Performance analysis of contention based bandwidth request mechanisms in WiMAX networks

This article is posted here with the permission of IEEE. The official version can be obtained from the DOI below - Copyright @ 2010 IEEEWiMAX networks have received wide attention as they support high data rate access and amazing ubiquitous connectivity with great quality-of-service (QoS) capabilities. In order to support QoS, bandwidth request (BW-REQ) mechanisms are suggested in the WiMAX standard for resource reservation, in which subscriber stations send BW-REQs to a base station which can grant or reject the requests according to the available radio resources. In this paper we propose a new analytical model for the performance analysis of various contention based bandwidth request mechanisms, including grouping and no-grouping schemes, as suggested in the WiMAX standard. Our analytical model covers both unsaturated and saturated traffic load conditions in both error-free and error-prone wireless channels. The accuracy of this model is verified by various simulation results. Our results show that the grouping mechanism outperforms the no-grouping mechanism when the system load is high, but it is not preferable when the system load is light. The channel noise degrades the performance of both throughput and delay.This work was supported by the U.K. Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/G070350/1 and by the Brunel University’s BRIEF Award

Scheduling with Predictions and the Price of Misprediction

In many traditional job scheduling settings, it is assumed that one knows the time it will take for a job to complete service. In such cases, strategies such as shortest job first can be used to improve performance in terms of measures such as the average time a job waits in the system. We consider the setting where the service time is not known, but is predicted by for example a machine learning algorithm. Our main result is the derivation, under natural assumptions, of formulae for the performance of several strategies for queueing systems that use predictions for service times in order to schedule jobs. As part of our analysis, we suggest the framework of the "price of misprediction," which offers a measure of the cost of using predicted information

Dynamic Vehicle Routing for Data Gathering in Wireless Networks

We consider a dynamic vehicle routing problem in wireless networks where messages arriving randomly in time and space are collected by a mobile receiver (vehicle or a collector). The collector is responsible for receiving these messages via wireless communication by dynamically adjusting its position in the network. Our goal is to utilize a combination of wireless transmission and controlled mobility to improve the delay performance in such networks. We show that the necessary and sufficient condition for the stability of such a system (in the bounded average number of messages sense) is given by {\rho}<1 where {\rho} is the average system load. We derive fundamental lower bounds for the delay in the system and develop policies that are stable for all loads {\rho}<1 and that have asymptotically optimal delay scaling. Furthermore, we extend our analysis to the case of multiple collectors in the network. We show that the combination of mobility and wireless transmission results in a delay scaling of {\Theta}(1/(1- {\rho})) with the system load {\rho} that is a factor of {\Theta}(1/(1- {\rho})) smaller than the delay scaling in the corresponding system where the collector visits each message location.Comment: 19 pages, 7 figure

The multi-state hard core model on a regular tree

The classical hard core model from statistical physics, with activity $\lambda > 0$ and capacity $C=1$, on a graph $G$, concerns a probability measure on the set ${\mathcal I}(G)$ of independent sets of $G$, with the measure of each independent set $I \in {\mathcal I}(G)$ being proportional to $\lambda^{|I|}$. Ramanan et al. proposed a generalization of the hard core model as an idealized model of multicasting in communication networks. In this generalization, the {\em multi-state} hard core model, the capacity $C$ is allowed to be a positive integer, and a configuration in the model is an assignment of states from $\{0,\ldots,C\}$ to $V(G)$ (the set of nodes of $G$) subject to the constraint that the states of adjacent nodes may not sum to more than $C$. The activity associated to state $i$ is $\lambda^{i}$, so that the probability of a configuration $\sigma:V(G)\rightarrow \{0,\ldots, C\}$ is proportional to $\lambda^{\sum_{v \in V(G)} \sigma(v)}$. In this work, we consider this generalization when $G$ is an infinite rooted $b$-ary tree and prove rigorously some of the conjectures made by Ramanan et al. In particular, we show that the $C=2$ model exhibits a (first-order) phase transition at a larger value of $\lambda$ than the $C=1$ model exhibits its (second-order) phase transition. In addition, for large $b$ we identify a short interval of values for $\lambda$ above which the model exhibits phase co-existence and below which there is phase uniqueness. For odd $C$, this transition occurs in the region of \lambda = (e/b)^{1/\ceil{C/2}}, while for even $C$, it occurs around $\lambda=(\log b/b(C+2))^{2/(C+2)}$. In the latter case, the transition is first-order.Comment: Will appear in {\em SIAM Journal on Discrete Mathematics}, Special Issue on Constraint Satisfaction Problems and Message Passing Algorithm

A Stochastic Resource-Sharing Network for Electric Vehicle Charging

We consider a distribution grid used to charge electric vehicles such that voltage drops stay bounded. We model this as a class of resource-sharing networks, known as bandwidth-sharing networks in the communication network literature. We focus on resource-sharing networks that are driven by a class of greedy control rules that can be implemented in a decentralized fashion. For a large number of such control rules, we can characterize the performance of the system by a fluid approximation. This leads to a set of dynamic equations that take into account the stochastic behavior of EVs. We show that the invariant point of these equations is unique and can be computed by solving a specific ACOPF problem, which admits an exact convex relaxation. We illustrate our findings with a case study using the SCE 47-bus network and several special cases that allow for explicit computations.Comment: 13 pages, 8 figure

A non-invasive method for link upgrade planning using coarse-grained measurements

A basic problem faced by network operators concerns the provisioning of bandwidth to meet quality of service (QoS) requirements. In the network core, the preferred solution is simply to overprovision link bandwidth. We propose a new approach to making link upgrade decisions based only on readily available coarse SNMP measurements