Data access

About: Data access is a research topic. Over the lifetime, 13141 publications have been published within this topic receiving 172859 citations. The topic is also known as: Data access.

Cachet: a decentralized architecture for privacy preserving social networking with caching

Abstract: Online social networks (OSNs) such as Facebook and Google+ have transformed the way our society communicates However, this success has come at the cost of user privacy; in today's OSNs, users are not in control of their own data, and depend on OSN operators to enforce access control policies A multitude of privacy breaches has spurred research into privacy-preserving alternatives for social networking, exploring a number of techniques for storing, disseminating, and controlling access to data in a decentralized fashion In this paper, we argue that a combination of techniques is necessary to efficiently support the complex functionality requirements of OSNsWe propose Cachet, an architecture that provides strong security and privacy guarantees while preserving the main functionality of online social networks In particular, Cachet protects the confidentiality, integrity and availability of user content, as well as the privacy of user relationships Cachet uses a distributed pool of nodes to store user data and ensure availability Storage nodes in Cachet are untrusted; we leverage cryptographic techniques such as attribute based encryption to protect the confidentiality of data For efficient dissemination and retrieval of data, Cachet uses a hybrid structured-unstructured overlay paradigm in which a conventional distributed hash table is augmented with social links between users Social contacts in our system act as caches to store recent updates in the social network, and help reduce the cryptographic as well as the communication overhead in the networkWe built a prototype implementation of Cachet in the FreePastry simulator To demonstrate the functionality of existing OSNs we implemented the "newsfeed" application Our evaluation demonstrates that (a) decentralized architectures for privacy preserving social networking are feasible, and (b) use of social contacts for object caching results in significant performance improvements

Method and apparatus for data management

Abstract: A data access system decouples the data processing from the data storage to provide improved accessibility, integrity, scalability and other features. The system comprises: database units arranged in virtual partitions each independently accessible, a plurality of data processing units, and a switching network for switching the data processing units between the virtual partitions, thereby to assign data processing capacity dynamically to respective virtual partitions.

System and method for securely managing data stored on mobile devices, such as enterprise mobility data

Abstract: A system and method for managing data stored on mobile devices is described. In some cases, the system stores data, such as data under enterprise mobility management, within a secured memory location of a SIM card. In some cases, the system may request validation credentials before providing access to data stored in secure locations. In some cases, the system may review an access policy and request validation based on instructions from the access policy.

Optimizing data access latencies in cloud systems by intelligent virtual machine placement

Abstract: Many cloud applications are data intensive requiring the processing of large data sets and the MapReduce/Hadoop architecture has become the de facto processing framework for these applications. Large data sets are stored in data nodes in the cloud which are typically SAN or NAS devices. Cloud applications process these data sets using a large number of application virtual machines (VMs), with the total completion time being an important performance metric. There are many factors that affect the total completion time of the processing task such as the load on the individual servers, the task scheduling mechanism, communication and data access bottlenecks, etc. One dominating factor that affects completion times for data intensive applications is the access latencies from processing nodes to data nodes. Ideally, one would like to keep all data access local to minimize access latency but this is often not possible due to the size of the data sets, capacity constraints in processing nodes which constrain VMs from being placed in their ideal location and so on. When it is not possible to keep all data access local, one would like to optimize the placement of VMs so that the impact of data access latencies on completion times is minimized. We address this problem of optimized VM placement - given the location of the data sets, we need to determine the locations for placing the VMs so as to minimize data access latencies while satisfying system constraints. We present optimal algorithms for determining the VM locations satisfying various constraints and with objectives that capture natural tradeoffs between minimizing latencies and incurring bandwidth costs. We also consider the problem of incorporating inter-VM latency constraints. In this case, the associated location problem is NP-hard with no effective approximation within a factor of 2 - ϵ for any ϵ > 0. We discuss an effective heuristic for this case and evaluate by simulation the impact of the various tradeoffs in the optimization objectives.