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Energy-Efficient Caching Strategies in Ad Hoc Wireless Networks

机译:Ad Hoc无线网络中的节能高速缓存策略

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In this paper, we address the problem of energy-conscious cache placement in wireless ad hoc networks. We consider a network comprising a server with an interface to the wired network, and some nodes requiring access to the information stored at the server. In order to reduce access latency in such a communication environment, an effective strategy is caching the server information at some nodes distributed across the network. Caching, however, can considerably impact the system energy expenditure; for instance, disseminating information incurs additional energy burden. Since wireless devices have limited amounts of available energy, we need to design caching strategies that optimally trade-off between energy consumption and access latency. We pose our problem as an integer linear program. We show that this problem is the same as a special case of the connected facility location problem, which is known to be NP-hard. We devise a polynomial time algorithm which provides a sub-optimal solution. The proposed algorithm applies to any arbitrary network topology and can be implemented in a distributed and asynchronous manner. In the case of a tree topology, our algorithm gives the optimal solution. In the case of an arbitrary topology, it finds a feasible solution with an objective function value within a factor of 6 of the optimal value. This performance is very close to the best approximate solution known today, which is obtained in a centralized manner. We compare the performance of our algorithm against three candidate caching schemes, and show via extensive simulation that our algorithm consistently outperforms these alternative schemes.
机译:在本文中,我们解决了无线自组织网络中能源敏感型缓存放置的问题。我们考虑一个网络,该网络包括一个服务器,该服务器具有到有线网络的接口,并且一些节点需要访问存储在服务器上的信息。为了减少这种通信环境中的访问延迟,一种有效的策略是将服务器信息缓存在分布在网络上的某些节点上。但是,缓存会极大地影响系统的能源消耗。例如,传播信息会带来额外的能源负担。由于无线设备的可用能量有限,因此我们需要设计缓存策略,以便在能耗和访问延迟之间进行最佳权衡。我们把问题摆成一个整数线性程序。我们证明此问题与连接设施位置问题的特例相同,已知为NP-hard。我们设计了一种多项式时间算法,该算法提供了次优的解决方案。所提出的算法适用于任何任意的网络拓扑,并且可以以分布式和异步方式实现。在树形拓扑的情况下,我们的算法给出了最佳解决方案。在任意拓扑的情况下,可以找到目标函数值在最佳值的6倍以内的可行解决方案。此性能非常接近当今已知的最佳近似解决方案,该解决方案是以集中方式获得的。我们将我们的算法与三种候选缓存方案的性能进行了比较,并通过广泛的仿真表明,我们的算法始终优于这些替代方案。

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