Energy-aware wireless systems with adaptive power-fidelity tradeoffs

Raghunathan, Vijay; Pereira, Cristiano; Srivastava, Mani; Gupta, Rajesh K.

doi:10.1109/tvlsi.2004.840773

Cited by 43 publications

(23 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Nonetheless, there are some other types of networked embedded systems, such as multimedia terminals and 3G cell phones, where energy conservation and low delay need to be simultaneously realized [13], [22]. Therefore, a more general energy-delay efficiency scheme that can be applied to a wide range of networked embedded systems is wanted.…”

Section: Related Work and Motivationmentioning

confidence: 99%

“…N ETWORKED embedded systems like wireless sensor networks and multimedia terminals have increasingly become popular as platforms for executing collaborative applications such as target tracking and infrastructure monitoring since the last decade [2], [8], [12], [17], [22]. Much of this trend can be attributed to rapid advances in processing power, network bandwidth, and storage capacity.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Energy-Delay Tunable Task Allocation Strategy for Collaborative Applications in Networked Embedded Systems

Xie

Qin

2008

IEEE Trans. Comput.

View full text Add to dashboard Cite

Abstract-Collaborative applications with energy and low-delay constraints are emerging in various networked embedded systems like wireless sensor networks and multimedia terminals. Conventional energy-aware task allocation schemes developed for collaborative applications only concentrated on energy savings when making allocation decisions. Consequently, the length of the schedules generated by such allocation schemes could be very long, which is unfavorable or, in some situations, even not tolerated. To remedy this problem, we developed a novel task allocation strategy called Balanced Energy-Aware Task Allocation (BEATA) for collaborative applications running on heterogeneous networked embedded systems. The BEATA algorithm aims at blending an energy-delay efficiency scheme with task allocations, thereby making the best trade-offs between energy savings and schedule lengths. Aside from that, we introduced the concept of an energy-adaptive window, which is a critical parameter in the BEATA strategy. By fine-tuning the size of the energy-adaptive window, users can readily customize BEATA to meet their specific energy-delay trade-off needs imposed by applications. Further, we built a mathematical model to approximate the energy consumption caused by both computation and communication activities. Experimental results show that BEATA significantly improves the performance of embedded systems in terms of energy savings and schedule length over existing allocation schemes.

show abstract

Section: Related Work and Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Energy-Delay Tunable Task Allocation Strategy for Collaborative Applications in Networked Embedded Systems

Xie

Qin

2008

IEEE Trans. Comput.

View full text Add to dashboard Cite

show abstract

“…Several of these schemes require run-time values for power and energy consumption as an input to the system [12,13,14]. However, run-time power and energy consumption values have not been feasibly available at run-time until recently [2].…”

Section: Related Workmentioning

confidence: 99%

Energy Driven Application Self-Adaptation at Run-time

Peddersen

Parameswaran

2008

JCP

View full text Add to dashboard Cite

Until recently, there has been a lack of methods to trade-off energy use for quality of service at run-time in stand-alone embedded systems. Such systems are motivated by the need to increase the apparent available battery energy of portable devices, with minimal compromise in quality. The available systems either drew too much power or added considerable overheads due to task swapping. In this paper we demonstrate a feasible method to perform these trade-offs. This work has been enabled by a low-impact power/energy estimating processor which utilizes counters to estimate power and energy consumption at run-time. Techniques are shown that modify multimedia applications to differ the fidelity of their output to optimize the energy/quality trade-off. Two adaptation algorithms are applied to multimedia applications demonstrating the efficacy of the method. The method increases code size by 1% and execution time by 0.02%, yet is able to produce an output which is acceptable and processes up to double the number of frames.

show abstract

“…As a result, power-aware algorithms have recently been the subjects of extensive research [2][3][4][5][6] regarding various key issues such as localization, deployment, environment estimation and coverage control, rendezvous and consensus. For example, energy-efficient localization algorithms were proposed to reposition sensors in desired locations in order to recover or enhance network coverage or to maximize the covered area in [7,8] and [9].…”

Section: Introductionmentioning

confidence: 99%