A green intelligent routing algorithm supporting flexible QoS for many-to-many multicast

The tremendous energy consumption attributed to the Information and Communication Technology (ICT) field has become a persistent concern during the last few years, attracting significant academic and industrial efforts. Networks have begun to be improved towards being “green”. Considering Quality of Service (QoS) and power consumption for green Internet, a Green Intelligent flexible QoS many-to-many Multicast routing algorithm (GIQM) is presented in this paper. In the proposed algorithm, a Rendezvous Point Confirming Stage (RPCS) is first carried out to obtain a rendezvous point and the candidate Many-to-many Multicast Sharing Tree (M2ST); then an Optimal Solution Identifying Stage (OSIS) is performed to generate a modified M2ST rooted at the rendezvous point, and an optimal M2ST is obtained by comparing the original M2ST and the modified M2ST. The network topology of Cernet2, GéANT and Internet2 were considered for the simulation of GIQM. The results from a series of experiments demonstrate the good performance and outstanding power-saving potential of the proposed GIQM with QoS satisfied

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 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

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

A simulated annealing based genetic local search algorithm for multi-objective multicast routing problems

This paper presents a new hybrid evolutionary algorithm to solve multi-objective multicast routing problems in telecommunication networks. The algorithm combines simulated annealing based strategies and a genetic local search, aiming at a more flexible and effective exploration and exploitation in the search space of the complex problem to find more non-dominated solutions in the Pareto Front. Due to the complex structure of the multicast tree, crossover and mutation operators have been specifically devised concerning the features and constraints in the problem. A new adaptive mutation probability based on simulated annealing is proposed in the hybrid algorithm to adaptively adjust the mutation rate according to the fitness of the new solution against the average quality of the current population during the evolution procedure. Two simulated annealing based search direction tuning strategies are applied to improve the efficiency and effectiveness of the hybrid evolutionary algorithm. Simulations have been carried out on some benchmark multi-objective multicast routing instances and a large amount of random networks with five real world objectives including cost, delay, link utilisations, average delay and delay variation in telecommunication networks. Experimental results demonstrate that both the simulated annealing based strategies and the genetic local search within the proposed multi-objective algorithm, compared with other multi-objective evolutionary algorithms, can efficiently identify high quality non-dominated solution set for multi-objective multicast routing problems and outperform other conventional multi-objective evolutionary algorithms in the literature

Multicast QoS Routing Using Collaborative Path Exploration

Quality of Service (QoS) is one of the most active research areas in networking. The most fundamental requirement for QoS routing is the ability to find and maintain a network path that provides the required network resources between two or more nodes. In this paper, we present a distributed collaborative multicast QoS routing architecture that uses a semi-greedy probing heuristic to quickly find a QoS path between a joining node and the multicast tree. The proposed architecture will enable the routers along the path to intelligently and dynamically discover a QoS path. Any router that receives a probe will only know its neighbours and it will create a link to the previous router from where the probe comes from. The proposed architecture is a tree-initiated QoS search and the first QoS packet to reach the joining node will be used as the QoS path. Analysis of this method shows that the path search time and message overhead is lower than other similar schemes

An efficient Particle Swarm Optimization technique for identification of shortest path in Distributed Network

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A Hybrid Approach to Quality of Service Multicast Routing in High Speed Networks

Multimedia services envisaged for high speed networks may have large numbers of users, require high volumes of network resources and have real-time delay constraints. For these reasons, several multicast routing heuristics that use two link metrics have been proposed with the objective of minimising multicast tree cost while maintaining a bound on delay. Previous evaluation work has compared the relative average performance of some of these heuristics and concludes that they are generally efficient. This thesis presents a detailed analysis and evaluation of these heuristics which illustrate that in some situations their average performance is prone to wide variance for a particular multicast in a specific network. It concludes that the efficiency of an heuristic solution depends on the topology of both the network and the multicast, which is difficult to predict. The integration of two heuristics with Dijkstras shortest path tree algorithm is proposed, to produce a hybrid that consistently generates efficient multicast solutions for all possible multicast groups in any network. The evaluation results show good performance over a wide range of networks (flat and hierarchical) and multicast groups, within differing delay bounds. The more efficient the multicast tree is, the less stable it will be as multicast group membership changes. An efficient heuristic is extended to ensure multicast tree stability where multicast group membership is dynamic. This extension decreases the efficiency of the heuristics solutions, although they remain significantly cheaper than the worst case, a shortest delay path tree. This thesis also discusses how the hybrid and the extended heuristic might be applied to multicast routing protocols for the Internet and ATM Networks. Additionally, the behaviour of the heuristics is examined in networks that use a single link metric to calculate multicast trees and concludes one of the heuristics may be of benefit in such networks