Robust self-stabilizing weight-based clustering algorithm

Johnen, Colette; Nguyen, Le Huy

doi:10.1016/j.tcs.2008.10.009

Cited by 44 publications

(37 citation statements)

References 6 publications

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“…Clustering is found very attractive in infrastructure-less networks, like ad-hoc networks, since it limits the responsibility of network management only to leaders, and it allows the use of hierarchical routing. This is why numerous self-stabilizing 1-hop clustering protocols were proposed in the literature [9,10,8,11,13,14,15,16,19,20].…”

Section: Introductionmentioning

confidence: 99%

Memory Efficient Self-Stabilizing k-Independent Dominating Set Construction

Johnen

2013

Lecture Notes in Computer Science

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We propose a memory efficient self-stabilizing protocol building k-independent dominating sets. A k-independent dominating set is a k-independent set and a kdominating set. A set of nodes, I, is k-independent if the distance between any pair of nodes in I is at least k + 1. A set of nodes, D, is a k-dominating if every node is within distance k of a node of D. Our algorithm, named SID, is silent; it converges under the unfair distributed scheduler (the weakest scheduling assumption). We established that any k-independent sets contains at most (2n)/(k + 2) nodes, n being the network size. The protocol SID is memory efficient : it requires only 2log((k + 1)n + 1) + 1 bits per node. The correctness and the termination of the protocol SID is proven. The computation of the convergence time of the protocol SID is opened question.

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Section: Introductionmentioning

confidence: 99%

Memory Efficient Self-Stabilizing k-Independent Dominating Set Construction

Johnen

2013

Lecture Notes in Computer Science

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“…Johnen and Nguyen present a self-stabilizing (1,1)-clustering algorithm that converges fast in [5]. Dolev and Tzachar tackle a lot of organizational problems in a self-stabilizing manner in [6].…”

Section: Introductionmentioning

confidence: 99%

Self-stabilizing (k,r)-Clustering in Clock Rate-Limited Systems

Larsson

Tsigas

2012

Structural Information and Communication Complexity

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Abstract-Wireless Ad-hoc networks are distributed systems that often reside in error-prone environments. Self-stabilization lets the system recover autonomously from an arbitrary system state, making the system recover from errors and temporarily broken assumptions. Clustering nodes within ad-hoc networks can help forming backbones, facilitating routing, improving scaling, aggregating information, saving power and much more. We present a selfstabilizing distributed (k,r)-clustering algorithm. A (k,r)-clustering assigns k cluster heads within r communication hops for all nodes in the network while trying to minimize the total number of cluster heads. The algorithm assumes a bound on clock frequency differences and a limited guarantee on message delivery. It uses multiple paths to different cluster heads for improved security, availability and fault tolerance. The algorithm assigns, when possible, at least k cluster heads to each node within O(rπλ 3 ) time from an arbitrary system configuration, where π is a limit on message loss and λ is a limit on pulse rate differences. The set of cluster heads stabilizes, with high probability, to a local minimum within O(rπλ 4 g log n) time, where n is the size of the network and g is an upper bound on the number of nodes within 2r hops.

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“…To overcome these drawbacks, the paradigm selfstabilization with service guarantee has been recently introduced in [17,20,18]. A protocol P is self-stabilizing with service guarantee if: (1) P is self-stabilizing; (2) from an arbitrary configuration, P quickly reaches a safe configuration, where a safety property is satisfied, so a minimal service is provided; (3) the safety property (minimal service) holds during progress of P towards the optimum service (i.e., during stabilization despite actions of P) and, (4) the safety property (minimal service) is also maintained despite the occurrences of some specific external disruptions, called highly tolerated disruptions, denoted HT D.…”

Section: Introductionmentioning

confidence: 99%

“…Clustering is found very attractive in infrastructure-less networks, like ad-hoc networks, since it limits the responsibility of network management only to leaders, and it allows the use of hierarchical routing. This is why numerous clustering protocols were proposed in the literature [1,2,6,11,15,17,19,20,21,23].…”

Section: Introductionmentioning

confidence: 99%

From Self- to Self-stabilizing with Service Guarantee 1-hop Weight-Based Clustering

Johnen

Mekhaldi

2012

Lecture Notes in Computer Science

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Abstract. We propose a transformer building a silent self-stabilizing with service guarantee 1-hop clustering protocol T P of an input silent self-stabilizing 1-hop clustering protocol P. From an arbitrary configuration, T P reaches a safe configuration in at most 3 rounds, where the following useful minimal service is provided: "each node belongs to a 1-hop cluster having an effective leader". During stabilization of T P, the minimal service is preserved, so the clustering structure is available throughout the entire network. The minimal service is also maintained despite the occurrences of some external disruptions, called highly tolerated disruptions, denoted HT D. T P reaches a terminal (also legitimate) configuration in at most 4 * SP rounds where SP is the stabilization time of P protocol. Moreover, T P requires only 2 bits per node more than P.

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Robust self-stabilizing weight-based clustering algorithm

Cited by 44 publications

References 6 publications

Memory Efficient Self-Stabilizing k-Independent Dominating Set Construction

Memory Efficient Self-Stabilizing k-Independent Dominating Set Construction

Self-stabilizing (k,r)-Clustering in Clock Rate-Limited Systems

From Self- to Self-stabilizing with Service Guarantee 1-hop Weight-Based Clustering

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