Heuristic algorithms for multiconstrained quality-of-servicerouting

Multiconstrained quality-of-service (QoS) routing deals with finding routes that satisfy multiple independent QoS constraints. This problem is NP-hard. Two heuristics, the limited granularity heuristic and the limited path heuristic, are investigated. Both heuristics extend the Bellman-Ford shortest path algorithm and solve general k-constrained QoS routing problems. Analytical and simulation studies are conducted to compare the time/space requirements of the heuristics and the effectiveness of the heuristics in finding paths that satisfy the QoS constraints. The major results of this paper are the following. For an N-nodes and E-edges network with k (a small constant) independent QoS constraints, the limited granularity heuristic must maintain a table of size O(|N|^k-1) in each node to be effective, which results in a time complexity of O(|N|^k|E|), while the limited path heuristic can achieve very high performance by maintaining O(|N|² lg(|N|)) entries in each node. These results indicate that the limited path heuristic is relatively insensitive to the number of constraints and is superior to the limited granularity heuristic in solving k-constrained QoS routing problems when k>3     

Routing to Multiple Destinations in Computer Networks

Algorithms for effectively routing messages from a source to multiple destination nodes in a store-and-forward computer network are studied. The focus is on minimizing the network cost (NC), which is the sum of weights of the links in the routing path. Several heuristic algorithms are studied for finding the NC minimum path (which is an NP-complete problem). Among them are variations of a minimum spanning tree (MST) heuristic and heuristics for the traveling salesman problem, both of which use global network information. Another set of heuristics examined are based on using only the shortest paths to the destinations. While the MST algorithm has the best worst case performance among all algorithms, a detailed, empirical study of the "average" performance of the algorithms on typical, randomly chosen networks reveals that simpler heuristics are almost as effective. The NC cost measure is also compared to the destination cost (DC), which is the sum of weights of the shortest path distances to all destinations. A scheme of algorithms is given which trades off between NC and DC.     

A sustainable heuristic QoS routing algorithm for pervasive multi-layered satellite wireless networks

Due to the recent developments in wireless technology and electronics, it is feasible to develop pervasive algorithms for satellite environments. Multi-Layered Satellite Networks (MLSNs) that consist of low earth orbit and medium earth orbit satellites are becoming increasingly important since they have higher coverage and better service than single-layered satellite networks. One of the challenges in MLSNs is the development of specialized and efficient routing algorithms. In this paper, we improved the virtual topology strategy and import heuristic algorithm to satisfy the QoS requirements of the MLSN users. The QoS requirements include end to end delay; link utilization, bandwidth, and package loss rate are mainly focused in this paper. To satisfy the QoS requirements is a multi-parameter optimization problem, and it is convinced as a Non-deterministic Polynomial Complete problem already. As a solution, three typical heuristic algorithms—Ant Colony Algorithm, Taboo Search Algorithm and Genetic Algorithm are applied in the routing scheme in order to reduce package loss, link congestion and call blocking. Simulation results show that heuristic routing algorithm can provide more QoS guarantees than shortest path first algorithm on package loss rate, link congestion and call blocking.     

Two Techniques for Fast Computation of Constrained Shortest Paths

Computing constrained shortest paths is fundamental to some important network functions such as QoS routing, MPLS path selection, ATM circuit routing, and traffic engineering. The problem is to find the cheapest path that satisfies certain constraints. In particular, finding the cheapest delay-constrained path is critical for real-time data flows such as voice/video calls. Because it is NP-complete, much research has been designing heuristic algorithms that solve the epsiv-approximation of the problem with an adjustable accuracy. A common approach is to discretize (i.e., scale and round) the link delay or link cost, which transforms the original problem to a simpler one solvable in polynomial time. The efficiency of the algorithms directly relates to the magnitude of the errors introduced during discretization. In this paper, we propose two techniques that reduce the discretization errors, which allows faster algorithms to be designed. Reducing the overhead of computing constrained shortest paths is practically important for the successful design of a high-throughput QoS router, which is limited at both processing power and memory space. Our simulations show that the new algorithms reduce the execution time by an order of magnitude on power-law topologies with 1000 nodes. The reduction in memory space is similar.     

Tabu search based algorithms for bandwidth-delay-constrained least-cost multicast routing

The advent of various real-time multimedia applications in high-speed networks creates a need for quality of service (QoS) based multicast routing. The Steiner tree problem, is a well-known NP-complete problem, provides the mathematical structure behind multicast communications. Two important QoS constraints are the bandwidth constraint and the end-to-end delay constraint. In this paper, we propose various algorithms to solve the bandwidth-delay-constrained least-cost multicast routing problem based on Tabu Search (TS), addressing issues of the selected initial solution and move type as two major building blocks in short-term memory version of Tabu Search and longer-term memory with associated intensification and diversification strategies as advanced Tabu Search techniques. We evaluate the performance and efficiency of the proposed TS-based algorithms in comparison with other existing TS-based algorithms and heuristics on a variety of random generated networks with regard to total tree cost. Finally we identify the most efficient algorithm uncovered by our testing.     

QoS multicast routing scheme using QGA in IP/DWDM networks

This article studies multi-constraints least-cost multicast routing problem in internet protocol over dense wavelength division multiplexing （IP/DWDM） networks. To address this problem, an individual-difference-based quantum genetic algorithm （IDQGA） is proposed. This algorithm considers individual differences among chromosomes by introducing an adaptive rotation angle step determination scheme and a grouping-based quantum mutation operation. Simulations are conducted over network topologies. The results indicate that compared with other heuristic algorithms, IDQGA has better optimal performance on solving quality of service （QoS） multicast routing problem in IP/DWDM networks and is characterized by strong robustness, high success ratio and excellent capability on global searching.     

Multicast routing and wavelength assignment with delay constraint in WDM networks with sparse wavelength conversions

With the developments in multimedia and other real-time group applications, the question of how to establish multicast trees satisfying Quality-of-Service (QoS) requirements is becoming a very important problem. In this paper, multicast routing and wavelength assignment with delay constraint (MCRWA-DC) in wavelength division multiplexing (WDM) networks with sparse wavelength conversions is studied. We propose a colored multigraph model for the temporarily available wavelengths. Based on this colored multigraph model, two heuristic algorithms are proposed to solve the MCRWA-DC problem. The proposed algorithms have the following advantages:(1) finish multicast routing and wavelength assignment in one step; (2) the total cost of the multicast tree is low; (3) the delay from the source node to any multicast destination node is bounded; and (4) locally minimize the number of wavelength conversions and the number of different wavelengths used to satisfy a multicast request. Simulation results show that the proposed algorithms work well and achieve satisfactory blocking probability.     

Distributed algorithms for multicast path setup in data networks

Establishing a multicast tree in a point-to-point network of switch nodes, such as a wide-area asynchronous transfer mode (ATM) network, can be modeled as the NP-complete Steiner problem in networks. In this paper, we introduce and evaluate two distributed algorithms for finding multicast trees in point-to-point data networks. These algorithms are based on the centralized Steiner heuristics, the shortest path heuristic (SPH) and the Kruskal-based shortest path heuristic (K-SPH), and have the advantage that only the multicast members and nodes in the neighborhood of the multicast tree need to participate in the execution of the algorithm. We compare our algorithms by simulation against a baseline algorithm, the pruned minimum spanning-tree heuristic that is the basis of many previously published algorithms for finding multicast trees. Our results show that the competitiveness (the ratio of the sum of the heuristic tree's edge weights to that of the best solution found) of both of our algorithms was, on the average, 25% better in comparison to that of the pruned spanning-tree approach. In addition, the competitiveness of our algorithms was, in almost all cases, within 10% of the best solution found by any of the Steiner heuristics considered, including both centralized and distributed algorithms. Limiting the execution of the algorithm to a subset of the nodes in the network results in an increase in convergence time over the pruned spanning-tree approach, but this overhead can be reduced by careful implementation     

A new delay‐constrained algorithm for multicast routing tree construction

New multimedia applications provide guaranteed end‐to‐end quality of service (QoS) and have stringent constraints on delay, delay‐jitter, bandwidth, cost, etc. The main task of QoS routing is to find a route in the network, with sufficient resources to satisfy the constraints. Most multicast routing algorithms are not fast enough for large‐scale networks and where the source node uses global cost information to construct a multicast tree. We propose a fast and simple heuristic algorithm (EPDT) for delay‐constrained routing problem for multicast tree construction. This algorithm uses a greedy strategy based on shortest‐path and minimal spanning trees. It combines the minimum cost and the minimum radius objectives by combining respectively optimal Prim's and Dijkstra's algorithms. It biases routes through destinations. Besides, it uses cost information only from neighbouring nodes as it proceeds, which makes it more practical, from an implementation point of view. Copyright © 2004 John Wiley & Sons, Ltd.     

QoS multicast routing by using multiple paths/trees in wireless ad hoc networks

In this paper, we investigate the issues of QoS multicast routing in wireless ad hoc networks. Due to limited bandwidth of a wireless node, a QoS multicast call could often be blocked if there does not exist a single multicast tree that has the requested bandwidth, even though there is enough bandwidth in the system to support the call. In this paper, we propose a new multicast routing scheme by using multiple paths or multiple trees to meet the bandwidth requirement of a call. Three multicast routing strategies are studied, SPT (shortest path tree) based multiple-paths (SPTM), least cost tree based multiple-paths (LCTM) and multiple least cost trees (MLCT). The final routing tree(s) can meet the user’s QoS requirements such that the delay from the source to any destination node shall not exceed the required bound and the aggregate bandwidth of the paths or trees shall meet the bandwidth requirement of the call. Extensive simulations have been conducted to evaluate the performance of our three multicast routing strategies. The simulation results show that the new scheme improves the call success ratio and makes a better use of network resources.     

An overview of quality of service routing for next-generationhigh-speed networks: problems and solutions

The upcoming gigabit-per-second high-speed networks are expected to support a wide range of communication-intensive real-time multimedia applications. The requirement for timely delivery of digitized audio-visual information raises new challenges for next-generation integrated services broadband networks. One of the key issues is QoS routing. It selects network routes with sufficient resources for the requested QoS parameters. The goal of routing solutions is twofold: (1) satisfying the QoS requirements for every admitted connection, and (2) achieving global efficiency in resource utilization. Many unicast/multicast QoS routing algorithms have been published, and they work with a variety of QoS requirements and resource constraints. Overall, they can be partitioned into three broad classes: (1) source routing, (2) distributed routing, and (3) hierarchical routing algorithms. We give an overview of the QoS routing problem as well as the existing solutions. We present the strengths and weaknesses of different routing strategies, and outline the challenges. We also discuss the basic algorithms in each class, classify and compare them, and point out possible future directions in the QoS routing area     

QoS routing in networks with inaccurate information: theory andalgorithms

This paper investigates the problem of routing flows with quality-of-service (QoS) requirements through one or more networks, when the information available for making such routing decisions is inaccurate. Inaccuracy in the information used in computing QoS routes, e.g., network state such as link and node metrics, arises naturally in a number of different environments that are reviewed in the paper. The goal is to determine the impact of such inaccuracy on the ability of the path-selection process to successfully identify paths with adequate available resources. In particular, we focus on devising algorithms capable of selecting path(s) that are most likely to successfully accommodate the desired QoS, in the presence of uncertain network state information for the purpose of the analysis, we assume that this uncertainty is expressed through probabilistic models, and we briefly discuss sample cases that can give rise to such models. We establish that the impact of uncertainty is minimal for flows with only bandwidth requirements, but that it makes path selection intractable when end-to-end delay requirements are considered. For this latter case, we provide efficient solutions for special cases of interest and develop useful heuristics     

Multi‐hour design of survivable classical IP networks

Most of Internet intra‐domain routing protocols (OSPF, RIP, and IS–IS) are based on shortest path routing. The path length is defined as the sum of metrics associated with the path links. These metrics are often managed by the network administrator. In this context, the design of an Internet backbone network consists in dimensioning the network (routers and transmission links) and establishing the metric. Many requirements have to be satisfied. First, Internet traffic is not static as significant variations can be observed during the day. Second, many failures can occur (cable cuts, hardware failures, software failures, etc.). In this paper, we present algorithms (meta‐heuristics and greedy heuristic) to design Internet backbone networks, taking into account the multi‐hour behaviour of traffic and some survivability requirements. Many multi‐hour and protection strategies are studied and numerically compared in this paper. Our algorithms can be extended to integrate other quality of service constraints. Copyright © 2002 John Wiley & Sons, Ltd.     

A DISTRIBUTED QOS ROUTING BASED ON ANT ALGORITHM FOR LEO SATELLITE NETWORK

Low Earth Orbit (LEO) satellites provide short round-trip delays and are becoming in- creasingly important. One of the challenges in LEO satellite networks is the development of specialized and efficient routing algorithms. To satisfy the QoS requirements of multimedia applications, satellite routing protocols should consider handovers and minimize their effect on the active connections. A distributed QoS routing scheme based on heuristic ant algorithm is proposed for satisfying delay bound and avoiding link congestion. Simulation results show that the call blocking probabilities of this al- gorithm are less than that of Shortest Path First (SPF) with different delay bound.     

QoS-driven multicast routing in sparse-splitting optical networks

This paper investigates the quality-of-service (QoS)-driven multicast routing problem in a sparse-splitting optical network. The main objective is to minimize the total cost of wavelength channels utilized by the light-tree while satisfying required QoS parameters. In this paper, both the optical-layer constraints (e.g., optical signal power) and application-layer requirements (e.g., end-to-end delay and inter-destination delay variation) are considered as the QoS parameters. First, integer linear programming (ILP) formulations to solve the optimal multicast routing problem with the given QoS parameters are presented. Solving the ILP formulations for large-scale networks can easily overwhelm the capabilities of state-of-the-art computing facilities, and hence, a heuristic algorithm is proposed to construct a feasible light-tree that satisfies the required QoS parameters in large-scale networks. Simulation results demonstrate the performance of the proposed heuristic algorithm in terms of the cost of utilized wavelength channels.     

Two algorithms for multi‐constrained optimal multicast routing

Multimedia applications, such as video‐conferencing and video‐on‐demand, often require quality of service (QoS) guarantees from the network, typically in the form of minimum bandwidth, maximum delay, jitter and packet loss constraints, among others. The problem of multicast routing subject to various forms of QoS constraints has been studied extensively. However, most previous efforts have focused on special situations where a single or a pair of constraints is considered. In general, routing under multiple constraints, even in the unicast case is an NP‐complete problem. We present in this paper two practical and efficient algorithms, called multi‐constrained QoS dependent multicast routing (M_QDMR) and (multicasting routing with multi‐constrained optimal path selection (M_MCOP)), for QoS‐based multicast routing under multiple constraints with cost optimization. We provide proof in the paper that our algorithms are correct. Furthermore, through extensive simulations, we illustrate the effectiveness and efficiency of our proposals and demonstrate their significant performance improvement in creating multicast trees with lower cost and higher success probability. Copyright © 2003 John Wiley & Sons, Ltd.     

Adaptive call admission control under quality of serviceconstraints: a reinforcement learning solution

We solve the adaptive call admission control (CAC) problem in multimedia networks via reinforcement learning (RL). The problem requires that network revenue be maximized while simultaneously meeting quality of service (QoS) constraints that forbid entry into certain states and use of certain actions. We show that RL provides a solution to this constrained semi-Markov decision problem and is able to earn significantly higher revenues than alternative heuristics. Unlike other model-based algorithms, RL does not require the explicit state transition models to solve the decision problems. This feature is very important if one considers large integrated service networks supporting a number of different service types, where the number of states is so large that model-based optimization algorithms are infeasible. Both packet-level and call-level QoS constraints are addressed, and both conservative and aggressive approaches to the QoS constraints are considered. Results are demonstrated on a single link and extended to routing on a multilink network     

基于链路状态的多约束路由预计算算法

作为下一代高速网络的核心问题之一,多约束的服务质量路由(QoSR)至今尚无有效算法,为此基于线性能量函数设计了预计算算法MEFPA.该算法将每个QoS度量的重要性均匀分成若干个等级,从而在多维QoS度量空间中构造出多个均匀分布的线性能量函数;算法通过能量函数将QoS链路状态转化成单一能量值,再使用Dijkstra算法计算最小能量树,最终产生QoS路由表.文章分析了多约束下的线性能量函数对算法性能的影响,给出了判定多维空间中QoS约束的可行区域和不可行区域的方法,最后基于这些理论为多约束QoSR问题给出了预计算算法.广泛深入的实验结果表明,高可扩展性、高性能、易实现的预计算算法MEFPA是一种值得在下一代网络中考虑的路由算法.     

Minimum-energy broadcast and multicast in wireless networks: An integer programming approach and improved heuristic algorithms

Both integer programming models and heuristic algorithms have been proposed for finding minimum-energy broadcast and multicast trees in wireless ad hoc networks. Among heuristic algorithms, the broadcast/multicast incremental power (BIP/MIP) algorithm is most known. The theoretical performance of BIP/MIP has been quantified in several studies. To assess the empirical performance of BIP/MIP and other heuristic algorithms, it is necessary to compute an optimal tree or a very good lower bound of the optimum. In this paper, we present an integer programming approach as well as improved heuristic algorithms. Our integer programming approach comprises a novel integer model and a relaxation scheme. Unlike previously proposed models, the continuous relaxation of our model leads to a very sharp lower bound of the optimum. Our relaxation scheme allows for performance evaluation of heuristics without having to compute optimal trees. Our contributions to heuristic algorithms consist of the power-improving algorithm successive power adjustment (SPA), and improved time complexity of some previously suggested algorithms. We report extensive numerical experiments. Algorithm SPA finds better solutions in comparison to a host of other algorithms. Moreover, the integer programming approach shows that trees found by algorithm SPA are optimal or near-optimal.     

一种基于计算智能的组播路由算法

在通信网络中,多约束组播通信是提高网络运行效率和服务质量的重要途径。一些启发式的算法已经被用来解决多约束条件下的组播路由问题,如模拟退火算法,遗传算法,蚁群算法和粒子群优化算法等。然而,这些算法在求解多约束组播路由问题时存在收敛速度低和计算复杂度高的问题。萤火虫群优化(GSO)算法是一种近期在计算智能领域出现的卓越算法,它可以在一定程度上解决多约束组播树生成过程中收敛速度低和计算复杂度高的问题。提出了一种基于GSO的多约束组播树生成算法(GSO-MCM)。该算法可有效生成满足多约束要求的组播路由树。仿真结果表明提出的GSO-MCM算法在求解和收敛速度,以及网络规模适应性方面均有良好的性能。