The articles in this special issue aim at collecting contributions focused on the application of soft computing, including the areas of fuzzy logic, neural networks, evolutionary computing, rough sets, and other similar techniques, in novel distributed and/or parallel systems, where cloud computing is one of the widely known examples, in order to bring intelligence to all architectural layers for data processing, routing, etc. Brief summaries are provided for the included articles.

This paper advocates the use of RESTful data services in mobile commerce information spaces. REST is a restriction of web services to a simple protocol centered on a limited set of access operations against data resources. This paper analyzes how REST may be used as a general design principle for mobile commerce spaces. This analysis is threefold. First, it provides an abstract component model that contains a minimal embodiment of the REST functionality needed to support mobile commerce. Second, it describes and analyzes the operation of a mobile commerce space, resulting in a reference REST-based data decomposition that may be reused across a variety of domains. Third, it provides and analyzes a set of usage cases in the mobile commerce domain, which can form the basis of future REST-oriented programming models and tools. This analysis is based on a substantial mobile commerce framework we have implemented, called Celadon. This framework is currently being used to demonstrate several ambitious mobile commerce applications.

Searching and presenting rich data using mobile devices is hard given their inherent I/O limitations. One approach for alleviating these limitations is device symbiosis, whereby the interaction with one’s personal mobile device is augmented by additionally engaging with more capable infrastructure d

A web-based database system for intelligent remote monitoring of an artificial heart has been developed. It is important for patients with an artificial heart implant to be discharged from the hospital after an appropriate stabilization period for better recovery and quality of life. Reliable continuous remote monitoring systems for these patients with life support devices are gaining practical meaning. The authors have developed a remote monitoring system for this purpose that consists of a portable/desktop monitoring terminal, a database for continuous recording of patient and device status, a web-based data access system with which clinicians can access real-time patient and device status data and past history data, and an intelligent diagnosis algorithm module that noninvasively estimates blood pump output and makes automatic classification of the device status. The system has been tested with data generation emulators installed on remote sites for simulation study, and in two cases of animal experiments conducted at remote facilities. The system showed acceptable functionality and reliability. The intelligence algorithm also showed acceptable practicality in an application to animal experiment data.