A simulation study of data discovery mechanism for scientific data grid environment

Research in the area of grid computing has given us various ideas and solutions to address the requirements in a modern scientific computing community that managed massive amounts of a very large data collections in a geographically distributed environment. Data Grids mostly deal with large computational problems and provide geographically distributed resources for large-scale data-intensive applications that generate large data sets. A number of research groups are working on the data distribution problems in Data Grids and they are investigating the data replication approaches on the data distribution. This leads to a new problem in discovery and access to data in Data Grid environment. To address this problem we have developed a model to study various discovery mechanisms and investigate these mechanisms for Dynamic Scientific Data Grid Environments using our Grid Simulator. In this paper, we illustrate our model and our Grid Simulator

Decentralized replication strategies for P2P based scientific data grid

Scientific Data Grid provides geographically distributed resources for large-scale data-intensive applications that generate large scientific data sets and it mostly deals with large computational problems. Research in the area of grid has given various ideas and solutions to address these requirements. However, since the number of participants (scientists and institutes) that involve in this kind of environment is increasing tremendously, scalability, availability and reliability have been the core problem for such system. Peer-to-peer (P2P) is one of the architecture that promising scale and dynamism environment. In this paper, we present a P2P model for Scientific Data Grid that utilizes the P2P services to address those problems. For the purpose of this study, we have developed and used our own data grid simulation written using PARSEC. In this paper, we illustrate our P2P Scientific Data Grid model, our data grid simulation and the design of proposed data replication strategies. We then analyze the performance of data discovery service with and without the existence of replication strategies relative to their success rates, response time, average number of hop and bandwidth consumption. The results from simulation study that show how the proposed replication strategies promote high data availability in the proposed Scientific Data Grid model and how these strategies improve the discovery process are presented

Load allocation model for scheduling divisible data grid applications.

Problem statement: In many data grid applications, data can be decomposed into multiple independent sub-datasets and distributed for parallel execution and analysis. Approach: This property had been successfully employed by using Divisible Load Theory (DLT), which had been proved as a powerful tool for modeling divisible load problems in data-intensive grid. Results: There were some scheduling models had been studied but no optimal solution has been reached due to the heterogeneity of the grids. This study proposed a new optimal load allocation based on DLT model recursive numerical closed form solutions are derived to find the optimal workload assigned to the processing nodes. Conclusion/Recommendations: Experimental results showed that the proposed model obtained better solution than other models (almost optimal) in terms of Makespan

Optimal workload allocation model for scheduling divisible data grid applications

In many data grid applications, data can be decomposed into multiple independent sub-datasets and distributed for parallel execution and analysis. This property has been successfully employed using Divisible Load Theory (DLT), which has been proved a powerful tool for modeling divisible load problems in data-intensive grids. There are some scheduling models that have been studied but no optimal solution has been reached due to the heterogeneity of the grids. This paper proposes a new model called the Iterative DLT (IDLT) for scheduling divisible data grid applications. Recursive numerical closed form solutions are derived to find the optimal workload assigned to the processing nodes. Experimental results show that the proposed IDLT model leads to a better solution than other models (almost optimal) in terms of makespan

A framework for an application based mobile cache consistency method.

In a mobile environment, maintaining cache consistency is challenging. Applying one type of consistency levels either strict or weak is not suitable all the time, as the consistency requirements mainly depend on the mobile application system and differ from one to another. Also forcing the mobile client to use its cache data for the purpose of reading only limits the functionality of the caching. The stateful scheme Multi-level Mobile Cache Consistency Protocol that works in client-server architecture supports different levels of consistency. The Mobile client is able to issue updates transactions, and determine the consistency requirements upon its interest. Based on the Multi-Level Mobile Cache Consistency Protocol this paper presents a framework of stateful strategy; Application Based Multi-level Mobile Cache Consistency Method (ABMMCCM) that preserves the advantages of multi-level mobile cache consistency protocol and enhances its drawbacks. In ABMMCCM the consistency requirements are designed at the server side based on the application requirements, and each data item has a single consistency requirement entry. The proposed framework is initially compared to Multi-level Mobile Cache Consistency Protocol, and it appears that ABMMCCM reduces the number of messages transfer between the base server and the mobile client, which helps in better utilizing the wireless network, and reduces the overhead from the mobile client and the base server

Issues in implementing a scientific data grid based on peer-to-peer architecture

Grid and peer-to-peer (P2P) networks enable the sharing and aggregation of geographically distributed resources. Grids mostly deal with large computational problems and provide geographically distributed resources for large-scale data-intensive applications that generate large data sets, whereas P2P provides a way for sharing huge volumes of data. In a modern scientific computing, the communities of researchers involves in organizing, moving, visualizing, and analyzing massive amounts of a very large data collections in a geographically distributed environment. Research in the area of grid and P2P computing; have given us various ideas and solutions to address the problems. One of the most challenging issues in grid computing that address above requirements is locating and sharing remote data. In this paper, we illustrate the idea of using P2P approach for locating and sharing data in scientific data grid environment through our P2P scientific data grid framework

Data discovery algorithm for scientific data grid environment

In modern scientific computing communities, scientists are involved in managing massive amounts of very large data collections in a geographically distributed environment. Research in the area of grid computing has given us various ideas and solutions to address these requirements. Data grid mostly deals with large computational problems and provides geographically distributed resources for large-scale data-intensive applications that generate large data sets. Peer-to-peer (P2P) networks have also become a major research topic over the last few years. In a distributed P2P system, a discovery algorithm is required to locate specific information, applications, or users within the system. In this research work, we present our scientific data grid as a large P2P-based distributed system model. By using this model, we study various discovery algorithms for locating data sets in a data grid system. The algorithms we studied are based on the P2P architecture. We investigate these algorithms using our Grid Simulator developed using PARSEC. In this paper, we illustrate our scientific data grid model and our Grid Simulator. We then analyze the performance of the discovery algorithms relative to their average number of hop, success rates and bandwidth consumption. © 2005 Elsevier Inc. All rights reserved

ABMMCCS: Application based multi-level mobile cache consistency scheme

Maintaining cache consistency in mobile computing system is a critical issue due to the inheritance limitations in mobile environment such as limited network bandwidth and mobile device energy power.Most of the existing schemes maintaining mobile cache consistency support only one level of consistency that is either strict or weak which is not suitable all the time, as various mobile applications systems have different consistency requirements on their data.Also majority of the schemes restrict the using of cached data for reading only which is limits the functionality of the caching system.In this paper, a new scheme is proposed to maintain the mobile cache consistency in a single cell wireless network called Application Based Multi-Level Mobile Cache Consistency Scheme (ABMMCCS).The main idea in ABMMCCS is to be suitable to various real mobile application systems, by supporting multiple levels of consistency based on the application requirements, while savingthe mobile client energy power and reducing the consumption of the network bandwidth.The initial evaluation results show that, ABMMCCM reduces the number of uplink messages issued from the mobile client, which is assist in saving the mobile client energy and better utilizing the limited network bandwidth