The task allocation problem with constant communication

In the module allocation problem we are given n tasks t 1,…, t n , to be executed by m processors P 1,…, P m , subject to both execution and communication costs. The cost of any assignment of the tasks to the processors is defined as the sum of the corresponding execution costs, and the communicatio...

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Vydané v:Discrete Applied Mathematics Ročník 131; číslo 1; s. 169 - 177
Hlavní autori: Fernandez de la Vega, W., Lamari, M.
Médium: Journal Article Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: Lausanne Elsevier B.V 06.09.2003
Amsterdam Elsevier
New York, NY
Predmet:
Applied sciences
Combinatorics
Combinatorics. Ordered structures
Computer science; control theory; systems
Computer systems performance. Reliability
Exact sciences and technology
Graph theory
Mathematics
Operational research and scientific management
Operational research. Management science
Polynomial time approximation scheme
Scheduling
Scheduling, sequencing
Sciences and techniques of general use
Software
Polynomial time approximation scheme
Scheduling
Polynomial
Costs
Processor
Scheme
Polynomial approximation
Complete
Constant
Numerical approximation
Assignment
Allocation
Number
Optimal allocation
Bipartite graph
Communication
Edge(graph)
Approximation
Complete graph
Graph clique
Graph theory
Algorithm
Cost control
Polynomial time
Problem
Communication graph
Module
Edge
Graph algorithm
ISSN:0166-218X, 1872-6771
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Popis
Shrnutí:In the module allocation problem we are given n tasks t 1,…, t n , to be executed by m processors P 1,…, P m , subject to both execution and communication costs. The cost of any assignment of the tasks to the processors is defined as the sum of the corresponding execution costs, and the communication costs for any pair of tasks assigned to distinct processors. We consider the case where all the tasks communicate with communication costs all equal to a constant c 0. When the number of processors is bounded, we give two exact, polynomial-time algorithms, an elementary one for the case where the execution costs take only two distinct values and one for the general case. When the number of processors is not bounded, we obtain a polynomial-time approximation scheme. We obtain a similar algorithm when the communication graph is the edge union of a bounded number of cliques and complete bipartite graphs.
ISSN:0166-218X
1872-6771
DOI:10.1016/S0166-218X(02)00423-7