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Cooperative service deployment and service allocation method for regional edge computing internet of things

An edge computing and collaborative service technology, applied in electrical components, transmission systems, etc., can solve problems such as increasing indirect computing resource occupation, load imbalance, and increasing network deployment costs, reducing resource consumption, reducing deployment, and improving resources. The effect of utilization

Active Publication Date: 2020-02-07
CHINA UNIV OF MINING & TECH
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  • Claims
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AI Technical Summary

Problems solved by technology

In the existing edge computing research, the edge server only provides services for the applications in the access network it covers, and it is necessary to deploy an edge server for each access network, which greatly increases the deployment cost of the network, and at the same time causes the above resource Low utilization and unbalanced load, as well as the repeated deployment of service applications of the same business in the regional Internet of Things in each edge server, greatly increasing the resource occupation of indirect computing
For some applications in the overloaded access network, the current solution is to further offload to the cloud server for execution, but does not consider the cloud-to-end uncertain delay problem

Method used

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  • Cooperative service deployment and service allocation method for regional edge computing internet of things
  • Cooperative service deployment and service allocation method for regional edge computing internet of things
  • Cooperative service deployment and service allocation method for regional edge computing internet of things

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Embodiment Construction

[0081] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0082] The regional edge computing IoT system model diagram of the present invention is as follows figure 1 As shown; Given a regional network, there are n IoT nodes installed with intelligent application services, and the IoT nodes are distributed in k access networks, and a total of j types of services are installed on these n nodes in the network. All access points in the network are connected to a central network management forwarding unit. The computing tasks of intelligent applications installed on IoT nodes in the network cannot be completed locally, and need to be offloaded to the edge server for assistance.

[0083] The invention aims at deploying edge servers for the network, and performing service distribution so that the service quality (QoS) of all services in the network can be satisfied. At the same time, the ...

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Abstract

The invention discloses a cooperative service deployment and service allocation method for a regional edge computing internet of things, and relates to the field of edge computing and internet of things. In order to improve the resource effectiveness in the edge computing Internet of Things service deployment and reduce the network deployment cost, an edge server cooperation mode in the regional edge computing Internet of Things is firstly constructed, and then the service deployment problem with the minimum deployment cost in the edge servers is modeled into a vector encasement problem; the minimum number of servers and an initial service allocation result are determined through a minimum resource proportion increment heuristic algorithm; and then, in order to balance the network load andreduce the forwarding load of the network management unit, an iterative search mobile switching heuristic algorithm is utilized to redistribute the service to a locally deployed edge server, and thenumber of service calculation tasks processed by the local edge server is maximized.

Description

technical field [0001] The invention belongs to the field of edge computing Internet of Things, and in particular relates to a collaborative service deployment and business distribution method for regional edge computing Internet of Things. Background technique [0002] Edge computing technology can make up for the uncertain delay caused by Internet transmission in the traditional cloud service architecture by deploying edge servers with relatively strong computing power and relatively abundant resources in the access network at the edge of the network close to users. Therefore, edge computing technology is regarded as a key technology in the implementation and application of intelligent Internet of Things in the future. However, in the actual application of edge computing, due to the relatively limited processing capabilities and resources of the edge server, it is necessary to allocate and schedule services in actual applications. [0003] In practical application scenari...

Claims

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Application Information

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IPC IPC(8): H04L29/08
CPCH04L67/1023H04L67/12
Inventor 孙彦景陈岩张亮徐宏力侯晓峰王斌程小舟陈晓晶杨俊秋
Owner CHINA UNIV OF MINING & TECH
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