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Internet Technol."],"published-print":{"date-parts":[[2022,11,30]]},"abstract":"<jats:p>Multi-access edge computing (MEC) is emerging to improve the quality of experience of mobile devices including internet of things sensors by offloading computing intensive tasks to MEC servers. Existing MEC-enabled cooperative computation offloading works focus on the optimization of total energy consumption but fail to exploit multi-relay diversity and min-max fairness of energy consumption on participated sensors. We explore a typical wireless sensor network with multi-source, multi-relay, and one edge server, where relay nodes can provide both cooperative communication and computation services. We divide the energy efficiency optimization problem into two sub-problems: One is to minimize the weighted average total energy consumption per time slot, and the other is to minimize the maximum weighted energy consumption. For the first sub-problem, we propose an optimal algorithm named as optimal weighted average total energy consumption algorithm (OTCA) based on bipartite matching. For the second sub-problem, greedy algorithm for fairness guarantee (GAF) is proposed with an approximation ratio of (1 + \u03b5), where \u03b5 is a small positive constant. Extensive numerical results show that OTCA outperforms the baseline algorithms by 26.7\u201377.4% on the average total weighted energy consumption while GAF outperforms benchmark algorithms by 30.7\u201384.4%. NS-3 simulation experiments comply with numerical results.<\/jats:p>","DOI":"10.1145\/3544969","type":"journal-article","created":{"date-parts":[[2022,6,23]],"date-time":"2022-06-23T08:58:26Z","timestamp":1655974706000},"page":"1-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["EECDN: Energy-efficient Cooperative DNN Edge Inference in Wireless Sensor Networks"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5807-7268","authenticated-orcid":false,"given":"Long","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangdong Province, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5626-4599","authenticated-orcid":false,"given":"Mianyang","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangdong Province, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0919-0766","authenticated-orcid":false,"given":"Yalan","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangdong Province, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6470-9794","authenticated-orcid":false,"given":"Jigang","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Guangdong University of Technology, Guangdong Province, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,11,14]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/IICETA.2018.8458077"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155484"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/LWC.2019.2950624"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.5555\/993483"},{"issue":"3","key":"e_1_3_3_6_2","first-page":"4188","article-title":"Joint computation and communication cooperation for energy-efficient mobile edge computing","volume":"6","author":"Cao Xiaowen","year":"2018","unstructured":"Xiaowen Cao, Feng Wang, Jie Xu, Rui Zhang, and Shuguang Cui. 2018. 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