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Adaptive allocation of resources and call admission control for wireless ATM using genetic algorithms

机译:使用遗传算法的无线ATM的资源自适应分配和呼叫接纳控制

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In wireless ATM-based networks, admission control is required to reserve resources in advance for calls requiring guaranteed services. In the case of a multimedia call, each of its substreams (i.e., video, audio, and data) has its own distinct quality of service (QoS) requirements (e.g., cell loss rate, delay, jitter, etc.). The network attempts to deliver the required QoS by allocating an appropriate amount of resources (e.g., bandwidth, buffers). The negotiated QoS requirements constitute a certain QoS level that remains fixed during the call (static allocation approach). Accordingly, the corresponding allocated resources also remain unchanged. We present and analyze an adaptive allocation of resources algorithm based on genetic algorithms. In contrast to the static approach, each substream declares a preset range of acceptable QoS levels (e.g., high, medium, low) instead of just a single one. As the availability of resources in the wireless network varies, the algorithm selects the best possible QoS level that each substream can obtain. In case of congestion, the algorithm attempts to free up some resources by degrading the QoS levels of the existing calls to lesser ones. This is done, however, under the constraint of achieving maximum utilization of the resources while simultaneously distributing them fairly among the calls. The degradation is limited to a minimum value predefined in a user-defined profile (UDP). Genetic algorithms have been used to solve the optimization problem. From the user perspective, the perception of the QoS degradation is very graceful and happens only during overload periods. The network services, on the other hand, are greatly enhanced due to the fact that the call blocking probability is significantly decreased. Simulation results demonstrate that the proposed algorithm performs well in terms of increasing the number of admitted calls while utilizing the available bandwidth fairly and effectively.
机译:在基于无线ATM的网络中,需要准入控制来为需要保证服务的呼叫预先预留资源。对于多媒体呼叫,其每个子流(即视频,音频和数据)都有其自己独特的服务质量(QoS)要求(例如,信元丢失率,延迟,抖动等)。网络尝试通过分配适当数量的资源(例如带宽,缓冲区)来交付所需的QoS。协商的QoS要求构成了某个QoS级别,该级别在呼叫期间保持固定(静态分配方法)。因此,相应的分配资源也保持不变。我们提出并分析了基于遗传算法的资源自适应分配算法。与静态方法相比,每个子流声明可接受的QoS级别的预设范围(例如,高,中,低),而不是一个单一的范围。随着无线网络中资源可用性的变化,算法选择每个子流可以获得的最佳可能QoS级别。在拥塞的情况下,该算法尝试通过将现有呼叫的QoS级别降级为较小的QoS来释放一些资源。然而,这是在实现资源的最大利用同时又在呼叫之间公平地分配资源的约束下完成的。降级限制为用户定义配置文件(UDP)中预定义的最小值。遗传算法已用于解决优化问题。从用户的角度来看,对QoS下降的感觉非常优美,并且仅在过载期间发生。另一方面,由于呼叫阻塞概率显着降低的事实,大大增强了网络服务。仿真结果表明,在公平有效地利用可用带宽的前提下,该算法在增加允许呼叫数量方面表现良好。

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