Abstract
In energy-constrained wireless sensor networks (WSNs), the design of an energy-efficient smart strategy is a key to extend the network lifetime, but the unbalance of energy consumption and node load severely restrict the long-term operation of the network. To address these issues, a novel routing algorithm which considers both energy saving and load balancing is proposed in this paper. First of all, the transmission energy consumption, node residual energy and path hops are considered to create the link cost, and then a minimum routing graph is generated based on the link cost. Finally, in order to ensure the balance of traffic and residual energy of each node in the network, an “edge-cutting” strategy is proposed to optimize the minimum routing graph and turn it into a minimum routing tree. The simulation results show that, the proposed algorithm not only can balance the network load and prolong the lifetime of network, but meet the needs of delay and packet loss rate.
Highlights
We proposed an “edge-cutting” strategy to balance the load in the minimum routing graph, so that the network structure can be adjusted in real time to optimize the route by dynamically sensing the node load
Five performance parameters will be used in the following paper: average energy consumption (AEC), average hop count (AH), packet loss rate (PLR), energy variance (EV), and node survival rate (NSR)
In order toof reduce the the transmission energy sensor consumption, and balance the node load to achieve the purpose of extending the lifetime of wireless sensor networks, this paper proposes routing optimization algorithm for wireless sensor networks (ESRA)
Summary
With the acceleration of the Internet of Things era, wireless sensor networks (WSNs) have been widely deployed in various application scenarios, such as volcanic eruption monitoring [1,2], medical care monitoring [3], and smart home monitoring [4]. Due to the limited energy storage [12,13] of battery-powered sensor networks, these applications have a common requirement for the network lifetime, reducing the energy consumption to extend the network lifetime is one of the key tasks of the WSN. In order to maximize the network lifetime, both energy consumption reducing and load balancing are needed to be considered when making routing decisions
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