A Dynamical Slot Assignment Method for Wireless Sensor Networks Based on Hopfield Network | Zendy

Qi Yang | Zendy; Xiao Lin | Zendy; Yuxiang Zhuang | Zendy; Xuemin Hong | Zendy

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A Dynamical Slot Assignment Method for Wireless Sensor Networks Based on Hopfield Network

Author(s) -

Qi Yang,

Xiao Lin,

Yuxiang Zhuang,

Xuemin Hong

Publication year - 2014

Publication title -

international journal of distributed sensor networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.324

H-Index - 53

eISSN - 1550-1477

pISSN - 1550-1329

DOI - 10.1155/2014/805142

Subject(s) - computer science , convergence (economics) , wireless sensor network , key (lock) , wireless , computer network , wireless network , scheme (mathematics) , artificial neural network , mathematical optimization , algorithm , telecommunications , artificial intelligence , mathematics , mathematical analysis , computer security , economics , economic growth

This paper proposes an improved Hopfield neural network (I-HNN) algorithm to optimize the slot assignment scheme in wireless sensor networks. The key advantage of the proposed algorithm is to increase the convergence probability under different traffic loads. To achieve this, nodes can adjust their slot demands according to the traffic load, slots number, and demand history. Various aspects of the network performances with the proposed I-HNN algorithm are evaluated via simulation. The results indicate that I-HNN is suitable for wireless sensor networks with dynamically varying traffic. In particular, it can increase the convergence probability and slot utilization under the heavy traffic load.

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