The state of the art of the field of feature interactions in telecommunications services is reviewed, concentrating on three major research trends: software engineering approaches, formal methods, and on line techniques. Then, the impact of the new, emerging architectures on the feature interaction problem is considered. A forecast is made about how research in feature interactions needs to readjust to address the new challenges posed by the emerging architectures.

In the near future general household appliances such as televisions, refrigerators, alarm clocks, stoves, and even lights, will be supplemented with a network interface connecting the appliance to the Internet. Homes are being equipped with such networked appliances to allow a more convenient way of living. Such extensive automatic control of appliances leads to the concept of the smart home. Behind such automation, there is a lot of software controlling the appliances. This software, which is often referred to as services, applications, or bundles is supplied by a range of service provider businesses. Hence in a single home, appliances may be controlled by a multitude of services, which are offered by a wide variety of different providers. Moreover, some services may require the use of other services. Importantly, these businesses are completely independent and may not even be aware of one another or their products. Hence appliances may be controlled by more than one service, and indeed these controlling services are often trying to achieve different goals. This causes compatibility issues, which need to be resolved for networked appliances to be successful in the mass market. This problem is well known in telephony and historically is referred to as the feature interaction problem. This paper discusses the issue of compatibility between services in a home environment. Reasons why and how services interact are discussed, and a taxonomy of interactions is presented. Finally, an approach is presented which prevents interactions. The approach presented uses accepted and known device and protocol interworking techniques. Throughout the paper, a number of example scenarios are used to illustrate the issues. However, the emphasis of the paper is not only to present sample services for controlling home appliances or identifying specific interactions between such services, but on finding a general solution to the feature interaction problem that can automatically detect interactions between services in the home.

Wireless sensor network (WSN)-based Internet of Things (IoT) applications suffer from issues including limited battery capacity, frequent disconnections due to multi-hop communication and a shorter transmission range. Clustering and routing are treated separately in different solutions and, therefore, efficient solutions in terms of energy consumption and network lifetime could not be provided. This work focuses data collection from IoT-nodes distributed in an area and connected through WSN. We address two interlinked issues, clustering and routing, for large-scale IoT-based WSN and propose an improved clustering and routing protocol to jointly solve both of these issues. Improved clustering and routing provide area-based clustering derived from the transmission range of network nodes. During process of clustering, cluster-heads are selected in such a way that provide fail-over-proof routing. An efficient routing path is achieved by finding the minimal hop-count with the availability of alternate routing paths. The results are compared with state-of-the-art benchmark protocols. Theoretical and simulation results demonstrate reliable network topology, improved network lifetime, efficient node density management and improved overall network capacity.

Abstract-It is argued that various factors including the increasingly ageing population will require more care services to be delivered to users in their own homes. Desirable characteristics of such services are outlined. The Open Services Gateway initiative has been adopted as a widely accepted framework that is particularly suitable for developing home care services. Service discovery in this context is enhanced through ontologies that achieve greater flexibility and precision in service description. A service ontology stack allows common concepts to be extended for new services. The architecture of a policy system for home care is explained. This is used for flexible creation and control of new services. The core policy language and its extension for home care are introduced, and illustrated through typical examples. Future extensions of the approach are discussed.

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