status: Published

For the rising hazard of pirate attacks, unmanned aerial vehicle (UAV) swarm monitoring is a promising countermeasure. Previous monitoring methods have deficiencies in either adaptivity to dynamic events or simple but effective path coordination mechanisms, and they are inapplicable to the large-area, low-target-density, and long-duration persistent counter-piracy monitoring. This article proposes a self-organized UAV swarm counter-piracy monitoring method. Based on the pheromone map, this method is characterized by (1) a reservation mechanism for anticipatory path coordination and (2) a ship-adaptive mechanism for adapting to merchant ship distributions. A heuristic depth-first branch and bound search algorithm is designed for solving individual path planning. Simulation experiments are conducted to study the optimal number of plan steps and adaptivity scaling factor for different numbers of UAVs. Results show that merely decreasing revisit intervals cannot effectively reduce pirate attacks. Without the ship-adaptive mechanism, the proposed method reduces up to 87.2%, 43.2%, and 5.5% of revisit intervals compared to the Lèvy Walk method, the sweep method, and the baseline self-organized method, respectively, but cannot reduce pirate attacks; while with the ship-adaptive mechanism, the proposed method can reduce pirate attacks by up to 6.7% compared to the best of the baseline methods.

IEEE SASO (Self-Adapting and Self-Organizing Systems) is the premier international conference for computer systems and networks that autonomously change some aspect of themselves: code, form, function, shape, structure, components, and so on. Over the past 10 years, it has emerged as a key multidisciplinary event for sharing theoretical insights and technical innovations across the numerous scientific fields and application domains impacted by this research. In 2013, the conference was hosted by Drexel University in Philadelphia, Pennsylvania, and offered an extensive program of high-quality papers. This special issue of ACM TAAS presents selected, revised, and extended best articles, which showcase the rich variety and depth of the SASO scientific community.

In today's volatile business environments, collaboration between information systems, both within and across company borders, has become essential to success. An efficient supply chain, for example, requires the collaboration of distributed and heterogeneous systems of multiple companies. Developing such collaborative applications and building the supporting information systems poses several engineering challenges. A key challenge is to manage the ever-growing design complexity. In this article, we argue that software architecture should play a more prominent role in the development of collaborative applications. This can help to better manage design complexity by modularizing collaborations and separating concerns. State-of-the-art solutions, however, often lack proper abstractions for modeling collaborations at architectural level or do not reify these abstractions at detailed design and implementation level. Developers, on the other hand, rely on middleware, business process management, and Web services, techniques that mainly focus on low-level infrastructure. To address the problem of managing the design complexity of collaborative applications, we present Macodo. Macodo consists of three complementary parts: (1) a set of abstractions for modeling adaptive collaborations, (2) a set of architectural views, the main contribution of this article, that reify these abstractions at architectural level, and (3) a proof-of-concept middleware infrastructure that supports the architectural abstractions at design and implementation level. We evaluate the architectural views in a controlled experiment. Results show that the use of Macodo can reduce fault density and design complexity, and improve reuse and productivity. The main contributions of this article are illustrated in a supply chain management case.

SUMMARY As software systems today increasingly operate in changing and complex environments, they are expected to dynamically adapt to the changing environments sometimes with multiple coexisting adaptation goals. In this paper, an adaptation framework to facilitate adaptation with multiple concerns by using reusable and composable adaptation modules is proposed. Rather than using one‐size‐fits‐all approach, in this framework, system global adaptation behavior is generated by contextually fusing adaptation plans from multiple adaptation modules. In order to handle possible conflicts from multiple adaptation plans, supports for conflict detection and resolution are provided. Following the framework design principles, a supporting middleware is implemented based on the service‐oriented component model. Adaptation behaviors are realized as individually deployable adaptation components. A strategy called normalized context matching degree is proposed to rate and select applicable adaptation components. Possible conflicts in dealing with multiple adaptation concerns are resolved by using the semantics of actuators and context conditions. This middleware is also designed to be readily reconfigurable to support new features. Case studies and experiment results show that our framework exhibits significant advantage over traditional approaches in light of flexibility and reusability of the adaptation modules, with little complexity and performance overhead. Copyright © 2012 John Wiley & Sons, Ltd.

Mobile devices such as netbooks, smartphones, and tablets have made computing ubiquitous. However, such battery powered devices often have limited computing power for the benefit of an extended runtime. Nevertheless, despite the reduced processing power, users expect to perform the same types of operations as they could do using their desktop or laptop computers. We address mobile devices's lack of computing power by leveraging cloud computing resources. We present a middleware that relocates computing-intensive parts of Java applications to cloud re-sources. Consequently, our middleware enables the execution of computing-intensive applications on mo-bile devices. We present a case study on which we adapt Sunflow, an open-source ray tracing application, to use our middleware and show the results obtained by deploying it on Amazon EC2. We show, via simulations, a cost analysis of using the different resource allocation strategies available on our solution.

Advanced vehicle guidance systems use real-time traffic information to route traffic and to avoid congestion. Unfortunately, these systems can only react upon the presence of traffic jams and not to prevent the creation of unnecessary congestion. Anticipatory vehicle routing is promising in that respect, because this approach allows directing vehicle routing by accounting for traffic forecast information. This paper presents a decentralized approach for anticipatory vehicle routing that is particularly useful in large-scale dynamic environments. The approach is based on delegate multiagent systems, i.e., an environment-centric coordination mechanism that is, in part, inspired by ant behavior. Antlike agents explore the environment on behalf of vehicles and detect a congestion forecast, allowing vehicles to reroute. The approach is explained in depth and is evaluated by comparison with three alternative routing strategies. The experiments are done in simulation of a real-world traffic environment. The experiments indicate a considerable performance gain compared with the most advanced strategy under test, i.e., a traffic-message-channel-based routing strategy.

One of the major challenges in engineering distributed multiagent systems is the coordination necessary to align the behavior of different agents. Decentralization of control implies a style of coordination in which the agents cooperate as peers with respect to each other and no agent has global control over the system, or global knowledge about the system. The dynamic interactions and collaborations among agents are usually structured and managed by means of roles and organizations. In existing approaches agents typically have a dual responsibility: on the one hand playing roles within the organization, on the other hand managing the life-cycle of the organization itself, for example, setting up the organization and managing organization dynamics. Engineering realistic multiagent systems in which agents encapsulate this dual responsibility is a complex task. In this article, we present a middleware for context-driven dynamic agent organizations. The middleware is part of an integrated approach, called MACODO: Middleware Architecture for COntext-driven Dynamic agent Organizations. The complementary part of the MACODO approach is an organization model that defines abstractions to support application developers in describing dynamic organizations, as described in Weyns et al. [2010]. The MACODO middleware offers the life-cycle management of dynamic organizations as a reusable service separated from the agents, which makes it easier to understand, design, and manage dynamic organizations in multiagent systems. We give a detailed description of the software architecture of the MADOCO middleware. The software architecture describes the essential building blocks of a distributed middleware platform that supports the MACODO organization model. We used the middleware architecture to develop a prototype middleware platform for a traffic monitoring application. We evaluate the MACODO middeware architecture by assessing the adaptability, scalability, and robustness of the prototype platform.

is becoming present in every aspect of our lives, pushing us inevitably towards a world of distributed, context-aware computing systems. SELMAS'05, Software Everywhere - Context-Aware Agents, builds on the success of precedent SELMAS workshops, but with a special emphasis on the impact of the agent technology in the development of large context-aware systems. SELMAS has a track record of bringing together researchers and practitioners with a variety of perspectives in order to engage in lively discussion and debate.

Unanticipated software adaptations are becoming increasingly important in the domain of distributed systems. Due to performance and availability requirements, these adaptations need to be enforced at run-time. However for dynamic changes to yield valid systems, a safe state for reconfiguration of the involved software modules must be enforced. This paper proposes a solution to modularize support for achieving safe reconfiguration and separate it from basic application functionality. In addition, we describe a mechanism to obtain a safe state for unanticipated reconfiguration of producer/consumer based systems, rather than being limited to updates of independent software components. The presented method imposes such a safe state with minimal interference to the rest of the system, and with minimal contribution from the programmer. We believe that a wide range of producer/consumer based systems can take advantage of the presented solution.