Title :
Dynamic Resource Management in Energy Constrained Heterogeneous Computing Systems Using Voltage Scaling
Author :
Kim, Jong-Kook ; Siegel, Howard Jay ; Maciejewski, Anthony A. ; Eigenmann, Rudolf
Author_Institution :
Sch. of Electr. Eng., Korea Univ., Seoul
Abstract :
An ad hoc grid is a wireless heterogeneous computing environment without a fixed infrastructure. This study considers wireless devices that have different capabilities, have limited battery capacity, support dynamic voltage scaling, and are expected to be used for eight hours at a time and then recharged. To maximize the performance of the system, it is essential to assign resources to tasks (match) and order the execution of tasks on each resource (schedule) in a manner that exploits the heterogeneity of the resources and tasks while considering the energy constraints of the devices. In the single-hop ad hoc grid heterogeneous environment considered in this study, tasks arrive unpredictably, are independent (i.e., no precedent constraints for tasks), and have priorities and deadlines. The problem is to map (match and schedule) tasks onto devices such that the number of highest priority tasks completed by their deadlines during eight hours is maximized while efficiently utilizing the overall system energy. A model for dynamically mapping tasks onto wireless devices is introduced. Seven dynamic mapping heuristics for this environment are designed and compared to each other and to a mathematical bound.
Keywords :
ad hoc networks; grid computing; mobile computing; power aware computing; resource allocation; ad hoc grid heterogeneous environment; dynamic resource management; dynamic task mapping heuristics; dynamic voltage scaling; energy constrained heterogeneous computing systems; mobile battery-powered computing devices; priority tasks; resource assignment; wireless heterogeneous computing environment; ad hoc; deadlines; dynamic mapping; dynamic voltage scaling; energy-aware computing; heterogeneous distributed computing; priority; resource allocation; resource management; scheduling;
Journal_Title :
Parallel and Distributed Systems, IEEE Transactions on
DOI :
10.1109/TPDS.2008.113