World Journal of Engineering Research and Technology (WJERT) has indexed with various reputed international bodies like : Google Scholar , Index Copernicus , Indian Science Publications , SOCOLAR, China , International Institute of Organized Research (I2OR) , Cosmos Impact Factor , Research Bible, Fuchu, Tokyo. JAPAN , Scientific Indexing Services (SIS) , Jour Informatics (Under Process) , UDLedge Science Citation Index , International Impact Factor Services , International Scientific Indexing, UAE , International Society for Research Activity (ISRA) Journal Impact Factor (JIF) , International Innovative Journal Impact Factor (IIJIF) , Science Library Index, Dubai, United Arab Emirates , Scientific Journal Impact Factor (SJIF) , Science Library Index, Dubai, United Arab Emirates , Eurasian Scientific Journal Index (ESJI) , Global Impact Factor (0.342) , IFSIJ Measure of Journal Quality , 

World Journal of Engineering
Research and Technology

An International Peer Reviewed Journal for Engineering Research and Technology

ISSN 2454-695X

Impact Factor : 5.218

ICV : 79.45

News & Updation

  • Article Invited for Publication

    Article are invited for publication in WJERT Coming Issue

  • WJERT MARCH ISSUE PUBLISHED

    MARCH 2019 Issue has been successfully launched on 1 March 2019

  • WJERT New Impact Factor

    Its our Pleasure to Inform you that WJERT Impact Factor has been increased from 4.236 to 5.218 due to high quality Publication at International Level

  • ICV

    WJERT Rank with Index Copernicus Value 79.45 due to high reputation at International Level

  • New Issue Published

    Its Our pleasure to inform you that, WJERT 1 March 2019 Issue has been Published, Kindly check it on http://wjert.org/home/current_issues

Indexing

Abstract

THROUGHPUT OPTIMIZATION FOR A LAMBDA GRID NETWORK USING ADAPTIVE RESOURCE SCHEDULING TECHNIQUE

ILO Somtoochukwu F.*, Prof. H. Inyama and Dr. K. Akpado

ABSTRACT

A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multi-gigabit rate bandwidth light-path is called a Lambda Grid network. Data-intensive Grid applications require huge data transfers between grid computing nodes. Many data-intensive e-science applications like electronic very long Baseline Interfemetry (e-VLB[3] and Genomes – to – life (GTL) require aggregating several hundred Gigabytes of data files from distributed databases to computing resources (such as super computers) frequently in real time. Since data is aggregated at the time of computation, the time required to transfer the data over the network may be the main computational bottleneck. The problem of reserving bandwidth in a lambda grid has been studied extensively in the literature resulting in the proposition of a number of resource scheduling algorithm. Unfortunately, none of the existing lambda grid scheduling algorithms dynamically readjusts the scheduler to accommodate the actual amount of time that is required to transfer a file. This dissertation is focused on the investigation of an adaptive resource scheduling techniques to minimize the delay in the data aggregation task required by the computational and data intensive e-science application running on lambda grid network. Simulation was carried out using the digital model of the 24 node National Lambda Rail (NLR) lambda grid network topology created with Cisco packet tracer 7.0. Results obtained showed that the proposed algorithm achieved 14% and 30% Average Finish Time improvement over the VBLS and ViFi algorithms respectively. The proposed technique achieved a substantial reduction in blocking probability. It achieved 15.4% and 23% improvement in blocking probability over the VBLS and ViFi algorithms respectively. Results obtained for the effect of connection duration on blocking probability showed improvement of 7.5% and 18% improvement over the VBLS and VIFi algorithm respectively. At 7.55%, the proposed algorithm showed a very low job blocking rate and indicates a 16% and 29% improvements compared to the VBLS and ViFi algorithms respectively. Reduction in the variation of the effectiveness of the algorithm with job size was found. It achieved 18% and 21% improvement over the VBSL and ViFi algorithms respectively. Simulation results also indicated that the proposed algorithm gives a substantially low reservation delay as per impact of request of lambda arrival rate.

[Full Text Article]