An Analytical Framework for The Characterization of Link Dynamics in MANETs - eScholarship

An Analytical Framework for The Charaterization of Link Dynamics in MANETs Invited Paper Xianren Wu, Hamid R. Sadjadpour J.J. Garcia-Luna-Aceves School of Engineering University of California at Santa Cruz (UCSC) Santa Cruz, CA 95064, USA Email: {wuxr,hamid}@soe.ucsc. edu School of Engineering at UCSC and Palo Alto Research Center 3333 Coyote Hill Road, Palo Alto, CA 94304, USA Email: jj@soe.ucsc. edu Abstract— We present an analytical framework and sta- tistical models to accurately characterize the lifetime of a wireless link in a mobile ad hoc network (MANET). We show that the lifetime of a link can be computed through a two-state Markov model and that the analytical solution follows closely the results obtained through discrete event simulations. The proposed framework has widespread ap- plication in the modeling of medium access control proto- cols, routing protocols, clustering, and the optimization of MANETs. I. I NTRODUCTION Mobile wireless ad hoc network (MANET) has cre- ated intensive interests for its unique features of flexible deployment, autonomous network, and potential applica- tions such as tactical deployment in the battlefield. Mo- bility brings opportunities to MANETs as well as creates challenges. Constant movements of nodes in MANETs result in a highly dynamic network topology. Meanwhile, communication links undergo frequent link breakages and protocol stacks of MANET need to adapt to this dynamic environment. In particular, clustering and routing algo- rithms are key to the success of MANET but an efficient design of them necessitate a thorough understanding of link behavior in MANETs. Interestingly, as critical as the problem of characteriz- ing link behavior is for the performance of the protocol stack of a MANET, no such analytical model exists to ac- curately characterize link lifetime as a function of node mobility, which is a defining attribute of MANETs! As a result, link behavior in MANETs has been analyzed mostly through simulations, and analytical modeling of channel access and routing protocols for MANETs have This work was supported in part by the US Army Research Office under grants W911NF-05-1-0246 and by the Basking Chair of Com- puter Engineering. not represented the temporal nature of MANET links ac- curately. For example, the few analytical models that have been developed for channel access protocols oper- ating in multihop ad hoc networks have either assumed static topologies (e.g., [1]) or focused on the immediate neighborhood of a node, such that nodes remain neighbors for the duration of their exchanges (e.g., [2]). Similarly, most studies of routing-protocol performance have relied exclusively on simulations, or had to use limited models of link availability (e.g., [3]) to address the dynamics of paths impacting routing protocols (e.g., [4]). This paper provides the most accurate analytical model of link behavior in MANETs to date, and characterizes link behaviors as a function of node mobility. The impor- tance of this model is twofold. First, it enables investiga- tion of many questions regarding fundamental tradeoffs in throughput, delay and storage requirements in MANETs, as well as the relationship between many protocol-design choices (e.g., packet length) and network dynamics (e.g., how long links last in a MANET). Second, it enables the development of analytical models for channel access, clustering and routing schemes operating in MANETs by allowing such models to use link lifetime expressions that are accurate with respect to simulations based on widely- used mobility models. Recently, Samar and Wicker [5], [6] presented an an- alytical evaluation of link dynamics. They also provided an example of how an analytical formulation of link dy- namics can be incorporated into the protocol design task. However, Samar and Wicker assume that communicating nodes maintain constant speed and direction in order to evaluate the distribution of link lifetime. This simplifica- tion overlooks the case in which either of the communicat- ing nodes change speed or direction while the nodes are in transmission range of each other. As a result, the results predicted by Samar and Wicker’s model can deviate from