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END-TO-END QOS-BASED ADMISSION CONTROL AND APNS INTERACTION FRAMEWORK WITH NEGOTIATION

机译:端到端基于QOS的协商访问控制和APNS交互框架

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Most of the admission control algorithms treat every admission request uniformly and hence optimize the system performance by maximizing the number of admitted and served requests. In practice, requests might have different levels of importance to the system. Requests offering high contribution or reward to the system performance deserve priority treatment. Failure of accepting a high-priority request would incur high penalty to the system. Our Proposed framework takes three priority classes of requests. The network capacity is divided into three partitions based on the threshold values: one for high class of requests and second for low class of request and third is common pool which accept the high, low and other classes of requests respectively. We take a condition in common pool if common pool is filled 3/4 of its total capacity and at this time new request comes then we degrade the low priority class and accept that coming request. Reward and penalty are adopted in the proposed system model. High-priority requests are associated with higher values of reward as well as penalty than low-priority ones. In this paper, we have used these characteristics of the system in access provider network to admit more requests and to increase workload with out degradation of system performance. Our proposed framework will improve the processing of the system model and optimize the system performance based on the objective function of the total reward minus the total penalty. The negotiation mechanism reduces the QoS requirements of several low-priority clients, by cutting out a small fraction of the assigned capacity, to accept a new high-priority client and to achieve a higher net earning value for enhancing the system performance.
机译:大多数准入控制算法均等地对待每个准入请求,因此通过最大化准入和服务请求的数量来优化系统性能。实际上,请求对系统的重要性可能不同。对系统性能提供高贡献或高回报的请求应优先处理。未能接受高优先级请求将对系统造成高额罚款。我们的建议框架采用三种优先级的请求。根据阈值,网络容量分为三个分区:一个用于高级别请求,第二个用于低级别请求,第三个是公共池,它们分别接受高,低和其他级别的请求。如果公共池被填充了其总容量的3/4,我们将在公共池中采取一个条件,这时新的请求到来,那么我们将低优先级降级并接受该请求。提议的系统模型采用了奖励和惩罚。与低优先级请求相比,高优先级请求与较高的奖励和惩罚值相关联。在本文中,我们利用访问提供商网络中系统的这些特征来接纳更多请求并增加工作量,而不会降低系统性能。我们提出的框架将基于总奖励减去总罚分的目标函数,改进系统模型的处理并优化系统性能。协商机制通过减少一小部分分配的容量,接受新的高优先级客户端并实现更高的净收益值来增强系统性能,从而降低了几个低优先级客户端的QoS要求。

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