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The proposed algorithm allows each node in wireless sensor network to save the distance and residual energy of neighbor nodes. Furthermore, in terms of probability selection of the nodes and the pheromone update, this algorithm focuses on the next hop node through the comparison of distance between the nodes and the residual energy, which ensures less possibility of nodes with low energy selected as the next hop. Therefore, the proposed algorithm improves energy load balancing, stability of wireless sensor network and, eventually, extends the life span of the wireless sensor network. The simulation results show that the improved ant colony algorithm avoids too much energy consumption of a certain local node resulting in more uniform energy consumption for each node. <\/jats:p>","DOI":"10.1177\/1550147717704831","type":"journal-article","created":{"date-parts":[[2017,4,28]],"date-time":"2017-04-28T09:58:38Z","timestamp":1493373518000},"page":"155014771770483","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":14,"title":["Energy optimization of ant colony algorithm in wireless sensor network"],"prefix":"10.1177","volume":"13","author":[{"given":"Peng","family":"Li","sequence":"first","affiliation":[{"name":"School of Computer Science & Technology, Nanjing University of Posts and Telecommunications, Nanjing, China"},{"name":"Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing, 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