Scheduling and Load Balancing in Large Scale Distributed Computing Environments

Summary

The project involves the development of resource allocation algorithms for large scale distributed systems for solving a variety of scheduling and load-balancing problems for static and dynamic scenarios.

Supervisor(s)

Professor Albert Y. Zomaya

Research Location

Computer Science

Program Type

Masters/PHD

Synopsis

Large scale distributed systems (e.g. Grid Computing, Cloud Computing) are quite prevalent today. These systems provide high performance capabilities to a wide range of applications. These applications normally have different, and sometimes conflicting, requirements. This will necessitate the development of more flexible scheduling techniques. Another factor which is detrimental to the performance of such these systems is the dynamic nature of such combination of heterogeneous resources that are, for most of the time, located in disparate locations. In addition, the availability of resources (e.g. computational, storage, etc) for some of the time does not mean that such resources will be available all the time. Such conditions will add more complexity to the design of these schedulers. This also suggests the need to suites of schedulers that can be used in different operating scenarios. This project deals with the study and development of a variety of scheduling scenarios and algorithms that can help in achieving the ultimate goal of furthering our understanding of scheduling in large scale distributed systems.

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Keywords

parallel systems, grid computing, cloud computing, internet-scale computing systems, Distributed computing, optimization, resource allocation, ICT, Distributed systems

Opportunity ID

The opportunity ID for this research opportunity is: 976

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