Use this URL to cite or link to this record in EThOS:
Title: Algorithms for power savings
Author: Atkins, Leon
ISNI:       0000 0004 5356 6876
Awarding Body: University of Bristol
Current Institution: University of Bristol
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
The aim of this thesis is to analyse the real-world performance of existing speed scaling algorithms and show how to improve these algorithms by using knowledge of the data the algorithms are running on. The method for doing this was running simulations of different speed scaling algorithms, using both real-world data and simulated data. In addition, the thesis improves the best known competitive ratio for minimising the maximum temperature of a schedule by an order 6f magnitude over previous results. This shows that different algorithms work better on certain types of data than others, and so the input data should be taken into account when choosing a speed scaling algorithm to run. This also means that the best performing speed scaling algorithm is not always that with the lowest competitive ratio, and to achieve the best performance, other factors should be taken into account when choosing which algorithm to run. In addition, an algorithm for minimising the maximum temperature is given. This algorithm is an order of magnitude improvement on the previous best known algorithm, and provides a novel technique for directly analysing the temperature competitiveness of an algorithm. Overall the thesis provides novel methods of improving the real-world performance of speed scaling. It both gives improved results for temperature scheduling, and also gives a new algorithm that can give improved performance on real-world data by taking the input into account. This is in contrast to previous speed scaling algorithms that only use factors such as the number of jobs to decide at what speed to run.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available