Results 1  10
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46
Dynamic and Aggressive Scheduling Techniques for PowerAware RealTime Systems
, 2001
"... In this paper, we address poweraware scheduling of periodic hard realtime tasks using dynamic voltage scaling. Our solution includes three parts: (a) a static (offline) solution to compute the optimal speed, assuming worstcase workload for each arrival, (b) an online speed reduction mechanism t ..."
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Cited by 153 (23 self)
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In this paper, we address poweraware scheduling of periodic hard realtime tasks using dynamic voltage scaling. Our solution includes three parts: (a) a static (offline) solution to compute the optimal speed, assuming worstcase workload for each arrival, (b) an online speed reduction mechanism to reclaim energy by adapting to the actual workload, and (c) an online, adaptive and speculative speed adjustment mechanism to anticipate early completions of future executions by using the averagecase workload information. All these solutions still guarantee that all deadlines are met. Our simulation results show that the reclaiming algorithm saves a striking 50% of the energy over the static algorithm. Further, our speculative techniques allow for an additional approximately 20% savings over the reclaiming algorithm. In this study, we also establish that solving an instance of the static poweraware scheduling problem is equivalent to solving an instance of the rewardbased scheduling problem [1, 4] with concave reward functions. 1
PowerAware Scheduling for Periodic RealTime Tasks
 IEEE TRANSACTIONS ON COMPUTERS
, 2004
"... In this paper, we address poweraware scheduling of periodic tasks to reduce CPU energy consumption in hard realtime systems through dynamic voltage scaling. Our intertask voltage scheduling solution includes three components: (a) a static (o#line) solution to compute the optimal speed, assumin ..."
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Cited by 85 (19 self)
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In this paper, we address poweraware scheduling of periodic tasks to reduce CPU energy consumption in hard realtime systems through dynamic voltage scaling. Our intertask voltage scheduling solution includes three components: (a) a static (o#line) solution to compute the optimal speed, assuming worstcase workload for each arrival, (b) an online speed reduction mechanism to reclaim energy by adapting to the actual workload, and (c) an online, adaptive and speculative speed adjustment mechanism to anticipate early completions of future executions by using the averagecase workload information. All these solutions still guarantee that all deadlines are met. Our simulation results show that our reclaiming algorithm alone outperforms other recently proposed intertask voltage scheduling schemes. Our speculative techniques are shown to provide additional gains, approaching the theoretical lowerbound by a margin of 10%.
Determining Optimal Processor Speeds for Periodic RealTime Tasks with Different Power Characteristics
 IN PROCEEDINGS OF EUROMICRO CONFERENCE ON REALTIME SYSTEMS
, 2001
"... In this paper, we provide an efficient solution for periodic realtime tasks with (potentially) different power consumption characteristics. We show that a task T i can run at a constant speed S i at every instance without hurting optimality. We sketch an O(n log n) algorithm to compute the optim ..."
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Cited by 75 (11 self)
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In this paper, we provide an efficient solution for periodic realtime tasks with (potentially) different power consumption characteristics. We show that a task T i can run at a constant speed S i at every instance without hurting optimality. We sketch an O(n log n) algorithm to compute the optimal S i values. We also prove that the EDF (Earliest Deadline First) scheduling policy can be used to obtain a feasible schedule with these optimal speed values.
OnLine Scheduling on Uniform Multiprocessors
, 2001
"... Each processor in a uniform multiprocessor machine is characterized by a speed or computing capacity, with the interpretation that a job executing on a processor with speed s for t time units completes (s t) units of execution. The online scheduling of hardrealtime systems, in which all jobs mus ..."
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Cited by 52 (10 self)
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Each processor in a uniform multiprocessor machine is characterized by a speed or computing capacity, with the interpretation that a job executing on a processor with speed s for t time units completes (s t) units of execution. The online scheduling of hardrealtime systems, in which all jobs must complete by specified deadlines, on uniform multiprocessor machines is considered. It is known that online algorithms tend to perform very poorly in scheduling such hardrealtime systems on multiprocessors; resourceaugmentation techniques are presented here that permit online algorithms to perform better than may be expected given the inherent limitations. Results derived here are applied to the scheduling of periodic task systems on uniform multiprocessor machines. 1.
Maximizing The System Value While Satisfying Time And Energy Constraints
, 2002
"... this paper may be copied or distributed royalty free without further permission by computerbased and other informationservice systems. Permission to republish any other portion of this paper must be obtained from the Editor ..."
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Cited by 49 (4 self)
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this paper may be copied or distributed royalty free without further permission by computerbased and other informationservice systems. Permission to republish any other portion of this paper must be obtained from the Editor
Energy Aware Scheduling for Distributed RealTime Systems
 In International Parallel and Distributed Processing Symposium
, 2003
"... Power management has become popular in mobile computing as well as in server farms. Although a lot of work has been done to manage the energy consumption on uniprocessor realtime systems, there is less work done on their multicomputer counterparts. For a set of realtime tasks with precedence const ..."
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Cited by 45 (2 self)
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Power management has become popular in mobile computing as well as in server farms. Although a lot of work has been done to manage the energy consumption on uniprocessor realtime systems, there is less work done on their multicomputer counterparts. For a set of realtime tasks with precedence constraints executing on a distributed system, we propose new static and dynamic power management schemes. Assuming a given static schedule generated from any list scheduling heuristic algorithm, our static power management scheme uses the static slack (if any) based on the degree of parallelism in the schedule. To consider the runtime behavior of tasks, an online dynamic power management technique is proposed to further explore the idle periods of processors. By comparing our static technique with the simple static power management, where the static slack is distributed to the schedule proportionally, we find that our static scheme can save an average of 10 % more energy. When combined with dynamic schemes, our schemes significantly improve energy savings. 1
Tardiness bounds under global EDF scheduling on a multiprocessor
 In Proceedings of the 26th IEEE RealTime Systems Symposium
, 2005
"... This paper considers the scheduling of soft realtime sporadic task systems under global EDF on an identical multiprocessor. Though Pfair scheduling is theoretically optimal for hard realtime task systems on multiprocessors, it can incur significant runtime overhead. Hence, other scheduling algor ..."
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Cited by 44 (33 self)
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This paper considers the scheduling of soft realtime sporadic task systems under global EDF on an identical multiprocessor. Though Pfair scheduling is theoretically optimal for hard realtime task systems on multiprocessors, it can incur significant runtime overhead. Hence, other scheduling algorithms that are not optimal, including EDF, have continued to receive considerable attention. However, prior research on such algorithms has focussed mostly on hard realtime systems, where, to ensure that all deadlines are met, approximately 50 % of the available processing capacity will have to be sacrificed in the worst case. This may be overkill for soft realtime systems that can tolerate deadline misses by bounded amounts (i.e., bounded tardiness). In this paper, we derive tardiness bounds under preemptive and nonpreemptive global EDF on multiprocessors when the total utilization of a task system is not restricted and may equal the number of processors. Our tardiness bounds depend on pertask utilizations and execution costs — the lower these values, the lower the tardiness bounds. As a final remark, we note that global EDF may be superior to partitioned EDF for multiprocessorbased soft realtime systems in that the latter does not offer any scope to improve system utilization even if bounded tardiness can be tolerated.
Maximizing Rewards for RealTime Applications with Energy Constraints
 IN ACM TRANSACTIONS ON EMBEDDED COMPUTER SYSTEMS, ACCEPTED
, 2003
"... ... this paper we propose a solution to this problem; to our knowledge, this is the first solution that combines the three constraints mentioned above. We devise two algorithms, an optimal algorithm for homogeneous applications (with respect to power consumption) and a heuristic iterative algorithm ..."
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Cited by 30 (3 self)
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... this paper we propose a solution to this problem; to our knowledge, this is the first solution that combines the three constraints mentioned above. We devise two algorithms, an optimal algorithm for homogeneous applications (with respect to power consumption) and a heuristic iterative algorithm that can also accommodate heterogeneous applications (that is, those with different power consumption functions). We show by simulation that our iterative algorithm is fast and within 1% of the optimal.
Multiversion Scheduling in Rechargeable Energyaware Realtime Systems
 Journal of Embedded Computing
, 2003
"... In the context of batterypowered realtime systems three constraints need to be addressed: energy, deadlines and task rewards. Many future realtime systems will count on different software versions, each with different rewards, time and energy requirements, to achieve a variety of QoSaware tradeo ..."
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Cited by 27 (1 self)
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In the context of batterypowered realtime systems three constraints need to be addressed: energy, deadlines and task rewards. Many future realtime systems will count on different software versions, each with different rewards, time and energy requirements, to achieve a variety of QoSaware tradeoffs. We propose a solution that allows the device to run the most valuable task versions while still meeting all deadlines and without depleting the energy. Assuming that the battery is rechargeable, we also propose (a) a static solution that maximizes the system value assuming a worstcase scenario (i.e., worstcase task execution times); and (b) a dynamic scheme that takes advantage of the extra energy in the system when worstcase scenarios do not happen. Three dynamic policies are shown to make better use of the recharging energy while improving the system value. 1
Energy Reduction Techniques for Multimedia Applications with Tolerance to Deadline Misses
 in ACM/IEEE Design Automation Conference (DAC), 2003
, 2003
"... Many embedded systems such as PDAs require processing of the given applications with rigid power budget. However, they are able to tolerate occasional failures due to the imperfect human visual/auditory systems. The problem we address in this paper is how to utilize such tolerance to reduce multimed ..."
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Cited by 25 (8 self)
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Many embedded systems such as PDAs require processing of the given applications with rigid power budget. However, they are able to tolerate occasional failures due to the imperfect human visual/auditory systems. The problem we address in this paper is how to utilize such tolerance to reduce multimedia system's energy consumption for providing guaranteed quality of service at the user level in terms of completion ratio. We explore a range of o#ine and online strategies that take this tolerance into account in conjunction with the modest nondeterminism in application's execution time. First, we give a simple beste#ort approach that achieves the maximum completion ratio; then we propose an enhanced online beste#ort energy minimization (BEEM) approach and a hybrid o#ine/online minimume #ort (O ME) approach. We prove that BEEM maintains the maximum completion ratio while consuming the provably least amount of energy and O ME guarantees the required completion ratio statistically. We apply both approaches to a variety of benchmark task graphs, most from popular DSP applications. Simulation results show that significant energy savings (38% for BEEM and 54% for O ME, both over the simple beste#ort approach) can be achieved while meeting the required completion ratio requirements.