Throughput Analysis of CSMA Wireless Networks with Finite Offered-load

This paper proposes an approximate method, equivalent access intensity (EAI), for the throughput analysis of CSMA wireless networks in which links have finite offered-load and their MAC-layer transmit buffers may be empty from time to time. Different from prior works that mainly considered the saturated network, we take into account in our analysis the impacts of empty transmit buffers on the interactions and dependencies among links in the network that is more common in practice. It is known that the empty transmit buffer incurs extra waiting time for a link to compete for the channel airtime usage, since when it has no packet waiting for transmission, the link will not perform channel competition. The basic idea behind EAI is that this extra waiting time can be mapped to an equivalent "longer" backoff countdown time for the unsaturated link, yielding a lower link access intensity that is defined as the mean packet transmission time divided by the mean backoff countdown time. That is, we can compute the "equivalent access intensity" of an unsaturated link to incorporate the effects of the empty transmit buffer on its behavior of channel competition. Then, prior saturated ideal CSMA network (ICN) model can be adopted for link throughput computation. Specifically, we propose an iterative algorithm, "Compute-and-Compare", to identify which links are unsaturated under current offered-load and protocol settings, compute their "equivalent access intensities" and calculate link throughputs. Simulation shows that our algorithm has high accuracy under various offered-load and protocol settings. We believe the ability to identify unsaturated links and compute links throughputs as established in this paper will serve an important first step toward the design and optimization of general CSMA wireless networks with offered-load control.Comment: 6 pages. arXiv admin note: text overlap with arXiv:1007.5255 by other author

CapEst: A Measurement-based Approach to Estimating Link Capacity in Wireless Networks

Estimating link capacity in a wireless network is a complex task because the available capacity at a link is a function of not only the current arrival rate at that link, but also of the arrival rate at links which interfere with that link as well as of the nature of interference between these links. Models which accurately characterize this dependence are either too computationally complex to be useful or lack accuracy. Further, they have a high implementation overhead and make restrictive assumptions, which makes them inapplicable to real networks. In this paper, we propose CapEst, a general, simple yet accurate, measurement-based approach to estimating link capacity in a wireless network. To be computationally light, CapEst allows inaccuracy in estimation; however, using measurements, it can correct this inaccuracy in an iterative fashion and converge to the correct estimate. Our evaluation shows that CapEst always converged to within 5% of the correct value in less than 18 iterations. CapEst is model-independent, hence, is applicable to any MAC/PHY layer and works with auto-rate adaptation. Moreover, it has a low implementation overhead, can be used with any application which requires an estimate of residual capacity on a wireless link and can be implemented completely at the network layer without any support from the underlying chipset

Throughput-Optimal Random Access with Order-Optimal Delay

In this paper, we consider CSMA policies for scheduling of multihop wireless networks with one-hop traffic. The main contribution of this paper is to propose Unlocking CSMA (U-CSMA) policy that enables to obtain high throughput with low (average) packet delay for large wireless networks. In particular, the delay under U-CSMA policy becomes order-optimal. For one-hop traffic, delay is defined to be order-optimal if it is O(1), i.e., it stays bounded, as the network-size increases to infinity. Using mean field theory techniques, we analytically show that for torus (grid-like) interference topologies with one-hop traffic, to achieve a network load of $\rho$, the delay under U-CSMA policy becomes $O(1/(1-\rho)^{3})$ as the network-size increases, and hence, delay becomes order optimal. We conduct simulations for general random geometric interference topologies under U-CSMA policy combined with congestion control to maximize a network-wide utility. These simulations confirm that order optimality holds, and that we can use U-CSMA policy jointly with congestion control to operate close to the optimal utility with a low packet delay in arbitrarily large random geometric topologies. To the best of our knowledge, it is for the first time that a simple distributed scheduling policy is proposed that in addition to throughput/utility-optimality exhibits delay order-optimality.Comment: 44 page

Clustered wireless sensor networks

The study of topology in randomly deployed wireless sensor networks (WSNs) is important in addressing the fundamental issue of stochastic coverage resulting from randomness in the deployment procedure and power management algorithms. This dissertation defines and studies clustered WSNs, WSNs whose topology due to the deployment procedure and the application requirements results in the phenomenon of clustering or clumping of nodes. The first part of this dissertation analyzes a range of topologies of clustered WSNs and their impact on the primary sensing objectives of coverage and connectivity. By exploiting the inherent advantages of clustered topologies of nodes, this dissertation presents techniques for optimizing the primary performance metrics of power consumption and network capacity. It analyzes clustering in the presence of obstacles, and studies varying levels of redundancy to determine the probability of coverage in the network. The proposed models for clustered WSNs embrace the domain of a wide range of topologies that are prevalent in actual real-world deployment scenarios, and call for clustering-specific protocols to enhance network performance. It has been shown that power management algorithms tailored to various clustering scenarios optimize the level of active coverage and maximize the network lifetime. The second part of this dissertation addresses the problem of edge effects and heavy traffic on queuing in clustered WSNs. In particular, an admission control model called directed ignoring model has been developed that aims to minimize the impact of edge effects in queuing by improving queuing metrics such as packet loss and wait time