Abstract

Optimized Link State Routing (OLSR) is a widespread routing protocol in wireless mesh networks: static, mobile, ad-hoc, and even sensor networks. The selection of Multi-Point Relays (MPR) that form a signaling backbone is at the heart of the protocol and it is a crucial process to reduce the signaling overhead. Since the protocol proposal and specification, the original heuristic for MPRs selection has been largely studied showing it has good local properties; however, this does not give insight about the properties of the global set of MPRs. Here lays the contribution of this paper: First we define the problem of the minimization of the global MPR set (the union of all the MPR sets) as a centralized integer linear programming problem, which is NP-hard. We are able to solve it for networks of practical size, up to 150 nodes. Second, we define a bound that we call the “distributed optimum,” which we show to be a lower bound for distributed MPR selection algorithms, still requiring considerable power to be computed. Finally, we set-up an experimental performance evaluation methodology and we show that a heuristic that we recently proposed performs very close to the distributed optimum, and always outperforms the original heuristic.

Highlights

  • Wireless mesh and ad-hoc networks are the subject of a very large body of literature that studied their characteristics and performances

  • The ILP Solver In each run, Omnet++ produces three outputs: i) the network topology G generated in a realistic scenario, ii) the number of Multi-Point Relays (MPRs) generated by the standard Optimized Link State Routing (OLSR) strategy during the simulation, and iii) the number of MPRs generated by the Selector Set Tie Breaker (SSTB) strategy

  • A first evidence shown in all the graphs is that the OLSR heuristic, even if it is theoretically close to the local minimum, produces global set Mg far from optimal

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Summary

Introduction

Wireless mesh and ad-hoc networks are the subject of a very large body of literature that studied their characteristics and performances. We formalize the global MPR set minimization problem as an ILP (Integer Linear Programming) problem that can be solved efficiently for networks of small to medium size on off-the-shelf hardware This is a key contribution that makes it possible to compare any technique with the true global minimum. To achieve this goal we split the problem in two steps: i) Enumerate all the local solutions; and ii) Choose one solution per node in order to minimize their union. We include in the comparison the results obtained with the standard OLSR heuristic, which is still relevant as it is included in both the first and the second version of the OLSR RFC

Related and Background Work
OLSR Primer
A different problem
A lower bound on distributed heuristic algorithms
Numerical Results and Discussion
Results
20 M-OLSR
Results with mobility
Conclusions
Full Text
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