scholarly journals GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE

2012 ◽  
Vol 02 (04) ◽  
pp. 357-360
Author(s):  
Ashish Jain ◽  
◽  
Narendra S. Chaudhari ◽  
Keyword(s):  
Genetic Algorithm ◽  
Load Balance ◽  
Concept Design ◽  
Network Load ◽  
Network Load Balance

Improving the Network Load Balance by Adding an Edge

2012 ◽  
Vol 433-440 ◽  
pp. 5147-5151 ◽  
Author(s):  
Zhong Yuan Jiang ◽  
Man Gui Liang
Keyword(s):  
Network Topology ◽  
Load Balance ◽  
Network Performance ◽  
Service Providers ◽  
Traffic Load ◽  
Network Load ◽  
Heavy Burden ◽  
Suitable Location ◽  
Edge Addition ◽  
Network Load Balance

Some previously proposed ways of improving the network load balance are reducing the link overload or reducing the node overload. Traffic load of a node or traffic load of a link can be characterized by betweenness of the node or betweenness of the edge respectively. Congestion mainly happens on nodes with maximum betweenness, so one way to improve the network load balance is mainly to minimize the maximum betweenness of node in the network. We present four edge addition strategies to minimize the maximum node betweenness by adding an edge. We do experiments on three benchmark networks to verify the effectiveness of the four edge addition strategies. By analyzing the experimental results, we confirm that adding an edge at the suitable location in the network can significantly minimize the maximum betweenness of node and improve the network load balance. It is very useful to mitigate the heavy burden of the most congested router only by adding one link with small cost without changing the network topology massively. Also, our work is helpful for service providers to optimize their network performance by adding an edge or to make good network planning by optimizing the existing network topology incrementally.

scholarly journals The Analysis of Network Performance with Different Routing and Interconnection Methods

1970 ◽  
Vol 108 (2) ◽  
pp. 43-46
Author(s):  
A. Kostic-Ljubisavljevic ◽  
S. Mladenovic ◽  
V. Acimovic-Raspopovic ◽  
A. Samcovic
Keyword(s):  
Load Balance ◽  
Network Performance ◽  
Telecommunication Network ◽  
Dynamic Traffic ◽  
Traffic Routing ◽  
Network Load ◽  
Routing Method ◽  
Network Load Balance

The effects of dynamic traffic routing and interconnection charging methods on telecommunication network load balance are analyzed in this paper. The results of numerous simulations performed with software specially developed for analysis of network performances are given. It is shown that adequately chosen routing method can give good balancing of link loads which impacts the choice of networks interconnection charging agreement. Ill. 7, bibl. 11 (in English; abstracts in English and Lithuanian).http://dx.doi.org/10.5755/j01.eee.108.2.142

Study on Network Load Balancing Algorithm Based on Server Cluster System

2012 ◽  
Vol 182-183 ◽  
pp. 1978-1981 ◽  
Author(s):  
Li Lan ◽  
Chu Huan Qi
Keyword(s):  
Load Balancing ◽  
Load Balance ◽  
Cluster System ◽  
Utilization Efficiency ◽  
Server Cluster ◽  
Use Of Resources ◽  
Network Load ◽  
System Resource ◽  
Network Load Balancing ◽  
Load Balancing Algorithm

The utilization efficiency of system resources is a key issue for cluster system while load balance is an important tool to realize the efficient use of resources. Based on server cluster system, this paper puts forwards an improved self-adaptive algorithm for network load balancing. Simulation results show that the algorithm can improve the utilization efficiency of system resource and reduce the server’s response time so as to achieve the request of real time when dealing with tasks and high availability of system.

Optimization of FPSO’s Main Dimensions Using Genetic Algorithm

2012 ◽  
Author(s):  
Grzegorz Mazerski
Keyword(s):  
Genetic Algorithm ◽  
Storage Capacity ◽  
Minimum Cost ◽  
Development Project ◽  
Load Carrying Capacity ◽  
Concept Design ◽  
Field Development ◽  
Multi Objective Genetic Algorithm ◽  
Load Carrying ◽  
Steel Weight

An efficient concept design of FPSO is supported by a wide variety of tools and methods. Some use parametric solutions for a variety of projects, while others deal with project-specific issues. One of the early challenges is to establish main dimensions of the “buoyancy element” for Floating Production System. The size should provide appropriate load-carrying capacity at minimum cost within limits of a given field development project. Since the financial implications of the hull size are significant, the choice should be made by means of a proper engineering study. One of the most promising approaches to this task is to utilize Multi Objective Genetic Algorithm (MOGA) for optimization of main particulars. A method was developed that aims at finding optimum main dimensions of the FPSO unit of given storage capacity with respect to steel weight and strength. This was achieved by utilizing MOGA optimization tool available in NAPA stability software package. The paper presents procedures, challenges and samples of results of such studies. The method was recently utilized in two different FPSO concept projects. First comments and conclusions that were drawn from the results of the procedure will be presented. Some ideas for future development will also be given.

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