Hierarchical Replication Research Articles

Cost Saving Replication Technique in Data Grid

Replication is a useful technique for distributed database systems. An existing popular technique that has been used before are Read One-write-All Monitoring Synchronization Transactions System (ROWA-MSTS) and Hierarchical Replication Scheme (HRS). Nevertheless, these techniques have their flaws in terms of replication time taken. Subsequently, ROWA and HRS take more executing time in order to complete a transaction. It is because they have to copy their data to all sites. This research, Binary Voting Fragmented Database Replication (BVFDR) model, the some-data-to-some-sites technique is proposed. In order to handle transactions in the systems, BVFDR considers the neighbouring servers binary vote assignment to its logical grid structure on fragmented data copies. Therefore, it reduces storage capacity. An experiment has been carried out in three replicated servers. The results have been compared with existing techniques such ROWA and HRS. The result shows that BVFDR is able to preserve data consistency and outperformed in terms of time taken for a complete transaction compare to existing techniques. Overall, BVFDR able to handle fragmented data replication as well as capable to manage transaction management in distributed database environment by maintaining consistency of the data through the synchronization approach.

Hierarchical replication and multiversion concurrency control model for mobile database systems (MDS)

In mobile ad hoc network, the existing replication technique and multiversion scheme increase the cost of overhead. In addition, there is possibility of mobility- and energy-related issues. In order to overcome these issues, in this paper, we propose a hierarchical replication and multiversion concurrency control model for mobile database systems. In this technique, cluster heads (CHs) are selected based on the distance from the past node movements. When the client raises a query, the database server distributes the replicated data to the nearer cluster heads. When any CH observes that one of its members is about to move, then it suggests the nearest cluster having the same data object to the moving client, so that it can quickly access the data during its movement. For concurrency control, each CH maintains a concurrency table for each of its replicated data object. By simulation results, we show that the proposed technique reduces the overhead and energy consumption.

Hierarchical structure formation and pattern replication by capillary force lithography

The soft lithographic method is gaining popularity in the manufacturing of low-cost micro and sub-microstructures. For several applications, it is desirable to fabricate structures with different lateral size as well as different height, i.e. hierarchical structures, on the same substrate. This is difficult for normal microfabrication methods, particularly for the photolithography method, which is the main method used in the IC industry. Here we demonstrate a simple yet cost-effective process to form hierarchical structures by capillary force lithography (CFL). In our process, the simple principle that the time needed for the fluid to fill up the cavity in the mould is different if the contact angle of the mould or the width of the cavity in the mould is different. Based on this principle, two methods were developed to achieve hierarchical structures by CFL. One is to selectively modify the PDMS mould by UV or oxygen plasma treatment to change its wettability in different areas. The other is to make patterns with variable dimensions in the mould. By using the PDMS mould with selectively modified wettability or patterns with different lateral dimensions, hierarchical structures with a convex/concave microlens array or stripes with convex/concave surfaces have been manufactured successfully.

An Experimental Study on the Processes of Hierarchical Morphology Replication by Means of a Mesocrystal: A Case Study of Poly(3,4-ethylenedioxythiophene)

The processes for the synthesis of polymers in a mesocrystal structure were studied for understanding of the mechanisms. The mesocrystal structure has the nanoscale pores between the unit crystals for incorporation of guest molecules. The monomers can be incorporated and polymerized in the nanospace of the mesocrystals. In the present work, a sea urchin spine and poly(3,4-ethylenedioxythiophene) (PEDOT) were adopted as a model of the original mesocrystal and replicated polymer material, respectively. A sea urchin spine, as an original material, has the hierarchical architectures based on the mesocrystal structure consisting of the oriented carbonate nanocrystals. The monomers were introduced in the nanoscale pores. The composite of the original carbonate and PEDOT was obtained after the incorporation and the polymerization. After dissolution of the original carbonate, the resultant PEDOT architecture showed the hierarchical morphologies similar to those of the original sea urchin spine. The morphology replication processes were compared with those of the different polymers. The important factors for the morphology replication are studied. The present work suggests that the approach can be applied to morphogenesis of a variety of polymer materials.

Network and data location aware approach for simultaneous job scheduling and data replication in large-scale data grid environments

Data Grid integrates graphically distributed resources for solving data intensive scientific applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Scheduling is a traditional problem in parallel and distributed system. However, due to special issues and goals of Grid, traditional approach is not effective in this environment any more. Therefore, it is necessary to propose methods specialized for this kind of parallel and distributed system. Another solution is to use a data replication strategy to create multiple copies of files and store them in convenient locations to shorten file access times. To utilize the above two concepts, in this paper we develop a job scheduling policy, called hierarchical job scheduling strategy (HJSS), and a dynamic data replication strategy, called advanced dynamic hierarchical replication strategy (ADHRS), to improve the data access efficiencies in a hierarchical Data Grid. HJSS uses hierarchical scheduling to reduce the search time for an appropriate computing node. It considers network characteristics, number of jobs waiting in queue, file locations, and disk read speed of storage drive at data sources. Moreover, due to the limited storage capacity, a good replica replacement algorithm is needed. We present a novel replacement strategy which deletes files in two steps when free space is not enough for the new replica: first, it deletes those files with minimum time for transferring. Second, if space is still insufficient then it considers the last time the replica was requested, number of access, size of replica and file transfer time. The simulation results show that our proposed algorithm has better performance in comparison with other algorithms in terms of job execution time, number of intercommunications, number of replications, hit ratio, computing resource usage and storage usage.

Recent Progress in the Replication of Hierarchical Biological Tissues

AbstractBioinspired materials research is a continuously growing field in interdisciplinary materials science and engineering with large potential for novel functional materials. One possibility of combining the hierarchical structure of natural materials with the broad range of available constituent materials is biotemplating, i.e., the use of biological materials as scaffolds or casting molds for the synthesis of ceramics, semiconductors, metals, polymers or composites thereof. However, the replication of structural details of complex biological tissues over several levels of hierarchy down to the nanometer level is still a big challenge. The biological templates need to be (made) accessible for the precursor materials down to the nanometer scale, and the desired inorganic replica often require a final thermal treatment with the danger of collapse of the nanostructure. Here, some of the current knowledge about the replication of hierarchical biological materials into ceramics or carbons with special emphasis on wood as a template is reviewed. It is concluded that real hierarchical replication down to the nanometer scale requires a careful preparation of the biological template, followed by elaborate template infiltration via gas or liquid phases and their transformation into a solid, and finally, the gentle removal of the template. Not surprisingly, retaining the replicated material in an amorphous or nanocrystalline state is a key requirement for a successful nanometer‐scale replication of biological materials.

Synthesis and Morphogenesis of Organic and Inorganic Polymers by Means of Biominerals and Biomimetic Materials

We have studied the simultaneous synthesis and morphogenesis of polymer materials with hierarchical structures from nanoscopic to macroscopic scales. The morphologies of the original materials can be replicated to the polymer materials. In general, it is not easy to achieve the simultaneous synthesis and morphogenesis of polymer material even using host materials. In the present work, four biominerals and three biomimetic mesocrystal structures are used as the host materials or templates and polypyrrole, poly(3-hexylthiopehene), and silica were used as the precursors for the simultaneous syntheses and morphogenesis of polymer materials. The host materials with the hierarchical structure possess the nanospace for the incorporation of the monomers. After the incorporation of the monomers, the polymerization reaction proceeds in the nanospace with addition of the initiator agents. Then, the dissolution of the host materials leads to the formation and morphogenesis of the polymer materials. The scheme of the replication can be classified into the three types based on the structures of the host materials (types I-III). The type I template facilitates the hierarchical replication of the whole host material, type II mediates the hierarchical surface replication, and type III induces the formation of the two-dimensional nanosheets. Based on these results, the approach for the coupled synthesis and morphogenesis can be applied to a variety of combinations of the templates and polymer materials.

Enhanced Dynamic Hierarchical Replication and Weighted Scheduling Strategy in Data Grid

The Data Grid provides massive aggregated computing resources and distributed storage space to deal with data-intensive applications. Due to the limitation of available resources in the grid as well as production of large volumes of data, efficient use of the Grid resources becomes an important challenge. Data replication is a key optimization technique for reducing access latency and managing large data by storing data in a wise manner. Effective scheduling in the Grid can reduce the amount of data transferred among nodes by submitting a job to a node where most of the requested data files are available. In this paper two strategies are proposed, first a novel job scheduling strategy called Weighted Scheduling Strategy (WSS) that uses hierarchical scheduling to reduce the search time for an appropriate computing node. It considers the number of jobs waiting in a queue, the location of the required data for the job and the computing capacity of the sites Second, a dynamic data replication strategy, called Enhanced Dynamic Hierarchical Replication (EDHR) that improves file access time. This strategy is an enhanced version of the Dynamic Hierarchical Replication strategy. It uses an economic model for file deletion when there is not enough space for the replica. The economic model is based on the future value of a data file. Best replica placement plays an important role for obtaining maximum benefit from replication as well as reducing storage cost and mean job execution time. So, it is considered in this paper. The proposed strategies are implemented by OptorSim, the European Data Grid simulator. Experiment results show that the proposed strategies achieve better performance by minimizing the data access time and avoiding unnecessary replication.

Job scheduling and dynamic data replication in data grid environment

Data Grid is a geographically distributed environment that deals with large-scale data-intensive applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Data replication is another key optimization technique for reducing access latency and managing large data by storing data in a wisely manner. In this paper, two algorithms are proposed: first, a novel job scheduling algorithm called Combined Scheduling Strategy (CSS) that considers the number of jobs waiting in queue, the location of required data for the job, and computational capability; second, a dynamic data replication strategy called Dynamic Hierarchical Replication Algorithm (DHRA) that improves file access time. DHRA stores each replica in an appropriate site, i.e., appropriate site in the requested region that has the highest number of access for that particular replica. Also, it can minimize access latency by selecting the best replica when various sites hold replicas of datasets. The simulation results demonstrate the proposed replication and scheduling strategies give better performance compared to the other algorithms.

Combination of data replication and scheduling algorithm for improving data availability in Data Grids

Data Grid is a geographically distributed environment that deals with large-scale data-intensive applications. Effective scheduling in Grid can reduce the amount of data transferred among nodes by submitting a job to a node, where most of the requested data files are available. Data replication is another key optimization technique for reducing access latency and managing large data by storing data in a wisely manner. In this paper two algorithms are proposed, first a novel job scheduling algorithm called Combined Scheduling Strategy (CSS) that uses hierarchical scheduling to reduce the search time for an appropriate computing node. It considers the number of jobs waiting in queue, the location of required data for the job and the computing capacity of sites. Second a dynamic data replication strategy, called the Modified Dynamic Hierarchical Replication Algorithm (MDHRA) that improves file access time. This strategy is an enhanced version of Dynamic Hierarchical Replication (DHR) strategy. Data replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement. MDHRA replaces replicas based on the last time the replica was requested, number of access, and size of replica. It selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. The simulation results demonstrate the proposed replication and scheduling strategies give better performance compared to the other algorithms.

A dynamic replica management strategy in data grid

Data Grid provides scalable infrastructure for storage resource and data files management, which supports several large scale applications. Due to limitation of available resources in grid, efficient use of the grid resources becomes an important challenge. Replication is a technique used in data grid to improve fault tolerance and to reduce the bandwidth consumption. This paper proposes a Dynamic Hierarchical Replication (DHR) algorithm that places replicas in appropriate sites i.e. best site that has the highest number of access for that particular replica. It also minimizes access latency by selecting the best replica when various sites hold replicas. The proposed replica selection strategy selects the best replica location for the users' running jobs by considering the replica requests that waiting in the storage and data transfer time. The simulated results with OptorSim, i.e. European Data Grid simulator show that DHR strategy gives better performance compared to the other algorithms and prevents unnecessary creation of replica which leads to efficient storage usage.

The Impact of Data Replication on Job Scheduling Performance in Hierarchical Data Grid

In data-intensive applications data transfer is a primary cause of job execution delay. Data access time depends on bandwidth. The major bottleneck to supporting fast data access in Grids is the high latencies of Wide Area Networks and Internet. Effective scheduling can reduce the amount of data transferred across the internet by dispatching a job to where the needed data are present. Another solution is to use a data replication mechanism. Objective of dynamic replica strategies is reducing file access time which leads to reducing job runtime. In this paper we develop a job scheduling policy and a dynamic data replication strategy, called HRS (Hierarchical Replication Strategy), to improve the data access efficiencies. We study our approach and evaluate it through simulation. The results show that our algorithm has improved 12% over the current strategies.

HIERARCHICAL REPLICATION TECHNIQUES TO ENSURE CHECKPOINT STORAGE RELIABILITY IN GRID ENVIRONMENT

An efficient and reliable fault tolerance protocol plays a key role in High Performance Computing. Rollback recovery is the most common fault tolerance technique used in High Performance Computing and especially in MPI applications. This technique relies on the reliability of the checkpoint storage. Most of the rollback recovery protocols assume that the checkpoint servers machines are reliable. However, in a grid environment any unit can fail at any moment, including components used to connect different administrative domains. Such failures lead to the loss of a whole set of machines, including the more reliable machines used to store the checkpoints in this administrative domain. Thus it is not safe to rely on the high Mean Time Between Failures of specific machines to store the checkpoint images.This paper introduces a new coordinated checkpoint protocol, which tolerates checkpoint server failures and clusters failures, and ensures a checkpoint storage reliability in a grid environment. To provide this reliability the protocol is based on a replication process. We propose new hierarchical replication strategies that exploit the locality of checkpoint images in order to minimize inter-cluster communication.We evaluate the effectiveness of our two hierarchical replication strategies through simulations against several criteria such as topology and scalability.

Job scheduling and data replication on data grids

In data grids, many distributed scientific and engineering applications often require access to a large amount of data (terabytes or petabytes). Data access time depends on bandwidth, especially in a cluster grid. Network bandwidth within the same cluster is larger than across clusters. In a communication environment, the major bottleneck to supporting fast data access in Grids is the high latencies of Wide Area Networks (WANs) and Internet. Effective scheduling in such network architecture can reduce the amount of data transferred across the Internet by dispatching a job to where the needed data are present. Another solution is to use a data replication mechanism to generate multiple copies of the existing data to reduce access opportunities from a remote site. To utilize the above two concepts, in this paper we develop a job scheduling policy, called HCS (Hierarchical Cluster Scheduling), and a dynamic data replication strategy, called HRS (Hierarchical Replication Strategy), to improve the data access efficiencies in a cluster grid. We simulate our algorithm to evaluate various combinations of data access patterns. We also implement HCS and HRS in the Taiwan Unigrid environment. The simulation and experiment results show that HCS and HRS successfully reduces data access time and the amount of inter-cluster-communications in comparison with other strategies in a cluster grid.