A Cloud-based Mobile Privacy Protection System with Efficient Cache Mechanism

People increasingly rely on their mobile devices and use them to store a lot of data. Some of the data are personal and private, whose leakage leads to users\u27 privacy harm. Meanwhile, mobile apps and services over-collect users\u27 data due to the coarse-grained access control approach utilized by the mobile operating system. We propose a cloud-based approach to provide fine-grained access control toward data requests. We add privacy level, as a new metadata, to data and manage the storage using different policies correspondingly. However, the proposed approach leads to performance decreases because of the extra communication cost. We also introduce a novel cache mechanism to eliminate the extra cost by storing non-private and popular data on the mobile device. As part of our cache mechanism, we design a user-preference-based ordering method along with the principle of locality to determine how popular some data are. We also design a configurable refresh policy to improve the overall performance. Finally, we evaluate our approach using a real phone in a simulated environment. The results show that our approach can keep the response time of all data requests within a reasonable range and the cache mechanism can further improve the performance

Model-driven dual caching For nomadic service-oriented architecture clients

Mobile devices have evolved over the years from resource constrained devices that supported only the most basic tasks to powerful handheld computing devices. However, the most significant step in the evolution of mobile devices was the introduction of wireless connectivity which enabled them to host applications that require internet connectivity such as email, web browsers and maybe most importantly smart/rich clients. Being able to host smart clients allows the users of mobile devices to seamlessly access the Information Technology (IT) resources of their organizations. One increasingly popular way of enabling access to IT resources is by using Web Services (WS). This trend has been aided by the rapid availability of WS packages/tools, most notably the efforts of the Apache group and Integrated Development Environment (IDE) vendors. But the widespread use of WS raises questions for users of mobile devices such as laptops or PDAs; how and if they can participate in WS. Unlike their “wired” counterparts (desktop computers and servers) they rely on a wireless network that is characterized by low bandwidth and unreliable connectivity.The aim of this thesis is to enable mobile devices to host Web Services consumers. It introduces a Model-Driven Dual Caching (MDDC) approach to overcome problems arising from temporarily loss of connectivity and fluctuations in bandwidth

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor