Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN

A Personalized Framework for Trust Assessment

The number of computational trust models has been increasing quickly in recent years yet their applications for automating trust evaluation are still limited. The main obstacle is the difficulties in selecting a suitable trust model and adapting it for particular trust modeling requirements, which varies greatly due to the subjectivity of human trust. The Personalized Trust Framework (PTF) presented in this paper aims to address this problem by providing a mechanism for human users to capture their trust evaluation process in order for it to be replicated by computers. In more details, a user can specify how he selects a trust model based on information about the subject whose trustworthiness he needs to evaluate and how that trust model is configured. This trust evaluation process is then automated by the PTF making use of the trust models flexibly plugged into the PTF by the user. By so doing, the PTF enable users reuse and personalize existing trust models to suit their requirements without having to reprogram those models

Exploratory study to explore the role of ICT in the process of knowledge management in an Indian business environment

In the 21st century and the emergence of a digital economy, knowledge and the knowledge base economy are rapidly growing. To effectively be able to understand the processes involved in the creating, managing and sharing of knowledge management in the business environment is critical to the success of an organization. This study builds on the previous research of the authors on the enablers of knowledge management by identifying the relationship between the enablers of knowledge management and the role played by information communication technologies (ICT) and ICT infrastructure in a business setting. This paper provides the findings of a survey collected from the four major Indian cities (Chennai, Coimbatore, Madurai and Villupuram) regarding their views and opinions about the enablers of knowledge management in business setting. A total of 80 organizations participated in the study with 100 participants in each city. The results show that ICT and ICT infrastructure can play a critical role in the creating, managing and sharing of knowledge in an Indian business environment

A PageRank-based Reputation Model for VGI Data

AbstractQuality of data is one of the key issues in the domain of Volunteered geographic information (VGI). To this purpose, in literature VGI data has been sometime compared with authoritative geospatial data. Evaluation of single contributions to VGI databases is more relevant for some applications and typically relies on evaluating reputation of contributors and using it as proxy measures for data quality. In this paper, we present a novel approach for reputation evaluation that is based on the well known PageRank algorithm for Web pages. We use a simple model for describing different versions of a geospatial entity in terms of corrections and completions. Authors, VGI contributions and their mutual relationships are modeled as nodes of a graph. In order to evaluate reputation of authors and contributions in the graph we propose an algorithm that is based on the personalized version of PageRank

Agent Based E-Market: Framework, Design, and Implementation

Attempt has been made to design and develop a complete adoptive Multi Agent System pertaining to merchant brokering stage of Customer Buying Behaviour Model with the intent of appropriate framework. Intelligent agents are autonomous entity which observe and act upon an environment. In general, they are software robots and vitally used in variety of e-Business applications. This paper focuses on the discussions on electronic markets and the adoptive role, which agents can play in information transformation for automating e-market transactions. It is proposed to develop a framework for agent-based electronic markets for buyers and sellers totally with the assistance of software agents.Agent Oriented e-Business, Agent Oriented e-Markets, Buyer/Seller Agents, Java, Multi Agent Systems

Data centric trust evaluation and prediction framework for IOT

© 2017 ITU. Application of trust principals in internet of things (IoT) has allowed to provide more trustworthy services among the corresponding stakeholders. The most common method of assessing trust in IoT applications is to estimate trust level of the end entities (entity-centric) relative to the trustor. In these systems, trust level of the data is assumed to be the same as the trust level of the data source. However, most of the IoT based systems are data centric and operate in dynamic environments, which need immediate actions without waiting for a trust report from end entities. We address this challenge by extending our previous proposals on trust establishment for entities based on their reputation, experience and knowledge, to trust estimation of data items [1-3]. First, we present a hybrid trust framework for evaluating both data trust and entity trust, which will be enhanced as a standardization for future data driven society. The modules including data trust metric extraction, data trust aggregation, evaluation and prediction are elaborated inside the proposed framework. Finally, a possible design model is described to implement the proposed ideas