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• W1745796857 abstract "We are honored and pleased to open this special issue of the Concurrency and Computation: Practice and Experience journal focused on intelligent distributed computing. Intelligent distributed computing (IDC) faces the challenges of adapting and combining research results in the fields of intelligent computing and distributed computing. Intelligent computing develops methods and technology ranging from classical artificial intelligence, computational intelligence, and multi-agent systems to game theory. Distributed computing develops methods and technology to build systems that are composed of collaborating components deployed on computer networks. IDC sets the foundation for the development of the new generation of intelligent distributed systems. One direction of IDC is the application of nature-inspired computing methods such as swarm intelligence and genetic algorithms (GA) to develop better distributed systems. On the other hand, distributed systems can help to develop more efficient systems that employ the metaphor of bio-inspiration for solving computationally difficult problems. Another direction of IDC proposes the use of intelligent software agents for the development of open and scalable distributed systems that can engage in complex intelligent processes. Intelligent software agents are endowed with high-level properties including knowledge and reasoning that make them appealing for building intelligent distributed systems. This special issue brings to the reader new research results and applications of intelligent distributed computing, with a special focus on the synergies between intelligent software agents and bio-inspired technologies on one side and parallel and distributed computing on the other side. In particular, some of the papers address interesting applications of intelligent distributed approaches in the areas of trust, security, protein structure prediction, and Semantic Web Services (SWS). We believe that the papers selected for presentation in this special issue will be a valuable resource for researchers and practitioners working in the emergent field of IDC, with a special focus for those especially interested in the recent advancements of the aforementioned research areas that are part of IDC. This issue includes extended versions of selected papers from the Fourth International Symposium on Intelligent Distributed Computing (IDC 2010) and the collocated Second International Workshop on Multi-Agent Systems Technology and Semantics (MASTS 2010), both held on 16–18 September 2010, Tangier, Morocco. There were 61 papers from 20 countries submitted to IDC 2010 and MASTS 2010 from which only 32 were accepted and included in the proceedings. From the accepted papers, related to the topic of Intelligent distributed computing, seven papers with higher review scores were selected and invited to be extended and submitted to this special issue. Finally, after two peer-review rounds, all of them were carefully revised, extended, and improved, thus being judged acceptable for inclusion in this special issue. The first article 1, by Gabriel Ciobanu and Calin Juravle, is in the area of mobile software agents. In this article, the authors introduce a systematic approach for deriving the software architecture of a mobile agents' environment. It is remarkable that the authors' work has a solid foundation on formal specification grounded on process calculi. This is one of the few papers showing clearly that advanced software engineering technologies can go hand-in-hand with formal foundations for the rigorous development of real distributed systems. The second article 2, by Igor Kotenko, Alexey Konovalov, and Andrey Shorov, is in the area of agent-based simulation applied to computer security. In this article, the authors introduce an interesting approach for investigation of cooperative distributed attacks and defense mechanisms by combining agent-based modeling with computer network simulation. On the one hand agents proved suitable for convenient representation of botnets and defense components, whereas on the other hand specialized network simulation packages (such as OMNeT++ INET) were used for creation of the agents' network environment, as realistically as possible. On top of this synergetic architecture, the authors employed a high-level specification of botnet and defense scenarios supporting botnet propagation, management, and attacks, as well as botnet defense and legitimate network activities. The flexibility of the agent-based approach allowed the creation of experiments with realistic simulation scenarios comprising many agents playing different roles and possibly organized in various attack and defense teams. The third article 3, by Antonio González-Pardo, Pablo Varona, David Camacho, and Francisco De Borja Rodríguez Ortíz, is in the area of bio-inspired multi-agent systems. In this article, the authors introduce a new bio-inspired method to improve agent communication for collaborative problem solving using a network of agents. Their method combines (i) an optimal communication topology based on scale-free networks with (ii) a discrimination policy for the messages that are analyzed by an agent. The approach was experimentally investigated for solving the blind jigsaw puzzle problem. The discrimination policy is based on the identification of the sender agent identity; this means that only messages from recognized agents are considered, whereas the other messages are discarded. Several experiments were performed with different agent populations, by varying the communication network topology of the agents (using the probability of redirection of the network communication channels), as well as the memory size that defines the size of the local informational context of agents. The fourth article 4, by Michele Malgeri, Vincenza Carchiolo, Giuseppe Mangioni, and Alessandro Longheu, is in the area of computational trust. In this article, the authors introduce a distributed and secure algorithm based on TrustWebRank metric. The algorithm was experimentally assessed using a large and realistic data set extracted from Epinions recommendation network. The experimental results included the convergence time and the bandwidth complexity. They revealed a fast convergence and a significant amount of messages exchanged by peer nodes. The fifth article 5, by Cristina Bianca Pop, Viorica Rozina Chifu, Ioan Salomie, Mihaela Dinsoreanu, Tudor David, Vlad Acretoaie, Aliz Nagy, and Ciprian Oprisa, is in the area of SWS. In this article, the authors present two new bio-inspired methods for clustering SWS based on the metaphors of ants' and birds' intelligence that employ particle swarm optimization and ant colony optimization algorithms. The evaluation of the matching degree of two services is based on an original metric that is using a decomposition technique. The two methods were experimentally evaluated using the standard SAWSDL-TC service test collection. The performance evaluation metrics were the Dunn index and the authors' original Average Item-Cluster Similarity metric. The experimental results revealed that algorithms based on particle swarm optimization outperform algorithms based on ant colony optimization. The sixth article 6, by César Manuel Benitez, Rafael Parpinelli, and Heitor Silvério Lopes, is in the area of parallel bio-inspired computational methods. In this article, the authors present a parallel computational approach that investigates the hybridization of artificial bee colony (ABC) with GA. The resulted hybrid method is then applied to solve the protein structure prediction problem. The experiments were carried out on the Beowulf cluster parallel processing environment. The experimental results show that the hybrid ABC-GA approach outperforms the simple ABC approach. Finally, the seventh article 7, by Daniel Diaz, Salvador Abreu, and Philippe Codognet, is in the area of parallel constraint satisfaction. In this article, the authors introduce a parallel extension of constraint-based local search algorithm called adaptive search (AS). They experiment with a parallel version of AS called AS/Cell that was designed for the Cell Broadband Engine (Cell/BE). The experimental results show a linear speedup when scaling up the number of cores. Moreover, simultaneous exploration of the different parts of the search space sometimes leads to super-linear speedups. Finally, the randomness for the diversification of the search increases robustness of the results; that is, the differences between the minimum and maximum execution times, as well as the overall variance of the results, decrease significantly. Concluding, we would like to thank the authors of the papers for preparing extended versions of their conference papers and the reviewers for their great job that assures the high quality of the final articles. Also, we would like to thank Prof. Mohammad Essaaidi and Prof. Michele Malgeri for co-organizing IDC 2010, whose high scientific quality standard enabled this special issue. Finally, we would like to express our appreciation to Prof. Geoffrey Fox, Editor-in-Chief of Concurrency and Computation: Practice and Experience, for offering us the opportunity to edit this exciting special issue. We really hope that the readers of this issue will find the articles quite interesting and stimulating." @default.
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• W1745796857 title "Preface to the Special Issue on intelligent distributed computing" @default.
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