Optimizing the Replication of Multi-Quality Web Applications Using Aco and Wolf

Name: Optimizing the Replication of Multi-Quality Web Applications Using Aco and Wolf
Brand: Biblioscholar
SKU: 9781288398805
Price: 68.52 PLN
Availability: InStock

Autor: Judson C Dressler

Język:

Oprawa: Miękka

Wydawca: Biblioscholar

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Since its introduction, the Ant Colony Optimization (ACO) meta-heuristic has been successfully appli...

Informacje o książce

Autor

Judson C Dressler

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2012

strony

EAN

9781288398805

ISBN

9781288398805

Enbook ID

08249545

Wydawca

Biblioscholar

Waga

159

Wymiary

189 x 246 x 4

Pełny opis

Since its introduction, the Ant Colony Optimization (ACO) meta-heuristic has been successfully applied to a wide range of combinatorial problems. This thesis presents the adaptation of ACO to a new NP-hard problem involving the replication of multi-quality database-driven web applications (DAs) by a large application service provider (ASP). This problem is a special case of the generalized assignment problem (GAP) which occurs in many military contexts such as logistics planning, air crew scheduling, and communications network management. The ASP must assign DA replicas to its network of heterogeneous servers so that user demand is satisfied at the desired quality level and replica update loads are minimized. The ACO algorithm proposed, AntDA, for solving the ASP's replication problem is novel in several respects: ants traverse a bipartite graph in both directions as they construct solutions, pheromone is used for traversing from one side of the bipartite graph to the other and back again, heuristic edge values change as ants construct solutions, and ants may sometimes produce infeasible solutions. Although experiments show that AntDA outperforms several other solution methods, there was room for improvement in the convergence rates of the ants in finding better solutions.

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