Cloud computing" is a term, which involves virtualization, distributed computing, networking, software and web services. A cloud consists of several elements such as clients, datacenter and distributed servers. It includes fault tolerance, high availability, scalability, flexibility, reduced overhead for users, reduced cost of ownership, on demand services etc.
Central to these issues lies the establishment of an effective load balancing algorithm. The load can be CPU load, memory capacity, delay or network load. Load balancing is the process of distributing the load among various nodes of a distributed system to improve both resource utilization and job response time while also avoiding a situation where some of the nodes are heavily loaded while other nodes are idle or doing very little work. Load balancing ensures that all the processor in the system or every node in the network does approximately the equal amount of work at any instant of time. This technique can be sender initiated, receiver initiated or symmetric type (combination of sender initiated and receiver initiated types).
Our objective is to develop an effective load balancing algorithm using Divisible load scheduling theorm to maximize or minimize different performance parameters (throughput, latency for example) for the clouds of different sizes (virtual topology depending on the application requirement).
[1]
Saudi Arabia,et al.
A Guide to Dynamic Load Balancing in Distributed Computer Systems
,
2010
.
[2]
Mladen A. Vouk,et al.
Cloud computing — Issues, research and implementations
,
2008,
ITI 2008 - 30th International Conference on Information Technology Interfaces.
[3]
Peter S. Pacheco.
Parallel programming with MPI
,
1996
.
[4]
Martin Randles,et al.
A Comparative Experiment in Distributed Load Balancing
,
2009,
2009 Second International Conference on Developments in eSystems Engineering.
[5]
Thomas G. Robertazzi,et al.
Load Scheduling for Measurement and Data Reporting in Wireless Sensor Networks
,
2004
.
[6]
A. Taleb-Bendiab,et al.
A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing
,
2010,
2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.
[7]
Rini Mahajan,et al.
Cloud Computing Issues
,
2005
.
[8]
M. Moges,et al.
Wireless sensor networks: scheduling for measurement and data reporting
,
2006,
IEEE Transactions on Aerospace and Electronic Systems.