Sudheendra Murthy

Region-based connectivity - a new paradigm for design of fault-tolerant networks

The studies in fault-tolerance in networks mostly focus on the connectivity of the graph as the metric of faulttolerance. If the underlying graph is k-connected, it can tolerate up to k — 1 failures. In measuring the fault tolerance in terms of connectivity, no assumption regarding the locations of the faulty nodes are made - the failed nodes may be close to each other or far from each other. In other words, the connectivity metric has no way of capturing the notion of locality of faults. However in many networks, faults may be highly localized. This is particularly true in military networks, where an enemy bomb may inflict massive but localized damage to the network. To capture the notion of locality of faults in a network, a new metric region-based connectivity (RBC) was introduced in [1]. It was shown that RBC can achieve the same level of fault-tolerance as the metric connectivity, with much lower networking resources. The study in [1] was restricted to single region fault model (SRFM), where faults are confined to one region only. In this paper, we extend the notion of RBC to multiple region fault model (MRFM), where faults are no longer confined to a single region. As faults in MRFM are still confined to regions, albeit multiple of them, it is different from unconstrained fault model where no constraint on locality of faults is imposed. The MRFM leads to several new concepts, such as region-disjoint paths and region cuts. We show that the classical result, the maximum number of node-disjoint paths between a pair of nodes is equal to the minimum number of nodes whose removal disconnects the pair, is no longer valid when region-disjoint paths and region cuts are considered. We prove that the problems of finding (i) the maximum number of region-disjoint paths between a pair of nodes, and (ii) minimum number of regions whose removal disconnect a pair of nodes, are both NP-complete. We provide heuristic solution to these two problems and evaluate their efficacy by comparing the results with optimal solutions.

On Sparse Placement of Regenerator Nodes in Translucent Optical Network

Since the optical reach (the distance an optical signal can travel before its quality degrades to a level that necessitates regeneration) ranges from 500 to 2000 miles, regeneration of optical signals is essential to establish lightpaths of lengths greater than the optical reach. In a translucent optical network, the optical signal is regenerated at selected nodes of the network before the signal quality degrades below a threshold. Given the optical reach of the signal, to minimize the overall network design cost, the goal of the regenerator placement problem is to find the minimum number of regenerators necessary in the network, so that every pair of nodes is able to establish a lightpath (either transparent or translucent) between them. In this paper, we study the regenerator placement problem and prove that the problem is NP-complete. We formulate the regenerator placement problem as a connected dominating set problem in a labeled graph (LCDS) and provide a procedure for computing it. We evaluate the effectiveness of our approach using a number of networks.

An Interference-Aware Channel Assignment Scheme for Wireless Mesh Networks

Multichannel communication in a wireless mesh network with routers having multiple radio interfaces significantly enhances the network capacity. Efficient channel assignment and routing is critical for realization of optimal throughput in such networks. In this paper, we investigate the problem of finding the largest number of links that can be activated simultaneously in a wireless mesh network subject to interference, radio and connectivity constraints. Our goal is to activate all such links and we present an interference aware channel assignment algorithm that realizes this goal. We show that the Link Interference Graph created by utilizing a frequently used interference model gives rise to a special class of graphs, known as overlapping double-disk (ODD) graphs. We prove that the Maximum Independent Set computation problem is NP-complete for this special class of graphs. We provide a Polynomial Time Approximation Scheme (PTAS) for computation of the Maximum Independent Set of an ODD graph. We use this PTAS to develop a channel assignment algorithm for a multiradio multichannel Wireless Mesh Network. We evaluate the performance of our channel assignment algorithm by comparing it with the optimal solution obtained by solving an integer linear program. Experimental results demonstrate that our channel assignment algorithm produces near optimal solution in almost all instances of the problem.

Improved Path Selection Algorithms for Multipath Video Streaming in Wireless Ad-Hoc Networks

In a recent paper, Wei and Zakhor [1] presented a novel multipath selection framework for streaming video over wireless ad-hoc networks. We point out some limitations of their approach and suggest techniques to overcome those limitations. We propose that different metrics for multipath computation should be used when different schemes (e.g., Multiple Description Coding and Layered Coding) are used for video encoding. We adopt a more practical measurement technique for predicting the quality of a link. In addition to analytical reasoning for improved performance of our techniques, we conduct extensive experimentation to evaluate the efficacy of our approach. The results demonstrate that our approach leads to significantly better performance when compared to the approach proposed in [1].

Dynamic Lightpath Allocation in Translucent WDM Optical Networks

The optical reach (the distance an optical signal can travel before the signal quality degrades to a level that necessitates regeneration) ranges from 500 to 2000 miles. To establish a lightpath of length greater than the optical reach, it is necessary to regenerate optical signals. In a translucent optical network, there are regeneration points, where the signal undergoes Optical-Electronic-Optical (O-E-O) conversion. In this paper we have proposed routing algorithms for translucent networks in a dynamic lightpath allocation environment in which requests for communication arrive continuously. In response to each request for communication, the objective is to establish, if possible, a path, from the source to the destination of the request for communication, so that a lightpath may be established, using the path that requires the fewest stages of regeneration. In practical transparent networks, a lightpath must satisfy the wavelength continuity constraint. However, in a translucent network, this constraint can be relaxed at the regeneration points. We have proposed an Integer Linear Program, to give the optimum results for small networks, as well as an efficient heuristic for this problem that works for larger networks. We have evaluated the heuristic through extensive simulations to establish that the heuristic produces close-to-optimal solutions in a fraction of the time needed for the optimal solutions. Our extensive evaluations demonstrate the relative impact of a set of network resources, such as (i) the number of regenerators, (ii) the optical reach of the regenerators and (iii) the number of wavelengths, on the network performance, measured in terms of the call blocking probability. To the best of our knowledge this is the first study that undertakes such an evaluation for translucent networks.

Coverage and connected coverage problems for sensors embedded in a temperature-sensitive environment

Several issues are encountered during deployment of bio-sensors in a human or animal body. Radio transmitters during operation dissipate energy and raise the temperature of its surroundings. A temperature-sensitive environment, such as the human body, can tolerate such increase in temperature only up to a certain threshold value, beyond which serious injury may result. To avoid such injury, the sensor placement must be carried out in a way that ensures the surrounding area temperature remains within the threshold. Using a thermal model for heat distribution from multiple heat sources (radio transmitters), we observed that if the sensor nodes are placed sufficiently apart from each other, then the temperature of the surrounding area does not exceed the threshold. This minimum separation distance constraint gives rise to a new variation of the sensor coverage problem.

Coverage Problem for Sensors Embedded in Temperature Sensitive Environments

The coverage and connectivity problem in sensor networks has received significant attention of the research community in the recent years. In this paper, we study this problem for sensors deployed in temperature sensitive environments. This paper is motivated by the issues encountered during deployment of bio-sensors in a human/animal body. Radio transmitters during operation dissipate energy and raise the temperature of its surroundings. A temperature sensitive environment like the human body can tolerate such increase in temperature only up to a certain threshold value, beyond which serious injury may occur. To avoid such injuries, the sensor placement must be carried out in a way that ensures the surrounding temperature to remain within the threshold. Using a thermal model for heat distribution from multiple heat sources (radio transmitters), we observed that if the sensor nodes are placed sufficiently apart from each other, then the temperature of the surrounding area does not exceed the threshold. This minimum separation distance constraint gives rise to a new version of the sensor coverage problem that has not been studied earlier. We prove that both the optimization version and the feasibility version of the new problem are NP-complete. We further show that an epsiv-approximation algorithm for the problem cannot exist unless P = NP. We provide two heuristic solutions for the problem and evaluate the efficacy of these solutions by comparing their performances against the optimal solution. The simulation results show that our heuristic solutions almost always find near optimal solution in a fraction of the time needed to find the optimal solution. Finally, an algorithm for forming a connected sensor network with minimum transmission power in such a scenario is provided.

Interference-aware multicasting in wireless mesh networks

Multicasting is one of the most important applications in Wireless Ad hoc Networks and the currently emerging Wireless Mesh Networks. In such networks, interference due to the shared wireless medium is a prime factor in determining the data rate achievable by a multicast application. In this research work, we present an interference-aware multicast routing algorithm that takes into account the effects of interference to determine the maximum bandwidth multicast structure. We characterize the problem of computing maximum bandwidth multicast structure as a graph problem of finding minimum degree weakly induced subgraph in a graph subject to the connectivity and interference constraints. We establish the intractability of the problem and provide efficient heuristic that performs close to the optimal in most of the cases. We also present the design of a more practical distributed algorithm. The simulation results demonstrate the benefits of our heuristic over Shortest Path Tree and Minimum Steiner Tree approximation algorithms.

On multipath routing with transit hubs

Empirical studies report frequent occurrences of path failure in the Internet. In providing resilience to such failures, we propose the computation of alternate backup end-to-end path that is disjoint to the default IP path. This disjoint path is created using transit hubs that can be located at diverse points in the Internet. Transit hubs provide better utilization of network resources. Assuming an IP layer routing between any two nodes, we show that the problem of computing such a disjoint path is NP-complete. We present an exact and a heuristic solution for the problem. Using routing data obtained from PlanetLab, we evaluate the efficacy of our heuristic solution.

On a fault-tolerant resource allocation scheme for revenue maximization in data centers

2011 has been the “Year of the Cloud” as organizations around the world have started migrating their services and applications to large-scale data center infrastructures. A large-scale data center experiences random failures of several hardware components every day. These hardware failures present challenging issues in providing reliable service to the end users. The notion of fault domains captures the effect of single hardware failures in data centers. In this paper, we use the concept of fault domains and investigate the problem of revenue maximization in fault-tolerant resource allocation in large data centers. We provide a novel formulation of the problem and prove that this problem is NP-complete. We provide optimal solution technique through Integer Linear Program formulation and present an efficient heuristic that produces near-optimal solution in a fraction of time required to compute the optimal. Through extensive experimentation, we prove the efficacy of our heuristics.