Distributed systems offer the ability to execute a job at other nodes than the originating one. Load sharing algorithms use this ability to distribute work around the system in order to achieve greater efficiency. This is reflected in substantially reduced response times. In the majority of studies the systems on which load sharing has been evaluated have been homogeneous in nature. This thesis considers load sharing in heterogeneous systems, in which the heterogeneity is exhibited in the processing power of the constituent nodes.
Existing algorithms are evaluated and improved ones proposed. Most of the performance analysis is done through simulation. A model of diskless workstations communicating and transferring jobs by Remote Procedure Call is used. All assumptions about the overheads of inter-node communication are based upon measurements made on the university networks.
The comparison of algorithms identifies those characteristics that offer improved performance in heterogeneous systems. The level of system information required for transfer is investigated and an optimum found. Judicious use of the collected information via algorithm design is shown to account for much of the improvement. However detailed examination of algorithm behaviour compared with that of a 'optimum' load sharing scenario reveals that there are occasions when full use of all the information available is not beneficial. Investigations are carried out on the most promising algorithms to assess their adaptability, scalability and stability under a variety of differing conditions. The standard definitions of load balancing and load sharing are shown not to apply when considering heterogeneous systems.
To validate the assumptions in the simulation model a load sharing scenario was implemented on a network of Sun workstations at the University. While the scope of the implementation was somewhat limited by lack of resources, it does demonstrate the relative ease with which the algorithms can be implemented without alteration of the operating system code or modification at the kernel level
