Middleware for distributed context-aware systems

Context-aware systems represent extremely complex and heterogeneous distributed systems, composed of sensors, actuators, application components, and a variety of context processing components that manage the flow of context information between the sensors/actuators and applications. The need for middleware to seamlessly bind these components together is well recognised. Numerous attempts to build middleware or infrastructure for context-aware systems have been made, but these have provided only partial solutions; for instance, most have not adequately addressed issues such as mobility, fault tolerance or privacy. One of the goals of this paper is to provide an analysis of the requirements of a middleware for context-aware systems, drawing from both traditional distributed system goals and our experiences with developing context-aware applications. The paper also provides a critical review of several middleware solutions, followed by a comprehensive discussion of our own PACE middleware. Finally, it provides a comparison of our solution with the previous work, highlighting both the advantages of our middleware and important topics for future research.

Investigations into MIMO systems from an electromagnetic perspective

The paper presents investigations into multiple input multiple output wireless communication systems, which are carried out from an electromagnetic perspective. The first part of the paper focuses on signal propagation models, which can be used for determining the MIMO system capacity or its performance when various space-time coding schemes are applied. Two types of models are considered. In the first model, array antennas are treated in an exact electromagnetic manner but interactions with scattering objects are incorporated using an approximate single bounce scattering approach. The other model is a simple but exact electromagnetic (EM) model, which takes into account EM interactions between antennas and scatterers. In this model, parallel wire dipoles represent antennas as well as scatterers. The second part of the paper reports on investigations into two types of MIMO testbeds. The first one is a simple transmit/receive diversity tested while the other one is a full MIMO testbed. The paper briefly describes the results obtained during the undertaken investigations

Patterns in complex systems modeling

The design, development, and use of complex systems models raises a unique class of challenges and potential pitfalls, many of which are commonly recurring problems. Over time, researchers gain experience in this form of modeling, choosing algorithms, techniques, and frameworks that improve the quality, confidence level, and speed of development of their models. This increasing collective experience of complex systems modellers is a resource that should be captured. Fields such as software engineering and architecture have benefited from the development of generic solutions to recurring problems, called patterns. Using pattern development techniques from these fields, insights from communities such as learning and information processing, data mining, bioinformatics, and agent-based modeling can be identified and captured. Collections of such 'pattern languages' would allow knowledge gained through experience to be readily accessible to less-experienced practitioners and to other domains. This paper proposes a methodology for capturing the wisdom of computational modelers by introducing example visualization patterns, and a pattern classification system for analyzing the relationship between micro and macro behaviour in complex systems models. We anticipate that a new field of complex systems patterns will provide an invaluable resource for both practicing and future generations of modelers.