Distributed Shared State with History Maintenance

Shared mutable state is challenging to maintain in a distributed environment. We develop a technique, based on the Operational Transform, that guides independent agents into producing consistent states through inconsistent but equivalent histories of operations. Our technique, history maintenance, extends and streamlines the Operational Transform for general distributed systems. We describe how to use history maintenance to create eventually-consistent, strongly-consistent, and hybrid systems whose correctness is easy to reason about

HVSTO: Efficient Privacy Preserving Hybrid Storage in Cloud Data Center

In cloud data center, shared storage with good management is a main structure used for the storage of virtual machines (VM). In this paper, we proposed Hybrid VM storage (HVSTO), a privacy preserving shared storage system designed for the virtual machine storage in large-scale cloud data center. Unlike traditional shared storage, HVSTO adopts a distributed structure to preserve privacy of virtual machines, which are a threat in traditional centralized structure. To improve the performance of I/O latency in this distributed structure, we use a hybrid system to combine solid state disk and distributed storage. From the evaluation of our demonstration system, HVSTO provides a scalable and sufficient throughput for the platform as a service infrastructure.Comment: 7 pages, 8 figures, in proceeding of The Second International Workshop on Security and Privacy in Big Data (BigSecurity 2014

Khazana An infrastructure for building distributed services

technical reportEssentially all distributed systems?? applications?? and services at some level boil down to the problem of man aging distributed shared state Unfortunately?? while the problem of managing distributed shared state is shared by many applications?? there is no common means of managing the data every application devises its own solution We have developed Khazana?? a distributed service exporting the abstraction of a distributed per sistent globally shared store that applications can use to store their shared state Khazana is responsible for performing many of the common operations needed by distributed applications?? including replication?? consis tency management?? fault recovery?? access control?? and location management Using Khazana as a form of middleware?? distributed applications can be quickly de veloped from corresponding uniprocessor applications through the insertion of Khazana data access and syn chronization operation

Khazana an infrastructure for building distributed services

technical reportEssentially all distributed systems, applications and service at some level boil down to the problem of managing distributed shared state. Unfortunately, while the problem of managing distributed shared state is shared by man applications, there is no common means of managing the data - every application devises its own solution. We have developed Khazana, a distributed service exporting the abstraction of a distributed persistent globally hared store that applications can use to store their shared state. Khazana is responsible for performing many of the common operations needed by distributed applications, including replication, consistency management, fault recovery, access control, and location management. Using Khazana as a form of middleware, distributed applications can be quickly developed from corresponding uniprocessor applications through the insertion of Khazana data access and synchronization operations

Distributed Bayesian Probabilistic Matrix Factorization

Matrix factorization is a common machine learning technique for recommender systems. Despite its high prediction accuracy, the Bayesian Probabilistic Matrix Factorization algorithm (BPMF) has not been widely used on large scale data because of its high computational cost. In this paper we propose a distributed high-performance parallel implementation of BPMF on shared memory and distributed architectures. We show by using efficient load balancing using work stealing on a single node, and by using asynchronous communication in the distributed version we beat state of the art implementations

Remote information concentration using a bound entangled state

Remote information concentration, the reverse process of quantum telecloning, is presented. In this scheme, quantum information originally from a single qubit, but now distributed into three spatially separated qubits, is remotely concentrated back to a single qubit via an initially shared entangled state without performing any global operations. This entangled state is an unlockable bound entangled state and we analyze its properties.Comment: 4 pages, 2 figure

Explicit equilibria in a kinetic model of gambling

We introduce and discuss a nonlinear kinetic equation of Boltzmann type which describes the evolution of wealth in a pure gambling process, where the entire sum of wealths of two agents is up for gambling, and randomly shared between the agents. For this equation the analytical form of the steady states is found for various realizations of the random fraction of the sum which is shared to the agents. Among others, Gibbs distribution appears as steady state in case of a uniformly distributed random fraction, while Gamma distribution appears for a random fraction which is Beta distributed. The case in which the gambling game is only conservative-in-the-mean is shown to lead to an explicit heavy tailed distribution

Shared Hash Tables in Parallel Model Checking

AbstractIn light of recent shift towards shared-memory systems in parallel explicit model checking, we explore relative advantages and disadvantages of shared versus private hash tables. Since usage of shared state storage allows for techniques unavailable in distributed memory, these are evaluated, both theoretically and practically, in a prototype implementation. Experimental data is presented to assess practical utility of those techniques, compared to static partitioning of state space, more traditional in distributed memory algorithms