Multifactorial evolutionary optimization for maximizing data aggregation tree lifetime in wireless sensor networks

Nguyen Thi Tam; Tran Quang Tuan; Huynh Thi Thanh Binh; Ananthram Swami

doi:10.1117/12.2557978

23 April 2020 Multifactorial evolutionary optimization for maximizing data aggregation tree lifetime in wireless sensor networks

Nguyen Thi Tam, Tran Quang Tuan, Huynh Thi Thanh Binh, Ananthram Swami

Author Affiliations +

Proceedings Volume 11413, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II; 114130Z (2020) https://doi.org/10.1117/12.2557978
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

In wireless sensor networks, sensors handle the aggregation of data from neighboring nodes to the base station, in addition to their primary sensing task. Networks can minimize energy usage by batching together multiple outbound packets at certain nodes over a data aggregation tree. Constructing optimal data aggregation trees is an NP-hard problem, thus requiring approximation methods for larger instances. In this paper, we propose a new Multifactorial Evolutionary Algorithm to solve multiple Data Aggregation Tree Problem with Minimum Energy Cost instances simultaneously. Our method utilizes a novel operator scheme for Edge-Set Tree Representation enabling the unification of search spaces between instances, which helps us to obtain better results than contemporary approaches.

Conference Presentation

Citation Download Citation

Nguyen Thi Tam, Tran Quang Tuan, Huynh Thi Thanh Binh, and Ananthram Swami "Multifactorial evolutionary optimization for maximizing data aggregation tree lifetime in wireless sensor networks", Proc. SPIE 11413, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications II, 114130Z (23 April 2020); https://doi.org/10.1117/12.2557978

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