We study delay tolerant networking (DTN) and in particular, its capacity to store, carry and forward messages so that the messages eventually reach their final destinations. We approach this broad question in the framework of percolation theory. To this end, we assume an elementary mobility model, where nodes arrive to an infinite plane according to a Poisson point process, move a certain distance L, and then depart. In this setting, we characterize the mean density of nodes required to support DTN style networking. In particular, under the given assumptions, we show that DTN is feasible when the mean node degree is greater than 4 e(g), where parameter g=L d is the ratio of the distance L to the transmission range d, and e(g) is the critical reduced number density of tilted cylinders in a directed continuum percolation model. By means of Monte Carlo simulations, we give numerical values for e(g). The asymptotic behavior of e(g) when g tends to infinity is also derived from a fluid flow analysis.
@cite_16 consider the propagation speed of the information in DTN for a fixed set of nodes moving in a finite region. The spatial dimension is explicitly present in their formulation. Somewhat related, Grossglauser and Tse @cite_18 studied the performance of adhoc networks under mobility. They focused on connected networks, where nodes can either communicate directly or via multi-hop connections, and showed that mobility increases the overall capacity in the network given the users tolerate additional delays.
@cite_18 @cite_16
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The goal of this paper is to increase our under- standing of the fundamental performance limits of mobile and Delay Tolerant Networks (DTNs), where end-to-end multihop paths may not exist and communication routes may only be available through time and mobility. We use analytical tools to derive generic theoretical upper bounds for the information propagation speed in large scale mobile and intermittently con- nected networks. In other words, we upper-bound the optimal performance, in terms of delay, that can be achieved using any routing algorithm. We then show how our analysis can be applied to specific mobility models to obtain specific analytical estimates. In particular, in 2-D networks, when nodes move at a maximum speed and their density is small (the network is sparse and asymptotically almost surely disconnected), we prove that the information propagation speed is upper bounded by in random waypoint-like models, while it is upper bounded by for other mobility models (random walk, Brownian motion). We also present simulations that confirm the validity of the bounds in these scenarios. Finally, we generalize our results to 1-D and 3-D networks. The goal of this paper is to increase our understanding of the fundamental performance limits of mobile and Delay Tolerant Networks (DTNs), where end-to-end multihop paths may not exist and communication routes may only be available through time and mobility. We use analytical tools to derive generic theoretical upper bounds for the information propagation speed in large scale mobile and intermittently connected networks. In other words, we upper-bound the optimal performance, in terms of delay, that can be achieved using any routing algorithm. We then show how our analysis can be applied to specific mobility models to obtain specific analytical estimates. In particular, in 2-D networks, when nodes move at a maximum speed v and their density is small (the network is sparse and asymptotically almost surely disconnected), we prove that the information propagation speed is upper bounded by (1 + O(v2))v in random waypoint-like models, while it is upper bounded by O(√vvv) for other mobility models (random walk, Brownian motion). We also present simulations that confirm the validity of the bounds in these scenarios. Finally, we generalize our results to 1-D and 3-D networks. The goal of this paper is to increase our understanding of the fundamental performance limits of mobile and Delay Tolerant Networks (DTNs), where end-to-end multi-hop paths may not exist and communication routes may only be available through time and mobility. We use analytical tools to derive generic theoretical upper bounds for the information propagation speed in large scale mobile and intermittently connected networks. In other words, we upper-bound the optimal performance, in terms of delay, that can be achieved using any routing algorithm. We then show how our analysis can be applied to specific mobility and graph models to obtain specific analytical estimates. In particular, in two-dimensional networks, when nodes move at a maximum speed @math and their density @math is small (the network is sparse and surely disconnected), we prove that the information propagation speed is upper bounded by ( @math in the random way-point model, while it is upper bounded by @math for other mobility models (random walk, Brownian motion). We also present simulations that confirm the validity of the bounds in these scenarios. Finally, we generalize our results to one-dimensional and three-dimensional networks. Gupta and Kumar (2000) introduced a random network model for studying the way throughput scales in a wireless network when the nodes are fixed, and showed that the throughput per source-destination pair is spl otimes (1 spl radic nlogn). Grossglauser and Tse (2001) showed that when nodes are mobile it is possible to have a constant or spl otimes (1) throughput scaling per source-destination pair. The focus of this paper is on characterizing the delay and determining the throughput-delay trade-off in such fixed and mobile ad hoc networks. For the Gupta-Kumar fixed network model, we show that the optimal throughput-delay trade-off is given by D(n) = spl otimes (nT(n)), where T(n) and D(n) are the throughput and delay respectively. For the Grossglauser-Tse mobile network model, we show that the delay scales as spl otimes (n sup 1 2 v(n)), where v(n) is the velocity of the mobile nodes. We then describe a scheme that achieves the optimal order of delay for any given throughput. The scheme varies (i) the number of hops, (ii) the transmission range and (iii) the degree of node mobility to achieve the optimal throughput-delay trade-off. The scheme produces a range of models that capture the Gupta-Kumar model at one extreme and the Grossglauser-Tse model at the other. In the course of our work, we recover previous results of Gupta and Kumar, and Grossglauser and Tse using simpler techniques, which might be of a separate interest.