In this paper, voltage scaling strategies for scheduling aperiodic tasks under average delay constraints are studied. Dynamic voltage scaling in single processor systems is formulated as a constrained stochastic optimization problem for which the optimal solution can be obtained using a combination of Lagrange relaxation and the value iteration method. For multiprocessor systems, we present a two-phase approach. In the first phase, the speed settings and static workload distribution of the processors are optimized to minimize the total power dissipation. Dynamic voltage scaling techniques are then applied to each individual processor in the second phase. Both homogeneous and heterogeneous systems have been investigated. Based on queueing theory, the proposed algorithms guarantee conformity to the average delay constraint. Moreover, our simulation experiments have shown they are effective for minimizing power consumption.

As mobile computing is getting popular, there is a growing need for techniques that minimize energy consumption on battery-powered mobile devices. Processor voltage scheduling can effectively reduce processor energy consumption by lowering the processor speed. In this paper, we study voltage scheduling for real-time periodic tasks with non-preemptible sections. Three schemes are proposed: The static speed algorithm derives the minimum static feasible speed based on the stack resource policy. Due to blocking, this static speed is usually higher than the speed required for scheduling fully preemptible tasks (called the utilization speed). Two dynamic speed algorithms are then introduced to further reduce energy consumption. The novel dual speed algorithm operates the processor at the utilization speed whenever possible and switches to the higher static speed only when blocking occurs. The dual speed dynamic reclaiming algorithm reserves time budget for each job, reclaims the unused time budget from completed jobs and redistributes it to subsequent jobs so they can run at a lower speed whenever possible. Feasibility conditions for real-time task sets have been derived and proved mathematically. Simulation results show that the proposed voltage scheduling algorithms dramatically reduce processor energy consumption over non-power-aware scheduling algorithms. Furthermore, the two dynamic speed algorithms consistently outperform the static speed scheme in a wide range of system and workload conditions.

Multimedia applications over the Internet are becoming increasingly popular. The soft real-time constraints of this type of application have given rise to interesting issues for scheduling in the network as well as the end systems. The paper presents a rate-based task scheduling framework for the receiving hosts. As multimedia streams are expected to be played back at constant rate, the proposed scheme tries to maintain the specified output frame rate by assigning proper deadlines to the frames. A multimedia stream that falls behind can catch up by skipping some frames. Interference among tasks is prevented using rate-controlled servers (RCS). The performance of these schemes has been analyzed mathematically and evaluated by simulations.

Energy efficient transmission is an important issue for mobile communication devices. In this paper, we study throughput and value-based packet scheduling over a wireless link under time and energy constraints. A mobile node is required to deliver multiple data streams to multiple receivers. These data streams may have different importance and incur different energy costs. In this research, point-to-point wireless data transmission is studied. The objective is to develop schemes that selectively transmit data streams at certain power levels so that the data throughput or the value of data delivery is maximized without violating the energy and time constraints. Exploiting the special properties of the throughput maximization problem, we propose an iterative algorithm that yields the optimal transmission schedule. The value maximization problem is formulated as a convex optimization problem and the optimal results can be obtained by solving the Kuhn-Tucker conditions. When time and transmission power are allocated at discrete slots and levels, respectively, a dynamic programming approach is proposed to find the optimal value.

Streaming media is expected to become one of the most popular types of Web content in the future. Due to increasing variety of client devices and the range of access speeds to the Internet, multimedia contents may be required to be transcoded to match the client's capability. With transcoding, both the network and the proxy CPU are potential bottlenecks for streaming media delivery. This paper discusses and compares various caching algorithms designed for transcoding proxies. In particular we propose a new adaptive algorithm that dynamically selects an appropriate metric for adjusting the management policy. Experimental results show that the proposed algorithm significantly outperforms those that cache only untranscoded or only transcoded objects. Moreover motivated by the characteristics of many video compression algorithms, we investigate partitioning a video object into sections based on frame type and handling them individually for proxy caching. It is found that partitioning improves performance when CPU power rather than network bandwidth is the limiting resource, particularly when the reference pattern is not highly skewed.

As mobile computing becomes more popular, there is increasing interest in techniques that can minimize energy consumption and prolong the battery life of mobile devices. Processor voltage scheduling is an effective way of reducing energy dissipation by reducing processor speed. We study voltage scheduling for real-time periodic tasks with non-preemptible sections. Three schemes are proposed to address this problem. The static speed algorithm derives a static feasible speed based on the stack resource policy (SRP). As worst-case blocking does not always occur, the novel dual speed algorithm switches processor speed to a lower value whenever possible. The dynamic reclaiming algorithm deploys a reservation-based approach to reclaim unused run time for redistribution. It effectively decreases processor idle time and further reduces processor speed Feasibility conditions are given and proved. Simulation results show that the two dynamic algorithms can reduce processor energy consumption by up to 80 percent over the static speed scheme.