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Distributed storage systems comprise a large number of commodity hardware distributed across several data centers. Even in the presence of failures (permanent failures) the system should provide reliable storage. While replication has advantages because of its simplicity there exist coding techniques that provide adaptable reliability properties with an optimal redundancy ratio at the same time e...
A complex workflow is often executed by geographically dispersed partners or different organizations. As a solution for dealing with the decentralized nature of workflow applications, a workflow can be fragmented into small pieces and scheduled to different servers for its execution. An important challenge in distributed workflows is to optimize the fragmentation and distribution to achieve efficiency...
MapReduce has been very successful in implementing large-scale data-intensive applications. Because of its simple programming model, MapReduce has also begun being utilized as a programming tool for more general distributed and parallel applications, e.g., HPC applications. However, its applicability is limited due to relatively inefficient runtime performance and hence insufficient support for flexible...
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...
With the permeation of information technology into the physical world and human society, we are on the way to a Cyber Physical Society (CPSocio). A CPSocio inter-connects the nature, the cyber space, and the society, so as to provide human beings with a better living and working environment. Researches on CPSocio will lead to a new revolution of information science and technology. In realizing CPSocio,...
The analysis and modeling of the failures bound to occur in today's large-scale production systems is invaluable in providing the understanding needed to make these systems fault-tolerant yet efficient. Many previous studies have modeled failures without taking into account the time-varying behavior of failures, under the assumption that failures are identically, but independently distributed. However,...
As the IEEE 1516 standard for distribution simulation, High Level Architecture (HLA) framework does not solve the issues of scalability, dynamic load-balance and fault tolerance. HLA does not support federation migration, which would balance the system workload on heterogeneous distributed resources and consequently improve simulation's performance either. In this paper, a Grid based Advanced Distributed...
Digital ocean prototype system is a key part of the China digital ocean information basic framework and the basic integration platform for China ocean information management and application. The purpose of marine environment data warehouse is to provide comprehensive and multiple marine information services. This paper proposed distributed marine environment data warehouse construction, and gives...
The growing amount of scientific data from sensors and field observations is posing a challenge to ??data valets?? responsible for managing them in data repositories. These repositories built on commodity clusters need to reliably ingest data continuously and ensure its availability to a wide user community. Workflows provide several benefits to modeling data-intensive science applications and many...
With the rapid development of e-commerce, there is increasingly tremendous amount of information available on the Web, which is always distributed across different platforms. Thus, how to integrate the information to meet the end-users' need becomes a challenge. The rise of mashup provides a promising solution for this problem. Generally, there are mainly two mashup models, which are client-side based...
With the growing complexity in computer systems, it has been a real challenge to detect and diagnose problems in today's large-scale distributed systems. Usually, the correlations between measurements collected across the distributed system contain rich information about the system behaviors, and thus a reasonable model to describe such correlations is crucially important in detecting and locating...
Many mobile devices have reached the point where the users' (active) working set is smaller than the amount of storage available and that trend is likely to continue. Currently these resources are made available for recording new data, but we think that we could make better use of this capacity. Hoarding previously not accessed data could give better data coverage in cases of disconnected operation,...
Originally, model versioning has been developed to enable teams of developers to work on common model data, concurrently. We have the idea to use the same techniques to facilitate the collaboration of collaboration applications. Multi threaded applications share a common main memory. Thus, all threads have access to the full data structures and each thread may query and update the data structures,...
This work enhances the current UML4ODP FDIS (Use of UML for ODP systems specification, final draft international standard) computational metamodel with QoS (quality of service) features relevant to distributed systems. We first introduce two new important concepts, namely; QoS-labeled interactions and QoS-embedded interfaces. Based on these, we provide a UML metamodel of interfaces and interaction...
Modern distributed systems that have to avoid performance degradation and system overload require several runtime management decisions for load balancing and load sharing, overload and admission control, job dispatching and request redirection. As the external workload and the internal resource behavior of the modern system is highly complex and variable, self-adaptive techniques require a stable...
Nowadays, massive amounts of data which are often geographically distributed and owned by different organisations, are being mined. As consequence, large volumes of knowledge is being generated. This causes the problem of efficient knowledge management in distributed data mining (DDM). The main aim of is to exploit fully the benefit of distributed data analysis while minimising the communication overhead...
In this paper, we propose a new distributed linkage method for the great amount of event data. This method is used for event-data processing such as system behavior visualization, which can diagnose and provide information about complex distributed IT system behavior from communication messages. In this method, we use two techniques: probe and data distribution by ??source??. The probe links event...
In this paper, we propose a new linkage method for the great amount of event data in distributed computing environments. This method is used for event-data processing such as System Behavior Visualization, which can diagnose and provide information about complex distributed IT system behavior. The event data using System Behavior Visualization are network messages between IT system servers. In this...
After analyzing the data exchange procedure of distributed network system, this paper presents a common disaster tolerance model based on dataflow replication. This model adopted replicating dataflow between two computers and restoring dataflow to backup data. Then it can use dataflow replay to recover data.
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