Privacy preserving social network data publication

The introduction of online social networks (OSN) has transformed the way people connect and interact with each other as well as share information. OSN have led to a tremendous explosion of network-centric data that could be harvested for better understanding of interesting phenomena such as sociological and behavioural aspects of individuals or groups. As a result, online social network service operators are compelled to publish the social network data for use by third party consumers such as researchers and advertisers. As social network data publication is vulnerable to a wide variety of reidentification and disclosure attacks, developing privacy preserving mechanisms are an active research area. This paper presents a comprehensive survey of the recent developments in social networks data publishing privacy risks, attacks, and privacy-preserving techniques. We survey and present various types of privacy attacks and information exploited by adversaries to perpetrate privacy attacks on anonymized social network data. We present an in-depth survey of the state-of-the-art privacy preserving techniques for social network data publishing, metrics for quantifying the anonymity level provided, and information loss as well as challenges and new research directions. The survey helps readers understand the threats, various privacy preserving mechanisms, and their vulnerabilities to privacy breach attacks in social network data publishing as well as observe common themes and future directions

Digital library service quality assessment model

With the introduction of digital library services, the quality of service (QoS) has become paramount importance for evaluating the performance of the digital library service provisioning. Various models and frameworks have been proposed to evaluate digital library QoS. However, the prevalent research concentration in QoS for digital library is on the dimensions of the perspective of users’ perception. In this paper, we address the same research problem from a different dimension which is from the perspective of the digital service providers. To this end, we propose a new model suitable for evaluating the performance of digital library services. We argue that the level of QoS provided by the digital service providers have direct impact on the perception and satisfaction of the digital service end-users

Sensor grid middleware metamodeling and analysis

Sensor grid is a platform that combines wireless sensor networks and grid computing with the aim of exploiting the complementary advantages of the two systems. Proper integration of these distinct systems into effective, logically single platform is challenging. This paper presents an approach for practical sensor grid implementation and management. The proposed approach uses a metamodeling technique and performance analysis and tuning as well as a middleware infrastructure that enable practical sensor grid implementation and management. The paper presents our implementation and analysis of the sensor grid. © 2014 Srimathi Chandrasekaran et al

Information provenance for open distributed collaborative system

In autonomously managed distributed systems for collaboration, provenance can facilitate reuse of information that are interchanged, repetition of successful experiments, or to provide evidence for trust mechanisms that certain information existed at a certain period during collaboration. In this paper, we propose domain independent information provenance architecture for open collaborative distributed systems. The proposed system uses XML for interchanging information and RDF to track information provenance. The use of XML and RDF also ensures that information is universally acceptable even among heterogeneous nodes. Our proposed information provenance model can work on any operating systems or workflows.<br /

An efficient scheduling method for grid systems based on a hierarchical stochastic petri net

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min