Supporting service discovery, querying and interaction in ubiquitous computing environments.

In this paper, we contend that ubiquitous computing environments will be highly heterogeneous, service rich domains. Moreover, future applications will consequently be required to interact with multiple, specialised service location and interaction protocols simultaneously. We argue that existing service discovery techniques do not provide sufficient support to address the challenges of building applications targeted to these emerging environments. This paper makes a number of contributions. Firstly, using a set of short ubiquitous computing scenarios we identify several key limitations of existing service discovery approaches that reduce their ability to support ubiquitous computing applications. Secondly, we present a detailed analysis of requirements for providing effective support in this domain. Thirdly, we provide the design of a simple extensible meta-service discovery architecture that uses database techniques to unify service discovery protocols and addresses several of our key requirements. Lastly, we examine the lessons learnt through the development of a prototype implementation of our architecture

DYAMAND: dynamic, adaptive management of networks and devices

Consumer devices increasingly are "smart" and hence offer services that can interwork with and/or be controlled by others. However, the full exploitation of the inherent opportunities this offers, is hurdled by a number of potential limitations. First of all, the interface towards the device might be vendor and even device specific, implying that extra effort is needed to support a specific device. Standardization efforts try to avoid this problem, but within a certain standard ecosystem the level of interoperability can vary (i.e. devices carrying the same standard logo are not necessarily interoperable). Secondly, different application domains (e.g. multimedia vs. energy management) today have their own standards, thus limiting trans-sector innovation because of the additional effort required to integrate devices from traditionally different domains into novel applications. In this paper, we discuss the basic components of current so-called service discovery protocols (SDPs) and present our DYAMAND (DYnamic, Adaptive MAnagement of Networks and Devices) framework. We position this framework as a middleware layer between applications and discoverable/controllable devices, and hence aim to provide the necessary tool to overcome the (intra- and inter-domain) interoperability gaps previously sketched. Thus, we believe it can act as a catalyst enabling trans-sector innovation

Secure Communication Architecture for Dynamic Energy Management in Smart Grid

open access articleSmart grid takes advantage of communication technologies for efficient energy management and utilization. It entails sacrifice from consumers in terms of reducing load during peak hours by using a dynamic energy pricing model. To enable an active participation of consumers in load management, the concept of home energy gateway (HEG) has recently been proposed in the literature. However, the HEG concept is rather new, and the literature still lacks to address challenges related to data representation, seamless discovery, interoperability, security, and privacy. This paper presents the design of a communication framework that effectively copes with the interoperability and integration challenges between devices from different manufacturers. The proposed communication framework offers seamless auto-discovery and zero- con figuration-based networking between heterogeneous devices at consumer sites. It uses elliptic-curve-based security mechanism for protecting consumers' privacy and providing the best possible shield against different types of cyberattacks. Experiments in real networking environment validated that the proposed communication framework is lightweight, secure, portable with low-bandwidth requirement, and flexible to be adopted for dynamic energy management in smart grid

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Middleware Technologies for Cloud of Things - a survey

The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

Service and device discovery of nodes in a wireless sensor network

Emerging wireless communication standards and more capable sensors and actuators have pushed further development of wireless sensor networks. Deploying a large number of sensor\ud nodes requires a high-level framework enabling the devices to present themselves and the resources they hold. The device and the resources can be described as services, and in this paper, we review a number of well-known service discovery protocols. Bonjour stands out with its auto-configuration, distributed architecture, and sharing of resources. We also present a lightweight implementation in order to demonstrate that an emerging standards-based device and service discovery protocol can actually be deployed on small wireless sensor nodes

A component-based middleware framework for configurable and reconfigurable Grid computing

Significant progress has been made in the design and development of Grid middleware which, in its present form, is founded on Web services technologies. However, we argue that present-day Grid middleware is severely limited in supporting projected next-generation applications which will involve pervasive and heterogeneous networked infrastructures, and advanced services such as collaborative distributed visualization. In this paper we discuss a new Grid middleware framework that features (i) support for advanced network services based on the novel concept of pluggable overlay networks, (ii) an architectural framework for constructing bespoke Grid middleware platforms in terms of 'middleware domains' such as extensible interaction types and resource discovery. We believe that such features will become increasingly essential with the emergence of next-generation e-Science applications. Copyright (c) 2005 John Wiley & Sons, Ltd

Software X10-UPNP Bridge

IADIS MULTI CONFERENCE ON COMPUTER SCIENCE AND INFORMATION SYSTEMS 2008 Amsterdam, The Netherlands JULY 22 - 24, 2008In a future of smart houses where multiple heterogeneous devices will be interconnected to provide new functionalities and to ease everyday tasks, several issues will challenge the research, including interoperability and interfaces between different systems. The work presented in this paper describes a software bridge that exposes X10 devices as UPnP devices to UPnP control points, banking on the networks integration and alternatives to create mixed installations that are optimized for ease, reliability and functionality

A Taxonomy of Self-configuring Service Discovery Systems

We analyze the fundamental concepts and issues in service discovery. This analysis places service discovery in the context of distributed systems by describing service discovery as a third generation naming system. We also describe the essential architectures and the functionalities in service discovery. We then proceed to show how service discovery fits into a system, by characterizing operational aspects. Subsequently, we describe how existing state of the art performs service discovery, in relation to the operational aspects and functionalities, and identify areas for improvement