Editorial

Citation

Khalil, I. (2013), "Editorial", International Journal of Pervasive Computing and Communications, Vol. 9 No. 1. https://doi.org/10.1108/ijpcc.2013.36109aaa.001

Editorial

Article Type: Editorial From: International Journal of Pervasive Computing and Communications, Volume 9, Issue 1

This is the first issue of Volume 9 of the International Journal of Pervasive Computing and Communication, which commences the ninth year of this journal which has served a large community of researchers and academics around the world with the highest quality articles reporting on the state-of-the-art research results and scientific findings in the field of pervasive computing and communication.

In this issue, we have four research papers. The first paper (“Using wireless proximity data to infer the behaviour of mobile people”) is about learning and predicting human behaviour from daily life activities. The aim of the work presented in this paper is to investigate a mechanism that can recognise high-level activities (like going for a walk, travelling, doing evening activity, etc.) and behaviour of low entropy people (people with regular daily life routines, e.g. elderly people with dementia, patients with regular routines) in order to help them improve their health related daily life activities by using wireless proximity data (e.g. Bluetooth, Wi-Fi). Generating the real time wireless proximity data and then recognising the tasks and high-level activities from that data are the major challenges that are discussed in this paper. A number of scenarios and experiments are designed to prove the validity of the proposed methodology.

The second paper (“Data confidentiality using fragmentation in cloud computing”) addresses one of the foremost issues in cloud computing research, which is data confidentiality. Storing sensitive business data at a semi-trusted cloud service provider (CSP) poses a number of threats to data security, privacy and control. Current approaches for data security in cloud environments rely on encryption; however, a purely cryptographic approach requires considerable computational resources, in particular if data fragments are distributed among several servers of a CSP. This paper proposes a minimum-encryption fragmentation method that stores data fragments at different CSPs in a way that makes them un-linkable. Normalized relational databases are used as a basis for the fragmentation process, with each table treated as a separate fragment. This fragmentation and distribution approach improves privacy and confidentiality when dealing with semi-trusted CSPs.

The third paper (“Situation-awareness and reasoning using uncertain context in mobile peer-to-peer environments”) focuses on how recent advances in mobile computing and sensing technologies have enabled mobile devices to individually sense environment context and develop situation awareness capability. In order to gain a better understanding of the environment, mobile devices, that are co-located, can establish a mobile peer-to-peer (MP2P) environment to share their individual context information. The purpose of this paper is to propose a theoretical model for representing and reasoning about situations using uncertain context information captured by multiple devices in an MP2P environment. The proposed model has been implemented as a middleware and evaluated using data from real experiments in various scenarios and environment settings. The results of the experiments show the robust performances of the proposed model as the basis for situation reasoning in the environment.

The fourth paper (“Towards a domain-specific context acquisition, presentation and rule-based control platform”) presents the design of a domain-specific context-aware platform supporting context acquisition, presentation and rule-based control. The proposed platform uses a formal context model, based on ontologies description, aiming to provide a common representation of contextual information, facilitating thus integration and reusability in application domains, which embrace a common set of requirements. A context-aware system has been built upon a well-defined data model, which inherits a list of offered functionalities and/or services at the acquisition, presentation and reasoning level. The presented platform entails an event-driven context-based inference mechanism aiming to enable automated reasoning.

February 2013

Ismail KhalilEditor-in-Chief