Abstract
Mobile terminal applications with high computing complexity and high time delay sensitivity are developing quite fast today, which aggravates the load of mobile cloud computing and storage and further leads to network congestion and service quality decline. Mobile edge computing (MEC) is a way of breaking through the limits of computing and storage resources of mobile cloud and alleviating the load of mobile cloud. Computing time costs and transmission time costs are considered to be the main issues for the mobile cloud when carrying out computing offloading and data caching. Therefore, an efficient resource management strategy, which could minimize the system delay, is proposed in this paper. The new scheme offloads reasonably computing tasks and caches the tasks’ data from the mobile cloud to mobile edge computing-enabled base stations. An intelligence algorithm, genetic algorithm, is being used to solve the global optimization problem which would cause transmission delay and computing resources occupation, and to determine the computing offloading and data caching probability. The simulation of the system using MATLAB is conducted in 8 different scenarios with different parameters. The results show that our new scheme improves the system computing speed and optimizes the user experience in all scenarios, compared with the scheme without data caching and the scheme without computing offloading and data caching.
Highlights
With the rapid development of the mobile Internet and the Internet of things in recent years, the functions of the mobile terminals (MTs) are becoming much more rich than ever before
The total time consumption for completing r j includes: (1) the time consumed by executing in the mobile cloud, if r j is selected to be executed at C; (2) the time consumed by computation offloading, if r j is selected to be offloaded to Mobile edge computing (MEC)-BS; (3) the time consumed by computation offloading, if r j is selected to be further offloaded to nk, ∀k ∈ K
In (2), the time consumption needs to be divided into two situations: (1) mobile edge computing-enabled base station (MEC-BS) has the data caching required by task r j ; (2) MEC-BS does not have the data caching required by task r j, and it needs to send the data caching request to C to get the data
Summary
With the rapid development of the mobile Internet and the Internet of things in recent years, the functions of the mobile terminals (MTs) are becoming much more rich than ever before. The character of mobile terminals has gradually evolved from a simple communication tool to a powerful station integrating communication, computing, entertainment and office Various applications, such as augmented reality, virtual reality, and location-based service (LBS), have been contained in one mobile terminal as required by the consumers. These typical applications with high computing complexity and long time delay sensitivity aggravate the load of the mobile cloud (C) in computing and storage resources, but they lead to system network congestion and service quality decline. The users can experience higher real-time performance of applications, and run more complex applications in their resource-constrained MTs. The steps for computing offloading and data caching under the mobile edge computing environments are as follows: (1) when.
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