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Sen. Netw."],"published-print":{"date-parts":[[2016,11,17]]},"abstract":"<jats:p>\n            Data sharing among multiple sampling tasks significantly reduces energy consumption and communication cost in low-power wireless sensor networks (WSNs). Conventional proposals have already scheduled the discrete point sampling tasks to decrease the amount of sampled data. However, less effort has been expended for applications that generate continuous interval sampling tasks. Moreover, most pioneering work limits its view to schedule sampling intervals of tasks on a single sensor node and neglects the process of task allocation in WSNs. Therefore, the gained efforts in prior work cannot benefit a large-scale WSN because the performance of a scheduling method is sensitive to the strategy of task allocation. Broadening the scope to an entire network, this article is the first work to maximize data sharing among continuous interval sampling tasks by jointly optimizing task allocation and scheduling of sampling intervals in WSNs. First, we formalize the joint optimization problem and prove it NP-hard. Second, we present the\n            <jats:italic>COMBINE<\/jats:italic>\n            operation, which is the crucial ingredient of our solution.\n            <jats:italic>COMBINE<\/jats:italic>\n            is a 2-factor approximate algorithm for maximizing data sharing among overlapping tasks. Furthermore, our heuristic named\n            <jats:italic>CATS<\/jats:italic>\n            is proposed.\n            <jats:italic>CATS<\/jats:italic>\n            is 2-factor approximate algorithm for jointly allocating tasks and scheduling sampling intervals so as to maximize data sharing in the entire network. Extensive empirical study is conducted on a testbed of 50 sensor nodes to evaluate the effectiveness of our methods. In addition, the scalability of our methods is verified by utilizing TOSSIM, a widely used simulation tool. The experimental results indicate that our methods successfully reduce the volume of sampled data and decrease energy consumption significantly.\n          <\/jats:p>","DOI":"10.1145\/2955102","type":"journal-article","created":{"date-parts":[[2016,9,7]],"date-time":"2016-09-07T12:14:47Z","timestamp":1473250487000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["CATS"],"prefix":"10.1145","volume":"12","author":[{"given":"Yawei","family":"Zhao","sequence":"first","affiliation":[{"name":"National University of Defense Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Deke","family":"Guo","sequence":"additional","affiliation":[{"name":"National University of Defense Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Xu","sequence":"additional","affiliation":[{"name":"Guangxi University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pin","family":"Lv","sequence":"additional","affiliation":[{"name":"Guangxi University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tao","family":"Chen","sequence":"additional","affiliation":[{"name":"National University of Defense Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianping","family":"Yin","sequence":"additional","affiliation":[{"name":"National University of Defense Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2016,9,7]]},"reference":[{"volume-title":"Proceedings of the 12th IEEE International Conference on Computer Communications and Networks. 539--544","author":"Arici T.","key":"e_1_2_1_1_1","unstructured":"T. Arici , B. Gedik , Y. Altunbasak , and L. Liu . 2003. PINCO: A pipelined in-network compression scheme for data collection in wireless sensor networks . In Proceedings of the 12th IEEE International Conference on Computer Communications and Networks. 539--544 . T. Arici, B. Gedik, Y. Altunbasak, and L. Liu. 2003. PINCO: A pipelined in-network compression scheme for data collection in wireless sensor networks. In Proceedings of the 12th IEEE International Conference on Computer Communications and Networks. 539--544."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/190314.190334"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2005.848361"},{"volume-title":"Energy Efficient Scheduling and Allocation of Tasks in Sensor Cloud. Master\u2019s Thesis","author":"Dalvi Rashmi","key":"e_1_2_1_4_1","unstructured":"Rashmi Dalvi . 2014. Energy Efficient Scheduling and Allocation of Tasks in Sensor Cloud. Master\u2019s Thesis . Missouri University of Science and Technology , Rolla, MO . Rashmi Dalvi. 2014. Energy Efficient Scheduling and Allocation of Tasks in Sensor Cloud. Master\u2019s Thesis. Missouri University of Science and Technology, Rolla, MO."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2006.1632658"},{"volume-title":"Design and Analysis of Approximation Algorithms","author":"Du Ding-Zhu","key":"e_1_2_1_6_1","unstructured":"Ding-Zhu Du , Ker- I Ko , and Xiaodong Hu. 2012. Design and Analysis of Approximation Algorithms . Springer-Verlag , New York, NY . Ding-Zhu Du, Ker-I Ko, and Xiaodong Hu. 2012. Design and Analysis of Approximation Algorithms. 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In Proceedings of the 8th Annual IEEE Communications Society Conference on Sensor, Mesh, and Ad Hoc Communications and Networks (SECON\u201911). 46--54."},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2007.148"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1145\/1031495.1031498"},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/1860093.1860118"}],"container-title":["ACM Transactions on Sensor Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2955102","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2955102","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:39:11Z","timestamp":1750221551000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2955102"}},"subtitle":["Cooperative Allocation of Tasks and Scheduling of Sampling Intervals for Maximizing Data Sharing in WSNs"],"short-title":[],"issued":{"date-parts":[[2016,9,7]]},"references-count":28,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2016,11,17]]}},"alternative-id":["10.1145\/2955102"],"URL":"https:\/\/doi.org\/10.1145\/2955102","relation":{},"ISSN":["1550-4859","1550-4867"],"issn-type":[{"type":"print","value":"1550-4859"},{"type":"electronic","value":"1550-4867"}],"subject":[],"published":{"date-parts":[[2016,9,7]]},"assertion":[{"value":"2016-01-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-06-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-09-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}