Dynamic Voltage/Frequency Scaling (DVFS) allows designers to improve energy efficiency through adjusting supply voltage at runtime in order to meet the workload demand. Previous works solving real-time DVFS problems often refer to the canonical schedules with the exponential length. Other solutions for online scheduling depend on empirical or stochastic heuristics, which potentially result in frequent fluctuations of voltage/speed scaling. This paper aims at increasing the schedule predictability using period transformation in the pinwheel task model and improves the control on power-awareness by decreasing the speeds of as many tasks as possible to the same level. Experimental results show the maximum energy savings of 6% over the recent Dynamic Power Management (DPM) method and 12% over other slack reclamation algorithms.

This paper addresses an application of the potential game theory to a power-aware mobile sensor coverage problem where each sensor tries to maximize a probability of target detection in a convex mission space. The probability of target detection depends on a sensing voltage of each mobile sensor as well as its current position. While a higher sensing voltage improves the target detection probability, this requires more power consumption. In this paper, we assume that mobile sensors have different sensing capabilities of detecting a target and they can adaptively change sensing areas by adjusting their sensing voltages. We consider an objective function to evaluate a trade-off between improving the target detection probability and reducing total power consumption of all sensors. We represent a sensing voltage and a position of each mobile sensor using a barycentric coordinate over an extended strategy space. Then, the sensor coverage problem can be formulated as a potential game where the power-aware objective function and the barycentric coordinates correspond to a potential function and players' mixed strategies, respectively. It is known that all local maximizers of a potential function in a potential game are equilibria of replicator dynamics. Based on this property of potential games, we propose decentralized control for the power-aware sensor coverage problem such that each mobile sensor finds a locally optimal position and sensing voltage by updating its barycentric coordinate using replicator dynamics.

Power-aware scheduling problem has been a recent issue in cluster systems not only for operational cost due to electricity cost, but also for system reliability. In this paper, we provide SLA-based scheduling algorithms for bag-of-tasks applications with deadline constraints on power-aware cluster systems. The scheduling objective is to minimize power consumption as long as the system provides the service levels of users. A bag-of-tasks application should finish all the sub-tasks before the deadline as the service level. We provide the power-aware scheduling algorithms for both time-shared and space-shared resource sharing policies. The simulation results show that the proposed algorithms reduce much power consumption compared to static voltage schemes.

Viable techniques such as dynamic voltage scaling (DVS) provide a new design technique to balance system performance and energy saving. In this paper, we extend previous works on task assignment problems for a set of linear-pipeline tasks over a set of processors. Different from previous works, we revisit the problems with two additional system factors: deadline and energy-consumption, which are key factors in real-time and power-aware computation. We propose an O(nm2) time complexity algorithm to determine optimal task-assignment and speed-setting schemes leading to minimal energy consumption, for a given set of m real-time tasks running on n identical processors (with or without DVS supports). The same result can be extended to a restricted form of heterogeneous processor model. Meanwhile, we show that on homogeneous processor model more efficient algorithms can be applied and result in time complexity of O(m2) when m ≤ n. For completeness, we also discuss cases without contiguity constraints. We show under such cases the problems become at least as hard as NP-hard.

A radio network (RN for short) is a distributed system with no central arbiter, consisting of n radio transceivers, henceforth referred to as stations. We assume that the stations run on batteries and expends power while broadcasting/receiving a data packet. Thus, the most important measure to evaluate protocols on the radio network is the number of awake time slots, in which a station is broadcasting/receiving a data packet. We also assume that the stations are identical and have no unique ID number, and no station knows the number n of the stations. For given n keys one for each station, the ranking problem asks each station to determine the number of keys in the RN smaller than its own key. The main contribution of this paper is to present an optimal randomized ranking protocol on the k-channel RN. Our protocol solves the ranking problem, with high probability, in O(+log n) time slots with every station being awake for at most O(log n) time slots. We also prove that any randomized ranking protocol is required to run in expected Ω(+log n) time slots with at least one station being awake for expected Ω(log n) time slots. Therefore, our ranking protocol is optimal.

Mobile applications require software reconfiguration to improve resource usage and availability. We propose a power-aware reconfiguration scheme that (1) moves energy-demanding applications to proxy servers, and (2) adjusts the fidelity of mobile applications as resources diminish. We formulate a cooperative reconfiguration plan which determines when, where, and which components should be deployed and have their fidelity controlled, so as to minimize the power consumption of mobile devices and to utilize the system resources of servers efficiently. We then construct a graph-theoretic model of the cost of migrating components to one proxy server or to a cluster of servers. In this model, changes to the residual energy of mobile devices, available server resources, and the wireless network bandwidth can all accelerate or decelerate the migration and fidelity control of applications. We suggest an approximation algorithm that achieves a near-optimal solution in terms of energy consumption. Our proposal will support mobile applications which require large amount of computation and need to maintain their services for an extended time such as video conferencing, multimedia e-mail, and real-time navigation. Simulation-based experiments verify that our scheme is an efficient way to extend the battery life of mobile devices and to improve the response time of mobile applications.

An energy-efficient power-aware design is highly desirable for DSP functions that encounter a wide diversity of operating scenarios in battery-powered wireless sensor network systems. Addressing this issue, this letter presents a low-power power-aware scalable pipelined Booth multiplier that makes use of dynamic-range detection unit, sharing common functional units, ensemble of optimized Wallace-trees and a 4-bit array-based adder-tree for DSP applications.

The conditional sum adder (CSA) has been shown to outperform other adders applied in high-speed applications. This investigation proposes a modified CSA called the conditional carry adder (CCA). Based on the proposed adder architecture, six 64-bit hybrid dual-threshold CCAs for power-aware applications were discussed. Architectural modification of the CCA raises the operation speed, decreases the power dissipation, and lowers the hardware overhead. The proposed 64-bit CCA can decrease the number of multiplexers and internal nodes in the adder design by around 27% compared to the 64-bit CSA. Furthermore, components on critical paths use a low threshold voltage to accelerate the speed of operation, and other components use the normal threshold voltage to save power. This feature is very useful in implementing power-aware arithmetic systems. One of the proposed circuits has the lowest power-delay product and energy-delay product. The hybrid circuit represents a fine compromise between power and performance. Its power efficiency is better than that of the single threshold voltage circuit designs.