Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using tabu search

Copyright @ 2009 IEEE Computer SocietyThis paper proposes a tabu search (TS) based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the tabu search procedure are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed TS multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

Joint multicast routing and channel assignment in multiradio multichannel wireless mesh networks using simulated annealing

This is the post-print version of the article - Copyright @ 2008 Springer-VerlagThis paper proposes a simulated annealing (SA) algorithm based optimization approach to search a minimum-interference multicast tree which satisfies the end-to-end delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. In the proposed SA multicast algorithm, the path-oriented encoding method is adopted and each candidate solution is represented by a tree data structure (i.e., a set of paths). Since we anticipate the multicast trees on which the minimum-interference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. The techniques for controlling the annealing process are well developed. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed SA based multicast algorithm can produce the multicast trees which have better performance in terms of both the total channel conflict and the tree cost than that of a well known multicast algorithm in wireless mesh networks.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1

Multipath routing for video delivery over bandwidth-limited networks

The delivery of quality video service often requires high bandwidth with low delay or cost in network transmission. Current routing protocols such as those used in the Internet are mainly based on the single-path approach (e.g., the shortest-path routing). This approach cannot meet the end-to-end bandwidth requirement when the video is streamed over bandwidth-limited networks. In order to overcome this limitation, we propose multipath routing, where the video takes multiple paths to reach its destination(s), thereby increasing the aggregate throughput. We consider both unicast (point-to-point) and multicast scenarios. For unicast, we present an efficient multipath heuristic (of complexity O(|V|3)), which achieves high bandwidth with low delay. Given a set of path lengths, we then present and prove a simple data scheduling algorithm as implemented at the server, which achieves the theoretical minimum end-to-end delay. For a network with unit-capacity links, the algorithm, when combined with disjoint-path routing, offers an exact and efficient solution to meet a bandwidth requirement with minimum delay. For multicast, we study the construction of multiple trees for layered video to satisfy the user bandwidth requirements. We propose two efficient heuristics on how such trees can be constructed so as to minimize the cost of their aggregation subject to a delay constraint.published_or_final_versio

Constrained shortest paths for QoS routing and path protection in communication networks.

The CSDP (k) problem requires the selection of a set of k > 1 link-disjoint paths with minimum total cost and with total delay bounded by a given upper bound. This problem arises in the context of provisioning paths in a network that could be used to provide resilience to link failures. Again we studied the LP relaxation of the ILP formulation of the problem from the primal perspective and proposed an approximation algorithm.We have studied certain combinatorial optimization problems that arise in the context of two important problems in computer communication networks: end-to-end Quality of Service (QoS) and fault tolerance. These problems can be modeled as constrained shortest path(s) selection problems on networks with each of their links associated with additive weights representing the cost, delay etc.The problems considered above assume that the network status is known and accurate. However, in real networks, this assumption is not realistic. So we considered the QoS route selection problem under inaccurate state information. Here the goal is to find a path with the highest probability that satisfies a given delay upper bound. We proposed a pseudo-polynomial time approximation algorithm, a fully polynomial time approximation scheme, and a strongly polynomial time heuristic for this problem.Finally we studied the constrained shortest path problem with multiple additive constraints. Using the LARAC algorithm as a building block and combining ideas from mathematical programming, we proposed a new approximation algorithm.First we studied the QoS single route selection problem, i.e., the constrained shortest path (CSP) problem. The goal of the CSP problem is to identify a minimum cost route which incurs a delay less than a specified bound. It can be formulated as an integer linear programming (ILP) problem which is computationally intractable. The LARAC algorithm reported in the literature is based on the dual of the linear programming relaxation of the ILP formulation and gives an approximate solution. We proposed two new approximation algorithms solving the dual problem. Next, we studied the CSP problem using the primal simplex method and exploiting certain structural properties of networks. This led to a novel approximation algorithm

Detection and Mitigation of Impairments for Real-Time Multimedia Applications

Measures of Quality of Service (QoS) for multimedia services should focus on phenomena that are observable to the end-user. Metrics such as delay and loss may have little direct meaning to the end-user because knowledge of specific coding and/or adaptive techniques is required to translate delay and loss to the user-perceived performance. Impairment events, as defined in this dissertation, are observable by the end-users independent of coding, adaptive playout or packet loss concealment techniques employed by their multimedia applications. Methods for detecting real-time multimedia (RTM) impairment events from end-to-end measurements are developed here and evaluated using 26 days of PlanetLab measurements collected over nine different Internet paths. Furthermore, methods for detecting impairment-causing network events like route changes and congestion are also developed. The advanced detection techniques developed in this work can be used by applications to detect and match response to network events. The heuristics-based techniques for detecting congestion and route changes were evaluated using PlanetLab measurements. It was found that Congestion events occurred for 6-8 hours during the days on weekdays on two paths. The heuristics-based route change detection algorithm detected 71\% of the visible layer 2 route changes and did not detect the events that occurred too close together in time or the events for which the minimum RTT change was small. A practical model-based route change detector named the parameter unaware detector (PUD) is also developed in this deissertation because it was expected that model-based detectors would perform better than the heuristics-based detector. Also, the optimal detector named the parameter aware detector (PAD) is developed and is useful because it provides the upper bound on the performance of any detector. The analysis for predicting the performance of PAD is another important contribution of this work. Simulation results prove that the model-based PUD algorithm has acceptable performance over a larger region of the parameter space than the heuristics-based algorithm and this difference in performance increases with an increase in the window size. Also, it is shown that both practical algorithms have a smaller acceptable performance region compared to the optimal algorithm. The model-based algorithms proposed in this dissertation are based on the assumption that RTTs have a Gamma density function. This Gamma distribution assumption may not hold when there are wireless links in the path. A study of CDMA 1xEVDO networks was initiated to understand the delay characteristics of these networks. During this study, it was found that the widely deployed proportional-fair (PF) scheduler can be corrupted accidentally or deliberately to cause RTM impairments. This is demonstrated using measurements conducted over both in-lab and deployed CDMA 1xEVDO networks. A new variant to PF that solves the impairment vulnerability of the PF algorithm is proposed and evaluated using ns-2 simulations. It is shown that this new scheduler solution together with a new adaptive-alpha initialization stratergy reduces the starvation problem of the PF algorithm

Detection and Mitigation of Impairments for Real-Time Multimedia Applications

Measures of Quality of Service (QoS) for multimedia services should focus on phenomena that are observable to the end-user. Metrics such as delay and loss may have little direct meaning to the end-user because knowledge of specific coding and/or adaptive techniques is required to translate delay and loss to the user-perceived performance. Impairment events, as defined in this dissertation, are observable by the end-users independent of coding, adaptive playout or packet loss concealment techniques employed by their multimedia applications. Methods for detecting real-time multimedia (RTM) impairment events from end-to-end measurements are developed here and evaluated using 26 days of PlanetLab measurements collected over nine different Internet paths. Furthermore, methods for detecting impairment-causing network events like route changes and congestion are also developed. The advanced detection techniques developed in this work can be used by applications to detect and match response to network events. The heuristics-based techniques for detecting congestion and route changes were evaluated using PlanetLab measurements. It was found that Congestion events occurred for 6-8 hours during the days on weekdays on two paths. The heuristics-based route change detection algorithm detected 71\% of the visible layer 2 route changes and did not detect the events that occurred too close together in time or the events for which the minimum RTT change was small. A practical model-based route change detector named the parameter unaware detector (PUD) is also developed in this deissertation because it was expected that model-based detectors would perform better than the heuristics-based detector. Also, the optimal detector named the parameter aware detector (PAD) is developed and is useful because it provides the upper bound on the performance of any detector. The analysis for predicting the performance of PAD is another important contribution of this work. Simulation results prove that the model-based PUD algorithm has acceptable performance over a larger region of the parameter space than the heuristics-based algorithm and this difference in performance increases with an increase in the window size. Also, it is shown that both practical algorithms have a smaller acceptable performance region compared to the optimal algorithm. The model-based algorithms proposed in this dissertation are based on the assumption that RTTs have a Gamma density function. This Gamma distribution assumption may not hold when there are wireless links in the path. A study of CDMA 1xEVDO networks was initiated to understand the delay characteristics of these networks. During this study, it was found that the widely deployed proportional-fair (PF) scheduler can be corrupted accidentally or deliberately to cause RTM impairments. This is demonstrated using measurements conducted over both in-lab and deployed CDMA 1xEVDO networks. A new variant to PF that solves the impairment vulnerability of the PF algorithm is proposed and evaluated using ns-2 simulations. It is shown that this new scheduler solution together with a new adaptive-alpha initialization stratergy reduces the starvation problem of the PF algorithm

Timing Closure in Chip Design

Achieving timing closure is a major challenge to the physical design of a computer chip. Its task is to find a physical realization fulfilling the speed specifications. In this thesis, we propose new algorithms for the key tasks of performance optimization, namely repeater tree construction; circuit sizing; clock skew scheduling; threshold voltage optimization and plane assignment. Furthermore, a new program flow for timing closure is developed that integrates these algorithms with placement and clocktree construction. For repeater tree construction a new algorithm for computing topologies, which are later filled with repeaters, is presented. To this end, we propose a new delay model for topologies that not only accounts for the path lengths, as existing approaches do, but also for the number of bifurcations on a path, which introduce extra capacitance and thereby delay. In the extreme cases of pure power optimization and pure delay optimization the optimum topologies regarding our delay model are minimum Steiner trees and alphabetic code trees with the shortest possible path lengths. We presented a new, extremely fast algorithm that scales seamlessly between the two opposite objectives. For special cases, we prove the optimality of our algorithm. The efficiency and effectiveness in practice is demonstrated by comprehensive experimental results. The task of circuit sizing is to assign millions of small elementary logic circuits to elements from a discrete set of logically equivalent, predefined physical layouts such that power consumption is minimized and all signal paths are sufficiently fast. In this thesis we develop a fast heuristic approach for global circuit sizing, followed by a local search into a local optimum. Our algorithms use, in contrast to existing approaches, the available discrete layout choices and accurate delay models with slew propagation. The global approach iteratively assigns slew targets to all source pins of the chip and chooses a discrete layout of minimum size preserving the slew targets. In comprehensive experiments on real instances, we demonstrate that the worst path delay is within 7% of its lower bound on average after a few iterations. The subsequent local search reduces this gap to 2% on average. Combining global and local sizing we are able to size more than 5.7 million circuits within 3 hours. For the clock skew scheduling problem we develop the first algorithm with a strongly polynomial running time for the cycle time minimization in the presence of different cycle times and multi-cycle paths. In practice, an iterative local search method is much more efficient. We prove that this iterative method maximizes the worst slack, even when restricting the feasible schedule to certain time intervals. Furthermore, we enhance the iterative local approach to determine a lexicographically optimum slack distribution. The clock skew scheduling problem is then generalized to allow for simultaneous data path optimization. In fact, this is a time-cost tradeoff problem. We developed the first combinatorial algorithm for computing time-cost tradeoff curves in graphs that may contain cycles. Starting from the lowest-cost solution, the algorithm iteratively computes a descent direction by a minimum cost flow computation. The maximum feasible step length is then determined by a minimum ratio cycle computation. This approach can be used in chip design for several optimization tasks, e.g. threshold voltage optimization or plane assignment. Finally, the optimization routines are combined into a timing closure flow. Here, the global placement is alternated with global performance optimization. Netweights are used to penalize the length of critical nets during placement. After the global phase, the performance is improved further by applying more comprehensive optimization routines on the most critical paths. In the end, the clock schedule is optimized and clocktrees are inserted. Computational results of the design flow are obtained on real-world computer chips

Joint QoS multicast routing and channel assignment in multiradio multichannel wireless mesh networks using intelligent computational methods

Copyright @ 2010 Elsevier B.V. All rights reserved.In this paper, the quality of service multicast routing and channel assignment (QoS-MRCA) problem is investigated. It is proved to be a NP-hard problem. Previous work separates the multicast tree construction from the channel assignment. Therefore they bear severe drawback, that is, channel assignment cannot work well with the determined multicast tree. In this paper, we integrate them together and solve it by intelligent computational methods. First, we develop a unified framework which consists of the problem formulation, the solution representation, the fitness function, and the channel assignment algorithm. Then, we propose three separate algorithms based on three representative intelligent computational methods (i.e., genetic algorithm, simulated annealing, and tabu search). These three algorithms aim to search minimum-interference multicast trees which also satisfy the end-to-end delay constraint and optimize the usage of the scarce radio network resource in wireless mesh networks. To achieve this goal, the optimization techniques based on state of the art genetic algorithm and the techniques to control the annealing process and the tabu search procedure are well developed separately. Simulation results show that the proposed three intelligent computational methods based multicast algorithms all achieve better performance in terms of both the total channel conflict and the tree cost than those comparative references.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) of UK under Grant EP/E060722/1