An energy-efficient and resource-constrained task allocation method for mobile edge computing

Abstract

The invention discloses an energy-efficient and resource-constrained mobile edge computing task allocation method. According to different task allocation schemes, the impact on edge cloud energy and processor resources in the case of specified execution delay is established based on energy consumption. A joint optimization model of waste of processor resources and processor resources, and then minimize the total energy consumption of task assignment and waste of processor resources under the specified execution delay, and then map the joint optimization problem into an ecosystem model of biogeographical algorithms, And according to the corresponding optimization objectives and optimization conditions, the optimal task allocation scheme is obtained; the present invention solves the problem that mobile user equipment with limited resources cannot meet the resource requirements of mobile applications, and the mobile user equipment will offload some tasks constituting the mobile application to the mobile On the base station or edge cloud of edge computing, the energy efficiency and processor resource utilization of the edge cloud are improved.

Description

Technical field: [0001] The present invention relates to mobile edge computing, in particular to an energy-efficient and resource-constrained mobile edge computing task allocation method. Background technique: [0002] Mobile Edge Computing (Mobile Edge Computing) provides cloud services by pushing cloud resources (such as computing, network, and storage) to the edge of the mobile network, and integrates wireless networks and applications, making traditional wireless access networks intelligent and application-friendly. The conditions for localization and short-distance deployment provide high-bandwidth and low-latency transmission capabilities. The schematic diagram of the environment is as follows figure 1 shown. There are six parts in this diagram: (1) mobile user equipment; (2) wireless cellular base station; (3) tasks (Tasks, Ts) assigned to virtual machines (Virtual Machines, VMs) and containers (Containers, Cs) ); (4) edge servers and cloud servers with built-in vir...

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Problems solved by technology

[0004] The technical problem to be solved by the present invention is: to overcome the deficiencies of the prior art, first establish a joint optimization model based on energy consumption and waste of processor resources, secondly, map the joint optimization problem into an ecosystem model of biogeographical algorithms, and An energy-efficient and resource-constrained task allocation method for mobile edge computing to obtain the optimal task allocation scheme according to the corresponding optimization objectives and optimization conditions

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