Abstract
With the increasing number of ubiquitous terminals and the continuous expansion of network scale, the problem of unbalanced energy consumption in sensor networks has become increasingly prominent in recent years. However, a node scheduling strategy or an energy consumption optimization algorithm may be not enough to meet the requirements of large-scale application. To address this problem a type of Annulus-based Energy Balanced Data Collection (AEBDC) method is proposed in this paper. The circular network is divided into several annular sectors of different sizes. Nodes in the same annulus-sector form a cluster. Based on this model, a multi-hop data forwarding strategy with the help of the candidate cluster headers is proposed to balance energy consumption during transmission and to avoid buffer overflow. Meanwhile, in each annulus, there is a Wireless Charging Vehicle (WCV) that is responsible for periodically recharging the cluster headers as well as the candidate cluster headers. By minimizing the recharging cost, the energy efficiency is enhanced. Simulation results show that AEBDC can not only alleviate the “energy hole problem” in sensor networks, but also effectively prolong the network lifetime.
Highlights
In the era of big data and artificial intelligence, wireless sensor networks (WSNs) with sensing, computing and communication ability have gradually become more and more important
To verify the performance of Annulus-based Energy Balanced Data Collection (AEBDC) in terms of energy consumption balance, network lifetime and recharging efficiency, relevant experiments were carried out with the help of Java (JDK1.8) and Matlab R2014a. These simulation results were compared with EBCAG [16] and Energy Balancing Cluster Head (EBCH) [17], which are two cluster-based data collection strategies in WSNs
The value of Ti r is unchanged during the network lifetime, so the value of vWCV needs to be discussed
Summary
In the era of big data and artificial intelligence, wireless sensor networks (WSNs) with sensing, computing and communication ability have gradually become more and more important. Nodes send their data to a sink which is located at the center of the network via single-hop or multi-hop transmission. The energy of nodes are limited and nodes nearer to the sink have more data forwarding tasks than other nodes, the energy of some nodes is exhausted quickly and the energy holes inevitably appear [1,2]. After an energy-hole appears no more data can be delivered to the sink [3,4]. Nodes near the energy-hole are required to bear the data load of those dead nodes so that their energy consumption level will increase more rapidly [5]. The network becomes disconnected and the network lifetime ends prematurely vast amounts of residual energy may remain unused
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