International Journal of Modern Engineering Research (IJMER)             Vol.2, Issue.6, Nov-Dec. 2...
International Journal of Modern Engineering Research (IJMER)              Vol.2, Issue.6, Nov-Dec. ...
International Journal of Modern Engineering Research (IJMER)              Vol.2, Issue.6, Nov-Dec. ...
International Journal of Modern Engineering Research (IJMER)              Vol.2, Issue.6, Nov-Dec. ...
International Journal of Modern Engineering Research (IJMER)            Vol.2, Issue.6, Nov-Dec. 20...
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Performance Analysis of Routing Metrics for Wireless Sensor Networks


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Performance Analysis of Routing Metrics for Wireless Sensor Networks

  1. 1. International Journal of Modern Engineering Research (IJMER) Vol.2, Issue.6, Nov-Dec. 2012 pp-4128-4132 ISSN: 2249-6645Performance Analysis of Routing Metrics for Wireless Sensor Networks Eswar Rao. K, 1 K Naresh Kumar2 (Assistant professor, Aditya Institute of Technology and Management, Andhra Pradesh, India)ABSTRACT: A wireless sensor network is a trivially based on simply flooding the entire network.heterogeneous network consisting of a large number of tiny However, more elaborate routing algorithms are essentiallow-cost nodes and one or more base stations. Each sensor for the applicability of such wireless networks, since energynode comprises sensing, processing, transmission, mobilize, has to be conserved in low powered devices and wirelessposition finding system, and power units. These networks communication always leads to increased energycan use in various applications like military, health and consumption.commercial. Routing in wireless sensor networks has been The rest of the paper is organized as section 2:an active area of research for many years. Sensor nodes discuss about various routing metrics, section 3: presents ahave a limited transmission range, processing, storage comparison of routing metrics, section 4: concludes thecapabilities and energy resources are also limited. In paper.wireless sensor networks data is forwarded using multi-hopmechanism. Therefore, a variety of routing metrics has II. ROUTING METRICSbeen proposed by various authors in wireless sensor The existing routing metrics are classified into fivenetworks for providing routing algorithms with high categories based on their operation. Topology based, Signalflexibility in the selection of best path and offering a strength based, Active probing based, Mobility aware andcompromise between throughput, end-to-end delay, and Energy aware consumption. In this paper, we present a detailedsurvey about existing routing metrics in wireless sensor 1.1. Topology Basednetworks. The routing metrics are also compared based on In this technique the topological information of thetheir essential characteristics and tabulated. network will be considered i,e. the number of neighbors of each node, number of hops and/or paths towards aKeywords: WCETT, ETT, ETX, Hopcount, RTT, MIC particular destination. The metrics always consider connectivity information which is available locally by the I. INTRODUCTION routing protocol, without requiring additional passive or A wireless sensor network (WSN) is a active measurements. The topology-based metrics do notheterogeneous network consisting of a large number of tiny take into account several variables that have an impact onlow-cost nodes (devices) and one or more base stations both the network and application performance, such as the(sinks). Main purpose of the WSN is to monitor some transmit rates of the links are popular due to theirphysical phenomena (e.g., temperature, barometric simplicity.pressure, light) inside an area of deployment. Nodes areequipped with radio transceiver, processing unit, battery Hop countand sensor(s). Nodes are constrained in processing power In this metric, every link counts as one equal unitand energy, whereas the base stations are not severely independent of the quality or other characteristics of theenergy resources. The base station act as gateways between link and very simple technique. The ease of implementationthe WSN and other networks such as Internet etc.. The has made hop count the most widely used metric in wiredWSN is used in various applications like military, health networks and it is the default metric in many wirelessand commercial. They provide simple and cheap sensor networks routing protocols, such as OLSR [2], DSRmechanism for monitoring in the specified area. WSNs are [3], DSDV [4] and AODV [5]. Fewer hops on the data pathfrequently deployed to collect sensitive information. WSN produce smaller delay, whether these involve network linkscan be used to monitor the movements of traffic in a city. or buffers or computational power. The implicit assumption Such a network can be used to determine location is the existence of error-free links. On the contrary, links inof people or vehicles [1]. WSNs can be classified according wireless sensor networks cannot be assumed several aspects with impact on the security protocoldesign. One such aspect is the mobility of nodes and the 1.2. Signal Strength Based Metricsbase station. The nodes can be mobile or placed on static Signal strength metric has been used as linkpositions. The same holds true for the base station. Another quality metrics in several routing protocols for wirelessconsideration is the way the nodes are placed. The nodes sensor networks. The signal strength can be viewed as acan be deployed manually on specific locations following good indicator for measuring link quality since a packet cansome predefined network topology or randomly deployed in be transferred successfully when the signal strength is morean area, e.g., by dropping from a plane. The number of than the threshold value.nodes is also a very important factor number of nodes in anetwork can range from tens to tens of thousands. Because 1.3. Active Probing Based Metricsof limited transmission range, communication between any To overcome the drawbacks of topology basedtwo devices requires collaborating intermediate forwarding metrics various authors have proposed active probingnetwork nodes, i.e. devices act as routers to forward the metrics to carry out active measurements and use probedata. Communication between any two nodes may be packets to directly estimate those probabilities. Probing 4128 | Page
  2. 2. International Journal of Modern Engineering Research (IJMER) Vol.2, Issue.6, Nov-Dec. 2012 pp-4128-4132 ISSN: 2249-6645technique had various challenges such as packet sizes of Expected Transmission Time (ETT) metric incorporatingprobes in the network should be equal to the data so that the throughput into its calculation. Let S be the size of thewhat probes measure is as close to the target as possible and probing packet and B the measured bandwidth of a link,probe packets should not give any priority in the network. then the ETT of this link is defined asThe probing based metrics have proved promising in thecontext of wireless sensor networks. They measure directlythe quantity of interest, rather than inferring it from indirectmeasurements, and do not rely on analytical assumptions. Awerbuch [8] proposed Medium Time Metric (MTM) based on overhead, reliability of the link and size of thePer-hop Round Trip Time (RTT) packet. The per-hop Round-Trip Time (RTT) metric isbased on the bidirectional delay on a link [6]. In order tomeasure the RTT, a probe packet is sent periodically toeach neighboring node with time stamp. Then eachneighbor node returns the probe immediately. This proberesponse enables the sending node to calculate the RTT Where overhead is defined as per-packet overheadvalue. The path RTT metric is the summation of all links of the link that includes control frames, back-off, and fixedRTT in the route. The RTT metric is dependent on the headers and reliability is denoted as the fraction of packetsnetwork traffic. Since it comprises queuing, channel delivered successfully over the link.contention, as well as 802.11 MAC retransmission delays. As wireless sensor networks provide multiple non- overlapping channels, they propose an adaptation of thePer-hop packet pair delay (PktPair) ETT metric accounting for the use of multiple channels, This delay technique is designed to overcome the namely the Weighted Cumulative ETT (WCETT). Let k beproblem of distortion of RTT measurements due to queuing the total number of channels of a system, the sum ofdelays and it consists periodic transmission of two probe transmission times over all nodes on channel j is defined as:packets with different sizes back-to-back from each node.The neighbor node calculates the inter-probe arrival delayand reports it back to the sender. This metric is lesssusceptible to self-interference than the RTT metric, but it As total path throughput will be dominated by theis not completely immune, as probe packets in multi-hop bottleneck channel, they propose to use a weighted averagescenario contend for the wireless channel with data packets. between the maximum value and the sum of all ETTs.Both the RTT and PktPair metrics measure delay directly,hence they are load-dependent and prone to the self-interference phenomenon. Moreover, the measurementoverhead they introduce is O(n 2), where n is the number of The main disadvantage of the WCETT metric is that it isnodes. not immediately clear if there is an algorithm that can compute the path with the lowest weight in polynomial orExpected Transmission Count (ETX) less time. To overcome drawbacks of RTT and PktPairtechniques, authors proposed Expected Transmission Count Metric of Interference and Channel switching (MIC)(ETX) metric which is first routing metric based on active The Metric of Interference and Channel switching (MIC)probing measurements designed for wireless sensor [9] considers intra-flow and inter-flow interferencenetworks. ETX estimates the number of transmissions problem. The MIC metric of a path p is definedrequired to send a packet over a link. Minimizing thenumber of transmissions optimize the overall throughputand energy consumption. Let df is the expected forwarddelivery ratio and dr is the reverse delivery ratio, Assumingthat each attempt to transmit a packet is statistically where N is the total number of nodes in the network andindependent from the precedent attempt, each transmission min(ETT) is the smallest ETT in the network, which can beattempt can be considered a Bernoulli trial and the number estimated based on the lowest transmission rate of theof attempts till the packet is successfully received a wireless cards. The two components of MIC, Interference-Geometric variable, the expected number of transmissions aware Re-source Usage (IRU) and Channel Switching Costis defined as (CSC) are defined as:Expected Transmission Time (ETT), Medium Time Metric(MTM), and Weighted Cumulative ExpectedTransmission Time (WCETT) Multi-Channel Routing Metric (MCR) Draves [7] presented the drawbacks of ETX Kyasanur and Vaidya [10] extend WCETT bytechnique such as it prefers heavily congested links to considering the cost of changing channels. Letunloaded links, if the link-layer loss rate of congested links InterfaceUsage(i) be the fraction of time a switchableis smaller than on the unloaded links. Later he proposed the 4129 | Page
  3. 3. International Journal of Modern Engineering Research (IJMER) Vol.2, Issue.6, Nov-Dec. 2012 pp-4128-4132 ISSN: 2249-6645interface spends on transmitting on channel i and let pi(j)be estimated as a function of the associativity ticks over allthe probability t used interface is on a different channel links along the routewhen we want to send a packet on channel j. If we assumethat the total of the current interface idle time canpotentially be used on channel j, we can estimate as ps(j) Link affinity and path stability The affinity of a link is related to the received power over that link, its rate of change and a threshold, determiningLet SwitchingDelay denote the switching latency of an whether the link is broken or not. Each node calculates theinterface. Then, the cost of using channel j is measured as strength of the signal received over periodically. The signal strength change rate as the average rate of signal strengthIn order to prevent frequent channel switching of the change aschosen paths, a switching cost is included into the ETTmetric, so that the resulting MCR metric becomes The link affinity is determined byModified ETX (mETX) and effective number oftransmissions (ENT)Koksal and Balakrishnan [11] considered the accuracy of The affinity between two nodes A and B is then given by loss estimator function. In certain conditions suchas links with low average loss rate but high variability, the The route stability is then given by the minimum of theestimation capacity of the mean statistic is poor. They affinities of all links lying in the routepropose two alternative statistics for the estimation ofrequired number of transmissions over a link. The route is selected as long as the estimated value for itsModified ETX (mETX), is defined as stability exceeds the required time to transfer data, whose estimate equals the time required to transmit data over the link capacity C.where μ is the estimated average packet loss ratio of a linkand the variance of this value. Like ETX, mETX is additive Mobility-model driven metricsover concatenated links. Mcdonald and Znati [14] proposed mobility-model driven metric, which defines a probabilistic measure of theEffective Number of Transmissions (ENT), is defined as availability of links that are subject to link failures caused by node mobility. Each node is characterized by statistical distribution of the mean, variance of the speed of a nodeThe δ acts as an additional degree of freedom with respect and average interval time. Gerharz et al. [15] and Jiang etto mETX and the value of δ depends on the number of al. [16] proposed metric based on the estimation of averagesubsequent retransmissions, which will cause the link layer residual lifetime of a link. However, the weak link in allprotocol to give up a transmission attempt. these studies is the assumption that all nodes have similar mobility characteristics which is not acceptable in wireless 1.4. Mobility-Aware Metrics sensor networks. Mobility-aware metrics selects routes with higherexpected life-time to minimize the routing overhead related 1.5. Energy-Aware Metricsto route changes and their impact on throughput. The Energy consumption is an important constraint inmetrics largely use signal strength measurements and their wireless sensor networks. Sensors have restricted batteryrate of variation to infer the stability of links and routes. lifetime and are most vulnerable to the energy constraints.The path average degree of association stability, as In some cases, choosing paths so that the overall delay isproposed in the context of associativity based routing minimized may result in overuse of certain nodes in the(ABR) and the affinity metric defined in [12] and reused network and premature exhaustion of their the Route-Lifetime Assessment Based Routing (RABR) Therefore, energy concerns have to be properly reflected inprotocol in [13]. the definition of routing metrics. The total energy consumed when sending and receiving a packet isLink associativity ticks and path average degree of influenced by various factors such as the wireless radioassociation stability propagation environment, interference from simultaneous Sensor nodes transmit beacon packets at fixed time transmissions, MAC protocol operation, and routingintervals and calculate the received number of probs from algorithm. The aim objective of energy aware metrics is totheir neighbors. These values serve as indicators of the minimize overall energy consumption and to maximize theactual stability of the link. Low values of associativity ticks time until the first node runs out of energy.imply mobile nodes in high mobility state, whereas highassociativity ticks, beyond some threshold value thrA, are Minimal Total Power routing (MTPR)obtained when a mobile node is more stable. The average K. Scott [17] proposed Minimal Total Powerdegree of association stability over route R, AaveR, is Routing metric MTPR to minimize the overall energy 4130 | Page
  4. 4. International Journal of Modern Engineering Research (IJMER) Vol.2, Issue.6, Nov-Dec. 2012 pp-4128-4132 ISSN: 2249-6645consumption. Later Singh [18] formalize this idea. Let ei,j Maximal residual energy path routing (MREP)denote the energy consumed for transferring a packet from Chang and Tassiulas [22] proposed Maximumnode i to the neighboring node j. Then, if the packet has to Residual Energy Path (MREP) link metric based on thetraverse the path p, including nodes n1…..nk, the total remaining battery capacity and the necessary transmissionenergy E required for the packet transfer is energy. Let ei,j be the energy consumed to send one packet over the link from node i to node j, Ej the initial battery energy and E‟j the residual energy at node j. Chang and Tassiulas define two metrics for the link i to j. TheMinimum battery cost routing (MBCR) remaining energy of a node di,j, defined as In this metric the battery capacity of a node istaken into consideration to balance the energy consumptionover all nodes in a network. The “Minimum Battery Cost and the inverse of the residual capacity of a node in termsRouting” (MBCR) [18] is based on the remaining battery of packets that can be delivered with the remaining energycapacity of the node. The ratio of battery capacity Rbrc isdefined as 2. Comparison of Routing MetricsUnder the assumption that all nodes have the same battery The various metrics are compared based on importantfull capacity, a cost value fi(Ei) is assigned to each node n i parameters and tabulated below table 1.based on its residual battery capacity E i Table 1: comparison of routing metrics Metrics Optimization Metric PathThen the total available battery lifetime along a path p is the Objectives Computation Metricsum of the battery capacities of all nodes along the route Method Function Topology Minimize Use of locally Summation based delay availableOut of the full set P of possible paths, the one selected p’ informationfeatures minimum total residual battery capacity Signal Higher Use of locally Based on strength expected available routingThe aim drawback of MBCR is that the selected route may based route life time information algorithmwell feature individual nodes with small remaining battery Active Minimize Active Summationcapacity. probing delay probing based MinimizeMin-Max Battery Cost Routing (MMBCR) probability of The Min-Max Battery Cost Routing (MMBCR) data deliverymetric [19] addresses the drawbacks of MCBR metric in Mobility Higher Active Based onavoiding nodes with very low residual battery capacity aware expected probing the routingalong paths with high overall battery capacity. The idea is route lifetime Metrics algorithmto select a path, which minimizes the maximum power piggybackedrequired at any node in a network. The MMCBR the chosen to routepath must p‟ fulfill discovery packets Energy Minimize Use of locally Summation aware energy availableConditional max-min battery capacity routing consumption information(CMMBCR) Toh [20] combines the MTPR and MMBCR into III. CONCLUSIONone single hybrid routing metric called Conditional Max- A wireless sensor network is a heterogeneous networkMin Battery Capacity Routing (CMMBCR) metric. It consisting of a large number of tiny low-cost nodes and onesearches paths using MTPR, with the restriction that all or more base stations. These networks can use in variousnodes need to have a remaining percentage battery capacity applications like military, health and commercial. Routingthat exceeds a threshold value γ. If there is no such path in wireless sensor networks has been an active area ofthen MMBCR is used. research for many years. Sensor nodes have a limited Later Kim [21] compares MTPR, MMBCR and transmission range, processing, storage capabilities andCMMBCR. He presented the overhearing transmissions of energy resources are also limited. In this paper, wesome neighboring nodes have a significant impact on the presented a detailed survey about existing routing metrics inperformance of each metric and all behave similarly. In wireless sensor networks. The routing metrics are alsodense networks MTPR allows connections to live longer, compared based on their essential characteristics andwhereas in sparse networks it is more important to avoid tabulated. As sensor nodes have limited battery capabilitynetwork partition hence MMBCR performs better. energy aware routing metrics are useful. 4131 | Page
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