The Fundamental Limits of Broadcasting in Dense Wireless Mobile Networks

In this paper, we investigate the fundamental properties of broadcasting in {em mobile} wireless networks. In particular, we characterize broadcast capacity and latency of a mobile network, subject to the condition that the stationary node spatial distribution generated by the mobility model is uniform. We first study the intrinsic properties of broadcasting, and present the {sc RippleCast} broadcasting scheme that simultaneously achieves asymptotically optimal broadcast capacity and latency, subject to a weak upper bound on maximum node velocity and under the assumption of static broadcast source. We then extend {sc RippleCast} with the novel notion of center-casting, and prove that asymptotically optimal broadcast capacity and latency can be achieved also when the broadcast source is mobile. This study intendedly ignores the burden related to the selection of broadcast relay nodes within the mobile network, and shows that optimal broadcasting in mobile networks is, in principle, possible. We then investigate the broadcasting problem when the relay selection burden is taken into account, and present a combined distributed leader election and broadcasting scheme achieving a broadcast capacity and latency which is within a $Theta((log n)^{1+frac{2}{alpha}})$ factor from optimal, where $n$ is the number of mobile nodes and $alpha>2$ is the path loss exponent. However, this result holds only under the assumption that the upper bound on node velocity converges to zero (although with a very slow, poly-logarithmic rate) as $n$ grows to infinity

On the Fundamental Limits of Broadcasting in Wireless Mobile Networks

In this talk, we investigate the fundamental properties of broadcasting in mobile wireless networks. In particular, we characterize broadcast capacity and latency of a mobile network, subject to the condition that the stationary node spatial distribution generated by the mobility model is uniform. We first study the intrinsic properties of broadcasting, and present a broadcasting scheme, called RippleCast, that simultaneously achieves asymptotically optimal broadcast capacity and latency, subject to a weak upper bound on the maximum node velocity. This study intendedly ignores the burden related to the selection of broadcast relay nodes within the mobile network, and shows that optimal broadcasting in mobile networks is, in principle, possible. We then investigate the broadcasting problem when the relay selection burden is taken into account, and present a combined distributed leader election and broadcasting scheme achieving a broadcast capacity and latency which is within a $Theta((log n)^{1+frac{2}{alpha}})$ factor from optimal, where $n$ is the number of mobile nodes and $alpha>2$ is the path loss exponent. However, this result holds only under the assumption that the upper bound on node velocity converges to zero (although with a very slow, poly-logarithmic rate) as $n$ grows to infinity. To the best of our knowledge, our is the first paper investigating the effects of node mobility on the fundamental properties of broadcasting, and showing that, while optimal broadcasting in a mobile network is in principle possible, the coordination efforts related to the selection of broadcast relay nodes lead to sub-optimal broadcasting performance

The k-Neigh Protocol for Symmetric Topology Control in Ad Hoc Networks

We propose an approach to topology control based on the principle of maintaining the number of neighbors of every node equal to or slightly below a specific value k. The approach enforces symmetry on the resulting communication graph, thereby easing the operation of higher layer protocols. To evaluate the performance of our approach, we estimate the value of k that guarantees connectivity of the communication graph with high probability. We then define k-Neigh, a fully distributed, asynchronous, and localized protocol that follows the above approach and uses distance estimation. We prove that k-Neigh terminates at every node after a total of 2n messages have been exchanged (with n nodes in the network) and within strictly bounded time. Finally, we present simulations results which show that our approach is about 20% more energy-efficient than a widelystudied existing protocol

The Node Spatial Distribution of the Generalized Random Waypoint Mobility Model for Wireless Ad Hoc Networks

In this paper we analyze the node spatial distribution generated by nodes moving according to the random waypoint model, which is widely used in the simulation of mobile ad hoc networks. We extend an existing analysis for the case in which nodes are continuously moving (i.e., the pause time is 0) to the more general case in which nodes have arbitrary pause times between movements. We also generalize the mobility model, allowing the nodes to remain stationary for the entire simulation time with a given probability. Our analysis shows that the structure of the resulting asymptotic spatial density is composed by three distinct components: the initial, the pause and the mobility component. The relative values of these components depend on the mobility parameters. We derive an explicit formula of the one-dimensional node spatial density, and an approximated formula for the two-dimensional case. The quality of this approximation is verified through experimentation, which shows that the accuracy heavily depends on the choice of the mobility parameters

The Node Distribution of the Random Waypoint Mobility Model for Wireless Ad Hoc Networks

The random waypoint model is a commonly used mobility model in the simulation of ad hoc networks. It is known that the spatial distribution of nodes moving according to this model is in general non-uniform. However, an in-depth investigation and a closed-form expression of this distribution is still missing. This fact impairs the accuracy of the current simulation methodology of ad hoc networks and makes it impossible to relate simulation results to analytical results on the properties of adhoc networks. To overcome these problems, we present a detailed analytical study of the node distribution resulting from random waypoint mobility. More specifically, we consider a generalization of the model, in which the pause time of the mobile nodes is chosen arbitrarily in each waypoint and a fraction of nodes may remain static for the entire simulation time. We show that the structure of the resulting distribution is the weighted sum of three independent components: the static, pause, and mobility component. This division enables us to understand how the model\u27s parameters influence the distribution. By describing mobility as a stochastic process, we derive an exact equation of the asymptotically stationary distribution for movement on a line segment, and an accurate approximation for a square area. The good quality of this approximation is validated through simulations with various settings of the mobility parameters

A Statistical Analysis of the Long-Run Node Spatial Distribution in Mobile Ad

In this paper, we analyze the node spatial distribution of mobile wireless ad hoc networks. Characterizing this distribution is of fundamental importance in the analysis of many relevant properties of mobile ad hoc networks, such as connectivity, average route length, and network capacity. In particular, we have investigated under what conditions the node spatial distribution resulting after a large number of mobility steps resembles the uniform distribution. This is motivated by the fact that the existing theoretical results concerning mobile ad hoc networks are based on this as sumption. In order to test this hypothesis, we performed extensive simulations using two well-known mobility models: the random waypoint model, which resembles intentional movement, and a Brownian-like model, which resembles non-intentional movement. Our analysis has shown that in the Brownian-like motion the uniformity assumption does hold,and that the intensity of the concentration of nodes in the center of the deployment region that occurs in the ran dom waypoint model heavily depends on the choice of some mobility parameters. For extreme values of these parameters,the uniformity assumption is impaired

WiQoSM: An Integrated QoS-Aware Mobility and User Behavior Model for Wireless Data Networks

Modeling mobility and user behavior is of fundamental importance in testing the performance of protocols for wireless data networks. While several models have been proposed in the literature, none of them can at the same time capture important features such as geographical mobility, user generated traffic, and wireless technology at hand. When collectively considered, these three aspects determine the user-perceived QoS-level, which, in turn, might have an influence on mobility of those users (we call them QoSdriven users) who do not display constrained mobility patterns, but they can decide to move to less congested areas of the network in case their perceived QoS-level becomes unacceptable. In this paper, we introduce the WiQoSM model which collectively considers all the above mentioned aspects of wireless data networks. WiQoSM is composed of i) a user mobility model, ii) a user traffic model, iii) a wireless technology model, and iv) a QoS model. Components i), ii), and iii) provide input to the QoS model, which, in turn, can influence the mobility behavior of QoS-driven users. WiQoSM is very simple to use and configure, and can be used to generate user and traffic traces at the APs composing a wireless data network. Based on WiQoSM, we perform an extensive simulation-based analysis of network usage under different combinations of network parameters, which discloses interesting insights and shows that WiQoSM, despite its simplicity, is able to capture important properties observed in real-world network deployments

The Effects of Node Cooperation Level on Routing Performance in Delay Tolerant Networks

In this paper, we analyze the effect of different degrees of node cooperation on the performance of routing protocols for delay tolerant networks. We first present an accurate analytical characterization of the performance of epidemic and two-hops routing in terms of expected packet delivery rate under the standard assumption of fully cooperative node behavior. This characterization is itself an interesting result, since it requires accurately approximating the distribution of the packet delivery delay. We then use the results derived in the first part of the paper to analytically characterize epidemic routing protocol performance in presence of different degrees of node cooperation. We also performed extensive simulations for a broader set of routing protocols and cooperation scenarios. The results of our simulations show that, while epidemic routing provides the better PDR performance under all investigated degrees of network cooperation, binary SW routing can achieve comparable performance, while significantly reducing message overhead. Binary SW routing shows also the better resilience to lower node cooperation levels amongst the considered routing protocols. Finally, our results suggest that even a modest level of node cooperation is sufficient to achieve 3-4-fold performance improvement with respect to the most pessimistic scenario in which all potential forwarders drop messages

Quantifying the benefits of vehicle pooling with shareability networks

Taxi services are a vital part of urban transportation, and a considerable contributor to traffic congestion and air pollution causing substantial adverse effects on human health. Sharing taxi trips is a possible way of reducing the negative impact of taxi services on cities, but this comes at the expense of passenger discomfort quantifiable in terms of a longer travel time. Due to computational challenges, taxi sharing has traditionally been approached on small scales, such as within airport perimeters, or with dynamical ad-hoc heuristics. However, a mathematical framework for the systematic understanding of the tradeoff between collective benefits of sharing and individual passenger discomfort is lacking. Here we introduce the notion of shareability network which allows us to model the collective benefits of sharing as a function of passenger inconvenience, and to efficiently compute optimal sharing strategies on massive datasets. We apply this framework to a dataset of millions of taxi trips taken in New York City, showing that with increasing but still relatively low passenger discomfort, cumulative trip length can be cut by 40% or more. This benefit comes with reductions in service cost, emissions, and with split fares, hinting towards a wide passenger acceptance of such a shared service. Simulation of a realistic online system demonstrates the feasibility of a shareable taxi service in New York City. Shareability as a function of trip density saturates fast, suggesting effectiveness of the taxi sharing system also in cities with much sparser taxi fleets or when willingness to share is low.Comment: Main text: 6 pages, 3 figures, SI: 24 page

Analysis of a Wireless Sensors Dropping Problem in Environmental Monitoring

In this paper we study the following problem: we are given a certain region R to monitor and a requirement on the degree of coverage (DoC) of R to meet by a network of deployed sensors. The latter will be dropped by a moving vehicle, which can release sensors at arbitrary points within R. The node spatial distribution when sensors are dropped at a certain points is modeled by a certain probability density function F. The network designer is allowed to choose an arbitrary set of drop points, and to release an arbitrary number of sensors at each point. Given this setting, we consider the problem of determining the optimal deployment strategy, i.e., the drop strategy such that the DoC requirement is fulfilled and the total number of deployed nodes n is minimum. We study this problem both analytically and through simulation, under the assumption that F is the two-dimensional Normal distribution of parameter s (sigma) centered at the drop point. We show that, for given value of s (sigma) and DoC requirement, optimal deployment strategies can be easly identified. The sensor dropping problem studied in this paper is relvant whenever manual node deployment is impossible or overly expensive, and partially controlled deployment (the network designer can choose the drop points, but the final node deployment is random) is the only feasible choice