Heterogeneous makespan and energy-constrained DAG scheduling

Young, Bobby Dalton; Pasricha, Sudeep; Maciejewski, Anthony A.; Siegel, Howard Jay; Smith, J.T.

doi:10.1145/2480347.2480348

Cited by 10 publications

(5 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Tasks in the DAG may be either preemptive or non-preemptive and we have concentrated on scheduling non-preemptive jobs. The objectives of scheduling are multifold: minimizing schedule length [7][8][9][10][11][12], minimizing tardiness [7], minimizing energy utilization [2,[7][8][9][10][11][12][13][14]17] and minimizing failure rate / maximizing reliability [15][16][17]. The proposed work concentrates on minimizing the schedule length (finish time), tardiness and energy utilization.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Real-Time Task Scheduling Using Hybrid Multi-objective Crow Search Algorithm

Subbaraj

Rengaraj²,

Sikkandar³

2023

Preprint

View full text Add to dashboard Cite

This paper proposes a Multi-objective Crow Search Algorithm (MOCSA) based task scheduling approach for determining optimal solutions with simultaneous optimization of finish time (F), tardiness (T) and energy consumption (E). The proposed algorithm solves real-time task scheduling problem in heterogeneous multi-processor systems by adopting novel crow search algorithm to solve the discrete optimization problem. The three different multiple objectives with different magnitudes are fused using a weighted product method. Our methodology enables the user to choose the solution that best suits their needs. Experimental results demonstrate the efficiency of the proposed algorithm in achieving all the three objectives: minimizing finish time, tardiness and energy consumption.

show abstract

Section: Related Workmentioning

confidence: 99%

“…We apply metaheuristic based scheduling to get sub-optimal solutions in better run times. There exists some work in the literature that considers energy and makespan [7,8,[10][11][12][13][14]17] as multiple objectives.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Task Scheduling Using Hybrid Multi-objective Crow Search Algorithm

Subbaraj

Rengaraj²,

Sikkandar³

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Authors in [13], considered the objective of maximizing the probability of completing tasks before a deadline D and to satisfy an energy constraint with execution times and stochastic communications delays. Zhang et al [15]h a v e treated the problem of robustness under energy constraint.…”

Section: Related Workmentioning

confidence: 99%

Approximation Algorithm for Scheduling a Chain of Tasks on Heterogeneous Systems

Ait

Zaourar

Munier

2018

Lecture Notes in Computer Science

View full text Add to dashboard Cite

This paper presents an efficient approximation algorithm to solve the task scheduling problem on heterogeneous platform for the particular case of the linear chain of tasks. The objective is to minimize both the total execution time (makespan) and the total energy consumed by the system. For this purpose, we introduce a constraint on the energy consumption during execution. Our goal is to provides an algorithm with a performance guarantee. Two algorithms have been proposed; the first provides an optimal solution for preemptive scheduling. This solution is then used in the second algorithm to provide an approximate solution for non-preemptive scheduling. Numerical evaluations demonstrate that the proposed algorithm achieves a close-to-optimal performance compared to exact solution obtained by CPLEX for small instances. For large instances, CPLEX is struggling to provide a feasible solution, whereas our approach takes less than a second to produce a solution for an instance of 10000 tasks.

show abstract

“…This allows turning off the extra servers which reduces the overall power consumption. Young et al [76] study the problem of energy-constrained static resource allocation of a collection of communicating tasks to a computing environment. They maximize the probability that the collection of tasks completes by a deadline and that an energy constraint is satisfied.…”

Section: Literature Reviewmentioning

confidence: 99%

A modified modeling approach and a heuristic procedure for the multi-mode resource constrained project scheduling problem with activity splitting

2015

View full text Add to dashboard Cite

This paper presents a new heuristic method for solving multi-mode resource constrained project scheduling problems with renewable resources. Assumptions such as resource vacation and activity splitting are also considered. The proposed heuristic determines one mode for the execution of each activity first, so that the multi-mode problem is reduced to a single-mode one. Our method is compared to two of the existing methods in terms of computational time and solution quality. The results show that while it can outperform one of them (especially as the size of the problem grows), it is outperformed by the other for tested instances with low complexity, but can yield good results for tested instances with higher values of this parameters. This quality may be useful in real-world scheduling problems. We also validate the first phase of our method, i.e., mode selection, with numerical experiments. Our results indicate that better mode vectors selected in the first phase lead to better makespans for the MRCPSP. Moreover, we correct some erroneous constraints in the mathematical model of the problem. We implement the mathematical programming model of the problem in GAMS, and show that solving it to optimality requires much more computational effort compared to our method.

show abstract

Heterogeneous makespan and energy-constrained DAG scheduling

Cited by 10 publications

References 28 publications

Real-Time Task Scheduling Using Hybrid Multi-objective Crow Search Algorithm

Real-Time Task Scheduling Using Hybrid Multi-objective Crow Search Algorithm

Approximation Algorithm for Scheduling a Chain of Tasks on Heterogeneous Systems

A modified modeling approach and a heuristic procedure for the multi-mode resource constrained project scheduling problem with activity splitting

Contact Info

Product

Resources

About