Data Replicas Research Articles

Efficient Dynamic Replicated Data Possession Checking in Distributed Cloud Storage Systems

More and more organizations outsource their data to remote cloud servers (RCSs). Data owners rent the cloud service providers (CSPs) infrastructure to store their unlimited resources by paying fees metered in month or gigabyte. For increasing the availability and scalability of data, the data owners store their data replicas on multiple servers across multiple data centers. Data owners should ensure that the CSPs actually store all their copies according to the service contract. In this paper, we present an efficient dynamic multicopies possession checking scheme that has the following properties: (1) the data owner uses fully homomorphic encryption (FHE) algorithm to generate multiple copies; (2) the scheme supports data block dynamic operation; (3) the scheme supports third-party auditor's public validation. Finally, security analysis and experimental results show that our scheme can resist forgery, replacement, and replay attack and perform better than some other related scheme published recently.

A secure access and associate deleting scheme for multi-replica in multi-cloud environment

With the rapid development of cloud services in multi-cloud environment, it is convenient to generate multi-replica for user's data stored in multi-cloud servers. On the one hand, multi-replica is able to improve data availability and users' experience. But on the other hand, it becomes increasingly easy to disclose sensitive data and brings serious challenges to security and privacy for user's data and its multi-replica. In order to tackle the above issues, in this paper, we propose a secure access and associate deleting scheme for multi-replica MADS in multi-cloud environment, which is based on symmetric encryption algorithm, attribute-based encryption and replica location technology. We construct a novel multi-layered key structure, called multi-way search key tree MSKT that ensures no key material will be revealed, yet the data owner is able to control the master key and manage other keys by performing some tree operations. We also propose a data replica associated model, which is able to associate all he data replicas in multi-cloud environment. Comprehensive comparison and security analysis demonstrate that the proposed MADS scheme is effective and secure.

Weighted Centrality by Potential for Replica Relocation in MANETs

Mobile Ad Hoc Networks (MANETs) are characterized by several dynamic factors (e.g., constant topology changes and limited node resources) which deeply affect data availability on the network. Therefore, a major challenge in this context is to develop autonomous adaptive application-dependent methods for data replication. This paper presents a distributed centrality algorithm based on an application-level message forward mechanism called Virtual Magnetic Fields that adjusts the center of the network graph according to dynamic factors such as data access frequency and node stability, while tackling changes in the network topology. By presenting and analyzing simulation results, this paper shows that the relocation of replicas of data based on the proposed algorithm significantly reduces the overall network traffic required to access those data.

Security-aware data replica selection strategy for Bag-of-Tasks application in cloud computing

As a typical distributed network computing environment, cloud computing has been growing tremendously recently. Although it could provide a convenient environment for the execution of data-intensive application, the primary challenge for it is how to choose the security date replica for data-intensive application from different storage resources. Considering that the security has the characteristic of fuzziness and randomness, it is quantified using the cloud model in this paper. On this basis, taking the constraints of time, cost, and security into account, a scheduling algorithm of data-intensive application based on weighted set covering problem (WSCP) is proposed. Simulation results demonstrate that the security-aware data replica selection strategy performs better than traditional selection strategy on time, cost, security utility value and load balancing deviation (LBD).

Storage Optimization for Energy-Saving Based on Hypergraph in Cloud Data Center

With the rapid growth of data-intensive computing, cloud data center using MapReduce framework are increasingly popular. The energy consumption has become the most important problem in cloud data center which is based on MapReduce framework. MapReduce framework is typically deployed in large-scale clusters with thousands of nodes. The replicas are used to provide data redundancy. In this paper, we proposed a hypergraph-based power saving algorithm of data replica, which is based on the analysis of default placement strategy in Hadoop. The experimental results show that the proposed algorithm has certain advantages such as fault tolerance and availability of data blocks. Also, the energy efficiency is better than CS-k algorithm in the same operating environment.

An efficient adjustable grid-based data replication scheme for wireless sensor networks

Wireless Sensor Networks (WSNs) consist of hundreds or thousands of sensor nodes connected to each other through short-distance wireless links. Because sensor nodes are energy-constrained, efficient energy use is a critical issue for WSNs. In WSNs, the energy of popular nodes may be quickly depleted when a large number of sensor nodes are interested in the same popular events, and they are frequently queried. This paper proposes a data replication scheme called adjustable data replication (ADR), which is based on a virtual grid in order to improve the lifetime of data nodes. In each grid, a head node is selected as a manager, and is responsible for receiving or transmitting packets from or to other nodes in the same virtual grid. The head nodes around data nodes or replica nodes will compute the number of requested packets in order to determine how best to build a replica node in an appropriate location. ADR repeatedly builds data replica nodes close to query nodes in order to balance the overhead and energy consumption of sensor nodes. Simulation results show that the proposed ADR scheme outperforms existing approaches.

Provable multiple replication data possession with full dynamics for secure cloud storage

SummaryCloud storage has been gaining tremendous popularity among individuals and corporations because of its low maintenance cost and on‐demand services for the clients. To improve the availability and the reliability of critical data, storing multiple replicas on multiple servers is a commonly used strategy. Currently, several provable data possession (PDP) protocols for multiple replicas of dynamic data have been proposed to ensure the integrity of outsourced multi‐copy data, but the efficiency of these protocols on verifying multiple replicas one by one is not satisfactory. In this paper, we propose a provable multiple replication data possession protocol with full dynamics, named MR‐DPDP. In MR‐DPDP, we utilize a novel authenticated data structure called Merkle hash tree with rank to support both full dynamic data updates and efficient integrity verification. In addition, our construction with RSA signature can support both variable‐sized file blocks and public verification. Through security proof and performance evaluation, we demonstrate that MR‐DPDP not only is sound but also incurs less communication overhead when updating data blocks as well as verifying a proof of the integrity of multiple replicas. Copyright © 2015 John Wiley & Sons, Ltd.

DiDuSoNet: A P2P architecture for distributed Dunbar-based social networks

Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. One of the most important challenges is the data availability problem when a user is offline. In this paper we propose DiDuSoNet, a novel P2P Distributed Online Social Network where users can exercise full access control on their data. Our system exploits trust relationships for providing a set of important social services, such as trustness, information diffusion, and data availability. In this paper we show how our system manages the problem of data availability by proposing a new P2P dynamic trusted storage approach. By following the Dunbar concept, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Differently from other approaches, nodes chosen to keep data replicas are not statically defined but dynamically change according to users churn. In according to our previous work, we use only two online profile replicas at time. By using real Facebook data traces we prove that our approach offers high availability.

Automatic Query Driven Data Modelling in Cassandra

Non-relational databases have recently been the preferred choice when it comes to dealing with BigData challenges, but their performance is very sensitive to the chosen data organisations. We have seen differences of over 70 times in response time for the same query on different models. This brings users the need to be fully conscious of the queries they intend to serve in order to design their data model. The common practice then, is to replicate data into different models designed to fit different query requirements. In this scenario, the user is in charge of the code implementation required to keep consistency between the different data replicas. We propose and design a mechanism and a prototype to provide users with transparent management, where queries are matched with a well-performing model option. Additionally, we propose to do so by transforming the replication mechanism into a heterogeneous replication one, in order to avoid squandering disk space while keeping the availability and reliability features.

A Study of Effective Replica Reconstruction Schemes for the Hadoop Distributed File System

Distributed file systems, which manage large amounts of data over multiple commercially available machines, have attracted attention as management and processing systems for Big Data applications. A distributed file system consists of multiple data nodes and provides reliability and availability by holding multiple replicas of data. Due to system failure or maintenance, a data node may be removed from the system, and the data blocks held by the removed data node are lost. If data blocks are missing, the access load of the other data nodes that hold the lost data blocks increases, and as a result, the performance of data processing over the distributed file system decreases. Therefore, replica reconstruction is an important issue to reallocate the missing data blocks to prevent such performance degradation. The Hadoop Distributed File System (HDFS) is a widely used distributed file system. In the HDFS replica reconstruction process, source and destination data nodes for replication are selected randomly. We find that this replica reconstruction scheme is inefficient because data transfer is biased. Therefore, we propose two more effective replica reconstruction schemes that aim to balance the workloads of replication processes. Our proposed replication scheduling strategy assumes that nodes are arranged in a ring, and data blocks are transferred based on this one-directional ring structure to minimize the difference in the amount of transfer data for each node. Based on this strategy, we propose two replica reconstruction schemes: an optimization scheme and a heuristic scheme. We have implemented the proposed schemes in HDFS and evaluate them on an actual HDFS cluster. We also conduct experiments on a large-scale environment by simulation. From the experiments in the actual environment, we confirm that the replica reconstruction throughputs of the proposed schemes show a 45% improvement compared to the HDFS default scheme. We also verify that the heuristic scheme is effective because it shows performance comparable to the optimization scheme. Furthermore, the experimental results on the large-scale simulation environment show that while the optimization scheme is unrealistic because a long time is required to find the optimal solution, the heuristic scheme is very efficient because it can be scalable, and that scheme improved replica reconstruction throughput by up to 25% compared to the default scheme.

Data and Job Aware Community Scheduler Framework for Grid Scheduling Problems

Grid technologies have brought the promise of flawless combination of distributed heterogeneous resources. Scheduling in Grid computing is the hot topic of research and challenging to manage task, job in efficient manner. For instance, tasks are assumed to include all data needed for its computation or tasks are just the processes and data is assumed to be available in Grid nodes. All the existing works doesn’t focus on the data aware scheduling framework and it is almost impossible to make an optimal or approximate optimal scheduling for the end-to-end workflow with considering the intermediate data movement in grid computing environment. In order to solve this problem in this study a novel Community Scheduler Framework (CSF) approach is proposed for solving the job and data aware scheduling problem together and it can be integrated to grid host environment. The system is able to find data-affinity hosts for user requested jobs and to adjust the data replicas dynamically according to the job load. The proposed work reviews the policies for scheduling of grid jobs in the context of data and task aware-intensive applications. Proposed data and task aware CSF Meta scheduler framework makes it possible for job requests to set data needs not only as absolute requirements but also as functions for resource ranking. As the experimental results show that, this makes it more flexible than currently used resource brokers to implement different data-aware scheduling algorithms. The experimentation of the proposed Meta scheduler work is implemented with the help of grid simulation toolkit.

A uto P lacer

This article addresses the problem of self-tuning the data placement in replicated key-value stores. The goal is to automatically optimize replica placement in a way that leverages locality patterns in data accesses, such that internode communication is minimized. To do this efficiently is extremely challenging, as one needs not only to find lightweight and scalable ways to identify the right assignment of data replicas to nodes but also to preserve fast data lookup. The article introduces new techniques that address these challenges. The first challenge is addressed by optimizing, in a decentralized way, the placement of the objects generating the largest number of remote operations for each node. The second challenge is addressed by combining the usage of consistent hashing with a novel data structure, which provides efficient probabilistic data placement. These techniques have been integrated in a popular open-source key-value store. The performance results show that the throughput of the optimized system can be six times better than a baseline system employing the widely used static placement based on consistent hashing.

Mathematical Modeling of Patient-Level Hemoglobin Delineates Ruxolitinib’s Complex Mechanism of Action and Quantifies Anemia Risk

Introduction: Ruxolitinib is a JAK 1/2 inhibitor approved in patients with myelofibrosis (MF). The safety profile is well characterized with anemia being a common adverse event. The aim of this mathematical modeling analysis is to characterize individual hemoglobin (Hb) dynamics during ruxolitinib treatment, and to establish a dose-response relationship between treatment and occurrence of an anemic event as defined by an on-treatment reduction in Hb to < 8g/dL.Methods: Hb values from MF patients collected during first 24 weeks of treatment in 2 trials (INCB 18424-251 & COMFORT-I) were used to build a mathematical dose-Hb model while data from a third trial (COMFORT-II) was used to independently validate this model. These trials have previously characterized that mean Hg reached a nadir 8 to 16 weeks from start of treatment, then stabilized or improved (Verstovsek et al., 2010 and 2012; NEJM. Harrison et al, 2012; NEJM). Observed data were fitted via a non-linear-mixed-effect model (NONMEM VII) to characterize individual trends and inter-patient variability in the dynamics of Hb versus time and daily dose. A mechanistic model was used assuming stable Hb and 5 hypothetical compartments representing the life span of reticulocytes and red blood cells, the main carriers of Hb. Blood transfusions were modeled as bolus of Hb with a different elimination rate than Hb synthetized by patients with myelofibrosis. In order to quantify the probabilities of observing at least one anemia event (Hb < 8g/dL) for different starting doses, Hb levels were predicted from the final model based on dose levels from 10 to 25 mg bid for 24 weeks assuming no dose changes and no transfusions.Results: Data from 421 patients including 4849 Hb values during the first 24 weeks of treatment were used to build the model and 1254 Hb values from 146 patients to validate it. The final model characterized Hb dynamics and established a dose-response relationship between ruxolitinib and on-treatment Hb concentrations. The model predicts a 19% higher probability of observing at least one anemia event for 25 mg bid compared to 10 mg bid during the first 24 weeks of ruxolitinib assuming no dose changes and no transfusions.Model building was guided by an observed transient improvement in the Hb values during the first 4 weeks of ruxolitinib treatment (A), followed by a drop in Hb (nadir) during the next 3-4 weeks (B) and then a gradual trend upwards (C) in the observed Hb concentrations towards baseline values over the next few months of continued treatment (Figure 1). An initial model included the JAK 1/2 inhibitor effect on Hb precursor synthesis rate (k-in). It captured the data well overall, but low Hb values at nadir (B) were overestimated. A natural negative feedback loop between circulating Hb and kin helped overcome the bias. Additional effects of ruxolitinib on ‘k-in’ and the Hb elimination rate, ‘k-out’, that accounted for the early (A) and late (C) increases in Hb also improved fitting of the nadir (B). Finally only the final model with a complex mechanism of action involving both positive and negative effects on Hb dynamics was adequate to fit the data. 1000 simulated replicas of the independent validation data from the COMFORT-II trial were used to derive individual Hb profiles versus time and compute the proportion of patients with at least one anemia event (< 8 g/dL). Consistency of the simulated 95% CI with the observed proportion from COMFORT-II confirmed predictability of the final model.Conclusions: The model provided a mechanistic capture of Hg changes and a return toward baseline Hg from the earlier nadir. Through this experimental model, we were able to establish a dose-response relationship which facilitates prediction of on-treatment Hb concentrations over time. Further investigations using prospective models alongside correlations with other treatment effects may be warranted to enable adapting this work into treatment management decisions while recognizing the transient nature of anemia events.Fittings are shown in solid lines: Blue line- fitting with Hg decrease component only (B), Green line- Fitting with Hg decrease (B) + return to baseline (C), Red line- Final model fitting capturing all 3 characteristics (A+B+C). [Display omitted] DisclosuresSarr:Novartis: Employment. Urva:Novartis: Employment. Nedelman:Novartis: Employment, Equity Ownership. Sallas:Novartis: Employment, Equity Ownership. Stalbovskaya:Novartis: Employment, Equity Ownership. Gopalakrishna:Novartis: Employment. Habr:Novartis: Employment. Capdeville:Novartis: Employment.

Data Redundancy Replication Strategy Based on Relevant Failure in Cloud Environment

Cloud storage is an active research domain currently, and how to secure the reliability of data is an important research issue. For the moment, most systems apply the static data replication strategy, which causes a serious waste of storage resources. Considering the user requirements and the factors influenced on data reliability, i.e., the node reliability and Relevant Failure Degree, Data Replication Strategy based on Relevant Failure is provided in this paper. According to the results of the experiments, our strategy reduces the number of data replicas and meets the user requirement of reliability at the same time. Besides, the strategy has a better performance on increasing the utilization of storage resources.

A Scalable and Mobility-Resilient Data Search System for Large-Scale Mobile Wireless Networks

This paper addresses the data search problem in large-scale highly mobile and dense wireless networks. Current wireless network data search systems are not suitable for large-scale highly mobile and dense wireless networks. This paper presents a scalable and mobility-resilient LOcality-based distRibuted Data search system (LORD) for large-scale wireless networks with high mobility and density. Taking advantage of the high density, rather than mapping data to a location point, LORD maps file metadata to a geographical region and stores it in multiple nodes in the region, thus enhancing mobility-resilience. LORD has a novel region-based geographic data routing protocol that does not rely on flooding or GPSs for data publishing and querying, and a coloring-based partial replication algorithm to reduce data replicas in a region while maintaining the querying efficiency. LORD also works for unbalanced wireless networks with sparse regions. Simulation results show the superior performance of LORD compared to representative data search systems in terms of scalability, overhead, and mobility resilience in a highly dense and mobile network. The results also show the high scalability and mobility-resilience of LORD in an unbalanced wireless network with sparse regions, and the effectiveness of its coloring-based partial replication algorithm.

A Data Replica Placement Scheme for Cloud Storage under Healthcare IoT Environment

In this paper, a multiple data replica placement scheme for cloud storage under health-care environment is proposed. It is based on p-center model with minimizing user access cost as its optimization objective. It uses GA (Genetic Algorithm) to find the optimal data replica placement solution. Simulation results have shown that it can not only improve user access time and promote load balance but also enhance system scalability and reliability.

Multiple-Replica Public Auditing Protocol for Cloud Storage

Cloud storage can provide a flexible on-demand data storage service to users anywhere and anytime. However, users data is owned by cloud service provider physically, and the physical boundary between two users data is fuzzy. Moreover, cloud storage provider stores multiple replicas of data in order to increase robustness of users data. The user is charged by the amount of replicas. However, the evidence cloud storage provider actually spends more storage space is scarce. In this environment, a method to ensure multi-replica integrity must be provided. In order to avoid retrieving enormous storage data and users themselves checking, a multi-replica public auditing protocol was proposed based on the BLS short signature scheme and the homomorphic hash function. Based on the computational Diffie-Hellman assumption, the presented protocol is secure against the lost attack and tamper attack from cloud service provider. As the independence among blocks and block signatures, this protocol supports block-level dynamic update, including insertion, modification and deletion. So, the protocol is secure and efficient, and supports for multi-replica, public verification, dynamic update and privacy preserving.

Monitoring Selfish Nodes in MANET during Replica Allocation

Mobile Ad Hoc Network is a collection of mobile hosts. The mobility nature of the MANET causes the mobile host to move freely in the network, due to that network disconnections occurs frequently and this causes frequent changes in the network topology. Data in one network cannot be accessed by the host in the another network, the data accessibility from one network to another network becomes impossible, consequently data accessibility become lower in the wireless network than in the conventional fixed network. This leads to performance degradation. Many Replica allocation methods are used to improve the data accessibility by replicating data item on mobile hosts other than the original owner of the data. This improves the data accessibility but some of the mobile hosts in the network may act as selfish nodes. These nodes use the services of other nodes but this does not cooperate with other nodes, this reduces the overall data accessibility. Selfish node detection algorithm is used to detect the selfish nodes and then the data replica allocation method is used for data replication. The simulation result shows that the conducted selfish node detection method and replica allocation techniques outperforms the improvement in data accessibility and reduce the communication cost and query delay. Keywords: Data accessibility, Selfish Nodes, Degree of selfishness, Mobile adhoc network, Replica allocation.

Efficient and robust large medical image retrieval in mobile cloud computing environment

This paper presents an efficient and robust content-based large medical image retrieval method in mobile Cloud computing environment, called the Mirc. The whole query process of the Mirc is composed of three steps. First, when a clinical user submits a query image Iq, a parallel image set reduction process is conducted at a master node. Then the candidate images are transferred to the slave nodes for a refinement process to obtain the answer set. The answer set is finally transferred to the query node. The proposed method including an priority-based robust image block transmission scheme is specifically designed for solving the instability and the heterogeneity of the mobile cloud environment, and an index-support image set reduction algorithm is introduced for reducing the data transfer cost involved. We also propose a content-aware and bandwidth-conscious multi-resolution-based image data replica selection method and a correlated data caching algorithm to further improve the query performance. The experimental results show that the performance of our approach is both efficient and effective, minimizing the response time by decreasing the network transfer cost while increasing the parallelism of I/O and CPU.

Review of Data Replication Techniques for Mobile Computing Environment

With the tremendous growth of the portable computing devices and wireless communication, the mobile computing has become extremely popular. The wireless enabled portable computing devices with massive storage capacity and high-end processing capabilities have started to make the extensive use of mobile databases already. The rising popularity in these computing paradigms demands that the mobile computing be reliable enough to ensure the continuous data availability and integrity. However mobility comes at the cost of bandwidth, limited power, security and interference. In modern mobile computing systems data replication has been adopted as an efficient means to ensure the data availability and integrity as well as an effective means to achieve the fault tolerance. Data replication not only ensure the availability of the data but also reduce the communication cost, increase data sharing and increase the safety of the critical data. Furthermore, it also determine when and where (location) to place the replica of data, controlling the number of data replicas over a network for efficient utilization of the network resources. In this study we survey the research work in data replication for mobile computing. We reviewed some of the existing data replication techniques proposed by the research community for mobile computing environment for efficient management of data replicas.