{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:53:11Z","timestamp":1740149591833,"version":"3.37.3"},"reference-count":43,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,18]],"date-time":"2023-03-18T00:00:00Z","timestamp":1679097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62061009"],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology)","award":["CRKL190110"]},{"name":"Basic Scientific Research Ability Improvement Project for Young and Middle-aged Teachers of Universities in Guangxi Province","award":["2020KY05029"]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Emergency event monitoring is a hot topic in wireless sensor networks (WSNs). Benefiting from the progress of Micro-Electro-Mechanical System (MEMS) technology, it is possible to process emergency events locally by using the computing capacities of redundant nodes in large-scale WSNs. However, it is challenging to design a resource scheduling and computation offloading strategy for a large number of nodes in an event-driven dynamic environment. In this paper, focusing on cooperative computing with a large number of nodes, we propose a set of solutions, including dynamic clustering, inter-cluster task assignment and intra-cluster one-to-multiple cooperative computing. Firstly, an equal-size K-means clustering algorithm is proposed, which activates the nodes around event location and then divides active nodes into several clusters. Then, through inter-cluster task assignment, every computation task of events is alternately assigned to the cluster heads. Next, in order to make each cluster efficiently complete the computation tasks within the deadline, a Deep Deterministic Policy Gradient (DDPG)-based intra-cluster one-to-multiple cooperative computing algorithm is proposed to obtain a computation offloading strategy. Simulation studies show that the performance of the proposed algorithm is close to that of the exhaustive algorithm and better than other classical algorithms and the Deep Q Network (DQN) algorithm.<\/jats:p>","DOI":"10.3390\/s23063237","type":"journal-article","created":{"date-parts":[[2023,3,20]],"date-time":"2023-03-20T07:30:31Z","timestamp":1679297431000},"page":"3237","source":"Crossref","is-referenced-by-count":2,"title":["Deep Reinforcement Learning-Based One-to-Multiple Cooperative Computing in Large-Scale Event-Driven Wireless Sensor Networks"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7306-0426","authenticated-orcid":false,"given":"Zhihui","family":"Guo","sequence":"first","affiliation":[{"name":"Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education, Guilin University of Electronic Technology, Guilin 541004, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4008-3704","authenticated-orcid":false,"given":"Hongbin","family":"Chen","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education, Guilin University of Electronic Technology, Guilin 541004, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6858-5031","authenticated-orcid":false,"given":"Shichao","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education, Guilin University of Electronic Technology, Guilin 541004, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1109\/JMEMS.2020.2978467","article-title":"Microfabricated Neuroaccelerometer: Integrating Sensing and Reservoir Computing in MEMS","volume":"29","author":"Barazani","year":"2020","journal-title":"J. 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