A generalized framework for throughput analysis in sparse mobile networks

R. Subramanian, B. Vellambi, F. Fekri
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引用次数: 15

Abstract

Consider a mobile network wherein nodes are confined to move and communicate in a given area. The network is assumed to be sparse, wherein a direct communication path from a source node via multiple hops to a destination node almost never exists. The nodes resort to storing, carrying, and forwarding packets when a contact occurs, as a means of communication. This paper investigates the question of computing the throughput capacity of the resulting network, in other words, the rate at which a source node can send packets to a destination node using the other nodes in the network as relays. It proposes an accurate generalized framework valid for any mobility model that exhibits stationarity. The framework uses the embedded Markov-Chain approach using which the capacity of such a network can be accurately determined by computing certain well-defined characteristic parameters from the mobility model. Constraints posed by limited node storage and contention between nodes for the wireless channel are also considered in order to obtain a realistic model for the throughput. The paper also illustrates the proposed framework under two specific cases: the random walk, random waypoint, and restricted random waypoint mobility models, and validates the same using simulations.
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稀疏移动网络吞吐量分析的广义框架
考虑一个移动网络,其中节点被限制在给定区域内移动和通信。假设网络是稀疏的,其中从源节点经过多跳到达目标节点的直接通信路径几乎不存在。当接触发生时,节点依靠存储、携带和转发数据包作为一种通信手段。本文研究计算最终网络的吞吐能力的问题,换句话说,一个源节点使用网络中的其他节点作为中继向目标节点发送数据包的速率。它提出了一个准确的广义框架,适用于任何具有平稳性的移动模型。该框架使用嵌入式马尔可夫链方法,使用该方法可以通过计算来自移动性模型的某些定义良好的特征参数来准确确定此类网络的容量。为了得到一个真实的吞吐量模型,还考虑了有限的节点存储和节点之间对无线信道的争用所带来的约束。本文还在随机行走、随机航路点和受限随机航路点移动模型两种具体情况下对所提出的框架进行了说明,并通过仿真对其进行了验证。
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