Using java mobile agents and PSO for implementing a distributed antenna-optimization platform

Papadopoulos, KA; Athanaileas, TE; Kaklamani, DI

dc.contributor.author	Papadopoulos, KA	en
dc.contributor.author	Athanaileas, TE	en
dc.contributor.author	Kaklamani, DI	en
dc.date.accessioned	2014-03-01T01:32:22Z
dc.date.available	2014-03-01T01:32:22Z
dc.date.issued	2009	en
dc.identifier.issn	1045-9243	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20101
dc.subject	Antenna optimization	en
dc.subject	Antenna radiation patterns	en
dc.subject	Distributed computing	en
dc.subject	Mobile agents	en
dc.subject	Optimization	en
dc.subject	Particle swarm optimization	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	Antenna optimization	en
dc.subject.other	Antenna radiation patterns	en
dc.subject.other	Computational grids	en
dc.subject.other	Data-level parallelism	en
dc.subject.other	Distributed antennas	en
dc.subject.other	Distributed computational resources	en
dc.subject.other	Distributed Computing	en
dc.subject.other	Distributed particles	en
dc.subject.other	Distributed resources	en
dc.subject.other	Entry barriers	en
dc.subject.other	Expandability	en
dc.subject.other	Loose couplings	en
dc.subject.other	Programming paradigms	en
dc.subject.other	Research communities	en
dc.subject.other	Simulation software	en
dc.subject.other	Steep learning curve	en
dc.subject.other	Application programming interfaces (API)	en
dc.subject.other	Computational efficiency	en
dc.subject.other	Computational electromagnetics	en
dc.subject.other	Computer software	en
dc.subject.other	Directional patterns (antenna)	en
dc.subject.other	Mobile agents	en
dc.subject.other	Mobile antennas	en
dc.subject.other	Object oriented programming	en
dc.subject.other	Research	en
dc.subject.other	Particle swarm optimization (PSO)	en
dc.title	Using java mobile agents and PSO for implementing a distributed antenna-optimization platform	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/MAP.2009.5432062	en
heal.identifier.secondary	http://dx.doi.org/10.1109/MAP.2009.5432062	en
heal.identifier.secondary	5432062	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	Various techniques and platforms have been introduced for the effective use of distributed computational resources when using specialized computational electromagnetics (CEM) simulation software for designing antennas. These techniques usually impose significant entry barriers to researchers, in the form of a steep learning curve for specialized application programming interfaces (APIs), or limited access to resources such as clusters or computational grids. The current paper discusses a sophisticated approach for alleviating these barriers, with the fusion of the programming paradigms of object-oriented programming and mobile agents. A case study concerning the development of a distributed Particle Swarm Optimization (PSO) platform-an increasingly popular algorithm within the antenna-research community-is thoroughly analyzed and presented as an example of data-level parallelism. Various aspects of computational efficiency in terms of scaling have been examined, in order to estimate the merits of the proposed approach. The aim of the analysis is to stress the advantages of the above-mentioned techniques for the effective loose coupling of CEM programs with distributed resources, demonstrating ease of application, improved scalability, and future expandability. © 2006 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Antennas and Propagation Magazine	en
dc.identifier.doi	10.1109/MAP.2009.5432062	en
dc.identifier.isi	ISI:000273883200012	en
dc.identifier.volume	51	en
dc.identifier.issue	5	en
dc.identifier.spage	128	en
dc.identifier.epage	136	en