MANETs: performance analysis and management

  • Authors:
  • Stephanie Demers;Latha Kant

  • Affiliations:
  • Telcordia Technologies Inc., Piscataway, NJ;Telcordia Technologies Inc., Piscataway, NJ

  • Venue:
  • MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
  • Year:
  • 2006

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Abstract

Known for their flexibility and dynamism, Mobile Ad hoc NETworks (MANETs) are being deployed in a variety of environments - ranging from on-demand networks in response to sudden events (e.g., a crisis,) to preplanned strategic networks (e.g., military networks). However, the very same features (flexibility, dynamism) that render MANETs powerful also render the design and analyses of MANETs a challenge. As an example, the fact that MANETs have the flexibility to respond to network fluctuations and reorganize themselves accordingly via MANET routing, renders both the design of appropriate MANET routing protocols as well as maintenance (via network management) of MANETs, a challenge. To further challenge the matter, since resources (in terms of bandwidth) in MANETs are scarce, the MANET routing protocol not only needs to be adaptive to the uncertainties (random mobility, link changes) in the network but should also not contribute much to the bandwidth overheads. In this work, we model and analyze the performance of Optimized Link State Routing (OLSR), a proactive routing protocol, in wireless mobile ad-hoc networks. More specifically, we identify key OLSR parameters that have significant impact on the amount of overhead produced and the network route convergence time. Observe that while reduction in protocol-related overheads is crucial in bandwidth sensitive wireless MANETs, it is also critical that route convergence times are minimized in order to ensure rapidity of information dissemination. However, bandwidth reduction and convergence times place opposing constraints on the key OLSR parameters. In this paper, we use detailed modeling, simulations and analyses (MSA), to analyze the effect of varying the key OLSR parameters and the trades they produce in terms of overheads and convergence times. In particular, our contribution is two-fold. Via MSA, we provide detailed insights on how the topology control and hello interval timers can be used to reduce overheads without adversely affecting MANET route convergence times. Next, we describe an approach that combines the rapidly emerging policy-based network management paradigm with MSA to result in an adaptive network management system (ANMS). Such an ANMS has the capability of providing powerful information to MANET designers in terms of provisioning the network as well as understanding how quickly the network can be deployed in order to support mission critical services.