A Break for Workaholics: Energy-Efficient Selective Tuning Mechanisms for Demand-Driven-Based Wireless Environment

Abstract

Existing work on demand-driven-based wireless environments has largely focused on energyefficient caching strategies. While these schemes minimize the number of uplink requests (and hence conserve energy), they are still not adequate as clients must continue to monitor the broadcast for data that is not found in the cache or has been invalidated. Other work on disseminating data via periodic broadcasting of the data file has developed techniques that organize data to allow clients to selectively tune to the desired portion of the broadcast. Such schemes, unfortunately, cannot be applied to demand-driven-based context because demand-driven data cannot be predetermined. In this paper, we study the issue of selective tuning in a demand-driven-based environment. We propose and study three strategies that allow clients to repeatedly toggle between doze mode and active mode until the desired objects are obtained. One of the strategies is stateful-based in the sense that the server is aware of the schedule of doze-ofl/awake time determined by the clients. The other two strategies are stateless-based approaches where the clients’ schedules of doze-off/awake time depend on cues broadcast by the server. We conducted a performance study and our results demonstrate that the proposed schemes are energy efficient without sacrificing on the average access times of object retrievals. Furthermore, our results show that none of the algorithms is superior in all cases.