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Dominating set clustering protocols for mobile ad hoc networks

Dominating set clustering protocols for mobile ad hoc networks

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A Mobile ad hoc Network (MANET) is a self-configuring, dynamic, multi-hop network composed of mobile nodes that operate without the need of any established infrastructure. The creation of stable, scalable and adaptive clusters with good performance, faster convergence rate and minimal overhead is a challenging task in MANET. This chapter proposes two clustering techniques for MANET, which are (k, r)-Dominating Set-based, weighted and adaptive to changes in the network topology. The set of dominating nodes functions as the clusterhead (CH) to relay the data and control packets. The proposed scenario-based clustering algorithm for MANETs (SCAMs) is a greedy approximation algorithm, whereas the Distributed SCAM (DSCAM) selects the (k, r)-dominating set through a distributed election mechanism. These algorithms achieve variable degree of CH redundancy through the parameter k, which contributes to reliability. Similarly, flexibility in creating variable diameter clusters is achieved with the parameter r. The performance of these algorithms are evaluated through simulation and the results show that these algorithms create stable, scalable and load-balanced clusters with relatively less control overhead in comparison with the existing popular algorithms.

Chapter Contents:

  • 11.1 Introduction
  • 11.1.1 Mobile ad hoc networks
  • 11.1.2 Dominating set (DS) graph
  • 11.1.3 Routing in wireless ad hoc networks
  • 11.1.4 Clustering and topology control in MANETs
  • 11.2 Scenario-based clustering for MANET
  • 11.2.1 Design objectives
  • 11.2.2 Design parameters
  • 11.2.3 SCAM algorithm
  • 11.2.3.1 Clustering Setup phase
  • 11.2.3.2 Cluster formation phase
  • 11.2.3.3 Cluster maintenance phase
  • 11.2.4 Performance evaluation
  • 11.3 Distributed scenario-based clustering for MANET
  • 11.3.1 Need for distributed algorithm
  • 11.3.2 Design principles
  • 11.3.2.1 Phases of DSCAM
  • 11.3.3 Performance evaluation
  • 11.4 Conclusion
  • References

Inspec keywords: approximation theory; mobile ad hoc networks; protocols; greedy algorithms; telecommunication network reliability; convergence; pattern clustering; redundancy; telecommunication network topology

Other keywords: scenario-based clustering algorithm; distributed election mechanism; mobile node; reliability; distributed SCAM; data relay; mobile ad hoc network; adaptive clustering technique; flexibility; DSCAM; convergence rate; (k,r)-dominating set-based clustering technique; CH redundancy; network topology; clusterhead; self-configuring network; scenario-based clustering algorithm for MANET; multihop network; greedy approximation algorithm; dynamic network; weighted clustering technique; dominating set clustering protocol

Subjects: Mobile radio systems; Interpolation and function approximation (numerical analysis); Reliability; Protocols; Communication network design, planning and routing

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