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Cell loss analysis for some alternative priority queues

机译:某些替代优先级队列的信元丢失分析

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The paper proposes and analyzes two alternative priority multiplexing schemes together with the associated Call Admission Control (CAC) algorithms. In one of the proposals we assume the well-known, two queue, strict-priority multiplexer with a buffering resource of fixed storage capacity that is divided into two disjoint parts representing the first and second priority queues. In traditional architectures the size of the first and second queues can be set off-line only during configuration procedures. The drawback of such a static configuration is the inability to adapt to the dynamic changes of traffic demands, which in turn may result in an inefficient utilization of both buffering and server resources. By using Large Deviation analysis, we show that there exists an optimal buffer sharing policy that distributes the total available buffer space between the first and second queues according to the current input traffic such that the attainable server utilization will be the highest. Our proposed dynamic mechanism relies on online traffic measurements in making the CAC decision and reconfiguring the buffers at the same time. As another way of improvement we analyze a new multiplexing scheme that includes a scheduling and buffer management algorithm, which is intended to be an efficient way of multiplexing delay but not loss-sensitive voice with loss but not delay sensitive data. In this setup we have only one joint buffer for both voice and data packets. Voice packets have service priority and data packets have storage priority, which means that an incoming data packer can push-out a voice packet from the buffer if there is no free space available. We also analyze this multiplexer, propose an associated CAC algorithm and compare it with the previous one.
机译:本文提出并分析了两种备选的优先级复用方案以及相关的呼叫准入控制(CAC)算法。在其中一个建议中,我们假设使用众所周知的两个队列的严格优先级多路复用器,该复用器具有固定存储容量的缓冲资源,该资源分为两个不相交的部分,分别代表第一优先级队列和第二优先级队列。在传统体系结构中,仅在配置过程中可以离线设置第一和第二队列的大小。这种静态配置的缺点是无法适应流量需求的动态变化,进而可能导致缓冲资源和服务器资源的利用效率低下。通过使用大偏差分析,我们表明存在一种最佳的缓冲区共享策略,该策略根据当前输入流量在第一和第二队列之间分配总的可用缓冲区空间,以使可获得的服务器利用率达到最高。我们提出的动态机制依靠在线流量测量来做出CAC决策并同时重新配置缓冲区。作为改进的另一种方法,我们分析了一种新的复用方案,其中包括调度和缓冲区管理算法,该方案旨在成为一种有效的复用延迟方式的方法,该方法可以将延迟而不是对丢失敏感的语音与丢失但对延迟不敏感的数据进行复用。在此设置中,我们只有一个联合缓冲区,用于语音和数据包。语音数据包具有服务优先级,数据数据包具有存储优先级,这意味着如果没有可用空间,传入的数据打包程序可以从缓冲区推出语音数据包。我们还分析了这种多路复用器,提出了一种关联的CAC算法,并将其与前一个算法进行了比较。

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