Ioannis V. Papaioannou

QoS awareness support in Web-Service semantics

Web Services (WSs) are a new breed of web application that have brought out quite challenging research issues. One of these is the establishment of an interoperable semantic framework suitable to represent all potential features of WSs. Apart from the functional properties that have already been modeled via standardized tools, there are also the nonfunctional features of WSs i.e. their Quality-of-Service, which in most cases are not included in the WS description. Nevertheless, integrating QoS features in WS profiles is to the advantage of both users and providers, as it supports QoS-aware WS selection and composition addressing the user’s QoS requirements, while enabling WS providers to increase their profit in the e-business domain. This paper is concerned with the creation of a QoS ontology framework adequate for WS provision. It has sprang from the work carried out in the IST-Amigo1 Integrated Project for Ambient Intelligence (AmI) homes, which aims to develop an open, standardized platform for the provision of QoSaware AmI Web Services in home environments.

Cross-community context management in Cooperating Smart Spaces

Recently, social networks have become the most prevalent IT paradigm, as the vast majority of Internet users maintain one or multiple social networking accounts. These accounts, irrespectively of the underlying service, contain rich information and data for the owner’s preferences, social skills, everyday activities, beliefs and interests. Along with these services, the computation, sensing and networking capabilities of the state of the art mobile and portable devices, with their always-on mode, assist users in their everyday lives. Thus, the integration of social networking services with current pervasive computing systems could provide the users with the potential to interact with other users that have similar interests, preferences and expectations; and in general, the same or similar context, for limited or not time periods, in order to ameliorate their overall experience, communicate, socialise and improve their everyday activities with minimal effort. This paper introduces a cross-community context management framework that is suitable for Cooperating Smart Spaces, which couple the advantages of pervasive computing and social networking. This framework goes beyond the state of the art, among others, in that cross-community context from a multitude of sources is collected and processed to enhance the end user experience and increase the perceived value of the services provided.

Neural networks against genetic algorithms for negotiating agent behaviour prediction

The deregulation of the electricity industry in many countries has created a number of marketplaces in which producers and consumers can operate in order to more effectively manage and meet their energy needs. To this end, this paper develops a new model for electricity retail where end-use customers choose their supplier from competing electricity retailers. The model is based on simultaneous reverse combinatorial auctions, designed as a second-price sealed-bid multi-item auction with supply function bidding. This model prevents strategic bidding and allows the auctioneer to maximise its payoff. Furthermore, we develop optimal single-item and multi-item algorithms for winner determination in such auctions that are significantly less complex than those currently available in the literature.The design and evaluation of agents handling automated negotiations on behalf of their human or corporate owners is a quite challenging research field. This paper proposes to enhance such agents with learning techniques, in order to achieve more profitable results for the parties they represent. The proposed learning techniques are based on MLP or RBF neural networks (NNs) and are quite lightweight. Alternatively, the agents use Genetic Algorithms (GAs) to predict the behaviour of their opponents. All designed approaches aim to reduce the cases of unsuccessful negotiations and maximize the clients utility. The designed NN- and GA-assisted negotiation strategies have been compared and empirically evaluated via numerous experiments. This work has in part been supported by the project “Amigo - Ambient intelligence for the networked home environment”. The Amigo project is funded by the European Commission as an integrated project (IP) in the Sixth Framework Programme under the contract number IST 004182. For more information you may refer to www.amigo-project.org.

Ontology Based Service Modelling for Composability in Smart Home Environments

The ontology-based semantic approaches are gradually gaining momentum in ambient intelligent environments such as smart homes, smart cars, intelligent offices, etc. In spite of the significant research work carried out in the ontology design and application field, several issues remain unresolved. The ontologies mainly focus on specific context information features. The capabilities of services from different functional domains are rarely addressed and are not aligned with context ontologies. No attempt has been made to integrate the existing ontologies, facilitating their future extension with emerging new technologies for networks, devices, software architectures and platforms. Moreover, the application developer support facilitating better understanding of semantic technologies is still in its infancy. The research work presented in this paper tackles the aforementioned issues.

Towards successful automated negotiations based on Neural Networks

Mobile intelligent agents may assist the rapid and wide market penetration of services and products offered via e-commerce channels, as they improve the performance and sophistication of systems in the e-business domain. In this framework, the design and evaluation of agents handling automated negotiations on behalf of their human or corporate owners is a challenging research field. This paper proposes to enhance such agents with learning techniques, in order to achieve more profitable results for the parties they represent. As mobile agents have reduced processing capabilities and have to remotely communicate with their peers or migrate to foreign network nodes, the learning mechanisms they employ should require minimal resources. The proposed learning technique is based on neural networks (NNs) and is quite lightweight. It aims to reduce the cases of unsuccessful negotiations and maximize the clients utility. The designed NN-assisted negotiation strategy has been empirically evaluated via numerous experiments

Context and Community Awareness in Support of User Intent Prediction

Proactive behaviour of pervasive computing systems cannot be realised without the establishment of suitable and reliable user intent prediction facilities. Most of the existing approaches focus on an individual end-user’s history of interactions and context in order to estimate future user behaviour. Recent trends in pervasive systems allow users to form communities with other individuals that share similar profiles, habits, and behaviours. Pervasive Communities set new challenges and opportunities regarding proactivity and context management. This chapter presents a context aware user intent learning and prediction framework that is able to exploit the knowledge available at the community level. Community knowledge, if appropriately managed, can significantly improve proactivity behaviour of individual users’ systems.

Addressing the Context-Awareness Requirements in Personal Smart Spaces

The provision of pervasive computing services is a challenging research area. This paper elaborates on the notion of Personal Smart Spaces (PSSs) that allows the delivery of pervasive services to mobile users. PSSs aim to couple the facilities offered by next generation mobile communications with the features provided by the static smart spaces to support a more ubiquitous, context-aware and personalised smart space that is able to follow the user wherever he/she goes. Moreover, PSSs provide interfaces between the user and the various services and sensors that are available via the Internet. One of the core PSS features is the management of static and dynamic context information of users. This paper elaborates on the context management approach that has been designed and implemented in order to address the advanced requirements of PSSs regarding context awareness.

Multi-modal opponent behaviour prognosis in E-negotiations

Automated negotiations introduce a challenging research field that aims to enhance the performance and optimise several aspects of the electronic marketplace. This paper is concerned with the design and evaluation of negotiation strategies suitable for intelligent agents acting in Business-to-Consumer ecommerce environments. In order to minimize the cases where an agreement is not reached upon the expiration of its deadline, the client agent is enhanced with various function approximation techniques, which aim to predict the behaviour of the provider agent during the last negotiation rounds.

USING NEURAL NETWORKS TO MINIMIZE THE DURATION OF AUTOMATED NEGOTIATION THREADS FOR HYBRID OPPONENTS

Neural networks (NNs) provide an efficient tool that can be trained to estimate the value of output parameters given certain metrics. In this paper, NNs are used to enhance intelligent agents that ...

Community context management research and challenges in pervasive and social computing

Context-awareness is one of the main aspects of pervasive computing environments. Recently, some social networking systems have also started to exploit context information. These two paradigms serve different purposes. Pervasive computing systems have been designed mainly to address the needs of individual users, thus neglecting the social nature of humans. On the other hand, social computing focuses on exploiting the social relations between users, on promoting their interactions and on supporting the sharing of digital resources among them. However, the recent development and popularity of social networking systems has happened in isolation from the developments in pervasive computing. This paper elaborates on the role of context in both pervasive and social computing environments and introduces the approach of the SOCIETIES project that integrates full scale pervasive functionality in social networking systems to develop the next generation of social media systems. Finally, it discusses the new research challenges that emerge in pervasive social media regarding community context-awareness and the respective benefits that the end users may experience.