Interference-Aware Routing Ram a Krishna

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  • 8/3/2019 Interference-Aware Routing Ram a Krishna


    Interference-Aware Routingin Wireless Multihop Networks

    Georgios Parissidis, Student Member, IEEE, Merkourios Karaliopoulos, Member, IEEE,

    Thrasyvoulos Spyropoulos, Member, IEEE, and Bernhard Plattner, Fellow, IEEE

    AbstractInterference is an inherent characteristic of wireless (multihop) communications. Adding interference-awareness to

    important control functions, e.g., routing, could significantly enhance the overall network performance. Despite some initial efforts, it is

    not yet clearly understood how to best capture the effects of interference in routing protocol design. Most existing proposals aim at

    inferring its effect by actively probing the link. However, active probe measurements impose an overhead and may often misrepresent

    the link quality due to their interaction with other networking functions. Therefore, in this paper we follow a different approach and:

    1) propose a simple yet accurate analytical model for the effect of interference on data reception probability, based only on passive

    measurements and information locally available at the node; 2) use this model to design an efficient interference-aware routing

    protocol that performs as well as probing-based protocols, yet avoids all pitfalls related to active probe measurements. To validate

    our proposal, we have performed experiments in a real testbed, setup in our indoor office environment. We show that the analytical

    predictions of our interference model exhibit good match with both experimental results as well as more complicated analytical models

    proposed in related literature. Furthermore, we demonstrate that a simple probeless routing protocol based on our model performs at

    least as good as well-known probe-based routing protocols in a large set of experiments including both intraflow and interflowinterference.

    Index TermsWireless networks, interference model, interference-aware routing, routing metric.


    THE standardization of Wireless Local Area Networks(WLANs) [1] opened the way to wireless networkaccess provision without the need for wired infrastructure.The IEEE 802.11 ad hoc mode, in particular, enabled the

    intercommunication of mobile, battery-powered devicesand opened the way to a revolutionary method ofcommunication that departs from the well-establishedinfrastructure-based network access paradigm. In this newparadigm, messages are routed (relayed) over multiplewireless (mesh) hops to reach their destination.

    Yet, within this paradigm, interference becomes a majorimpact factor on the network efficiency and performance.Due to the broadcast nature of the medium and the complex-ity of wireless propagation phenomena, it is inherentlydifficult to spatially partition the wireless medium intoclearly disjoint links as in the case of wired networks. Thiscombined with the random access mechanism (implemented

    by a carrier sense function) of the 802.11 MAC protocol givesrise to nodes that do transmit while they shouldnt (hiddennodes), but also nodes that do not transmit while they could(exposed nodes). Both phenomena result in significantreductionoftheinformationdeliverycapacityofthenetwork.

    Adding interference-awareness to routing decisions cantherefore enhance significantly the network performance.

    Jain et al. in [2] show that under ideal interference-awarerouting, the data delivery capability of the network can besignificantly improved with respect to shortest-path rout-ing, even under nonoptimal MAC scheduling. There have

    been efforts to capture the effect of interference in thedesign of routing metrics (see, e.g., [3], [4], [5]) that canserve as alternatives to minimum hop count; nevertheless,their common feature is that they are based on activelymeasuring (probing) the link. Such measurement-basedapproaches have three major disadvantages. First, the activemeasurements impose additional data overhead on thenetwork. Second, part of the node radio resources is spenton probe transmissions, which may be a concern for energy-constrained nodes. Third, the achievable accuracy andreliability of the measurements can sometimes be low,either because the estimation of small or moderate errorrates would need a large number of sample measurements

    or due to the various interactions between the activemeasurement packets and other packets in the network.These considerations motivate a different approach,

    which is to pose and try to answer the following questions:how well can we estimate interference and predict thesuccess probability of transmitting a message over a linkwithout resorting to measurements and probing, but ratherby exploiting only information that is locally available to thenode? Can an interference-aware routing metric based on asimple analytical model achieve similar performance toprobing-based schemes?

    To this end, we first develop an analytical model toestimate the probability that a transmission destined to a

    node is successful in the presence of interference. Startingfrom the simple physical (Signal-to-Interference and Noise-Ratio (SINR)) model [6], we introduce the concepts ofinterference zones that aim at quantifying the effect of


    . The authors are with the Computer Engineering and Networks Laboratory,Swiss Federal Institute of Technology in Zurich (ETHZ), Gloriastrasse 35,8092 Zurich, Switzerland.E-mail: {parissid, karaliopoulos, spyropoulos, plattner}

    Manuscript received 27 Aug. 2008; revised 13 Aug. 2009; accepted 1 July2010; published online 19 Oct. 2010.For information on obtaining reprints of this article, please send e-mail, and reference IEEECS Log Number TMC-2008-08-0344.Digital Object Identifier no. 10.1109/TMC.2010.205.

    1536-1233/11/$26.00 2011 IEEE Published by the IEEE CS, CASS, ComSoc, IES, & SPS

  • 8/3/2019 Interference-Aware Routing Ram a Krishna


    cumulative interference by concurrently transmittingnodes, such as hidden nodes and nodes outside the sensingrange. Furthermore, to also capture the carrier sensefunction common to many real MAC protocols, we includein our model a very simple and generic MAC model, whichensures that nodes within range of the transmitting sourcedefer from transmitting. Accounting for both these effects,we derive an analytical expression for the probability ofsuccessful reception in the presence of interference, as afunction of the node degree, node transmission probability,radio propagation environment, and network card recep-tion sensitivity. Compared to probe-based approaches, theadvantage of this derivation is that all model inputs can beavailable (or estimated) locally to the node; for example,information regarding a nodes degree can be extractedfrom the routing layer at no additional cost in terms ofcommunication overhead. Finally, compared to other, morecomplex analytical models of wireless interference [7], [8],our model does not require prior measurements and canscale up to large number of nodes.

    It is important to note here that our analytical modeldoes not aim to capture the exact working details of arealistic 802.11 protocol (e.g., Distributed CoordinationFunction of 802.11 [1]), and unavoidably makes someassumptions with respect to real propagation phenomena,in order to ensure it remains simple enough to be utilized as ahandy interference-aware routing metric. This is the real goal ofthis work. Nevertheless, to evaluate the effect of ourassumptions in a real world setting, we validate our modelagainst experiments in a real testbed, setup for this purposein our indoor office environment. Despite the generic natureof the model, the experimental results from our IEEE 802.11

    testbed show good match with the analytical predictionsand advocate the models utility. What is more, we find thatour model predictions also follow closely those of moreelaborate well-known analytical models [8].

    Having confirmed the utility of our model, we nextdefine an interference-aware routing metric that explicitlytakes interference into account via our derivation. Thismetric is generic and could be used by various routingprotocols to estimate link and path weights. Similar tothe Expected Transmission count (ETX) metric [9], ourmetric estimates the number of transmissions (includingretransmissions) required to send a packet over a link.

    However, the important difference between the two is that,unlike ETX which measures link quality directly (actively)using small probe packets, our metric tries to predict thelink quality based on information locally available at anode (passively).

    Naturally, we are interested in whether and how muchthis lack of direct link measurements deteriorates therouting performance. To evaluate this, we use our testbedto perform two sets of experiments featuring intraflow andinterflow interference and variable settings for transmissionrate and transmit power. In all experiments, our metric iscompared against the minimum hop count and the ETX

    metrics, the latter being the first of a whole family of probe- based metrics. In the first set, with one node-pair (dataflow) active at a time, our metric finds more high-throughput paths than ETX and minimum hop count do.

    Varying the transmission rate and the transmit power doesnot change the relative performance of the metrics althoughthe absolute throughput values change, as expected. In thesecond set of experiments, we evaluate the three metricswith multiple active node-pairs (flows) simultaneously. Weobserve that our interference-aware routing metric per-forms at least as good as ETX and better than minimum hopcount despite the lack of probing.

    Summarizing, the contribution