55.62 0.69 ~ TS 0.37 0.31 0.11 0.505 13 15.83 - 50.53 0.70 ~ TS 0.69 0.80 0.55 0.556 71 8.71 - 67.88 0.78 ~ T s 0.87 0.91 0.79 0.797 40 6.88 - 63.92 0.13 < TS 0.74 0.80 0.59 _-0-8 93 31.66 - 64.61 0.08 < TS 0.82 0.43 0.35 ----9 15 31.66 - 48.77 0.83 ~ T s 0.58 0.75 0.44 0.5010 78 15.83 - 66.10 0.27 < TS 0.06 0.55 0.03 .---Starting from simple performance metrics, it is not possible to designan affordable ad hoc without also taking into account battery powercapacity, transmission power consumption, stability of routes, and so on,10 CRESCENZIO GALLOet al.In this work, we hypothesize a model to reduce battery energyconsumption of mobile nodes in ad hoc networks by improving the routediscovery algorithm for the link stability routing protocol [4], withoutintroducing an additional overhead,Our simulation shows that often nodes in an ad hoc wireless networkoveruses their power to perform communication and routing tasks.Battery energy can be fruitfully reduced by following a scheme with a"reduction" factor, It can be periodically computed after an observation ofthe operation conditions of the link to which the transmitting nodebelongs, and taking also into account of entire network's environmentalparameters, such as "average nodes' mobility rate" µ and "signalattenuation" a.In the future, it will be very interesting to find the appropriate a andµ values depending on the implementation environment, besides havinga mapping between these values and the specific application,References(1] L. Feeney, An energy consumption model for performance analysis of routingprotocols for mobile ad hoc networks, Mobile Networks and Applications 6 (2001),239-249, 10.1023/A:101l474616255. [Online]. Available:http://dx.doi.org/10.1023/A:1011474616255[2] L. Feeney and M. Nilsson, Investigating the energy consumption of a wirelessnetwork interface in an ad hoc networking environment, INFO COM 2001,Twentieth Annual Joint Conference of the IEEE Computer and CommunicationsSocieties, Proceedings IEEE. IEEE, USA, Aug 2002.[3] L. Feeney, Energy-efficient communication in ad hoc wireless networks, Mobile AdHoc Networking, Basagni, Conti, Giordano, and Stojmenovic, Eds., Piscataway,IEEE, USA, (2004), 301-327.[4] C. Gallo, M. Perilli and M, D, Bonis, Link stability in manets routing protocols,IARIA UBICOMM 2010. The Fourth International Conference on Mobile UbiquitousComputing, Systems, Services and Technologies (UBICOMM'10), Xpert PublishingServices, USA, Oct 2010.[5] A. Goldsmith and S. Wicker, Design challenges for energy-constrained ad hocwireless networks, IEEE Wireless Commun. Mag. (2002), 8-27.ENERGY SAVIING lIN LINK STABIILITY ,.. 11[6) C,-K. Toh, Maximum battery life routing to support ubiquitous mobile computing inwireless ad hoc networks, IEEE Wireless Commun. Mag. (2001), 2-11.[7) Y. Xu, J, Heidemann and D. Estrin, Geography-informed energy conservation for adhoc routing, Proceedings of the Seventh Annual ACMIIEEE InternationalConference on Mobile Computing and Networking (ACM Mobicom), ACM, July2001.•Current Development in Theory and Applications of Computer Science, Engineeringand TechnologyAims and Scope: The Current Development in Theol)' and Applications of Computer Science,Engineering and Technology is a broad based journal covering all aspects of Computer Science,Engineering and Technology. 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Energy Saving in Link Stability Routing Protocol

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Energy Saving in Link Stability Routing Protocol

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