SUMMARY This paper describes key aspects of remote service invocation in federations of OSGi containers. It refers to the OSGi Remote Service Admin specification and describes its efficient implementation over message‐oriented middleware. Scalability problems of several different approaches to implementation are identified, and a solution in a form of innovative Remote Service Admin model extension is proposed. The extension, named On‐demand Remote Service Admin, is analyzed and validated in the context of a motivating scenario. Validation includes performance and scalability evaluation, which confirms that all assumed requirements have been satisfied by the constructed prototype. Finally, the presented research is compared with related works. Copyright © 2011 John Wiley & Sons, Ltd.

The paper presents a Monitoring Framework for the integration layer of SOA systems realized by an Enterprise Service Bus (ESB). It introduces a generic ESB Metamodel (EMM) and defines mechanisms which gather monitoring data related to the model entities. Applicability of the model is verified on the Java Business Integration (JBI) specification—available standardization of an ESB. An analysis of the JBI specification from the Metamodel perspective is presented, resulting in identification of JBI monitoring deficiencies. Then, the paper illustrates a realization of mechanisms ameliorating JBI deficiencies. The paper also defines the notion of a Monitoring Goal Metamodel which lays a foundation for a fully featured and technology-agnostic monitoring framework established on the EMM. The Monitoring Goal Metamodel allows a declarative definition of how the framework should react to anomalies by performing drill-down monitoring to diagnose the root cause of the problems. Evaluation of the prototype implementation of the ESB Monitoring Framework that verifies its correctness and fulfillment of the nonfunctional requirements is presented. Related work and some important relevant projects and technologies are also briefly described. Finally, the paper is summarized with conclusions and a vision of the proposed framework usage and extensions.

It has been already proofed and discussed in our previous works that thanks to its computational as well as implemental simplicity evolutionary multi-agent system (EMAS) approach can be easily adjusted and widely used for solving almost any type of multi-objective optimization task. Unfortunately, results obtained by distributed and decentralized agent-based evolutionary heuristic approach applied for solving multi-objective optimization problems (MOOPs) can be limited by such factors, as stagnation of agents' evolution or problems with distributing agents evenly over the whole approximation of the Pareto frontier. In the course of this paper three main shortcomings of EMAS-based approach are diagnosed and ideas of possible solutions of identified problems with the use of "flock-based" mechanisms are presented. Next, one of many possible realization of flock-based ideas i.e. so-called densityplus realization of floEMAS paradigm is discussed. Finally, experimental results obtained by floEMAS system in solving noisy multi-objective optimization tasks are presented. The goal of this paper is: to discuss shortcomings identified in applying EMAS for solving MOOPs, to present flock-based mechanisms allowing for overcoming such shortcomings, to discuss one of possible realization of floEMAS approach and to present the behavior of proposed floEMAS realization in noisy environment - since in the case of EMAS-based approaches there is no need to introduce any additional mechanisms to solve efficiently noisy problems.