Multiprocessor speed scaling for jobs with arbitrary sizes and deadlines

Bell, Paul C.; Wong, Prudence W. H.

doi:10.1007/s10878-013-9618-8

Cited by 14 publications

(2 citation statements)

References 32 publications

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“…Chan et al [15] proposed an algorithm, the scheduling with arrival time alignment, which is

false(1 + τ false)

‐speed

O false(1 / τ^{2} false)

‐competitive with sleep management for the objective of minimising flow time plus energy. Bell and Wong [16] studied an energy efficient deadline scheduling on multiprocessors and proposes a deterministic online algorithm for the general setting and showed that it is

O false(normallo g^{α} R false)

‐competitive, where R is the ratio of the maximum to the minimum job size. Sun et al [17] gave an online non‐clairvoyant algorithm N‐EQUI for the objective of total flow time plus energy.…”

Section: Related Resultsmentioning

confidence: 99%

Energy‐aware online non‐clairvoyant multiprocessor scheduling: multiprocessor priority round robin

Singh

Hailu

2016

IET Computers & Digital Techniques

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In the current epoch, the energy consumption is a great concern in the online non‐clairvoyant job scheduling. The online non‐clairvoyant scheduling is studied less extensively than the online clairvoyant scheduling. The authors study non‐clairvoyant scheduling problem of minimising the total prioritised flow time plus energy, where the jobs with arbitrary sizes and priorities arrive online. The authors consider unbounded speed model in multiprocessor settings, where the speed of m individual processors can vary from zero to infinity, i.e. [0, ∞), to save the energy and to optimise the prioritised flow time plus energy. The authors consider the traditional power function bold-italicP)(s=sα, where s is the speed of a processor and α > 1, a constant. In this study, the authors introduce an online non‐clairvoyant scheduling multiprocessor priority round robin (MPRR), which is bold-italicOfalse(bold-italicαfalse)‐competitive; more precisely )(false(2α2/false(bold-italicα−false(1/2false)false)false)‐competitive, i.e. the competitive ratio is 5.33 for α = 2 and 7.3 for α = 3. In this study, the algorithm is studied using the potential analysis against an optimal offline adversary.

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“…Chan et al [15] proposed an algorithm, the scheduling with arrival time alignment, which is

false(1 + τ false)

‐speed

O false(1 / τ^{2} false)

O false(normallo g^{α} R false)

‐competitive, where R is the ratio of the maximum to the minimum job size. Sun et al [17] gave an online non‐clairvoyant algorithm N‐EQUI for the objective of total flow time plus energy.…”

Section: Related Resultsmentioning

confidence: 99%

Energy‐aware online non‐clairvoyant multiprocessor scheduling: multiprocessor priority round robin

Singh

Hailu

2016

IET Computers & Digital Techniques

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“…The scheduling policy applied on every processor is a variant of weighted round robin (WRR), wherein the larger speed is allotted to jobs residing at the tail of the queue (like Latest Arrival Processor Sharing (LAPS) and Weighted Latest Arrival Processor Sharing (WLAPS)). Bell et al [39] proposed an online deterministic clairvoyant algorithm dual-classified round robin (DCRR) for the multiprocessor system using the traditional power function. The motive of 2 4α log α P + α α 2 α−1 -competitive DCRR is to schedule the jobs so that they can be completed within deadlines using minimum energy, i.e., the objective is to maximize the throughput and energy consumption.…”

Section: Related Workmentioning

confidence: 99%

Managing Energy Plus Performance in Data Centers and Battery-Based Devices Using an Online Non-Clairvoyant Speed-Bounded Multiprocessor Scheduling

Singh

Khan

Mahela³

et al. 2020

Applied Sciences

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An efficient scheduling reduces the time required to process the jobs, and energy management decreases the service cost as well as increases the lifetime of a battery. A balanced trade-off between the energy consumed and processing time gives an ideal objective for scheduling jobs in data centers and battery based devices. An online multiprocessor scheduling multiprocessor with bounded speed (MBS) is proposed in this paper. The objective of MBS is to minimize the importance-based flow time plus energy (IbFt+E), wherein the jobs arrive over time and the job’s sizes are known only at completion time. Every processor can execute at a different speed, to reduce the energy consumption. MBS is using the tradition power function and bounded speed model. The functioning of MBS is evaluated by utilizing potential function analysis against an offline adversary. For processors m ≥ 2, MBS is O(1)-competitive. The working of a set of jobs is simulated to compare MBS with the best known non-clairvoyant scheduling. The comparative analysis shows that the MBS outperforms other algorithms. The competitiveness of MBS is the least to date.

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An Exact Algorithm for Non-preemptive Peak Demand Job Scheduling

Yaw

Mumey

2014

Combinatorial Optimization and Applications

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Multiprocessor speed scaling for jobs with arbitrary sizes and deadlines

Cited by 14 publications

References 32 publications

Energy‐aware online non‐clairvoyant multiprocessor scheduling: multiprocessor priority round robin

Energy‐aware online non‐clairvoyant multiprocessor scheduling: multiprocessor priority round robin

Managing Energy Plus Performance in Data Centers and Battery-Based Devices Using an Online Non-Clairvoyant Speed-Bounded Multiprocessor Scheduling

An Exact Algorithm for Non-preemptive Peak Demand Job Scheduling

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