Adaptive ant-based routing in wireless sensor networks using Energy*Delay metrics
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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.
Key wordsAnt colony optimization (ACO) Pheromones Power consumption Wireless sensor networks (WSNs)
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- Arici, T., Altunbasak, Y., 2004. Adaptive Sensing for Environment Monitoring Using Wireless Sensor Networks. Proc. Wireless Communications and Networking Conf., 3:2347–2352.Google Scholar
- Baran, B., Sosa, R., 2000. A New Approach for AntNet Routing. Proc. 9th Int. Conf. Computer Communications Networks, 10:303–308. [doi:10.1109/ICCCN.2000.885506]Google Scholar
- Chang, J.H., Tassiulas, L., 2000. Energy-Conserving Routing in Wireless Ad-hoc Networks. Proc. IEEE INFOCOM, 1:22–31. [doi:10.1109/INFCOM.2000.832170]Google Scholar
- De Couto, D.S.J., Aguayo, D., Bicket, J., Morris, R., 2003. A High-Throughput Path Metric for Multi-Hop Wireless Routing. Proc. 9th Annual Int. Conf. on Mobile Computing and Networking, 9:134–146. [doi:10.1145/938985.939000]Google Scholar
- Di Caro, G., Dorigo, M., 1997. AntNet: A Mobile Agents Approach to Adaptive Routing. Tech. Rep. IRIDIA/97-12, IRIDIA. Free Brussels University, Belgium.Google Scholar
- Ding, N., Liu, P.X., Hu, C., 2005. Data Gathering Communication in Wireless Sensor Networks Using Ant Colony Optimization. Proc. Int. Conf. on Intelligent Robots and Systems, 8:729–734. [doi:10.1109/IROS.2005.1545067]Google Scholar
- Dorigo, M., Di Caro, G., 1999. Ant Colony Optimization: A New Meta-Heuristic. Proc. Congress on Evolutionary Computation, 2:1470–1477. [doi:10.1109/CEC.1999.782657]Google Scholar
- Nemeroff, J., Garcia, L., Hampel, D., Di Pierro, S., 2001. Application of Sensor Network Communications. Proc. Military Communications Conf., 1:336–341. [doi:10.1109/MILCOM.2001.985815]Google Scholar
- Wu, C.M., Chen, Z., Jiang, M., 2006. The research on initialization of ants system and configuration of parameters for different TSP problems in ant algorithm. Acta Electronica Sinica, 34(8):1530–1533 (in Chinese).Google Scholar