Abstract-Inter-meeting time between mobile nodes is one of the key metrics in a Mobile Ad-hoc Network (MANET) and central to the end-to-end delay of forwarding algorithms. It is typically assumed to be exponentially distributed in many performance studies of MANET or numerically shown to be exponentially distributed under most existing mobility models in the literature. However, recent empirical results show otherwise: the inter-meeting time distribution in fact follows a power-law. This outright discrepancy potentially undermines our understanding of the performance tradeoffs in MANET obtained under the exponential distribution of the inter-meeting time, and thus calls for further study on the power-law inter-meeting time including its fundamental cause, mobility modeling, and its effect. In this paper, we rigorously prove that a finite domain, on which most of the current mobility models are defined, plays an important role in creating the exponential tail of the inter-meeting time. We also prove that by simply removing the boundary in a simple two-dimensional isotropic random walk model, we are able to obtain the empirically observed power-law decay of the inter-meeting time. We then discuss the relationship between the size of the boundary and the relevant timescale of the network scenario under consideration. Our results thus provide guidelines on the mobility modeling with power-law inter-meeting time distribution, new protocols including packet forwarding algorithms, as well as their performance analysis.Index Terms-mobile ad-hoc network, inter-meeting time distribution, exponential vs. power-law, bounded domain, time and space scaling.

No abstract

No abstract

-The average download time of a file is an important performance metric for a user in a peerto-peer network. We point out that the common approach of analyzing the average download time based on average service capacity is fundamentally flawed, and show that spatial heterogeneity and temporal correlation in the service capacity over different paths are the two major factors that have negative impact on the average file download time. We then propose a simple and distributed algorithm that can completely remove this negative impact of the two factors and yield the smallest possible average download time for each user in the network.

No abstract