A FAST HYBRID ALGORITHM FOR MULTICAST ROUTING IN WIRELESS NETWORKS

2007 ◽  
Vol 16 (01) ◽  
pp. 45-68 ◽  
Author(s):  
S. AL-SHARHAN ◽  
W. GUEAIEB
Keyword(s):  
Wireless Networks ◽  
Hybrid Algorithm ◽  
Heuristic Algorithms ◽  
Multicast Routing ◽  
Learning Algorithm ◽  
Population Based ◽  
Multicast Tree ◽  
Recent Developments ◽  
Real Challenge

This paper tackles the issue of constrained multicast routing in wireless networks using a hybrid soft computing-based algorithm. Recent developments in multimedia applications and the dynamic and rapidly changed environment of the wireless networks make the constrained multicast routing a real challenge. The problem can be formulated as minimizing a multicast tree cost under several constraints or Quality of Service (QoS) metrics. This problem has been proven to be NP-complete. The proposed hybrid algorithm is based on a population based incremental learning algorithm that combines in an efficient way the features of genetic algorithms and competitive learning. Experimental results show that, in most cases, the proposed algorithm yields better solutions than other heuristic algorithms proposed in the literature.

A HYBRID EVOLUTIONARY ALGORITHM FOR MULTIPLE-DESTINATIONS ROUTING PROBLEM

2004 ◽  
Vol 04 (04) ◽  
pp. 337-353 ◽  
Author(s):  
SALAH AL-SHARHAN ◽  
FAWAZ AL-ANZI
Keyword(s):  
Evolutionary Algorithm ◽  
Incremental Learning ◽  
Heuristic Algorithms ◽  
Learning Algorithm ◽  
Population Based ◽  
Multicast Tree ◽  
Routing Problem ◽  
Hybrid Evolutionary Algorithm ◽  
Np Complete ◽  
Qos Metrics

This paper presents a hybrid evolutionary algorithm for constrained multiple destinations routing problem. The problem can be formulated as minimising tree cost under several constraints or QoS metrics. Computing such constrained multicast tree has been proven to be NP-complete. The proposed hybrid algorithm is based on a population based incremental learning algorithm and a constrained distance network heuristic (or CKMB) algorithm. In the proposed algorithm, CKMB is utilised as a decoding scheme. Experimental results show that, in most cases, the proposed algorithm yields better solutions than other heuristic algorithms proposed in the literature including the best known one BSMA.

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.

scholarly journals Scalable Video Streaming for Single-Hop Wireless Networks Using a Contention-Based Access MAC Protocol

2008 ◽  
Vol 2008 ◽  
pp. 1-21
Author(s):  
Monchai Lertsutthiwong ◽  
Thinh Nguyen ◽  
Alan Fern
Keyword(s):  
Wireless Networks ◽  
Video Streaming ◽  
Admission Control ◽  
Packet Loss ◽  
Optimization Problem ◽  
Heuristic Algorithms ◽  
Mac Protocol ◽  
Video Quality ◽  
Streaming Applications

Limited bandwidth and high packet loss rate pose a serious challenge for video streaming applications over wireless networks. Even when packet loss is not present, the bandwidth fluctuation, as a result of an arbitrary number of active flows in an IEEE 802.11 network, can significantly degrade the video quality. This paper aims to enhance the quality of video streaming applications in wireless home networks via a joint optimization of video layer-allocation technique, admission control algorithm, and medium access control (MAC) protocol. Using an Aloha-like MAC protocol, we propose a novel admission control framework, which can be viewed as an optimization problem that maximizes the average quality of admitted videos, given a specified minimum video quality for each flow. We present some hardness results for the optimization problem under various conditions and propose some heuristic algorithms for finding a good solution. In particular, we show that a simple greedy layer-allocation algorithm can perform reasonably well, although it is typically not optimal. Consequently, we present a more expensive heuristic algorithm that guarantees to approximate the optimal solution within a constant factor. Simulation results demonstrate that our proposed framework can improve the video quality up to 26% as compared to those of the existing approaches.

scholarly journals An Efficient Algorithm for Delay and Delay- Variation Bounded Core Based Tree Generation

2010 ◽  
pp. 202-207
Author(s):  
Manoj Kumar Patel ◽  
MANAS RANJAN KABAT ◽  
Chita Ranjan Tripathy
Keyword(s):  
Upper Bound ◽  
Heuristic Algorithms ◽  
Multicast Tree ◽  
End To End Delay ◽  
Tree Generation ◽  
Core Selection ◽  
End To End ◽  
Better Than ◽  
Delay Variation

Many multimedia group applications require the construction of multicast tree satisfying the quality of service (QoS) requirements. To support real time communication, computer networks need to optimize the Delay and Delay-Variation Bounded Multicast Tree (DVBMT). The problem is to satisfy the end-to-end delay and delay-variation within an upper bound. The DVBMT problem is known to be NP complete. In this paper, we propose an efficient core selection algorithm for satisfying the end-to-end delay and delay-variation within an upper bound. The efficiency of the proposed algorithm is validated through the simulation. The simulation results reveal that our algorithm performs better than the existing heuristic algorithms.

Tabu Search for Low-Cost Dynamic Multicast Tree Generation with Quality of Service Guarantees

2015 ◽  
Vol 24 (4) ◽  
pp. 479-489
Author(s):  
Muhammad Atif Tahir ◽  
Asif Jamshed ◽  
Habib-ur Rehman ◽  
Yassine Daadaa
Keyword(s):  
Quality Of Service ◽  
Tabu Search ◽  
Multicast Routing ◽  
Low Cost ◽  
Multicast Tree ◽  
Source Node ◽  
Delay Constraint ◽  
Routing Problem ◽  
Dynamic Multicast

AbstractIn a communication network with a source node, a multicast tree is defined as a tree rooted at the source node and all its leaves being recipients of the multicast originating at the source. The tree or bandwidth cost is normally measured by its utilization of tree links along with the quality of service (QoS) measures such as delay constraint and end-to-end delay. However, if nodes are allowed to join or leave the multicast group at any time during the lifetime of the multicast connection, then the problem is known as dynamic multicast routing problem. In this article, we combine a greedy approach with static multicast routing using Tabu Search to find a low-cost dynamic multicast tree with desirable QoS parameters. The proposed algorithm is then compared with several static multicast routing algorithms. The simulation results show that, on a large number of events, i.e., where nodes are leaving or joining, the proposed algorithm is able to find multicast trees of lower cost and more desirable QoS properties.

scholarly journals Multi-Source Reliable Multicast Routing with QoS Constraints of NFV in Edge Computing

Electronics ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1106 ◽  
Author(s):  
Shiming He He ◽  
Kun Xie ◽  
Xuhui Zhou ◽  
Thabo Semong ◽  
Jin Wang
Keyword(s):  
Heuristic Algorithms ◽  
Multicast Routing ◽  
Multicast Tree ◽  
Edge Computing ◽  
Network Function Virtualization ◽  
Reliable Multicast ◽  
Network Function ◽  
Tree Construction ◽  
Service Function Chain ◽  
The Cost

Edge Computing (EC) allows processing to take place near the user, hence ensuring scalability and low latency. Network Function Virtualization (NFV) provides the significant convenience of network layout and reduces the service operation cost in EC and data center. Nowadays, the interests of the NFV layout focus on one-to-one communication, which is costly when applied to multicast or group services directly. Furthermore, many artificial intelligence applications and services of cloud and EC are generally communicated through groups and have special Quality of Service (QoS) and reliable requirements. Therefore, we are devoted to the problem of reliable Virtual Network Function (VNF) layout with various deployment costs in multi-source multicast. To guarantee QoS, we take into account the bandwidth, latency, and reliability constraints. Additionally, a heuristic algorithm, named Multi-Source Reliable Multicast Tree Construction (RMTC), is proposed. The algorithm aims to find a common link to place the Service Function Chain (SFC) in the multilevel overlay directed (MOD) network of the original network, so that the deployed SFC can be shared by all users, thereby improving the resource utilization. We then constructed a Steiner tree to find the reliable multicast tree. Two real topologies are used to evaluate the performance of the proposed algorithm. Simulation results indicate that, compared to other heuristic algorithms, our scheme effectively reduces the cost of reliable services and satisfies the QoS requirements.

An Improved Chaotic Binary Bat Algorithm for QoS Multicast Routing

2016 ◽  
Vol 25 (04) ◽  
pp. 1650025 ◽  
Author(s):  
Yassine Meraihi ◽  
Dalila Acheli ◽  
Amar Ramdane-Cherif
Keyword(s):  
Particle Swarm Optimization ◽  
Communication Networks ◽  
Heuristic Algorithms ◽  
Multicast Routing ◽  
Logistic Map ◽  
Particle Swarm ◽  
Bat Algorithm ◽  
Multicast Tree ◽  
Swarm Optimization ◽  
Routing Problem

The quality of service (QoS) multicast routing problem is one of the main issues for transmission in communication networks. It is known to be an NP-hard problem, so many heuristic algorithms have been employed to solve the multicast routing problem and find the optimal multicast tree which satisfies the requirements of multiple QoS constraints such as delay, delay jitter, bandwidth and packet loss rate. In this paper, we propose an improved chaotic binary bat algorithm to solve the QoS multicast routing problem. We introduce two modification methods into the binary bat algorithm. First, we use the two most representative chaotic maps, namely the logistic map and the tent map, to determine the parameter [Formula: see text] of the pulse frequency [Formula: see text]. Second, we use a dynamic formulation to update the parameter α of the loudness [Formula: see text]. The aim of these modifications is to enhance the performance and the robustness of the binary bat algorithm and ensure the diversity of the solutions. The simulation results reveal the superiority, effectiveness and efficiency of our proposed algorithms compared with some well-known algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Jumping Particle Swarm Optimization (JPSO), and Binary Bat Algorithm (BBA).

A Delay-Constrained Multicast Routing Balanced-Optimization Algorithm of Link-Sharing

2012 ◽  
Vol 152-154 ◽  
pp. 1834-1839
Author(s):  
Wei Qun Liu ◽  
Xiang Kui Chen
Keyword(s):  
Computational Complexity ◽  
Multicast Routing ◽  
Routing Algorithm ◽  
Shortest Paths ◽  
Multicast Tree ◽  
Selection Function ◽  
Minimum Delay ◽  
The Cost ◽  
Balanced Optimization

In multimedia network, Quality of service (QoS) provisioning generally assumes more than one QoS measure which implies that QoS routing can be categorized as an instance of routing subject to multiple constraints: delay, cost, bandwidth, etc. We study the problem of constructing multicast trees to meet the QoS requirements of real-time applications where it is necessary to provide bounded delays among the source and all destinations while keeping overall cost of the multicast tree low. So the cost and computational complexity are analyzed as constructing delay-constrained multicast tree. So as to optimize shortest paths, a new algorithm of ORLSB(optimal routing algorithm for link-sharing balance) is proposed.The link selection function of the algorithm not only considers the priority of the destination nodes, but also takes into account the priority of the low delay path based on local information. Because the multicast tree has fewer possible path, the algorithm reduces the probability of creating multicast tree through the minimum delay path and improves the sharing paths. Simulation results show that this algorithm has balanced cost, delay and computational complexity, and has better overall performance.

scholarly journals Studying the Impact of Initialization for Population-Based Algorithms with Low-Discrepancy Sequences

2021 ◽  
Vol 11 (17) ◽  
pp. 8190
Author(s):  
Adnan Ashraf ◽  
Sobia Pervaiz ◽  
Waqas Haider Bangyal ◽  
Kashif Nisar ◽  
Ag. Asri Ag. Ibrahim ◽  
...  
Keyword(s):  
Heuristic Algorithms ◽  
Random Sequence ◽  
Search Space ◽  
Population Based ◽  
Test Problems ◽  
Low Discrepancy Sequences ◽  
Experimental Findings ◽  
Optimum Solution ◽  
The Impact

To solve different kinds of optimization challenges, meta-heuristic algorithms have been extensively used. Population initialization plays a prominent role in meta-heuristic algorithms for the problem of optimization. These algorithms can affect convergence to identify a robust optimum solution. To investigate the effectiveness of diversity, many scholars have a focus on the reliability and quality of meta-heuristic algorithms for enhancement. To initialize the population in the search space, this dissertation proposes three new low discrepancy sequences for population initialization instead of uniform distribution called the WELL sequence, Knuth sequence, and Torus sequence. This paper also introduces a detailed survey of the different initialization methods of PSO and DE based on quasi-random sequence families such as the Sobol sequence, Halton sequence, and uniform random distribution. For well-known benchmark test problems and learning of artificial neural network, the proposed methods for PSO (TO-PSO, KN-PSO, and WE-PSO), BA (BA-TO, BA-WE, and BA-KN), and DE (DE-TO, DE-WE, and DE-KN) have been evaluated. The synthesis of our strategies demonstrates promising success over uniform random numbers using low discrepancy sequences. The experimental findings indicate that the initialization based on low discrepancy sequences is exceptionally stronger than the uniform random number. Furthermore, our work outlines the profound effects on convergence and heterogeneity of the proposed methodology. It is expected that a comparative simulation survey of the low discrepancy sequence would be beneficial for the investigator to analyze the meta-heuristic algorithms in detail.

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