Improved Approximation Algorithms for the Capacitated Multicast Routing Problem

2005 ◽  
pp. 136-145 ◽  
Author(s):  
Zhipeng Cai ◽  
Guohui Lin ◽  
Guoliang Xue
Keyword(s):  
Approximation Algorithms ◽  
Multicast Routing ◽  
Routing Problem

Solving Multi-Objective Multicast Routing Problem Using a New Hybrid Approach

2018 ◽  
Vol 9 (4) ◽  
pp. 22-36
Author(s):  
Mohammed Mahseur ◽  
Abdelmadjid Boukra ◽  
Yassine Meraihi
Keyword(s):  
Multicast Routing ◽  
Hybrid Approach ◽  
Bat Algorithm ◽  
Pareto Optimal Solutions ◽  
Optimal Solutions ◽  
Routing Problem ◽  
Multi Objective ◽  
Strength Pareto Evolutionary Algorithm ◽  
Quality Of Service Parameters

Multicast routing is the problem of finding the spanning tree of a set of destinations whose roots are the source node and its leaves are the set of destination nodes by optimizing a set of quality of service parameters and satisfying a set of transmission constraints. This article proposes a new hybrid multicast algorithm called Hybrid Multi-objective Multicast Algorithm (HMMA) based on the Strength Pareto Evolutionary Algorithm (SPEA) to evaluate and classify the population in dominated solutions and non-dominated solutions. Dominated solutions are evolved by the Bat Algorithm, and non-dominated solutions are evolved by the Firefly Algorithm. Old and weak solutions are replaced by new random solutions by a process of mutation. The simulation results demonstrate that the proposed algorithm is able to find good Pareto optimal solutions compared to other algorithms.

Multicast Routing Algorithm with QoS Constraints in Mobile Ad Hoc Networks

2014 ◽  
Vol 602-605 ◽  
pp. 3169-3172 ◽  
Author(s):  
Yue Li ◽  
Yin Hui Liu ◽  
Zhong Bao Luo
Keyword(s):  
Ad Hoc ◽  
Multicast Routing ◽  
Routing Algorithm ◽  
Estimation Algorithm ◽  
Bandwidth Estimation ◽  
Routing Problem ◽  
Network Bandwidth ◽  
Hoc Networks ◽  
Multicast Routing Algorithm ◽  
Select Function

Through the study of MANET's QoS multicast routing problem, we propose a heuristic-demand multicast routing algorithm. Algorithm combines the MANET network bandwidth estimation algorithm, redefined the select function, restrictions request packets of flooding algorithm, to ensure fair treatment delay and bandwidth. Simulation results show that the algorithm has the advantage of fewer routing overhead, high success rate.

scholarly journals A Quantum MMAS Based Algorithm for Multicast Routing Problem

2021 ◽  
Vol 1920 (1) ◽  
pp. 012105
Author(s):  
Yalong Li ◽  
Wang Wei ◽  
Sun Jing ◽  
Wan Jie
Keyword(s):  
Multicast Routing ◽  
Routing Problem

Analysis of Quality of Service Routing Algorithms

2011 ◽  
pp. 159-169
Author(s):  
E.George Dharma Prakash Raj ◽  
Sinthu Janita Prakash ◽  
S.V.Kasmir Raja
Keyword(s):  
Multicast Routing ◽  
Source Node ◽  
Destination Node ◽  
Path Delay ◽  
Quality Of Service Routing ◽  
Routing Problem ◽  
Unicast Routing ◽  
Service Routing ◽  
Feasible Path

The routing problems can be divided into two major classes. They are 1) Unicast routing and 2) Multicast routing. The Unicast routing problem is as follows. Given a source node sr, a destination node dn, a set of QoS constraints qc and an optimization goal (optional), find the best feasible path from sr to dn, which satisfies qc. The Multicast routing problem is as follows. Given a source node sr, a set st of destination nodes, a set of constraints cts and an optimization goal (optional), find the best feasible path covering sr and all nodes in st, which satisfies cts. This article presents two such Unicast QoS based algorithms called as Source Routing and the proposed Heuristic Routing. A Client Server based model has been generated to study the performance of the two algorithms with respect to the message overhead, response time and path delay. The Experiments and the results are analyzed.

USING NEURAL NETWORKS TO SOLVE THE MULTICAST ROUTING PROBLEM IN PACKET RADIO NETWORKS

1996 ◽  
Vol 07 (05) ◽  
pp. 617-626 ◽  
Author(s):  
THOMAS L. HEMMINGER ◽  
CARLOS A. POMALAZA-RAEZ
Keyword(s):  
Multicast Routing ◽  
Optimal Solution ◽  
Packet Delay ◽  
Hopfield Neural Network ◽  
Routing Problem ◽  
Packet Radio ◽  
Packet Radio Network ◽  
End To End Delay ◽  
Packet Delays ◽  
End To End

The primary function of a packet radio network is the efficient transfer of information between source and destination nodes using minimal bandwidth and end-to-end delay. Many researchers have investigated the problem of minimizing the end-to-end delay from a single source to a single destination for a variety of networks; however, very little work is reported about routing mechanisms for the common case where a particular information packet is intended to be sent to more than one destination in the network. This is known as multicasting. A simplified version of the problem is to ignore the packet delay at each node, then the problem becomes one of finding solutions which require the least number of transmissions. Determination of an optimal solution is NP-complete meaning that suboptimal solutions are frequently tolerated. The problem becomes more rigorous if packet delays are included in the network topology. This paper describes a practical technique for the computation of optimum or near optimum solutions to the multicasting problem with and without packet delay. The method is based on the Hopfield neural network and experiment has shown this method to yield near optimal solutions while requiring a minimum of CPU time.

scholarly journals Multicast Utility Maximization with Load Balanc-ing in Private Cloud Environment

2018 ◽  
Vol 7 (2.19) ◽  
pp. 12
Author(s):  
N Senthamarai ◽  
M Vijayalakshmi
Keyword(s):  
Cloud Computing ◽  
Utility Maximization ◽  
Multicast Routing ◽  
Multicast Tree ◽  
Cloud Environment ◽  
Selection Algorithm ◽  
Private Cloud ◽  
Queuing Delay ◽  
Routing Problem ◽  
Transmission Overhead

Multicast is a technique for one-to-many communication over the network. It plays important role in cloud computing and reduces the transmission overhead in the private cloud environment. In this paper, build an efficient multicast tree for the multicast routing problem in which a network consists of different categories of nodes, where each category can have one or more nodes of the same characteristic which is different from the characteristics of nodes from other categories. So it is used to reduce the message traffic in such a network, to build a multicast tree and minimize the queuing delay using multicast selection algorithm.

A Multicast Routing Algorithm with Cost, Delay and Bandwidth Constraints

2013 ◽  
Vol 756-759 ◽  
pp. 1850-1854
Author(s):  
Yuan Chen Li ◽  
Guo Fang Kuang
Keyword(s):  
Communication Networks ◽  
Multicast Routing ◽  
Routing Algorithm ◽  
Multicast Tree ◽  
Routing Problem ◽  
Qos Parameters ◽  
The Cost ◽  
Multicast Routing Algorithm ◽  
Multiple Qos

Quality of service (QoS) generally assumes more than one QoS measure which implies that routing can be categorized as an instance of routing subject to multiple constraints: such as cost, delay, bandwidth, etc. The problem of constructing multicast trees is studied to meet the QoS requirements where it is necessary to provide bounded constraints among the source and all destinations while keeping the cost of the multicast tree low. So, a kind of source-destination QoS multicast routing problem is addressed about communication networks. The algorithm we presented takes bandwidth, delay and loss rate as premise, constructs routing selected function based on shortest path, modifies selected path according to the function above so as to fit multi-QoS parameters. Simulation results show that the algorithm has both lower delay and better performance and can be extended to cases of multiple QoS parameters conveniently.

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