期刊
IEEE ACCESS
卷 6, 期 -, 页码 3962-3976出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2791504
关键词
Mobile cloud computing; mobile edge computing; offloading; decision-making; energy-efficient
资金
- Huawei Innovation Research Program (HIRP) grant - Huawei Technologies Co. Ltd [HIRPO2017050307]
Running very complex applications on mobile devices is still challenging since they are constrained by limited resources, such as memory capacity, network bandwidth, processor speed, and battery power. Mobile Cloud Computing (MCC) is a combination of cloud computing and mobile internet, which could effectively alleviate the resource constraints of mobile devices. How to efficiently offload computation-intensive parts of mobile applications from mobile devices to capable cloud servers is one of the keys. In mobile environments, the resource heterogeneity of mobile devices and cloud services, the interruption of heterogeneous wireless networks, the complexity of mobile applications, and the characteristic of transferring a large amount of data, are the major bottlenecks that have prevented this technology from being widely used. This paper takes these constraints into an account at the same time and explores methods of multi-objective decision making for time- and energy-aware task offloading for MCC. It is designed to ensure the right computational tasks are executed in the right way, at the right time and place.
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