Lower bounds for constrained task allocation problem in distributed computing environment

In this paper, we propose three lower bounds to the constrained task allocation problem (CTAP). These three lower bounds are: a heuristic lower bound (HLB), a linear programming relaxation (LPR) lower bound and a lagrangean relaxation with subgradient optimization (LRSO) based lower bound. We empiri...

Full description

Saved in:
Bibliographic Details
Published in2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE) pp. 1 - 4
Main Author Pendharkar, P. C.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2012
Subjects
Distributed computing
Lagrangean Relaxation
Linear programming
Lower Bounds
Mathematical Programming
Optimization
Program processors
Resource management
Task Allocation
Throughput
Vectors
Online AccessGet full text
ISBN1467314315
9781467314312
ISSN0840-7789
DOI10.1109/CCECE.2012.6335052

Cover

More Information
Summary:In this paper, we propose three lower bounds to the constrained task allocation problem (CTAP). These three lower bounds are: a heuristic lower bound (HLB), a linear programming relaxation (LPR) lower bound and a lagrangean relaxation with subgradient optimization (LRSO) based lower bound. We empirically compare the performance of these three bounds under different task executing times. Our experiments with real-world CTAPs indicate that the LPR provides efficient and tight lower bounds for the CTAP.
ISBN:1467314315
9781467314312
ISSN:0840-7789
DOI:10.1109/CCECE.2012.6335052