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In this paper, a hybrid cloud architecture is adopted for provisioning mobile service to mobile device users, which include nearby local cloud and remote public cloud. The computation\u2010intensive tasks can be processed by the remote public cloud, while the delay\u2010sensitive computation can be processed by the nearby local cloud. On the basis of the system context and mobile user preferences, the energy\u2010aware cross\u2010layer mobile cloud resource allocation approach can optimize the consumption of cloud resource and system performance. The cooperation and collaboration among local cloud agent, public cloud supplier, and mobile cloud user are regulated through the economic approach. The energy\u2010aware cross\u2010layer mobile cloud resource allocation is performed on the local cloud level and the public cloud level, which comprehensively considers the benefits of all participants. The energy\u2010aware cross\u2010layer mobile cloud resource allocation algorithm is proposed, which is evaluated in the experiment environment, and comparison results and analysis are discussed.<\/jats:p>","DOI":"10.1002\/dac.3258","type":"journal-article","created":{"date-parts":[[2017,1,9]],"date-time":"2017-01-09T09:52:46Z","timestamp":1483955566000},"source":"Crossref","is-referenced-by-count":5,"title":["Energy\u2010aware cross\u2010layer resource allocation in mobile cloud"],"prefix":"10.1002","volume":"30","author":[{"given":"Li","family":"Chunlin","sequence":"first","affiliation":[{"name":"Department of Computer Science Wuhan University of Technology Wuhan China"},{"name":"Key Laboratory of Spatial Data Mining &amp; Information Sharing of Ministry of Education Fuzhou University Fuzhou China"}]},{"given":"Liu","family":"Yanpei","sequence":"additional","affiliation":[{"name":"Department of Computer Science Wuhan University of Technology Wuhan 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