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Topology control, wherein nodes adjust their transmission ranges to conserve energy and reduce interference, is an important feature in wireless ad hoc networks. Contrary to most of the literature on topology control which focuses on reducing energy consumption, in this paper we tackle the topology control problem with the goal of limiting interference as much as possible, while keeping the communication graph connected with high probability. Our approach is based on the principle of maintaining the number of physical neighbors of every node equal to or slightly below a specific value k. As we will discuss in this paper, having a nontrivially bounded physical node degree allows a network topology with bounded interference to be generated. The proposed 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 both theoretically and through simulation. We then define k-NEIGH, a fully distributed, asynchronous, and localized protocol that uses distance estimation. k-NEIGH guarantees logarithmically bounded physical degree at every node, is the most efficient known protocol (requiring 2n messages in total, where n is the number of nodes in the network), and relies on simpler assumptions than existing protocols. Furthermore, we verify through simulation that the network topologies produced by k-NEIGH show good performance in terms of node energy consumption and expected interference

In this paper, we consider how proportional fairness in wireless networks is impacted by spatial reuse and the interference it produces. We observe that, in scenarios where spatial reuse is possible (e.g., in high-density WLAN environments), the classic notion of time-based proportional fairness can be severely impacted: some users might experience very large interference penalties while other users might get larger bandwidth proportions than what they would have received with time-based proportional fairness and no spatial reuse. To account for this, we introduce the concept of inter\-ference-aware STDMA time-based proportional fairness ($i$-STPF), and compare it to ordinary STDMA time-based proportional fairness (STPF). We present the $\epsilon i$-STPF scheduling algorithm, and prove that it approximates the time-based fair bandwidth allocation (up to a small positive constant $\epsilon$), while providing an aggregate throughput that is within a constant factor from optimal. We also present a heuristic $i$-STPF scheduling algorithm and compare it through simulation to a similar heuristic STPF scheduler, and to an interference-aware, rate-based scheduler. The results show that the i-STPF scheduler achieves excellent aggregate throughput while maintaining a close approximation to time-based fairness without interference.

International audience; In this paper, we tackle the problem of designing a random mobility model generating a target node spatial distribution. More specifically, we solve a long standing open problem by presenting two versions of the well-known random waypoint (RWP) mobility model in bounded regions generating a uniform steady-state node spatial distribution. In the first version, named temporal-RWP, we exploit the temporal dimension of node mobility and achieve uniformity by continuously changing the speed of a mobile node as a function of its location and of the density function of trajectories in the movement region R. In the second version, named spatial-RWP, we instead exploit the spatial dimension and achieve uniformity by selecting waypoints according to a suitably defined mix of probability density functions. Both proposed models can be easily incorporated in wireless network simulators, and are thus of practical use. The RWP models presented in this paper allow for the first time completely removing the well-known border effect causing possible inaccuracies in mobile network simulation, thus completing the picture of a "perfect" simulation methodology drawn in existing literature.

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.

A MIMO network is a wireless network made up of individual MIMO links. The problem we consider is to maximize throughput in a multihop MIMO network with interference suppression. Our problem formulation accounts for variable rates on the MIMO links, which depend on the channel conditions of the link, and the manner in which the diversity-multiplexing trade-off is handled. We present an ILP formulation of the MIMO one-shot scheduling problem with variable rates, which is the first exact formulation of a MIMO network optimization problem that accounts for full interference suppression capabilities of MIMO links. We use CPLEX to evaluate the optimal solution based on the ILP formulation for wireless networks with up to 32 concurrently transmitting links. We also modify a heuristic algorithm from a related MIMO scheduling problem to work in our problem setting. Results show that the heuristic can scale to networks with 80 or more concurrent links, but is 10–20% from optimal in terms of throughput. We show that the heuristic scheduler is not able to fully exploit the diversity-multiplexing-interference suppression tradeoff, which is inherent in the problem. This shows that there is substantial room for developing improved scheduling algorithms for MIMO networks and provides some insight into promising directions to explore.

One way in which wireless nodes can organize themselves into an ad hoc network is to execute a topology control protocol, which is designed to build a network satisfying specific properties. A number of basic topology control protocols exist and have been extensively analyzed. Unfortunately, most of these protocols are designed primarily for static networks and the protocol designers simply advise that the protocols should be repeated periodically to deal with failures, mobility, and other sources of dynamism. However, continuously maintaining a network topology with basic connectivity properties is a fundamental requirement for overall network dependability. Current approaches consider failures only as an afterthought or take a static fault tolerance approach, which results in extremely high energy usage and low throughput. In addition, most of the existing topology control protocols assume that transmission power is a continuous variable and, therefore, nodes can choose an arbitrary power value between some minimum and maximum powers. However, wireless network interfaces with dynamic transmission power control permit the power to be set to one of a discrete number of possible values. This simple restriction complicates the design of the topology control protocol substantially. In this paper, we present a set of topology control protocols, which work with discrete power levels and for which we specify a version that deals specifically with dynamic networks that experience failures, mobility, and other dynamic conditions. Our protocols are also novel in the sense that they are the first to consider explicit coordination between neighboring nodes, which results in more efficient power settings. In this paper, we present the design of these topology control protocols, and we report on extensive simulations to evaluate them and compare their performance against existing protocols. The results demonstrate that our protocols produce very similar topologies as the best protocols that assume power is a continuous variable, while having very low communication cost and seamlessly handling failures and mobility.

In this paper, we consider the classical problem of link scheduling in wireless networks under an accurate interference model, in which correct packet reception at a receiver node de- pends on the signa-to-interference-plus-noise ratio (SINR). While most previous work on wireless networks has addressed the sched- uling problem using simplistic graph-based or distance-based interference models, a few recent papers have investigated sched- uling with SINR-based interference models. However, these papers have either used approximations to the SINR model or have ignored important aspects of the problem. We study the problem of wireless link scheduling under the exact SINR model and present the first known true approximation algorithms for transmission scheduling under the exact model. We also introduce an algorithm with a proven approximation bound with respect to the length of the optimal schedule under primary interference. As an aside, our study identifies a class of "difficult to schedule" links, which hinder the derivation of tighter approximation bounds. Furthermore, we characterize conditions under which scheduling under SINR-based interference is within a constant factor from optimal under primary interference, which implies that secondary interference only degrades performance by a constant factor in these situations

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.

Congestion is expected to become a prominent problem to deal with as the popularity of wireless data networks continues to increase. However, this problem can in principle be mitigated if a fraction of the network users could decide to move to another location in case their perceived QoS degrades. To account for this, we propose an extension of the well-known RWP model called QoS-RWP, in which users are divided into mobile users displaying constrained movement patterns, and QoS-driven users who are mainly stationary, but they can decide to move to a better location to improve their QoS level. Another enhancement of QoS-RWP with respect to the original RWP model is that waypoints are chosen according to an access point (AP) popularity metric, which reflects the recently observed phenomenon that different APs in a wireless data network display very different degrees of popularity among users. The QoS-RWP model also accounts for different classes of load offered to the network by the users, and for different channel access methods. Based on QoS-RWP, we perform a simulation-based analysis of network usage under different combinations of network parameters such as the number of users, number of APs, relative fraction of QoS-driven users, and channel access method. Our investigation discloses interesting insights on network usage, and shows that our model is able to capture important properties observed in real-world network deployments.

We study the problem of building and maintaining a network topology with certain desirable features in a wireless multi-hop network where nodes behave as selfish agents. We first provide examples showing that existing topology control approaches are not resilient to strategic node behavior, indicating the need to consider possible selfish node behavior at the design stage. To this end, we propose a general framework that can be used as a guideline in the design of incentive compatible topology control protocols. As an example of how to apply our framework to specific topology control protocols, we present an incentive compatible distributed algorithm for building the minimum spanning tree (MST), which is a very well-known topology control approach. We test the economic validity of our protocol through simulation of wireless networks under various advanced signal loss models on the physical layer. To the best of our knowledge, this is the first incentive compatible realization of topology control presented in the literature.