AN EFFICIENT MULTI-PURPOSE OPTIMIZATION METHOD FOR QOS ROUTING USING GENETIC ALGORITHM

2004 ◽  
Vol 05 (04) ◽  
pp. 409-428 ◽  
Author(s):  
AKIO KOYAMA ◽  
LEONARD BAROLLI ◽  
GENCI CAPI ◽  
BERNADY O. APDUHAN ◽  
JUNPEI ARAI ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Video On Demand ◽  
Optimization Method ◽  
Qos Routing ◽  
Routing Algorithms ◽  
Path Constraints ◽  
Np Complete ◽  
Independent Path ◽  
Multiple Qos

In order to support multimedia communication, it is necessary to develop routing algorithms that make decisions based on multiple Quality of Service (QoS) parameters. This is because new services such as video on demand and remote meeting systems have multiple QoS requirements. However, the problem of QoS routing is difficult because finding a feasible route with two independent path constraints is NP-complete problem. Also, QoS routing algorithms for broadband networks must be adaptive, flexible, and intelligent for efficient network management. In this paper, we propose a multi-purpose optimization method for QoS routing based on Genetic Algorithm (GA). The simulation results show that the proposed method has a good performance and therefore is a promising method for QoS routing.

Quality of Service for Multimedia and Real-Time Services

2010 ◽  
Vol 5 (4) ◽  
pp. 1-22
Author(s):  
F. W. Albalas ◽  
B. A. Abu-Alhaija ◽  
A. Awajan ◽  
A. Awajan ◽  
Khalid Al-Begain
Keyword(s):  
Decision Making ◽  
Quality Of Service ◽  
Real Time ◽  
Qos Routing ◽  
Routing Algorithms ◽  
Complete Problem ◽  
Filtering Technique ◽  
Np Complete ◽  
Multiple Metrics

New web technologies have encouraged the deployment of various network applications that are rich with multimedia and real-time services. These services demand stringent requirements are defined through Quality of Service (QoS) parameters such as delay, jitter, loss, etc. To guarantee the delivery of these services QoS routing algorithms that deal with multiple metrics are needed. Unfortunately, QoS routing with multiple metrics is considered an NP-complete problem that cannot be solved by a simple algorithm. This paper proposes three source based QoS routing algorithms that find the optimal path from the service provider to the user that best satisfies the QoS requirements for a particular service. The three algorithms use the same filtering technique to prune all the paths that do not meet the requirements which solves the complexity of NP-complete problem. Next, each of the three algorithms integrates a different Multiple Criteria Decision Making method to select one of the paths that have resulted from the route filtering technique. The three decision making methods used are the Analytic Hierarchy Process (AHP), Multi-Attribute Utility Theory (MAUT), and Kepner-Tregoe KT. Results show that the algorithms find a path using multiple constraints with a high ability to handle multimedia and real-time applications.

Quality of Service for Multimedia and Real-Time Services

2012 ◽  
pp. 241-262
Author(s):  
F. W. Albalas ◽  
B. A. Abu-Alhaija ◽  
A. Awajan ◽  
A. Awajan ◽  
Khalid Al-Begain
Keyword(s):  
Decision Making ◽  
Quality Of Service ◽  
Real Time ◽  
Qos Routing ◽  
Routing Algorithms ◽  
Complete Problem ◽  
Filtering Technique ◽  
Np Complete ◽  
Multiple Metrics

New web technologies have encouraged the deployment of various network applications that are rich with multimedia and real-time services. These services demand stringent requirements are defined through Quality of Service (QoS) parameters such as delay, jitter, loss, etc. To guarantee the delivery of these services QoS routing algorithms that deal with multiple metrics are needed. Unfortunately, QoS routing with multiple metrics is considered an NP-complete problem that cannot be solved by a simple algorithm. This paper proposes three source based QoS routing algorithms that find the optimal path from the service provider to the user that best satisfies the QoS requirements for a particular service. The three algorithms use the same filtering technique to prune all the paths that do not meet the requirements which solves the complexity of NP-complete problem. Next, each of the three algorithms integrates a different Multiple Criteria Decision Making method to select one of the paths that have resulted from the route filtering technique. The three decision making methods used are the Analytic Hierarchy Process (AHP), Multi-Attribute Utility Theory (MAUT), and Kepner-Tregoe KT. Results show that the algorithms find a path using multiple constraints with a high ability to handle multimedia and real-time applications.

An Improved Hybrid Genetic Algorithm and Performance Study

2012 ◽  
Vol 482-484 ◽  
pp. 95-98
Author(s):  
Wei Dong Ji ◽  
Ke Qi Wang
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Optimization Method ◽  
Convergence Speed ◽  
Test Results ◽  
Improved Genetic Algorithm ◽  
Performance Study ◽  
Speed Up ◽  
And Performance

Put forward a kind of the hybrid improved genetic algorithm of particle swarm optimization method (PSO) combine with and BFGS algorithm of, this method using PSO good global optimization ability and the overall convergence of BFGS algorithm to overcome the blemish of in the conventional algorithm slow convergence speed and precocious and local convergence and so on. Through the three typical high dimensional function test results show that this method not only improved the algorithm of the global search ability, to speed up the convergence speed, but also improve the quality of the solution and its reliability of optimization results.

Propose a new algorithm of routing with information collected locally

2016 ◽  
Vol 2 (1) ◽  
pp. 70
Author(s):  
Tran Minh Anh ◽  
Nguyen Chien Trinh
Keyword(s):  
Routing Algorithm ◽  
Qos Routing ◽  
Local Information ◽  
Routing Algorithms ◽  
Source Node ◽  
Quality Of Services ◽  
Global State ◽  
State Information ◽  
Near Future

The type of algorithm which uses local information collected from source node for Quality of Service (QoS) routing has recently been researched as an alternative to QoS routing algorithms that traditionally use global state information. This algorithm, collecting information from source node only, helps flow routing better and assures more flexibly QoS for network. This trend leads to a new solution for satisfying the higher and higher demand of telecom market in the near future. In this paper, we introduce a new algorithm of routing like that type for assuring the quality of network as well as quality of services. The simulations at last section show the advantages over some other localized routing algorithms and global routing algorithm.

scholarly journals The EuQoS system: a solution for QoS routing in heterogeneous networks [Quality of Service based Routing Algorithms for Heterogeneous Networks]

2007 ◽  
Vol 45 (2) ◽  
pp. 96-103 ◽  
Author(s):  
Xavi Masip-Bruin ◽  
Marcelo Yannuzzi ◽  
Rene Serral-Gracia ◽  
Jordi Domingo-Pascual ◽  
Jose Enriquez-Gabeiras ◽  
...  
Keyword(s):  
Quality Of Service ◽  
Heterogeneous Networks ◽  
Qos Routing ◽  
Routing Algorithms ◽  
System A

A New Localized Multi-Constraint QoS Routing Algorithm

2017 ◽  
Author(s):  
Tran Minh Anh ◽  
Nguyen Chien Trinh
Keyword(s):  
Routing Algorithm ◽  
Qos Routing ◽  
Routing Algorithms ◽  
Source Node ◽  
Global Network ◽  
Traffic Patterns ◽  
State Information ◽  
Alternative Approach ◽  
Qos Routing Algorithm

The scheme of Quality of Service (QoS) routing algorithms based on local state information has recently been proposed as an alternative approach to the traditional QoS routing algorithms. By implementing this localized QoS routing algorithm, each source node predetermines and maintains a set of candidate paths for each destination. These sets of paths will help the source node to decide the most appropriate path for a connection request. Hence, it helps to avoid the problems associated with the maintenance of the global network state information. In this paper, we propose a new and effective localized QoS routing algorithm, compare its performance with those of other localized algorithms and a traditional QoS routing algorithm under the same type of network topology, QoS requirements and traffic patterns. The simulations results show that our proposed algorithm can perform better than other routing algorithms. DOI: 10.32913/rd-ict.vol3.no14.258

scholarly journals Genetic Algorithm Applied to Planning IEEE 802.11g Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 59-64
Author(s):  
Hamid Barkouk ◽  
El Mokhtar En-Naimi ◽  
Aziz Mahboub
Keyword(s):  
Genetic Algorithm ◽  
Quality Of Service ◽  
Quality Criteria ◽  
Optimization Method ◽  
Local Network ◽  
Local Networks ◽  
Total Interaction ◽  
Network Quality ◽  
Required Quality

The problem of planning local wireless network IEEE 802.11g consists of automatically positioning and setting up wireless access points (APs) in order to provide access to the local network with the desired coverage and the required quality of service (QOS).In addition to the complexity of predicting the Quality of Service (QoS) of a network from the variables of the problem (positions, parameters and frequency of the APs), the planning of WLAN networks faces several difficulties. In particular, the location of APs and the allocation of frequencies. There is no single model to solve the problem of designing wireless local networks. Depending on the situations and the hypotheses studied, different criteria can be considered and expressed in terms of constraints to be observed or in terms of objectives to be optimized. The first distinction is to separate the financial criteria from the network quality criteria. The nature of these two criteria being fundamentally different. Then there are a variety of service quality criteria, but we can still group them into three main categories: coverage criteria, interference criteria and capacity criteria.. In this article, we will use an optimization method based on an algorithm of stochastic optimization, which is also based on the mechanisms of natural selection and of genetic. It is genetic algorithm. Our goal consist of minimizing the total interaction between the APs to perform the good choices when deploying a network 802.11g in a way that gives users signal-to-interference ratios (SIR) greater than the required threshold ß.

A Bandwidth and Energy Aware QoS Routing Protocol for Enhanced Performance in Ad-hoc Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 203-213
Author(s):  
Priyanka Bharadwaj ◽  
Surjeet Balhara
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Qos Routing ◽  
Delivery Ratio ◽  
Energy Aware ◽  
Multimedia Services ◽  
Average Delay ◽  
Hoc Networks

Background & Objective: There are some challenging issues such as providing Quality of Service (QoS), restricted usage of channels and shared bandwidth pertaining to ad-hoc networks in a dynamic topology. Hence, there is a requirement to support QoS for the application environment and multimedia services in ad-hoc networks with the fast growing and emerging development of information technology. Eventually, bandwidth is one of the key elements to be considered. Methods: Energy aware QoS routing protocol in an ad-hoc network is presented in this article. Results and Conclusion: The simulation results indicate that the improved protocol outperforms Adhoc On-Demand Distance Vector (AODV) routing protocol in terms of QoS metric such as throughput, packet delivery ratio, loss rate and average delay.

Task scheduling algorithm based on improved genetic algorithm in cloud computing environment

2020 ◽  
Vol 13 ◽  
Author(s):  
Ge Weiqing ◽  
Cui Yanru
Keyword(s):  
Genetic Algorithm ◽  
Cloud Computing ◽  
Task Scheduling ◽  
Scheduling Algorithm ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Fitness Functions ◽  
Task Scheduling Algorithm ◽  
Simulation Results

Background: In order to make up for the shortcomings of the traditional algorithm, Min-Min and Max-Min algorithm are combined on the basis of the traditional genetic algorithm. Methods: In this paper, a new cloud computing task scheduling algorithm is proposed, which introduces Min-Min and Max-Min algorithm to generate initialization population, and selects task completion time and load balancing as double fitness functions, which improves the quality of initialization population, algorithm search ability and convergence speed. Results: The simulation results show that the algorithm is superior to the traditional genetic algorithm and is an effective cloud computing task scheduling algorithm. Conclusion: Finally, this paper proposes the possibility of the fusion of the two quadratively improved algorithms and completes the preliminary fusion of the algorithm, but the simulation results of the new algorithm are not ideal and need to be further studied.

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