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Energy‐aware cross‐layer resource allocation in mobile cloud

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SummaryThis paper proposed an energy‐aware cross‐layer mobile cloud resource allocation approach. 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‐intensive tasks can be processed by the remote public cloud, while the delay‐sensitive computation can be processed by the nearby local cloud. On the basis of the system context and mobile user preferences, the energy‐aware cross‐layer 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‐aware cross‐layer 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‐aware cross‐layer mobile cloud resource allocation algorithm is proposed, which is evaluated in the experiment environment, and comparison results and analysis are discussed.
Title: Energy‐aware cross‐layer resource allocation in mobile cloud
Description:
SummaryThis paper proposed an energy‐aware cross‐layer mobile cloud resource allocation approach.
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‐intensive tasks can be processed by the remote public cloud, while the delay‐sensitive computation can be processed by the nearby local cloud.
On the basis of the system context and mobile user preferences, the energy‐aware cross‐layer 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‐aware cross‐layer 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‐aware cross‐layer mobile cloud resource allocation algorithm is proposed, which is evaluated in the experiment environment, and comparison results and analysis are discussed.

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