Self-stabilizing Consensus Average Algorithm in Distributed Sensor Networks

Bahi, Jacques M.; Haddad, Mohammed; Hakem, Mourad; Kheddouci, Hamamache

doi:10.1007/978-3-642-40069-8_2

Cited by 2 publications

(3 citation statements)

References 28 publications

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“…More precisely, the information exchange between nodes involves only the connected dominating set (CDS) of the network graph to reduce the sensors' overall power consumption. [4] developed a novel approach using self stabilization under a serial daemon scheduler. It was shown that the proposed algorithm converges in a linear time complexity with a tighter bound of the global equilibrium threshold.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficient distributed average consensus in wireless sensor networks

Guyeux

Haddad

Hakem

et al. 2020

Computer Communications

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Computing the distributed average consensus in Wireless Sensor Networks (WSNs) is investigated in this article. This problem, which is both natural and important, plays a significant role in various application fields such as mobile agents and fleet vehicle coordination, network synchronization, distributed voting and decision, load balancing of divisible loads in distributed computing network systems, and so on. By and large, the average consensus' objective is to have all nodes in the network converged to the average value of the initial nodes' measurements based only on local nodes' information states. In this paper, we introduce a fully distributed algorithm to average the sensed data within the network itself. The network may be large since we never broadcast over all its nodes. Unlike earlier works, when a node detects a load (scalar value) imbalance in its closed neighborhoods during the average process, instead of sending parsimonious amount of load values from highly loaded nodes to less loaded ones, we move a large amount of load values by involving parallel atomic transactions between mutually exclusive pairs of neighbors. This improves the global convergence time speedup with low-cost communication and minimal energy consumption. First, we give the convergence proof of the distributed consensus process, and next we provide some experimental results based on NS3 framework to assess the behaviour of the proposed algorithm.

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Section: Literature Reviewmentioning

confidence: 99%

Efficient distributed average consensus in wireless sensor networks

Guyeux

Haddad

Hakem

et al. 2020

Computer Communications

Self Cite

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“…This approach often proves to be the most effective solution when there is a lack of global information about the topology of a network. This applies to a range of possible networks, ad‐hoc, wireless sensor, and so on, so the approach has attracted a significant amount of attention …”

Section: Introductionmentioning

confidence: 99%

“…This applies to a range of possible networks, ad-hoc, wireless sensor, and so on, so the approach has attracted a significant amount of attention. [2][3][4][5][6][7][8] The advantage of self-stabilization algorithms lies in their elegance and simplicity. However, this comes at a cost.…”

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confidence: 99%

Performance analysis of Israeli‐Jalfon's algorithm using probabilistic model checking

2018

Concurrency and Computation

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Summary Israeli‐Jalfon's self‐stabilization algorithm provides a solution to the problem of fault tolerance in distributed systems. To quantitatively evaluate the algorithm and discover the factors contributing to its performance, we used a probabilistic model checking technique to study the algorithm across different configurations. The mainstream probabilistic model checker PRISM assisted with our final assessment. We focus here on three aspects of the algorithm's performance: convergence, time complexity, and maximum execution time. Our experimental results show that time complexity is O (N^2) when N is less than 23, and we examine the factors contributing to this performance. These prove to be: the number of tokens, the number of processes, the probability of token transmission, and how tokens are spaced. Performance degrades as the number of tokens grows. For a certain number of processes, better performance can be obtained when the probability of token transmission is 0.5. Three tokens spaced evenly, meanwhile, yields the worst performance. The main contribution of this paper is its exhaustive quantitative performance analysis of Israeli‐Jalfon's algorithm and the presentation of accurate rather than approximate numerical results. Moreover, our assessment was undertaken in a reducible fashion, with stable states being set against a proper subset of the set of possible configurations rather than allowing two sets to coincide.

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Self-stabilizing Consensus Average Algorithm in Distributed Sensor Networks

Cited by 2 publications

References 28 publications

Efficient distributed average consensus in wireless sensor networks

Efficient distributed average consensus in wireless sensor networks

Performance analysis of Israeli‐Jalfon's algorithm using probabilistic model checking

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