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Service quality assurance oriented cognitive network service migration method

A cognitive network and quality assurance technology, applied in network traffic/resource management, electrical components, wireless communication, etc., can solve problems such as difficulty in meeting large-scale cognition, lack of cognitive network OoS guarantee solutions, decentralization, etc., to achieve good Market application prospects, avoiding the overall collapse of the system, and the effect of small side effects

Inactive Publication Date: 2011-09-21
HARBIN ENG UNIV
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Problems solved by technology

Since the existing cognitive network QoS guarantee method does not change the traditional control mode in essence, the means of adjusting network QoS quality are relatively scattered, and there is a lack of an effective, networked, and adaptive cognitive network OoS guarantee scheme , so it is difficult to meet the specific QoS requirements of services in large-scale cognitive networks

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  • Service quality assurance oriented cognitive network service migration method
  • Service quality assurance oriented cognitive network service migration method
  • Service quality assurance oriented cognitive network service migration method

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Embodiment Construction

[0026] The present invention is described in more detail below in conjunction with accompanying drawing example:

[0027] to combine Figure 1~2 , the core node of the cognitive network system first imports different service migration instances into different service node service queues to wait and execute according to the set initial service allocation plan. If the service execution is normal, the service migration mechanism will not start; if the system detects If there is a working node service failure in the system, the service migration mechanism will be started. The specific steps are as follows:

[0028] (1) When it is found that a working node fails to complete the service execution, suspend the currently executing service on the node, obtain the execution status of other services, and create a service migration instance at the same time. The creation of the service migration instance is generated by the current working node, and the service migration instance include...

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Abstract

The invention aims to provide a service quality assurance oriented cognitive network service migration method. The method comprises the steps of starting a service migration mechanism if a cognitive network system detects the situation that the service of a working node is not valid in the system; pausing the service which currently executed on the node with invalid service and establishing a service migration instance; reconstructing the paused service in a layered way; figuring out a migration path and then sending a service migration request to a migration node; carrying out migration and informing a new migration position by the migration node after receiving the request; registering the service on a new working node; activating a suspended migration service; and deleting a backup of the migration service by the original working node to finish the service migration process. According to the invention, the technical difficulty of large service fault-tolerant recovery expense and poor effect under a network environment is fundamentally solved; and the service quality assurance oriented cognitive network service migration method provided by the invention has the characteristics of low cost, small side effect, simplicity in implementation and better market application prospect.

Description

technical field [0001] The invention relates to a quality of service guarantee (quality of service, QoS) of a network system. Background technique [0002] Cognitive Networks (CN) was proposed inspired by Cognitive Radio (CR) technology. Its core idea is to enable the network to perceive changes in the internal and external environment, adjust the configuration of the network in real time, and dynamically and intelligently adapt to the external environment. Change and guide future autonomous decision-making, that is, introduce biological self-regulation properties at the network level, and enhance its environmental adaptability and cognitive ability. At present, the research on cognitive network is in its infancy. Because the complexity of the cognitive network application environment far exceeds the level expected by developers in the initial stage of network design, integrated service IntServ and differentiated service DiffServ have been successfully deployed on the tradit...

Claims

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Application Information

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IPC IPC(8): H04W28/10H04W28/24H04W40/02
Inventor 王慧强林俊宇卢旭冯光升吕宏武李冰洋徐俊波
Owner HARBIN ENG UNIV
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