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Causal consistency is an intermediate consistency model that can be achieved together with high availability and high-performance requirements even in presence of network partitions. In the context of partitioned data stores, it has been shown that implicit dependency tracking using clocks is more efficient than explicit dependency tracking by sending dependency check messages. Existing clock-based...
We investigate the problem of data synchronization in which a sender has a set of packets to be distributed to all the receivers via a broadcast channel. Initially, each receiver has some fraction of the packets. At each time slot, the sender might broadcast a packet to all the receivers. The goal is to find a broadcast scheme that minimizes the number of time slots until all the receivers successfully...
With the increasing popularity of serving and storing data in multiple data centers, we investigate the efficiency of majority quorum-based data consistency algorithms under this scenario. Because of the failure-prone nature of distributed storage systems, majority quorum-based data consistency algorithms become one of the most widely adopted approaches. In this paper, we propose the MeteorShower...
In extremely connected and dynamic environments, such as data centers, SDN network devices can be exploited to simplify the management of network provisioning. However, they leverage on TCAMs to implement the flow tables, i.e., on size-limited memories that can be quickly filled up when fine-grained traffic control is required, eventually preventing the installation of new forwarding rules. In this...
The demand for multi-dimensional range query over Distributed Ordered Table (DOT) has become increasingly popular, however, the DOT does not support queries very well other than the primary key. One solution to this problem is indexing. Many indexing techniques are focusing on how to improve the query ability, but do not care about the consistency between the index table and base data table. This...
Concurrent Big Data applications often require high-performance storage, as well as ACID (Atomicity, Consistency, Isolation, Durability) transaction support. Although blobs (binary large objects) are an increasingly popular storage model for such applications, state-of-the-art blob storage systems offer no transaction semantics. This demands users to coordinate data access carefully in order to avoid...
The world keeps contributing to the increase in data everyday drastically. Scientific applications, weather forecasting, researches, hospitals, military services are few such major contributors. As the amount of data increases, the need to provide efficient, easy to use solutions has become one of the main issues for these type of computations. The best solution to this issue is the use of Distributed...
For datacenter applications that require tight synchronization, transactions are commonly employed for achieving concurrency while preserving correctness. Unfortunately, distributed transactions are hard to scale due to the decentralized lock acquisition and coordination protocols they employ. We investigate the use of a centralized lock broker architecture to improve the efficiency/scalability for...
Information sharing among a group of friends or colleagues in real life is usually a distributed process: we tell each other interesting or important news without any mandatory assistance or approval from a third party. Surprisingly, this is not what happens when sharing files among a group of friends over the Internet. While the goal of file sharing is to disseminate files among multiple parties,...
Simulation is an important and widely used method for the analysis of the behavior of large systems, many applications exist. Special branches of research are the simulation of very large models using distributed simulation, and embedded simulation, i.e. The coupling of virtual models with physical hardware. In our work, we approach the combination of both challenges, thus we use distributed simulation...
With their globally distributed datacenters, clouds now provide an opportunity to run complex large-scale applications on dynamically provisioned, networked and federated infrastructures. However, there is a lack of tools supporting data intensive applications across geographically distributed sites. For instance, scientific workflows which handle many small files can easily saturate state-of-the-art...
In this paper, we describe xBook, a generic, opensource e-Science infrastructure for distributed, relational data management that is particularly designed for the needs of archaeological related disciplines. The key feature of xBook is that it can be used as an offline resource at remote sites during excavations and can be synchronized with a central server at any time. While some scientists can record...
Electronic Health Record (EHR) Systems are widely considered a crucial tool for the excellence in patient care, especially in the context of chronic diseases. Nevertheless, patients often do not have full control on their clinical data, which are generated by different health centers. Moreover, collecting, storing and providing clinical data are intensive tasks for health structures, which frequently...
Deferred update replication (DUR) is an established approach to implementing highly efficient and available storage. While the throughput of read-only transactions scales linearly with the number of deployed replicas in DUR, the throughput of update transactions experiences limited improvements as replicas are added. This paper presents Parallel Deferred Update Replication (P-DUR), a variation of...
Data replication is an increasingly important topic as databases are more and more deployed over distributed systems, grid community and clustering systems. The performance, reliability and portability of entire database may possible by using replication technique. Replication may be considered as a data backup policy. Replication in homogeneous system is common practice in real life, but replication...
Named Data Networking [1] has an intrinsic distributed nature, which eases decentralizing formerly centralized protocols as discussed in [12], [10]. Nevertheless, implementing fully distributed protocols for many-to-many communications remains challenging. The NDN architecture, built upon CCN [3], makes the following assumptions in order to place content as the narrow waist of the communication stack:...
A lot of research effort is being spent in the field of synchronization between mobile devices and cloud lately, but most of the applications use a centralized cloud storage solution. In contrast, Mobile Cloud Synchronization (MCSync) framework aims to give developers the ability to easily create and maintain a distributed, decentralized database, which allows users to reliably store and synchronize...
To store and manage data efficiently is the critical issue which modern information infrastructures confront with. To accommodate the massive scale of data in the Internet environment, most common solutions utilize distributed file systems. However there still exist disadvantages preventing these systems from delivering satisfying performance. In this paper, we present a Name Node cluster file system...
Metadata in a parallel distributed database contains information about table fragmentation, physical storage distribution, and access control policies. It is essential to query processing and security policy enforcement. Metadata in a parallel distributed database is usually stored in the form of system tables, it can be replicated through out every site in the system in order to improve performance...
Fault tolerance in distributed systems relies heavily on some form of replication. Replication can also be used to reduce the access latency and the bandwidth consumption in large scale distributed systems. However, in case of large volumes of data, the replica placing strategy and the consistency algorithms become key factors for the performance of the data replication strategy. We present a simulation...
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