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123
Energy Consumption in Mobile Phones: A Measurement Study and Implications for Network Applications
, 2009
"... In this paper, we present a measurement study of the energy consumption characteristics of three widespread mobile networking technologies: 3G, GSM, and WiFi. We find that 3G and GSM incur a high tail energy overhead because of lingering in high power states after completing a transfer. Based on the ..."
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Cited by 209 (2 self)
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In this paper, we present a measurement study of the energy consumption characteristics of three widespread mobile networking technologies: 3G, GSM, and WiFi. We find that 3G and GSM incur a high tail energy overhead because of lingering in high power states after completing a transfer. Based on these measurements, we develop a model for the energy consumed by network activity for each technology. Using this model, we develop TailEnder, a protocol that reduces energy consumption of common mobile applications. For applications that can tolerate a small delay such as email, TailEnder schedules transfers so as to minimize the cumulative energy consumed while meeting userspecified deadlines. We show that the TailEnder scheduling algorithm is within a factor 2 × of the optimal and show that any online algorithm can at best be within a factor 1.62 × of the optimal. For applications like web search that can benefit from prefetching, TailEnder aggressively prefetches several times more data and improves userspecified response times while consuming less energy. We evaluate the benefits of TailEnder for three different case study applications—email, news feeds, and web search—based on real user logs and show significant reduction in energy consumption in each case. Experiments conducted on the mobile phone show that TailEnder can download 60 % more news feed updates and download search results for more than 50 % of web queries, compared to using the default policy.
Speed scaling to manage energy and temperature
 Journal of the ACM
"... We first consider online speed scaling algorithms to minimize the energy used subject to the constraint that every job finishes by its deadline. We assume that the power required to run at speed s is P s s. We provide a tight bound on the competitive ratio of the previously proposed Optimal A ..."
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Cited by 169 (17 self)
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We first consider online speed scaling algorithms to minimize the energy used subject to the constraint that every job finishes by its deadline. We assume that the power required to run at speed s is P s s. We provide a tight bound on the competitive ratio of the previously proposed Optimal Available algorithm. This improves the best known competitive ratio by a factor of . We then introduce a new online algorithm, and show that this algorithm’s competitive ratio is at most e. This competitive ratio is significantly better and is approximately e for large . Our result is essentially tight for large . In particular, as approaches infinity, we show that any algorithm must have competitive ratio e (up to lower order terms). We then turn to the problem of dynamic speed scaling to minimize the maximum temperature that the device ever reaches, again subject to the constraint that all jobs finish by their deadlines. We assume that the device cools according to Fourier’s law. We show how to solve this problem in polynomial time, within any error bound, using the Ellipsoid algorithm. 1.
Leakage aware dynamic voltage scaling for realtime embedded systems
 In CECS
, 2003
"... A fivefold increase in leakage current is predicted with each technology generation. While Dynamic Voltage Scaling (DVS) is known to reduce dynamic power consumption, it also causes increased leakage energy drain by lengthening the interval over which a computation is carried out. Therefore, for mi ..."
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Cited by 139 (8 self)
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A fivefold increase in leakage current is predicted with each technology generation. While Dynamic Voltage Scaling (DVS) is known to reduce dynamic power consumption, it also causes increased leakage energy drain by lengthening the interval over which a computation is carried out. Therefore, for minimization of the total energy, one needs to determine an operating point, called the critical speed. We compute processor slowdown factors based on the critical speed for energy minimization. Procrastination scheduling attempts to maximize the duration of idle intervals by keeping the processor in a sleep/shutdown state even if there are pending tasks, within the constraints imposed by performance requirements. Our simulation experiments show that the critical speed slowdown results in up to 5 % energy gains over a leakage oblivious dynamic voltage scaling. Procrastination scheduling scheme extends the sleep intervals to up to 5 times, resulting in up to an additional 18 % energy gains, while meeting all timing requirements.
Energyefficient algorithms for flow time minimization
 In Proc. of STACS 2006
"... Topic classification: Algorithms and data structures We study scheduling problems in batteryoperated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadlinebased settings, in this paper we are i ..."
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Cited by 95 (4 self)
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Topic classification: Algorithms and data structures We study scheduling problems in batteryoperated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadlinebased settings, in this paper we are interested in schedules that guarantee a good QualityofService. More specifically, our goal is to schedule a sequence of jobs on a variable speed processor so as to minimize the total cost consisting of the power consumption and the total flow time of all the jobs. We first show that when the amount of work, for any job, may take an arbitrary value, then no online algorithm can achieve a constant competitive ratio. Therefore, most of the paper is concerned with unitsize jobs. We devise a deterministic constant competitive online algorithm and show that the offline problem can be solved in polynomial time. 1
Getting the Best Response for Your Erg
"... We consider the speed scaling problem of minimizing the average response time of a collection of dynamically released jobs subject to a constraint A on energy used. We propose an algorithmic approach in which an energy optimal schedule is computed for a huge A, and then the energy optimal schedule ..."
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Cited by 64 (10 self)
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We consider the speed scaling problem of minimizing the average response time of a collection of dynamically released jobs subject to a constraint A on energy used. We propose an algorithmic approach in which an energy optimal schedule is computed for a huge A, and then the energy optimal schedule is maintained as A decreases. We show that this approach yields an efficient algorithm for equiwork jobs. We note that the energy optimal schedule has the surprising feature that the job speeds are not monotone functions of the available energy. We then explain why this algorithmic approach is problematic for arbitrary work jobs. Finally, we explain how to use the algorithm for equiwork jobs to obtain an algorithm for arbitrary work jobs that is O(1)approximate with respect to average response time, given an additional factor of (1 + ffl)energy.
Speed Scaling Functions for Flow Time Scheduling based on Active Job Count
"... Abstract. We study online scheduling to minimize flow time plus energy usage in the dynamic speed scaling model. We devise new speed scaling functions that depend on the number of active jobs, replacing the existing speed scaling functions in the literature that depend on the remaining work of activ ..."
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Cited by 46 (12 self)
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Abstract. We study online scheduling to minimize flow time plus energy usage in the dynamic speed scaling model. We devise new speed scaling functions that depend on the number of active jobs, replacing the existing speed scaling functions in the literature that depend on the remaining work of active jobs. The new speed functions are more stable and also more efficient. They can support better job selection strategies to improve the competitive ratios of existing algorithms [5,8], and, more importantly, to remove the requirement of extra speed. These functions further distinguish themselves from others as they can readily be used in the nonclairvoyant model (where the size of a job is only known when the job finishes). As a first step, we study the scheduling of batched jobs (i.e., jobs with the same release time) in the nonclairvoyant model and present the first competitive algorithm for minimizing flow time plus energy (as well as for weighted flow time plus energy); the performance is close to optimal. 1
A Survey of Techniques for Energy Efficient OnChip Communication
 Communication,” Proceedings of Design Automation Conference
, 2003
"... Interconnects have been shown to be a dominant source of energy consumption in modern day SystemonChip (SoC) designs. With a large (and growing) number of electronic systems being designed with battery considerations in mind, minimizing the energy consumed in onchip interconnects becomes crucial. ..."
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Cited by 42 (0 self)
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Interconnects have been shown to be a dominant source of energy consumption in modern day SystemonChip (SoC) designs. With a large (and growing) number of electronic systems being designed with battery considerations in mind, minimizing the energy consumed in onchip interconnects becomes crucial. Further, the use of nanometer technologies is making it increasingly important to consider reliability issues during the design of SoC communication architectures. Continued supply voltage scaling has led to decreased noise margins, making interconnects more susceptible to noise sources such as crosstalk, power supply noise, radiation induced defects, etc. The resulting transient faults cause the interconnect to behave as an unreliable transport medium for data signals. Therefore, fault tolerant communication mechanisms, such as Automatic Repeat Request (ARQ), Forward Error Correction (FEC), etc., which have been widely used in the networking community, are likely to percolate to the SoC domain.
Speed scaling on parallel processors
 In Proc. 19th Annual Symp. on Parallelism in Algorithms and Architectures (SPAA’07
, 2007
"... In this paper we investigate algorithmic instruments leading to low power consumption in computing devices. While previous work on energyefficient algorithms has mostly focused on single processor environments, in this paper we investigate multiprocessor settings. We study the basic problem of sch ..."
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Cited by 40 (3 self)
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In this paper we investigate algorithmic instruments leading to low power consumption in computing devices. While previous work on energyefficient algorithms has mostly focused on single processor environments, in this paper we investigate multiprocessor settings. We study the basic problem of scheduling a set of jobs, each specified by a release time, a deadline and a processing volume, on variable speed processors so as to minimize the total energy consumption. We first settle the complexity of speed scaling with unit size jobs. More specifically, we devise a polynomial time algorithm for agreeable deadlines and prove NPhardness results for arbitrary release dates and deadlines. For the latter setting we also develop a polynomial time algorithm achieving a constant factor approximation guarantee that is independent of the number of processors. Additionally, we study speed scaling of jobs with arbitrary processing requirements and, again, develop constant factor approximation algorithms. We finally transform our offline algorithms into constant competitive online strategies.
ReliabilityAware Energy Management for Periodic RealTime Tasks
 in Proc. of the RealTime and Embedded Technology and Applications Symposium, 225–235, 2007. Absolute reliability (k = 2) 0.98 0.96 0.94 0.92 0.90 0.88 SS REO EO
"... The prominent energy management technique, Dynamic Voltage and Frequency Scaling (DVFS), was recently shown to have direct and adverse effects on system reliability. In this work, we investigate static and dynamic reliabilityaware energy management schemes for a set of periodic realtime tasks to m ..."
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Cited by 35 (19 self)
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The prominent energy management technique, Dynamic Voltage and Frequency Scaling (DVFS), was recently shown to have direct and adverse effects on system reliability. In this work, we investigate static and dynamic reliabilityaware energy management schemes for a set of periodic realtime tasks to minimize energy consumption while preserving system reliability. Focusing on EDF scheduling, we first show that the static problem is NPhard and propose two tasklevel utilizationbased heuristics. Then, we develop a joblevel dynamic (online) scheme by building on the idea of wrappertasks, to monitor and manage dynamic slack efficiently in reliabilityaware settings. Our schemes incorporate recovery tasks/jobs into the schedule as needed for reliability preservation, while still using the remaining slack for energy savings. Simulation results show that all the proposed schemes can achieve significant energy savings while preserving the system reliability. Moreover, the energy savings of the static heuristics are close to those of the static optimal solution by a margin of 5%. 1
Reliabilityaware dynamic energy management in dependable embedded realtime systems
 In Proceedings of the 12th IEEE RealTime and Embedded Technology and Applications Symposium
, 2006
"... Recent studies show that, voltage scaling, which is an efficient energy management technique, has a direct and negative effect on system reliability because of the increased rate of transient faults (e.g., those induced by cosmic particles). In this work, we propose energy management schemes that ex ..."
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Cited by 33 (17 self)
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Recent studies show that, voltage scaling, which is an efficient energy management technique, has a direct and negative effect on system reliability because of the increased rate of transient faults (e.g., those induced by cosmic particles). In this work, we propose energy management schemes that explicitly take system reliability into consideration. The proposed reliabilityaware energy management schemes dynamically schedule recoveries for tasks to be scaled down to recuperate the reliability loss due to energy management. Based on the amount of available slack, the application size and the fault rate changes, we analyze when it is profitable to reclaim the slack for energy savings without sacrificing system reliability. Checkpoint technique is further explored to efficiently use the slack. Analytical and simulation results show that, the proposed schemes can achieve comparable energy savings as ordinary energy management schemes while preserving system reliability. The ordinary energy management schemes that ignore the effects of voltage scaling on fault rate changes could lead to drastically decreased system reliability.