Othman, Mazliza; (1999) Load Sharing as a Power Management Strategy for Mobile Computers. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Load sharing has traditionally been used to improve system performance in distributed networks by transferring jobs from heavily loaded hosts to idle or lightly loaded hosts. Performance is improved by distributing workload more evenly among hosts, thus better utilising system resources. This thesis investigates the use of load sharing for a different purpose, that is as a power management strategy for mobile computers. Since mobile computers operate on limited battery power, which is a scarce resource, and there is unlikely to be a vast improvement in battery capacity in the near future, it is vital that power utilisation is managed efficiently and economically. The power management strategy proposed in this thesis is based on the concept of load sharing. The strategy attempts to reduce power consumption by the CPU, which is one of the components consuming a substantial amount of power, by off-loading computations from a mobile computer to a fixed host. A load sharing algorithm which selects suitable jobs for remote execution is proposed. When designing the algorithm, the inherent limitation of wireless networks must be taken into account. For example, low bandwidth means that communications delays are no longer negligible; sending and receiving messages must also be considered carefully as transmitting and receiving also consume a substantial amount of power. Consequently, when performing load sharing on wireless networks, more constraints have to be dealt with compared to when performing load sharing on fixed networks. In addition to reducing power consumption, transferring jobs for remote execution also gives users access to faster machines, thus improving response time. This study identifies the conditions and factors which make job transfer a viable option. The results obtained show that under suitable conditions, load sharing can extend battery lifetime significantly. Since stability is an important concern when designing load sharing algorithms, this issue is also addressed by this study.

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