Decentralized market-based resource allocation in a heterogeneous computing system

2008 ◽  
Author(s):  
James Smith ◽  
Edwin K. P. Chong ◽  
Anthony A. Maciejewski ◽  
Howard Jay Siegel
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Computing ◽  
Computing System ◽  
Decentralized Market ◽  
Heterogeneous Computing System

scholarly journals Makespan and Energy Robust Stochastic Static Resource Allocation of a Bag-of-Tasks to a Heterogeneous Computing System

2015 ◽  
Vol 26 (10) ◽  
pp. 2791-2805 ◽  
Author(s):  
Mark A. Oxley ◽  
Sudeep Pasricha ◽  
Anthony A. Maciejewski ◽  
Howard Jay Siegel ◽  
Jonathan Apodaca ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Heterogeneous Computing ◽  
Computing System ◽  
Heterogeneous Computing System ◽  
Static Resource

Energy Optimization Heuristics for Budget-Constrained Workflow in Heterogeneous Computing System

2019 ◽  
Vol 28 (09) ◽  
pp. 1950159 ◽  
Author(s):  
Junqiang Jiang ◽  
Wenbin Li ◽  
Li Pan ◽  
Bo Yang ◽  
Xin Peng
Keyword(s):  
Energy Consumption ◽  
Heterogeneous Computing ◽  
Rapid Development ◽  
Energy Optimization ◽  
Minimum Cost ◽  
Computing System ◽  
Directed Acyclic Graphs ◽  
Optimization Heuristics ◽  
Dynamic Voltage ◽  
Heterogeneous Computing System

With the rapid development of commercialized computation, the heterogeneous computing system (HCS) has evolved into a new method of service provisioning based on utility computing models, in which the users consume services and resources based on their quality of service requirements. In certain models using the pay-as-you-go concept, the users are charged for accessed services based on their usage. In addition, the commercialized HCS provider also assumes the responsibility to reduce the energy consumption to protect the environment. This paper considers a basic model known as directed acyclic graphs (DAG), which is designed for workflow applications, and investigates heuristics that allows the scheduling of various tasks of a workflow into the dynamic voltage and frequency scaling enabled HCS. The proposed approaches, which are Minimum-Cost-Up-to-Budget (MCUB) and Maximum-Cost-Down-to-Budget (MCDB), could not only satisfy budget constrains but could also optimize overall energy consumption. The approaches along with their variants are implemented and evaluated using four types of basic DAGs. From the experimental results, we conclude that MCDB outperforms MCUB in energy optimization and makespan criterion while meeting budget constraints faced by users.

Grid Scheduling

2011 ◽  
pp. 86-111
Author(s):  
Florin Pop
Keyword(s):  
Distributed System ◽  
Critical Analysis ◽  
Heterogeneous Computing ◽  
Computing System ◽  
Optimization Techniques ◽  
Grid Scheduling ◽  
Grid Systems ◽  
Grid Environments ◽  
Scheduling Models ◽  
Heterogeneous Computing System

This chapter will present the scheduling mechanism in distributed systems with direct application in grids. The resource heterogeneity, the size and number of tasks, the variety of policies, and the high number of constraints are some of the main characteristics that contribute to this complexity. The necessity of scheduling in grid is sustained by the increasing of number of users and applications. The design of scheduling algorithms for a heterogeneous computing system interconnected with an arbitrary communication network is one of the actual concerns in distributed system research. The main concerns presented in the chapter refers to general presentation of scheduling for grid systems, specific requirements of scheduling in grids, critical analysis of existing methods and algorithms for grid schedulers, scheduling policies, fault tolerance in scheduling process in grid environments, scheduling models and algorithms and optimization techniques for grid scheduling.

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