A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks-Reference-Cited by-同舟云学术

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A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks

Published:2012-12-04 Issue:1 Volume:15 Page:170-191
ISSN:1530-8669
Container-title:Wireless Communications and Mobile Computing
language:en
Short-container-title:Wirel. Commun. Mob. Comput.

Author:

Lin Xiao-Hui¹²,Kwok Yu-Kwong³,Wang Hui¹,Xie Ning¹

Affiliation:

1. Department of Communication Engineering; Shenzhen University; Shenzen China

2. State Key Laboratory of Networking and Switching Technology; Beijing University of Posts and Telecommunications; Beijing China

3. Department of Electrical and Electronic Engineering; The University of Hong Kong; Hong Kong

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

Reference39 articles.

1. A survey on sensor networks;Akyildiz;IEEE Communications Magazine,2002

2. Wireless sensor networks: a survey;Akyildiz;Computer Networks,2002

3. Towards adaptive sleep schedules for balancing energy consumption in wireless sensor networks;AbdelSalam;IEEE Transactions on Computer,2011

4. Game-theoretic models for reliable path-length and energy-constrained routing with data aggregation in wireless sensor networks;Kannan;IEEE Journal on Selected Areas in Communications,2004

5. Sensor-centric energy-constrained reliable query routing for wireless sensor networks;Kannan;Journal of Parallel and Distributed Computing,2004

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1. Game-Theory-Based Clustering Scheme for Energy Balancing in Underwater Acoustic Sensor Networks;IEEE Internet of Things Journal;2021-06-01

2. Improved W-LEACH Decentralized protocol with game theory;Procedia Computer Science;2020

3. The optimal game model of energy consumption for nodes cooperation in WSN;Journal of Ambient Intelligence and Humanized Computing;2018-11-15

4. A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks;Sensors;2017-11-17

5. Probabilistic routing using multimodal data;Neurocomputing;2017-08

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