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

Qi Yang, Xiao Lin, Yuxiang Zhuang and Xuemin Hong

International Journal of Distributed Sensor Networks, 2014, vol. 10, issue 5, 805142

Abstract: 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.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1155/2014/805142 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:10:y:2014:i:5:p:805142

DOI: 10.1155/2014/805142

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().