On the Catalyzing Effect of Randomness on the Per-Flow Throughput in Wireless Networks

This paper investigates the throughput capacity of a flow crossing a multi-hop wireless network, whose geometry is characterized by general randomness laws including Uniform, Poisson, Heavy-Tailed distributions for both the nodes' densities and the number of hops. The key contribution is to demonstrate \textit{how} the \textit{per-flow throughput} depends on the distribution of 1) the number of nodes $N_j$ inside hops' interference sets, 2) the number of hops $K$, and 3) the degree of spatial correlations. The randomness in both $N_j$'s and $K$ is advantageous, i.e., it can yield larger scalings (as large as $\Theta(n)$) than in non-random settings. An interesting consequence is that the per-flow capacity can exhibit the opposite behavior to the network capacity, which was shown to suffer from a logarithmic decrease in the presence of randomness. In turn, spatial correlations along the end-to-end path are detrimental by a logarithmic term

Setting the parameters right for two-hop IEEE 802.11e ad hoc networks

Two-hop ad-hoc networks, in which some nodes forward traffic for multiple sources, with which they also compete for channel access suffer from large queues building up in bottleneck nodes. This problem can often be alleviated by using IEEE 802.11e to give preferential treatment to bottleneck nodes. Previous results have shown that differentiation parameters can be used to allocate capacity in a more efficient way in the two-hop scenario. However, the overall throughput of the bottleneck may differ considerably, depending on the differentiation method used. By applying a very fast and accurate analysis method, based on steady-state analysis of an QBD-type infinite Markov chain, we find the maximum throughput that is possible per differentiation parameter. All possible parameter settings are explored with respect to the maximum throughput conditioned on a maximum buffer occupancy. This design space exploration cannot be done with network simulators like NS2 or Opnet, as each simulation run simply takes to long.\ud The results, which have been validated by detailed simulations, show that by differentiating TXOP it is possible to achieve a throughput that is about 50% larger than when differentiating AIFS and CW_min.\u

Accurate non-intrusive residual bandwidth estimation in WMNs

The multi-access scheme of 802.11 wireless networks imposes difficulties in achieving predictable service quality in multi-hop networks. In such networks, the residual capacity of wireless links should be estimated for resource allocation services such as flow admission control. In this paper, we propose an accurate and non-intrusive method to estimate the residual bandwidth of an 802.11 link. Inputs from neighboring network activity measurements and from a basic collision detection mechanism are fed to the analytical model so that the proposed algorithm calculates the maximum allowable traffic level for this link. We evaluate the efficiency of the method via OPNET simulations, and show that the percent estimation error is significantly lower than two other prominent estimation methods, bounded only between 2.5-7.5%. We also demonstrate that flow admission control is successfully achieved in a realistic WMN scenario. Flow control through our proposed algorithm keeps the unsatisfied traffic demand bounded and at a negligibly low level, which is less than an order of magnitude of the other two methods

A versatile infinite-state Markov reward model to study bottlenecks in 2-hop ad hoc networks

In a 2-hop IEEE 801.11-based wireless LAN, the distributed coordination function (DCF) tends to equally share the available capacity among the contending stations. Recently alternative capacity sharing strategies have been made possible. We propose a versatile infinite-state Markov reward model to study the bottleneck node in a 2-hop IEEE 801.11-based ad hoc network for different adaptive capacity sharing strategies. We use infinite-state stochastic Petri nets (iSPNs) to specify our model, from which the underlying QBD-type Markov-reward models are automatically derived. The impact of the different capacity sharing strategies is analyzed by CSRL model checking of the underlying infinite-state QBD, for which we provide new techniques. Our modeling approach helps in deciding under which circumstances which adaptive capacity sharing strategy is most appropriate

A Lightweight Distributed Solution to Content Replication in Mobile Networks

Performance and reliability of content access in mobile networks is conditioned by the number and location of content replicas deployed at the network nodes. Facility location theory has been the traditional, centralized approach to study content replication: computing the number and placement of replicas in a network can be cast as an uncapacitated facility location problem. The endeavour of this work is to design a distributed, lightweight solution to the above joint optimization problem, while taking into account the network dynamics. In particular, we devise a mechanism that lets nodes share the burden of storing and providing content, so as to achieve load balancing, and decide whether to replicate or drop the information so as to adapt to a dynamic content demand and time-varying topology. We evaluate our mechanism through simulation, by exploring a wide range of settings and studying realistic content access mechanisms that go beyond the traditional assumptionmatching demand points to their closest content replica. Results show that our mechanism, which uses local measurements only, is: (i) extremely precise in approximating an optimal solution to content placement and replication; (ii) robust against network mobility; (iii) flexible in accommodating various content access patterns, including variation in time and space of the content demand.Comment: 12 page

Performance modeling of a bottleneck node in an IEEE 802.11 ad-hoc network

This paper presents a performance analysis of wireless ad-hoc networks, with IEEE 802.11 as the underlying Wireless LAN technology. WLAN has, due to the fair radio resource sharing at the MAC-layer, the tendency to share the capacity equally amongst the active nodes, irrespective of their loads. An inherent drawback of this sharing policy is that a node that serves as a relay-node for multiple flows is likely to become a bottleneck. This paper proposes to model such a bottleneck by a fluid-flow model. Importantly, this is a model at the flow-level: flows arrive at the bottleneck node, and are served according to the sharing policy mentioned above. Assuming Poisson initiations of new flow transfers, we obtain insightful, robust, and explicit expressions for characteristics related to the overall flow transfer time, the buffer occupancy, and the packet delay at the bottleneck node. The analysis is enabled by a translation of the buffer dynamics at the bottleneck node in terms of an M/G/1 queueing model. We conclude the paper by an assessment of the impact of alternative sharing policies (which can be obtained by the IEEE 802.11E version), in order to improve the performance of the bottleneck

SDDV: scalable data dissemination in vehicular ad hoc networks

An important challenge in the domain of vehicular ad hoc networks (VANET) is the scalability of data dissemination. Under dense traffic conditions, the large number of communicating vehicles can easily result in a congested wireless channel. In that situation, delays and packet losses increase to a level where the VANET cannot be applied for road safety applications anymore. This paper introduces scalable data dissemination in vehicular ad hoc networks (SDDV), a holistic solution to this problem. It is composed of several techniques spread across the different layers of the protocol stack. Simulation results are presented that illustrate the severity of the scalability problem when applying common state-of-the-art techniques and parameters. Starting from such a baseline solution, optimization techniques are gradually added to SDDV until the scalability problem is entirely solved. Besides the performance evaluation based on simulations, the paper ends with an evaluation of the final SDDV configuration on real hardware. Experiments including 110 nodes are performed on the iMinds w-iLab.t wireless lab. The results of these experiments confirm the results obtained in the corresponding simulations