Design and Implementation of S-MARKS: A Secure Middleware for Pervasive Computing Applications

As portable devices have become a part of our everyday life, more people are unknowingly participating in a pervasive computing environment. People engage with not a single device for a specific purpose but many devices interacting with each other in the course of ordinary activity. With such prevalence of pervasive technology, the interaction between portable devices needs to be continuous and imperceptible to device users. Pervasive computing requires a small, scalable and robust network which relies heavily on the middleware to resolve communication and security issues. In this paper, we present the design and implementation of S-MARKS which incorporates device validation, resource discovery and a privacy module

Building Smart Space Applications with PErvasive Computing in Embedded Systems (PECES) Middleware

The increasing number of devices that are invisibly embedded into our surrounding environment as well as the proliferation of wireless communication and sensing technologies are the basis for visions like ambient intelligence, ubiquitous and pervasive computing. PErvasive Computing in Embedded Systems (PECES) project develops the technological basis to enable the global cooperation of embedded devices residing in different smart spaces in a context-dependent, secure and trustworthy manner. This paper presents PECES middleware that consists of flexible context ontology, a middleware that is capable of dynamically forming execution environments that are secure and trustworthy. This paper also presents set of tools to facilitate application development using the PECES middleware

ETS (Efficient, Transparent, and Secured) Self-healing Service for Pervasive Computing Applications

To ensure smooth functioning of numerous handheld devices anywhere anytime, the importance of self-healing mechanism cannot be overlooked. Incorporation of efficient fault detection and recovery in device itself is the quest for long but there is no existing self-healing scheme for devices running in pervasive computing environments that can be claimed as the ultimate solution. Moreover, the highest degree of transparency, security and privacy attainability should also be maintained. ETS Self-healing service, an integral part of our developing middleware named MARKS (Middleware Adaptability for Resource discovery, Knowledge usability, and Self-healing), holds promise for offering all of those functionalities

Active architecture for pervasive contextual services

International Workshop on Middleware for Pervasive and Ad-hoc Computing MPAC 2003), ACM/IFIP/USENIX International Middleware Conference (Middleware 2003), Rio de Janeiro, Brazil This work was supported by the FP5 Gloss project IST2000-26070, with partners at Trinity College Dublin and Université Joseph Fourier, and by EPSRC grants GR/M78403/GR/M76225, Supporting Internet Computation in Arbitrary Geographical Locations, and GR/R45154, Bulk Storage of XML Documents.Pervasive services may be defined as services that are available "to any client (anytime, anywhere)". Here we focus on the software and network infrastructure required to support pervasive contextual services operating over a wide area. One of the key requirements is a matching service capable of as-similating and filtering information from various sources and determining matches relevant to those services. We consider some of the challenges in engineering a globally distributed matching service that is scalable, manageable, and able to evolve incrementally as usage patterns, data formats, services, network topologies and deployment technologies change. We outline an approach based on the use of a peer-to-peer architecture to distribute user events and data, and to support the deployment and evolution of the infrastructure itself.Peer reviewe

The CLARITY modular ambient health and wellness measurement platform

Emerging healthcare applications can benefit enormously from recent advances in pervasive technology and computing. This paper introduces the CLARITY Modular Ambient Health and Wellness Measurement Platform:, which is a heterogeneous and robust pervasive healthcare solution currently under development at the CLARITY Center for Sensor Web Technologies. This intelligent and context-aware platform comprises the Tyndall Wireless Sensor Network prototyping system, augmented with an agent-based middleware and frontend computing architecture. The key contribution of this work is to highlight how interoperability, expandability, reusability and robustness can be manifested in the modular design of the constituent nodes and the inherently distributed nature of the controlling software architecture.Emerging healthcare applications can benefit enormously from recent advances in pervasive technology and computing. This paper introduces the CLARITY Modular Ambient Health and Wellness Measurement Platform:, which is a heterogeneous and robust pervasive healthcare solution currently under development at the CLARITY Center for Sensor Web Technologies. This intelligent and context-aware platform comprises the Tyndall Wireless Sensor Network prototyping system, augmented with an agent-based middleware and frontend computing architecture. The key contribution of this work is to highlight how interoperability, expandability, reusability and robustness can be manifested in the modular design of the constituent nodes and the inherently distributed nature of the controlling software architecture

Correlating context-awareness and mutation analysis for pervasive computing systems

Proceedings of the International Conference on Quality Software, 2010, p. 151-160Pervasive computing systems often use middleware as a means to communicate with the changing environment. However, the interactions with the context-aware middleware as well as the interactions among applications sharing the same middleware may introduce faults that are difficult to reveal by existing testing techniques. Our previous work proposed the notion of context diversity as a metric to measure the degree of changes in test inputs for pervasive software. In this paper, we present a case study on how much context diversity for test cases relates to fault-based mutants in pervasive software. Our empirical results show that conventional mutation operators can generate sufficient candidate mutants to support test effectiveness evaluation of pervasive software, and test cases with higher context diversity values tend to have higher mean mutation scores. On the other hand, for test cases sharing the same context diversity, their mutation scores can vary significantly in terms of standard derivations © 2010 IEEE.published_or_final_versio

Self-healing for Autonomic Pervasive Computing

ABSTRACT Self-healing is one of the main challenges to growing autonomic pervasive computing. Fault detection and recovery are the main steps of self-healing. Due to the characteristics of pervasive computing the self-healing becomes difficult. In this paper, the challenges of self-healing have been addressed and an approach to develop a self-healing service for autonomic pervasive computing is presented. The self-healing service has been developed and integrated into the middleware named MARKS+ (Middleware Adaptability for Resource discovery, Knowledge usability, and Self-healing). The self-healing approach is being evaluated on a test bed of PDAs. An application is being developed by using the proposed service

A Survey on Service Composition Middleware in Pervasive Environments

The development of pervasive computing has put the light on a challenging problem: how to dynamically compose services in heterogeneous and highly changing environments? We propose a survey that defines the service composition as a sequence of four steps: the translation, the generation, the evaluation, and finally the execution. With this powerful and simple model we describe the major service composition middleware. Then, a classification of these service composition middleware according to pervasive requirements - interoperability, discoverability, adaptability, context awareness, QoS management, security, spontaneous management, and autonomous management - is given. The classification highlights what has been done and what remains to do to develop the service composition in pervasive environments