Resolution mechanism model for heterogeneous systems in smart home environment

Emerging growth of heterogeneous devices can be seen in smart home environment. These devices are diversified and highly heterogeneous in nature. Hence, there is a need of multiple devices in the same environment are orchestrating with one another in harmonic way. However, this thing becoming complicated whenever more heterogeneous systems are introducing into the same environment from time to time. This condition leads to system dependencies with each other and eventually leading towards conflict occurrences among them. In this work, we present a conflict resolution mechanism for heterogeneous devices in home environment using Resolution Mechanism model. The performance of the proposed model verified and justified within the need of smart home context

Multimedia delivery in the future internet

The term “Networked Media” implies that all kinds of media including text, image, 3D graphics, audio and video are produced, distributed, shared, managed and consumed on-line through various networks, like the Internet, Fiber, WiFi, WiMAX, GPRS, 3G and so on, in a convergent manner [1]. This white paper is the contribution of the Media Delivery Platform (MDP) cluster and aims to cover the Networked challenges of the Networked Media in the transition to the Future of the Internet. Internet has evolved and changed the way we work and live. End users of the Internet have been confronted with a bewildering range of media, services and applications and of technological innovations concerning media formats, wireless networks, terminal types and capabilities. And there is little evidence that the pace of this innovation is slowing. Today, over one billion of users access the Internet on regular basis, more than 100 million users have downloaded at least one (multi)media file and over 47 millions of them do so regularly, searching in more than 160 Exabytes1 of content. In the near future these numbers are expected to exponentially rise. It is expected that the Internet content will be increased by at least a factor of 6, rising to more than 990 Exabytes before 2012, fuelled mainly by the users themselves. Moreover, it is envisaged that in a near- to mid-term future, the Internet will provide the means to share and distribute (new) multimedia content and services with superior quality and striking flexibility, in a trusted and personalized way, improving citizens’ quality of life, working conditions, edutainment and safety. In this evolving environment, new transport protocols, new multimedia encoding schemes, cross-layer inthe network adaptation, machine-to-machine communication (including RFIDs), rich 3D content as well as community networks and the use of peer-to-peer (P2P) overlays are expected to generate new models of interaction and cooperation, and be able to support enhanced perceived quality-of-experience (PQoE) and innovative applications “on the move”, like virtual collaboration environments, personalised services/ media, virtual sport groups, on-line gaming, edutainment. In this context, the interaction with content combined with interactive/multimedia search capabilities across distributed repositories, opportunistic P2P networks and the dynamic adaptation to the characteristics of diverse mobile terminals are expected to contribute towards such a vision. Based on work that has taken place in a number of EC co-funded projects, in Framework Program 6 (FP6) and Framework Program 7 (FP7), a group of experts and technology visionaries have voluntarily contributed in this white paper aiming to describe the status, the state-of-the art, the challenges and the way ahead in the area of Content Aware media delivery platforms

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Features Interaction Detection and Resolution in Smart home systems Using Agent-Based Negotiation Approach

Smart home systems (SHS) have become an increasingly important technology in modern life. Apart from safety, security, convenience and entertainment, they offer significant potential benefits for the elderly, disabled and others who cannot live independently. Furthermore, smart homes are environmentally friendly. SHS functionality is based on perceiving residents’ needs and desires, then offering services accordingly. In order to be smart, homes have to be equipped with sensors, actuators and intelligent devices and appliances, as well as connectivity and control mechanisms. A typical SHS comprises heterogeneous services and appliances that are designed by many different developers and which may meet for the first time in the home network. The heterogeneous nature of the systems, in addition to the dynamic environment in which they are deployed, exposes them to undesirable interactions between services, known as Feature Interaction (FI). Another reason for FI is the divergence between the policies, needs and desires of different residents. Proposed approaches to FI detection and resolution should take these different types of interaction into account. Negotiation is an effective mechanism to address FI, as conflicting features can then negotiate with each other to reach a compromise agreement. The ultimate goal of this study is to develop an Agent-Based Negotiation Approach (ABNA) to detect and resolve feature interaction in a SHS. A smart home architecture incorporating the components of the ABNA has been proposed. The backbone of the proposed approach is a hierarchy in which features are organised according to their importance in terms of their functional contribution to the overall service. Thus, features are categorised according to their priority, those which are essential for the service to function having the highest priority. An agent model of the ABNA is proposed and comprehensive definitions of its components are presented. A computational model of the system also has been proposed which is used to explain the behaviour of different components when a proposal to perform a task is raised. To clarify the system requirements and also to aid the design and implementation of its properties, a formal specification of the ABNA is presented using the mathematical notations of Calculus of Context-aware Ambient (CCA), then in order to evaluate the approach a case study is reported, involving two services within the SHS: ventilation and air conditioning. For the purpose of evaluation, the execution environment of CCA is utilised to execute and analyse the ABNA

Integration of Legacy Appliances into Home Energy Management Systems

The progressive installation of renewable energy sources requires the coordination of energy consuming devices. At consumer level, this coordination can be done by a home energy management system (HEMS). Interoperability issues need to be solved among smart appliances as well as between smart and non-smart, i.e., legacy devices. We expect current standardization efforts to soon provide technologies to design smart appliances in order to cope with the current interoperability issues. Nevertheless, common electrical devices affect energy consumption significantly and therefore deserve consideration within energy management applications. This paper discusses the integration of smart and legacy devices into a generic system architecture and, subsequently, elaborates the requirements and components which are necessary to realize such an architecture including an application of load detection for the identification of running loads and their integration into existing HEM systems. We assess the feasibility of such an approach with a case study based on a measurement campaign on real households. We show how the information of detected appliances can be extracted in order to create device profiles allowing for their integration and management within a HEMS