• العربية
    • English
  • English 
    • العربية
    • English
  • Login
Home
Publisher PoliciesTerms of InterestHelp Videos
Submit Thesis
IntroductionIUGSpace Policies
JavaScript is disabled for your browser. Some features of this site may not work without it.
View Item 
  •   Home
  • Faculty of Information Technology
  • PhD and MSc Theses- Faculty of Information Technology
  • View Item
  •   Home
  • Faculty of Information Technology
  • PhD and MSc Theses- Faculty of Information Technology
  • View Item

Please use this identifier to cite or link to this item:

http://hdl.handle.net/20.500.12358/20200
TitleEfficient Load Balancing Algorithm in Cloud Computing
Untitled
Abstract

Recently, cloud computing become a new global trend of computing. It is a modern style of using the power of Internet and wide area network (WAN) to offer resources remotely. It’s a new solution and strategy to achieve high availability, flexibility, cost reduced and on demand scalability. However cloud computing has many challenges such as poor resource utilization which has deep impact in the performance of cloud computing. These problems arisen due to the huge amounts of information. So the need for efficient and powerful cloud computing load balancing algorithms is one of the most important issues in this area to improve the performance of cloud computing. Many researchers proposed various load balancing and job scheduling algorithms in cloud computing, but there is still some inefficiency in the system performance and load still imbalance. Therefore, in this research we propose a load balancing algorithm to improve the performance and efficiency in heterogeneous cloud computing environment. We propose a hybrid algorithm based on randomization and greedy algorithm, it takes advantages of both random and greedy algorithms. The algorithm considers the current resource information and the CPU capacity factor to achieve the objectives. The hybrid algorithm has been evaluated and compared with other algorithms using CloudAnalyst simulator. The results showed improvements on average response time and on processing time by considering the current resource information and the CPU capacity factor compared with other algorithms, and this means the performance has improved.

Authors
Hafiz, Jabr Younis
Supervisors
Laa, EL Halees
Typeرسالة ماجستير
Date2015
LanguageEnglish
Publisherالجامعة الإسلامية - غزة
Citation
License
Collections
  • PhD and MSc Theses- Faculty of Information Technology [124]
Files in this item
file_1.pdf3.330Mb
Thumbnail

The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Contact Us | Send Feedback
 

 

Browse

All of IUGSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsSupervisorsThis CollectionBy Issue DateAuthorsTitlesSubjectsSupervisors

My Account

LoginRegister

Statistics

View Usage Statistics

The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

Contact Us | Send Feedback