Amrinder Arora

Converter placement in wavelength routing mesh topologies

The blocking performance of wavelength routing WDM optical networks can be improved by employing wavelength conversion. In this paper, we address the problem of optimally placing a limited number of wavelength converters in mesh topologies. Two objective functions, namely, minimizing the average blocking probability and minimizing the maximum blocking probability over all routes, are considered. We first extend an earlier analytical model to compute the blocking probability on an arbitrary route in a mesh topology, given the traffic and locations of converters. We then propose heuristic algorithms to place wavelength converters, and evaluate the performance of the proposed heuristics using the analytical model.

Predictive scheduling in multi-carrier wireless networks with link adaptation

Channel-aware scheduling and link adaptation methods are widely considered to be crucial for realizing high data rates in wireless networks. However, predicting future channel states, and adjusting transmission schedules and parameters accordingly, may consume valuable system resources, such as bandwidth, time, and power. The paper considers the trade-offs between prediction quality and throughput in a wireless network that uses link adaptation and channel-aware scheduling. In particular, we study the effects on the throughput of the look-ahead window, i.e., the range of future time slots on which we have channel state estimates, and the reliability of the channel state estimates. We develop an online scheduling algorithm for a multichannel multiuser network that employs predictive link adaptation, and generalize it to incorporate imperfect channel state estimates. We apply this heuristic together with performance bounds to the offline version of the problem to evaluate the performance with varying prediction qualities. Our results suggest that it may be possible to reap most of the potential channel-aware scheduling benefits with a small look-ahead and imperfect channel state estimates. Thus, a modest consumption of resources for channel prediction and link adaptation may result in a significant throughput improvement, with only marginal gains through further enhancement of the prediction quality. Our results can provide meaningful guidelines in deciding what level of system resource consumption is justified for channel quality estimation and link adaptation.

Logical topology design for linear and ring optical networks

The design of logical topologies in wavelength-routing multihop optical networks is a well-studied problem. We consider logical topology (LT) design over the popular ring and linear topologies. Our objective is the minimization of the electronic processing delay for the worst case traffic flow. For uniform traffic between nodes, this delay minimization corresponds to minimizing the number of hops on a shortest path between the farthest two nodes in the logical topology (the diameter of the logical topology). The simple structure of the physical topologies enables us to present a rigorous analysis of the problem. We present lower bounds for the achievable diameter wherever possible and propose practical logical topology design algorithms and corresponding upper bounds. We also present an application of the LT designs in the linear topology to the survivability of ring networks.

Channel-Assignment and Scheduling in Wireless Mesh Networks Considering Switching Overhead

This paper considers the channel-assignment and scheduling in wireless mesh networks that employ multiple radios and multiple channels. In contrast to the various algorithms available in the literature, we explicitly model the delay overhead that is incurred during channel switching, and use that delay in the design of algorithms. We prove that the well known Greedy Maximal Scheduling (GMS) algorithm does not have any provable efficiency ratio when the switching overhead is considered. We present a centralized algorithm (CGSSO), and a dynamic algorithm (DMSSO), both of which consider switching overhead. Simulation results show that the proposed algorithms significantly outperform other algorithms in packet throughput and average packet delay metrics. Results also show that the improvements in performance become more pronounced as the switching delay increases.

Wavelength Conversion Placement in WDM Mesh Optical Networks

Wavelength conversion helps improve the performance of wavelength division multiplexed (WDM) optical networks that employ wavelength routing. In this paper, we address the problem of optimally placing a limited number of wavelength converters in mesh topologies. Two objective functions, namely, minimizing the average blocking probability and minimizing the maximum blocking probability over all routes, are considered. In the first part of the paper, we extend an earlier analytical model to compute the blocking probability on an arbitrary route in a mesh topology, given the traffic and locations of converters. We then propose heuristic algorithms to place wavelength converters, and evaluate the performance of the proposed heuristics using the analytical model. Results suggest that simple heuristics are sufficient to give near-optimal performance.

Routing and packet scheduling in WiMAX mesh networks

This paper considers the problem of maximizing the system throughput in IEEE 802.16 broadband access networks with mesh topology, and the following results are presented. We consider a linear chain network and discuss its applicability for providing cost effective solutions in sparsely populated areas, such as interstate highways and rural communities. We provide an optimal scheduling algorithm and establish an analytical result on the length of the schedule for linear chain networks. We also consider the problem of routing and packet scheduling in general topology, and show its NP-completeness. Based on our optimal algorithm for linear networks, we propose algorithms that find routes and schedules of packet transmissions in general mesh topologies. The performance of our proposed algorithms is analyzed using the NS-2 simulator. The results show that the proposed algorithms perform significantly better than other existing algorithms.

Throughput analysis in wireless networks with multiple users and multiple channels

We consider the problem of maximizing throughput in a multi-carrier wireless network that employs predictive link adaptation. We explicitly consider the time-penalty incurred due to link adaptation. The contributions of this paper are twofold. Firstly, several high performance algorithms (offline and online) are developed for efficient performance in multiple user and multiple channel environment under the practicable lookahead prediction of one time slot. Secondly, the presented algorithms and heuristics are shown to be competitive by deterministic and probabilistic analyses. Our results show that a modest consumption of resources for channel prediction and link adaptation may result in a significant throughput improvement.

The effects of the sub-carrier grouping on multi-carrier channel aware scheduling

This paper studies the effects of the sub-carrier grouping on the scheduling problem in a wireless network with multiple carriers. In particular, the authors consider the trade-offs between the size of the sub-carrier groups and the link throughput for various sub-carrier grouping models, with each corresponding to a different level of CSI tracking and system design complexity. The paper assumes that a single user is communicating with the base station using the entire sub-carriers. This assumption is motivated by the OFDM, which uses multiple carriers in order to benefit from the frequency selective fading introduced by spreading the information bits over the entire signal band. An offline dynamic programming algorithm for finding an optimal solution for the case of spectrum- and time-perfect estimates is also presented. The performance can potentially be improved by using high-level modulation on the sub-carriers with good channel conditions.

Battle event detection using sensor networks and distributed query processing

We consider the problem of identifying battlefield events using sensors deployed in the area. The goal is to alert centralized headquarters about the occurrence of significant events so that it can respond appropriately to the events. We propose a mechanism using which the sensors can exchange information using signatures of events instead of data to save on transmission costs. Further, we propose an algorithm that dynamically generates phases of information exchange based on the cost and selectivity of each filter.We present simulation results that compare the proposed algorithm to other alternatives. Our results show that the proposed algorithm detects events while minimizing the transmission and processing costs at sensors.

Scheduling resource allocation with timeslot penalty for changeover

Given a time slotted list of resource capacities, we address the problem of scheduling resource allocation considering that a change in allocation results in the changeover penalty of one timeslot. The goal is to maximize the overall allocation of resources. We prove that no 1-lookahead algorithm can be better than 8/5-competitive. We provide improved analysis of Wait Dominate Hold (WDH) algorithm that was previously known to be 4-competitive. We prove that WDH is 8/3-competitive. We also consider k-lookahead algorithms, and prove lower bound of (k + 2)/(k + 1) on their competitiveness and give an online algorithm that is 2-competitive.