An Efficient Data Broadcasting Scheduler for Energy-Constraint Broadcast Servers

Abstract. In this paper, we study the problem of maximizing the data broadcasting server’s service rate, defined as the ratio of satisfied vs. unsatisfied time-constrained data requests in an energy-limited on-demand data dissemination environment. The paper’s main contribution is an algorithm, called PBS (standing for Power-aware Broadcast Scheduler), with O(n) space and time requirements, which significantly outperforms state-of-the-art on-demand real-time scheduling algorithms in terms of its primary performance metric, i.e., the service rate. Additionally, even though designed to maximize the service rate of the server, it only slightly underperforms other schedulers in terms of the mean response time which use this metric as the main performance criterion. Our further contribution is the PBSlight algorithm, which is a low-overhead, approximate and parameterized variant of PBS. Even though still running in linear time, PBSlight significantly reduces the scheduling costs of PBS. Additionally, it provides performance results comparable to or even slightly better than those of PBS, however, at the expense of servicing requests for less frequently requested data items less often. The third contribution is that both proposed algorithms are built upon the criteria of providing continuous broadcasting services to mobile clients until either the estimated service period is completed or battery resources are recharged. This objective is achieved by calculating a broadcast area schedule which maps regional communication areas located within the communication coverage area of the server to upcoming broadcast cycles in accordance to the durability of the available energy resources and the workload conditions of the server.