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Energy-efficient and resource-limited mobile edge computing task allocation method

A task allocation and resource-constrained technology, applied in the field of mobile edge computing task allocation, can solve problems such as waste of processor resources

Active Publication Date: 2020-12-11
HENAN INST OF ENG
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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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  • Energy-efficient and resource-limited mobile edge computing task allocation method
  • Energy-efficient and resource-limited mobile edge computing task allocation method
  • Energy-efficient and resource-limited mobile edge computing task allocation method

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[0058] Example: see figure 1 , figure 2 , image 3 , Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 , Figure 9 and Figure 10.

[0059] An energy-efficient and resource-constrained mobile edge computing task assignment method, the steps are: step 1, according to the linear relationship between the energy consumption of the edge server and the CPU utilization on it, the energy consumption model of the edge server is defined as CPU function of utilization;

[0060] Step 2. Extend the existing model to quantify resource waste in all dimensions of the edge server, and balance the remaining resources of the jth edge server in different dimensions to obtain a processor resource waste model;

[0061] Step 3: Minimize overall energy consumption and overall processor resource waste while meeting resource requirements and prescribed execution delays, and obtain a joint optimization objective function in the optimization phase;

[0062] Step 4: Map the joint optimiz...

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Abstract

The invention discloses an energy-efficient and resource-limited mobile edge computing task allocation method, which comprises the following steps: establishing a joint optimization model based on energy consumption and processor resource waste according to different task allocation schemes and the influence on energy and processor resources of edge clouds under the condition of stipulated execution delay; further minimizing total energy consumption of task allocation and processor resource waste under the condition of stipulating execution delay, then mapping the joint optimization problem into an ecosystem model of a biogeography algorithm, and obtaining an optimal task allocation scheme according to a corresponding optimization target and a corresponding optimization condition; according to the invention, the problem that the mobile user equipment with limited resources cannot meet the resource requirements of the mobile application is solved, the mobile user equipment can unload part of tasks forming the mobile application to the base station or the edge cloud of the mobile edge computing, and the energy efficiency of the edge cloud and the resource utilization rate of the processor 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...

Claims

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Application Information

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IPC IPC(8): H04L29/08
CPCH04L67/10H04L67/60
Inventor 高继勋刘家磊李刚黄全振张大俊孙凤霞张洋黄明明李新
Owner HENAN INST OF ENG
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