A metric and mixed-integer-programming-based approach for resource allocation in dynamic real-time systems Gertphol, Sethavidh ; Yu, Yang ; Gundala, Shriram Bhargava ; Prasanna Kumar, V. K. ; Ali, Shoukat ; Kim, Jong-Kook ; Maciejewski, Anthony A. ; Siegel, Howard Jay "This research was supported by the DARPA/ITO Quorum Program through the Office of Naval Research under Grant No. N00014-00-1-0599." 10 p. Dynamic real-time systems such as embedded systems operate in environments in which several parameters vary at run time. These systems must satisfy several performance requirements. Resource allocation on these systems becomes challenging because variations of run-time parameters may cause violations of the performance requirements. Performance violations result in the need for dynamic re-allocation, which is a costly operation. In this paper, a method for allocating resources such that the allocation can sustain the system in the light of a continuously changing environment is developed. We introduce a novel performance metric called MAIL (maximum allowable increase in load) to capture the effectiveness of a resource allocation. Given a resource allocation, MAIL quantifies the amount of additional load that can be sustained by the system without any performance violations. A Mixed-Integer-Programming-based approach (MIP) is developed to determine a resource allocation that has the highest MAIL value. Using simulations, several sets of experiments are conducted to evaluate our heuristics in various scenarios of machine and task heterogeneities. The performance of MIP is compared with three other heuristics: Integer-Programming based, Greedy, and classic Min-Min. Our results show that MIP performs signifantly better when compared with the other heuristics. Colorado State University. Libraries 2002 text ; image application/pdf ECEaam00093.pdf FACFECEN100093ARTI eng c2002 IEEE
A metric and mixed-integer-programming-based approach for resource allocation in dynamic real-time systems
Gertphol, Sethavidh ; Yu, Yang ; Gundala, Shriram Bhargava ; Prasanna Kumar, V. K. ; Ali, Shoukat ; Kim, Jong-Kook ; Maciejewski, Anthony A. ; Siegel, Howard Jay
"This research was supported by the DARPA/ITO Quorum Program through the Office of Naval Research under Grant No. N00014-00-1-0599."
10 p.
Dynamic real-time systems such as embedded systems operate in environments in which several parameters vary at run time. These systems must satisfy several performance requirements. Resource allocation on these systems becomes challenging because variations of run-time parameters may cause violations of the performance requirements. Performance violations result in the need for dynamic re-allocation, which is a costly operation. In this paper, a method for allocating resources such that the allocation can sustain the system in the light of a continuously changing environment is developed. We introduce a novel performance metric called MAIL (maximum allowable increase in load) to capture the effectiveness of a resource allocation. Given a resource allocation, MAIL quantifies the amount of additional load that can be sustained by the system without any performance violations. A Mixed-Integer-Programming-based approach (MIP) is developed to determine a resource allocation that has the highest MAIL value. Using simulations, several sets of experiments are conducted to evaluate our heuristics in various scenarios of machine and task heterogeneities. The performance of MIP is compared with three other heuristics: Integer-Programming based, Greedy, and classic Min-Min. Our results show that MIP performs signifantly better when compared with the other heuristics.
Colorado State University. Libraries
2002
text ; image
application/pdf
ECEaam00093.pdf
FACFECEN100093ARTI
eng
c2002 IEEE