Energy Efficiency and Renewable Energy Management with Multi-State Power-Down Systems

A power-down system has an on-state, an off-state, and a finite or infinite number of intermediate states. In the off-state, the system uses no energy and in the on-state energy it is used fully. Intermediate states consume only some fraction of energy but switching back to the on-state comes at a cost. Previous work has mainly focused on asymptotic results for systems with a large number of states. In contrast, the authors study problems with a few states as well as systems with one continuous state. Such systems play a role in energy-efficiency for information technology but are especially important in the management of renewable energy. The authors analyze power-down problems in the framework of online competitive analysis as to obtain performance guarantees in the absence of reliable forecasting. In a discrete case, the authors give detailed results for the case of three and five states, which corresponds to a system with on-off states and three additional intermediate states “power save”, “suspend”, and “hibernate”. The authors use a novel balancing technique to obtain optimally competitive solutions. With this, the authors show that the overall best competitive ratio for three-state systems is 95 role= presentation style= box-sizing: border-box; max-height: none; display: inline; line-height: normal; text-align: left; word-spacing: normal; overflow-wrap: normal; white-space: nowrap; float: none; direction: ltr; max-width: none; min-width: 0px; min-height: 0px; border: 0px; padding: 0px; margin: 0px; position: relative; \u3e95 and the authors obtain optimal ratios for various five state systems. For the continuous case, the authors develop various strategies, namely linear, optimal-following, progressive and exponential. The authors show that the best competitive strategies are those that follow the offline schedule in an accelerated manner. Strategy “progressive” consistently produces competitive ratios significantly better than 2

Analysis of Power-Down Systems with Five States

We consider a device, which has states ON, OFF and fixed number of intermediate states.In the ON state the device uses full power whereas in the OFF state the device consumes no energy but a constant cost is associated with switching back to ON. Intermediate states use some fraction of energy proportional to the usage time but switching back to the ON state has a constant setup cost depending on the current state. Such systems are widely used to conserve energy, for example to speed scale CPUs, to control data centers, or to manage renewable energy. We analyze such a system in terms of competitive analysis and give a heuristic for finding optimal online algorithms. We then use our approach to discuss five-state systems which are widely used in practice

Competitive Power Down Methods in Green Computing

For the power-down problem one considers a device which has states OFF, ON, and a number of intermediate states. The state of the device can be switched at any time. In the OFF state the device consumes zero energy and in the ON state it works at its full power consumption. The intermediate states consume only some fraction of energy proportional to the usage time but switching back to the ON state has has different constant setup cost depending on the current state. Requests for service (i.e. for when the device has to be in the ON state) are not known in advance, thus power-down problems are studied in the framework of online algorithms, where a system has to react without knowledge of future requests. Online algorithms are analyzed in terms of competitiveness, a measure of performance that compares the solution obtained online with the optimal online solution for the same problem, where the lowest possible competitiveness is best. Power-down mechanisms are widely used to save energy and were one of the first problems to be studied in green computing. They can be used to optimize energy usage in cloud computing, or for scheduling energy supply in the smart grid. However, many approaches are simplistic, and do not work well in practice nor do they have a good theoretical underpinning. In fact, it is surprising that only very few algorithmic techniques exist. This thesis widens the algorithmic base for such problems in a number of ways. We study systems with few states which are especially relevant in real wold applications. We give exact ratios for systems with three and five states. We then introduce a new technique, called “decrease and reset”, where the algorithm automatically attunes itself to the frequency of requests, and gives a better performance for real world inputs than currently existing algorithms. We further refine this approach by a budget-based methods which keeps a tally of gains and losses as requests are processed. We also analyze systems with infinite states and devise several strategies to transition between states. The thesis gives results both in terms of theoretical analysis as well as a result of extensive simulation