期刊
IEEE INTERNET OF THINGS JOURNAL
卷 6, 期 3, 页码 4283-4294出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2018.2875917
关键词
Content caching; Internet of Things (IoT); mobile edge computing (MEC); resource allocation
资金
- Shenzhen-Hongkong Innovative Project [SGLH20161212140718841]
- Shenzhen Engineering Laboratory for 3-D Content Generating Technologies [[2017]476]
- Key Research Plan of Hunan Province [2016JC2021, 2016JC2022]
- Guangdong Technology Project [2016B010108010, 2016B010125003, 2017B010110007]
- National Basic Research Program of China (973 Program) [2014CB744600]
- National Nature Science Foundation of China [61601482, 61403365, 61402458, 61502075, 61632014, 61772508]
- Program of International S&T Cooperation of MOST [2013DFA11140]
Mobile edge computing (MEC) has risen as a promising paradigm to provide high quality of experience via relocating the cloud server in close proximity to smart mobile devices (SMDs). In MEC networks, the MEC server with computation capability and storage resource can jointly execute the latency-sensitive offloading tasks and cache the contents requested by SMDs. In order to minimize the total latency consumption of the computation tasks, we jointly consider computation offloading, content caching, and resource allocation as an integrated model, which is formulated as a mixed integer nonlinear programming (MINLP) problem. We design an asymmetric search tree and improve the branch and bound method to obtain a set of accurate decisions and resource allocation strategies. Furthermore, we introduce the auxiliary variables to reformulate the proposed model and apply the modified generalized benders decomposition method to solve the MINLP problem in polynomial computation complexity time. Simulation results demonstrate the superiority of the proposed schemes.
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