access icon openaccess Joint optimisation for time consumption and energy consumption of multi-application and load balancing of cloudlets in mobile edge computing

Mobile edge computing (MEC) is an effective assistant technology that can overcome some defects of cloud computing. For the sake of alleviating the clashes between the capability constraint of cloudlets and the needs of mobile devices (MDs) for reducing executing latency as well as decreasing the power consumption of MDs, a user-oriented use case in the MEC named computation offloading is taken into consideration. Computation offloading is capable of effectively making the MEC adapt to the resources of cloudlets and MDs in different environments, and it is very beneficial to the development of the internet of things. Owing to the finite computation capabilities of the MDs and the resources of cloudlets are heterogeneous and limited; a three-objective model is established to optimise the time consumption, and the energy consumption of MDs as well as the load balancing of cloudlets jointly. Technically, the authors propose an effective multi-user multi-application computation offloading method in the multi-cloudlet environment on the basis of improved non-dominated sorting genetic algorithm III. Finally, comprehensive experiments and analysis were conducted to validate the effectiveness and efficiency of the proposed method.

Inspec keywords: mobile computing; genetic algorithms; power aware computing; resource allocation; cloud computing

Other keywords: mobile devices; MEC; multicloudlet environment; user-oriented use case; finite computation capabilities; energy consumption; power consumption; effective assistant technology; mobile edge computing; multiuser multiapplication computation offloading method; cloud computing; joint optimisation; MD

Subjects: Optimisation techniques; Operating systems; Internet software; Mobile, ubiquitous and pervasive computing; Performance evaluation and testing

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