Journal ArticleDOI
Energy Conscious Scheduling for Distributed Computing Systems under Different Operating Conditions
Young Choon Lee,Albert Y. Zomaya +1 more
TLDR
This work addresses the problem of scheduling precedence-constrained parallel applications on multiprocessor computer systems and presents two energy-conscious scheduling algorithms using dynamic voltage scaling (DVS) and a novel objective function and a variant from that.Abstract:
Traditionally, the primary performance goal of computer systems has focused on reducing the execution time of applications while increasing throughput. This performance goal has been mostly achieved by the development of high-density computer systems. As witnessed recently, these systems provide very powerful processing capability and capacity. They often consist of tens or hundreds of thousands of processors and other resource-hungry devices. The energy consumption of these systems has become a major concern. In this paper, we address the problem of scheduling precedence-constrained parallel applications on multiprocessor computer systems and present two energy-conscious scheduling algorithms using dynamic voltage scaling (DVS). A number of recent commodity processors are capable of DVS, which enables processors to operate at different voltage supply levels at the expense of sacrificing clock frequencies. In the context of scheduling, this multiple voltage facility implies that there is a trade-off between the quality of schedules and energy consumption. To effectively balance these two performance goals, we have devised a novel objective function and a variant from that. The main difference between the two algorithms is in their measurement of energy consumption. The extensive comparative evaluations conducted as part of this work show that the performance of our algorithms is very compelling in terms of both application completion time and energy consumption.read more
Citations
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Journal ArticleDOI
Data Center Energy Consumption Modeling: A Survey
TL;DR: An in-depth study of the existing literature on data center power modeling, covering more than 200 models, organized in a hierarchical structure with two main branches focusing on hardware-centric and software-centric power models.
Journal ArticleDOI
Multi-User Computation Partitioning for Latency Sensitive Mobile Cloud Applications
TL;DR: This paper studies, for the first time, multi-user computation partitioning problem (MCPP), which considers the partitioning of multiple users' computations together with the scheduling of offloaded computations on the cloud resources, and designs an offline heuristic algorithm, namely SearchAdjust, to solve MCPP.
Journal ArticleDOI
An Energy-Efficient Task Scheduling Algorithm in DVFS-enabled Cloud Environment
TL;DR: Based on the amount of randomly generated DAGs workflows, the experimental results show that DEWTS can reduce the total power consumption by up to 46.5 % for various parallel applications as well as balance the scheduling performance.
Journal ArticleDOI
Workflow scheduling in cloud: a survey
Fuhui Wu,Qingbo Wu,Yusong Tan +2 more
TL;DR: This paper makes a comprehensive survey of workflow scheduling in cloud environment in a problem–solution manner and conducts taxonomy and comparative review on workflow scheduling algorithms.
Journal ArticleDOI
Energy-Efficient Stochastic Task Scheduling on Heterogeneous Computing Systems
Kenli Li,Xiaoyong Tang,Keqin Li +2 more
TL;DR: This work proposes a heuristic energy-aware stochastic task scheduling algorithm called ESTS, which can achieve high scheduling performance for BoT applications with low time complexity O(n(M + logn), where n is the number of tasks and M is the total number of processor frequencies.
References
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Journal ArticleDOI
Power-aware scheduling for AND/OR graphs in real-time systems
TL;DR: This paper proposes a greedy slack stealing algorithm to deal with applications represented by AND/OR graphs and proves its correctness in terms of meeting the timing constraints and proposes a few variations of speculative scheduling algorithms that intend to save energy by reducing the number of speed changes while ensuring that the application meets its timing constraints.
Proceedings ArticleDOI
A task duplication based bottom-up scheduling algorithm for heterogeneous environments
TL;DR: Experimental results show that the makespansgenerated by the proposed DBUS algorithm are much better than those generated by the existing algorithms, HEFT, HCPFD and HCNF.
Journal ArticleDOI
Push-Pull: Deterministic Search-Based DAG Scheduling for Heterogeneous Cluster Systems
TL;DR: This paper proposes an alternative strategy, termed Push-Pull, which starts with the best task schedule found by a fast deterministic task scheduling algorithm and then iteratively attempts to improve the current best solution using a deterministic guided search method.
Journal ArticleDOI
A Novel State Transition Method for Metaheuristic-Based Scheduling in Heterogeneous Computing Systems
Young Choon Lee,Albert Y. Zomaya +1 more
TL;DR: The proposed Duplication-based State Transition (DST) method is incorporated into three different metaheuristics: genetic algorithms (GAs), simulated annealing (SA), and artificial immune system (AISs) and experimental results confirm DST's promising impact on the performance of meta heuristics.
Proceedings ArticleDOI
Real-time task mapping and scheduling for collaborative in-network processing in DVS-enabled wireless sensor networks
TL;DR: Simulation results show significant performance improvements compared with existing mechanisms in terms of providing deadline guarantee with minimum energy consumption, and real-time task mapping and scheduling (RT-MapS), is presented.