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One of the challenging issues in a distributed computing system is to reach on a decision with the presence of so many faulty nodes. These faulty nodes may update the wrong information, provide misleading results and may be nodes with the depleted battery power. Consensus algorithms help to reach on a decision even with the faulty nodes. Every correct node decides some values by a consensus algorithm. If all correct nodes propose the same value, then all the nodes decide on that. Every correct node must agree on the same value. Faulty nodes do not reach on the decision that correct nodes agreed on. Binary consensus algorithm and average consensus algorithm are the most widely used consensus algorithm in a distributed system. We apply binary consensus and average consensus algorithm in a distributed sensor network with the presence of some faulty nodes. We evaluate these algorithms for better convergence rate and error rate.
IF Akyildiz, W Su, Y Sankarasubramaniam, E Cayirci, Wireless sensor network: a survey. Comput. Netw. 38:, 393–422 (2002). CrossRef
F Benezit, AG Dimakis, P Thiran, M Vetterli, in Allerton Conference on Communication, Control, and Computing. Gossip along the way: order-optimal consensus through randomized path averaging (EPFLAllerton, USA, 2007), pp. 26–28.
M Draief, M Vojnovic, in Annual joint conference of the IEEE computer and communications societies (INFOCOM 2010). Convergence speed of binary interval consensus (SIAMSan Diego, California, 2010), pp. 15–19.
Y Li, Z Zhou, T Sato, A cluster-based consensus algorithm in a wireless sensor network. Int. J. Distributed Sensor Netw. Hindawi. 60(547124), 1–15 (2013).
N Al-Nakhala, R Riley, TM Elfouly, in International Wireless Communications and Mobile Computing Conference (IWCMC). Binary consensus in sensor motes (IEEESardinia, 2013), pp. 1337–1342.
D Culler, D Estrin, M Srivastava, Overview of sensor networks. Computer. 37(8), 41–49 (2004). CrossRef
A Gogolev, L Marcenaro, Randomized binary consensus with faulty agents. Entropy. 16:, 2820–2838 (2014). CrossRef
WJ Li, HY Dai, Cluster-based distributed consensus. IEEE Trans. Wireless Commun. 8(1), 28–31 (2009). CrossRef
W Ren, RW Beard, Distributed Consensus in MultiVehicle Cooperative Control: Theory and Applications (Springer, London, UK, 2010).
KI Tsianos, MG Rabbat, in International Conference on Distributed Computing in Sensor System. Fast decentralized averaging via multi-scale gossip (ACMSanta Barbara, Calif, USA, 2010), pp. 21–23.
M Zheng, M Goldenbaum, S Stanczak, Y Haibin, in IEEE Wireless Communication and Networking Conference. Fast average consensus in clustered wireless sensor networks by superposition gossiping (IEEEParis, France, 2012), p. 14.
M Chatterjee, SK Das, D Turgut, Wca: a weighted clustering algorithm for mobile ad hoc networks. J. Cluster Comput. 5(2), 193–204 (2002). CrossRef
DJ Baker, A Ephremides, The architectural organization of a mobile radio network via a distributed algorithm. IEEE Trans. Commun. 29(11), 1694–1701 (1981). CrossRef
- Efficient consensus algorithm for the accurate faulty node tracking with faster convergence rate in a distributed sensor network
Muhidul Islam Khan
- Springer International Publishing
EURASIP Journal on Wireless Communications and Networking
Elektronische ISSN: 1687-1499
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