Adaptive ant-based routing in wireless sensor networks using Energy*Delay metrics |
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| Authors: | Yao-feng Wen Yu-quan Chen Min Pan |
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| Institution: | State Specialized Laboratory of Biomedical Sensors, Zhejiang University, Hangzhou 310027, China |
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| Abstract: | To find the optimal routing is always an important topic in wireless sensor networks (WSNs). Considering a WSN where the nodes
have limited energy, we propose a novel Energy*Delay model based on ant algorithms (“E&D ANTS” for short) to minimize the
time delay in transferring a fixed number of data packets in an energy-constrained manner in one round. Our goal is not only
to maximize the lifetime of the network but also to provide real-time data transmission services. However, because of the
tradeoff of energy and delay in wireless network systems, the reinforcement learning (RL) algorithm is introduced to train
the model. In this survey, the paradigm of E&D ANTS is explicated and compared to other ant-based routing algorithms like
AntNet and AntChain about the issues of routing information, routing overhead and adaptation. Simulation results show that
our method performs about seven times better than AntNet and also outperforms AntChain by more than 150% in terms of energy
cost and delay per round.
Project (No. 30470461) supported in part by the National Natural Science Foundation of China |
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| Keywords: | Ant colony optimization (ACO) Pheromones Power consumption Wireless sensor networks (WSNs) |
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