This paper presents our approach for service provisioning in pervasive computing environments. The presented approach is based on the usage of context-aware features and transactions during the discovery and the deployment of composite services. Context ensures that the best service offers are selected to participate in a service composition. Transactions help in improving the reliability and efficiency of the composite services.
Internet of Things is a concept that many physical devices can connect and share information. IoT development in mobile apps aimed to control connected devices. This paper describes the form of an application-led project by building a smart application system using the Lego Mindstorm kit. It decides on and simulates scenarios for the IoT solutions and the design and develop a proof-of-concept mobile and IoT application with emphasis on the technical implementations, architectural considerations, and interoperability. It demonstrates through graphical programming environment the configuring, implement and evaluation of distance sensor technologies in a mobile application.
Privacy challenges are a growing point of research in both political science and computer science as the pervasive nature of IoT devices turns Orwell’s dystopic state into a potential reality. This research maps out potential scenarios for IoT privacy challenges in the interdisciplinary effort to understand what it means to have privacy in world of internet-enabled sensors.
Rapid advances in software systems, wireless networks,and embedded devices have led to the development of apervasive and mobile cyberspace that provides an infrastructurefor anywhere/anytime service provisioning in different domainssuch as engineering, commerce, education, and entertainment.This style of service provisioning enables users to freely move betweengeographical areas and to continuously access informationand conduct online transactions. However, such a high mobilitymay cause performance and reliability problems during the executionof transactions. For example, the unavailability of sufficientbandwidth can result in failure of transactions when usersmove from one area (cell) to another. We present a context-awaretransaction model that dynamically adapts to the users' needs andexecution environments. Accordingly, we develop a new mobilitymanagement scheme that ensures seamless connectivity andreliable execution of context-aware transactions during mobilityof users. The proposed scheme is designed an…
The mapping of regulatory guidelines with organizational processes is an important aspect of a regulatory compliance management system. Automating this mapping process can greatly improve the overall compliance process. Currently, there is research on mapping between different entities such as ontology mapping, sentence similarity, semantic similarity and regulation-requirement mapping. However, there has not been adequate research on the automation of the mapping process between regulatory guidelines and organizational processes. In this paper, we explain how Natural Language Processing and Semantic Web technologies can be applied in this area. In particular, we explain how we can take advantage of the structures of regulation-ontology and the process-ontology in order to compute the similarity between a regulatory guideline and a process. Our methodology is validated using a case study in the Pharmaceutical industry, which has shown promising results.
Big Data encompasses large volume of complex structured, semi-structured, and unstructured data, which is beyond the processing capabilities of conventional databases. The processing and analysis of Big Data now play a central role in decision making, forecasting, business analysis, product development, customer experience, and loyalty, to name but a few. In this paper, we examine the distinguishing characteristics of Big Data along the lines of the 3Vs: variety, volume, and velocity. Accordingly, the paper provides an insight into the main processing paradigms in relation to the 3Vs. It defines a lifecycle for Big Data processing and classifies various available tools and technologies in terms of the lifecycle phases of Big Data, which include data acquisition, data storage, data analysis, and data exploitation of the results. This paper is first of its kind that reviews and analyzes current trends and technologies in relation to the characteristics, evolution, and processing of Big Data.
Risk analysis is considered as an important process to identify the known and potential vulnerabilities and threats in the web services security. It is quite difficult for users to collect adequate events to estimate the full vulnerabilities and probability of threats in the Web, due to the rapid change of the malicious attacks and the new computer’s vulnerabilities. In this paper, a fuzzy risk assessment model is developed in order to evaluate the risk of web services in a situation where complete information is not available. The proposed model extends Pseudo-Order Preference Model (POPM) to estimate the imprecise risk based on richness of information and to determine their ranking using a weighted additive rule. A case study of a number of web services is presented in order to test the proposed approach.