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For some pc homeowners, finding enough cupboard space to carry all the information they've non inheritable may be a real challenge. Some folks invest in larger exhausting drives. Others like auxiliary storage devices like thumb drives or compact discs. Desperate pc homeowners would possibly delete entire folders price of recent files so as to create house for brand new info. however some ar selecting to deem a growing trend: cloud storage.
While cloud storage looks like it's one thing to try and do with weather fronts and storm systems, it extremely refers to saving information to Associate in Nursing off-site storage system maintained by a 3rd party. Rather than storing info to your computer's disc drive or different native memory device, you reserve it to a distant information. The web provides the affiliation between your pc and also the information.
On the surface, cloud storage has many blessings over ancient information storage. for instance, if you store your information on a cloud storage system, you will be ready to get to it information from any location that has net access. you would not got to carry around a physical memory device or use an equivalent pc to avoid wasting and retrieve your info. With the proper storage system, you'll even permit others to access the information, turning a private project into a cooperative effort.
Many recently proposed cloud storage architectures build a single virtual cloud storage system by using a combination of diverse commercial cloud storage services - the so called cloud of clouds approach. Thereby, the data to be stored is dispersed among different (independent) cloud storage providers in a redundant way. This is commonly accomplished either by naively replicating the data to several providers (storing an entire copy of a file at each provider) or by dispersing suitably encoded data, i.e., only a certain threshold of file fragments is required for reconstruction of a file. Furthermore, since many vendors of commercial cloud storage services do not provide adequate means to securing the cloud from within the cloud infrastructure, many recently proposed cloud storage architectures (transparently) add relevant security and privacy features from the outside. In doing so, they are mainly trying not to affect the cloud provider's interfaces and inner workings. In this paper we take a closer look at distributed cloud storage systems. We provide an overview of information dispersal strategies to realize reliable distributed cloud storage systems and provide an overview of state-of-the-art cloud storage approaches. Then, we analyze them with respect to security properties. Furthermore, we discuss the lack of privacy features and in particular features to provide access privacy in existing distributed cloud storage systems, which is an important direction for future research on distributed cloud storage.
With the development of cloud computing, as a cloud computing service, cloud storage widely applied to enterprises and people's daily life in the form of the public cloud storage, hybrid cloud storage, internal cloud storage. In the current internet environment, the annual investment in providing public cloud storage services is more than? 500 million. More and more companies have joined the R & D team on cloud storage. Because the product differentiation of Cloud storage products is small, the personal preferences of user groups is completed, the market is a buyer's market, and other reasons. Further, the profit of private cloud storage model is also not clear. Cloud storage pricing model has become the focus for the user and vendor. In this article, the authors will be starting from different pricing strategies to discuss the pricing model of cloud storage.
Cloud storage services like Drop box and Google Drive offer convenient file syncing, sharing, and collaboration services. These services are popular, however many enterprises have been wary to adopt them for business documents because of security, privacy, and ownership issues. Enterprises' concerns create large amount of private cloud storage service demands, but not all enterprises have enough resources to build and maintain their own private services. To address this issue, this study developed cloud storage system software, which can be easily installed on commodity server to be a private cloud storage appliance to serve services like public offers in enterprises. Since the availability of a pure private service is not enough, hybrid cloud storage architecture is also introduced in this paper along with the proposed storage system software. In the proposed hybrid architecture, the encrypted remote backup store and automatic service restore mechanism will be illustrated. With this hybrid cloud storage architecture, private storage appliance can cooperate with public virtual one to provide enterprises with a service operational high availability. The performance of the local cloud storage system software was measured. The result indicates that our cloud storage system software is able to be installed on resource limited devices to serve enterprise employees.
Cloud computing enables on-demand network access to a shared pool of configurable computing resources such as servers, storage and applications. These shared resources can be rapidly provisioned to the consumers on the basis of paying only for whatever they use. Cloud storage refers to the delivery of storage resources to the consumers over the Internet. Private cloud storage is restricted to a particular organization and data security risks are less compared to the public cloud storage. Hence, private cloud storage is built by exploiting the commodity machines within the organization and the important data is stored in it. When the utilization of such private cloud storage increases, there will be an increase in the storage demand. It leads to the expansion of the cloud storage with additional storage nodes. During such expansion, storage nodes in the cloud storage need to be balanced in terms of load. In order to maintain the load across several storage nodes, the data need to be migrated across the storage nodes. This data migration consumes more network bandwidth. The key idea behind this paper is to develop a dynamic load balancing algorithm to balance the load across the storage nodes during the expansion of private cloud storage.
During recent years cloud service providers have successfully provided reliable and flexible resources to cloud users. For example Amazon Elastic Block Store (Amazon EBS) and Simple Storage Service (Amazon S3) provides users storage in the cloud. Despite the tremendous efforts cloud service providers have devoted to the availability of their services, the interruption is still inevitable. Therefore just as an Internet service provider will not count on a single network provider, a cloud user should not depend on a single cloud service provider either. However, cloud service providers provide different levels of services. A more costly service is usually more reliable. As a result it is an important and challenging problem to choose among a set of service providers to fit one's need, which could be budget, failure probability, or the amount of data that can survive failure. The goal of this paper is to select cloud service providers in order to maximize the benefits with a given budget. The contributions of this paper include a mathematical formulation of the cloud service provider selection problem in which both the object functions and cost measurements are clearly defined, algorithms that selects among cloud storage providers to maximize the data survival probability or the amount of surviving data, subject to a fixed budget, and a series of experiments that demonstrate During recent years cloud service providers have successfully provided reliable and flexible resources to cloud users. For example Amazon Elastic Block Store (Amazon EBS) and Simple Storage Service (Amazon S3) provides users storage in the cloud. Despite the tremendous efforts cloud service providers have devoted to the availability of their services, the interruption is still inevitable. Therefore just as an Internet service provider will not count on a single network provider, a cloud user should not depend on a single cloud service provider either. However, cloud service providers provide different levels of services. A more costly service is usually more reliable. As a result it is an important and challenging problem to choose among a set of service providers to fit one's need, which could be budget, failure probability, or the amount of data that can survive failure. The goal of this paper is to select cloud service providers in order to maximize the benefits with a given budget. The contributions of this paper include a mathematical formulation of the cloud service provider selection problem in which both the object functions and cost measurements are clearly defined, algorithms that selects among cloud storage providers to maximize the data survival probability or the amount of surviving data, subject to a fixed budget, and a series of experiments that demonstrate that the proposed algorithms are efficient enough to find optimal solutions in reasonable amount of time, using price and fail probability taken from real cloud providers. That the proposed algorithms are efficient enough to find optimal solutions in reasonable amount of time, using price and fail probability taken from real cloud providers.
Many Cloud services provide generic (e.g., Amazon S3 or Drop box) or data-specific Cloud storage(e.g., Google Picasa or Sound Cloud). Although both Cloud storage service types have the data storage in common, they present heterogeneous characteristics: different interfaces, accounting and charging schemes, privacy and security levels, and functionality and, among the data-specific Cloud storage services, different data type restrictions. This paper proposes PiCsMu (Platform-independent Cloud Storage System for Multiple Usage), a novel approach exploiting heterogeneous data storage of different Cloud services by building a Cloud storage overlay, which aggregates multiple Cloud storage services, provides enhanced privacy, and offers a distributed file sharing system. As opposed to P2P file sharing, where data and indices are stored on peers, PiCsMu uses Cloud storage systems for data storage, while maintaining a distributed index. The main contribution of this work is to show the feasibility to store arbitrary data in different Cloud services for private use and/or for file sharing. Furthermore, the evaluation of the prototype confirms the scalability with respect to different file sizes and also shows that a moderate overhead in terms of storage and processing time is required.
In recent years, cloud storage providers have gained popularity for personal and organizational data, and provided highly reliable, scalable and flexible resources to cloud users. Although cloud providers bring advantages to their users, most cloud providers suffer outages from time-to-time. Therefore, relying on a single cloud storage services threatens service availability of cloud users. We believe that using multi-cloud broker is a plausible solution to remove single point of failure and to achieve very high availability. Since highly reliable cloud storage services impose enormous cost to the user, and also as the size of data objects in the cloud storage reaches magnitude of Exabyte, optimal selection among a set of cloud storage providers is a crucial decision for users. To solve this problem, we propose an algorithm that determines the minimum replication cost of objects such that the expected availability for users is guaranteed. We also propose an algorithm to optimally select data centers for striped objects such that the expected availability under a given budget is maximized. Simulation experiments are conducted to evaluate our algorithms, using failure probability and storage cost taken from real cloud storage providers.
In order to solve the problem that enterprise-level users mass data storage and high-speed data processing services growth, and the traditional storage system can not meet the data services business growth, enterprise file cloud storage system is proposed. It is based on Hadoop, uses Linux cluster technology, distributed file systems and cloud computing framework, provides large-scale data storage and data storage flexible extension. This paper compares private cloud storage and traditional storage model, analyzes the advantage and feasibility of private cloud storage technology, presents mass data storage and data storage flexible extension methods based on Hadoop. Theoretical analysis shows that the enterprise private cloud storage platform is suit for critical business applications, online transaction processing, the platform can meet mass data storage, is easy to expand the scale of data.
According to the identity authentication mode of "user name/password" in the cloud storage system is easy to forget and crack, etc., then propose a cloud storage identity authentication design scheme based on fingerprint identification. The design will be fingerprint identification technology into the cloud storage authentication system, and the fingerprint identification authentication mode will be used for the cloud storage users' identity authentication so that greatly enhances the reliability and safety of the cloud storage identity authentication, and solves the problem of cloud storage users' accounts illegal accessing and tampering, etc. Proposed the hybrid encryption algorithm as an identity authentication protocol effectively improves the efficiency of authentication and realizes the mass of data transmission efficiency. Fingerprint sensor online acquisition data identity authentication experimental results show that the scheme in the cloud storage fingerprint identity authentication system obtains the very good application.
Cloud storage systems commonly use replication of stored data sets to ensure high reliability and availability. However, the high storage overhead of replication becomes increasingly unacceptable with the explosive growth of data stored in cloud. Some cloud storage systems have attempted to replace replication with erasure coding to reduce storage overhead that is just the thinking behind Cloud RAID. A well-designed Cloud RAID mechanism should achieve the right tradeoffs between storage efficiency, performance, and reliability. As there exists no widely-accepted methods for Cloud RAID, we present a workloads-based Cloud RAID schema-Selective Cloud RAID (SCR for short). SCR treats primary storage and backup storage with different RAID methods, the former at the level of directories, and the latter at the level of individual files. SCR has three distinct advantages over previous attempts at Cloud RAID: (1) it can significantly reduce the storage overhead compared with three way replication, (2) it can avoid most cases of the "small write bottleneck" and simplify system maintenance, (3) its implementation is modular, and therefore, it is easy to configure different erasure codes for different workloads. Additionally, we have implemented a SCR prototype with RDP code, which shows significant benefits over Blaum-Roth codes in degraded read performance. To verify the effectiveness of SCR, we perform theoretical analysis and elaborate benchmark tests to evaluate the performance of SCR prototype.
Cloud storage has changed the way we store our data. Cloud can be considered as the next stage in the evolution of data storage; in that, just like flash drives phased out compact disks, it is phasing out flash drives for many users and cloud dependence is steadily increasing. Cloud has become ubiquitous in a relatively shorter span of time and it is predicted that, within the next few years, most personal and corporate storage will move to the cloud servers. We are already starting to see user trends shift towards that end. This means that local storage will become redundant, for most users. Looking at the increasing access data rates for both wired and wireless networks, it seems probable that cloud storage will eventually replace local storage on a large scale if not completely. Against the same backdrop, we propose to reduce network load, in the wake of upcoming increase in Internet traffic, due to increased storage on the cloud and synchronization services. Latency-aware Self-aligning Storage(LSS) - a purely network oriented approach, acts as an intelligent latency reduction mechanism that reduces the amount of information that travels across the globe every day, to a minimum, by intelligently changing file locations while keeping the associations intact. This results in significant reduction in retrieval times.
How to maximally use and efficiently manage cloud storage resources has become one of major problem in cloud computing area. If cloud storage capacity is limited or restrictions on a single file size, user may hire more cloud computing storage services. Data partitioning and distributed storage technologies are focused on to solve the problem that size of large dataset is limited in cloud storage. A model of partition-based data storage in cloud is put forward and its availability is discussed. Fragment partition description is given and three algorithms are designed on the basis of model. The first algorithm is about partition and storage of data, the second algorithm is about data query and connection, and the last algorithm is about fragment updated and re-partitioned. The experimental results show that the model can be applied to the situation with multiple cloud storage services and large dataset or file.
Cloud computing is the most demanded advanced technology throughout the world. It is one of the most significant topics whose application is being researched in today's time. One of the prominent services offered in cloud computing is the cloud storage. With the cloud storage, data is stored on multiple third party servers, rather than on the dedicated server used in traditional networked data storage. All data stored on multiple third party servers is not cared by the user and no one knows where exactly data saved. It is cared by the cloud storage provider that claims that they can protect the data but no one believes them. Data stored over cloud and flow through network in the plain text format is security threat. This paper proposes a method that allows user to store and access the data securely from the cloud storage. It also guarantees that no one except the authenticated user can access the data neither the cloud storage provider. This method ensures the security and privacy of data stored on cloud. A further advantage of this method is that if there is security breach at the cloud provider, the user's data will continue to be secure since all data is encrypted. Users also need not to worry about cloud providers gaining access to their data illegally.
In a cloud storage environment, file distribution and storage is processed by storage devices providers or physical storage devices rented from the third-party companies. Through centralized management and virtualization, files are integrated into available resources for users to access. However, because of the increasing number of files, the manager cannot guarantee the optimal status of each storage node. The great number of files not only leads to the waste of hardware resources, but also worsens the control complexity of data center, which further degrades the performance of the cloud storage system. For this reason, to decrease the workload caused by duplicated files, this paper proposes a new data management structure: Index Name Server (INS), which integrates data de-duplication with nodes optimization mechanisms for cloud storage performance enhancement. INS can manage and optimize the nodes according to the client-side transmission conditions. By INS, each node can be controlled to work in the best status and matched to suitable clients as possible. In such a manner, we can improve the performance of the cloud storage system efficiently and distribute the files reasonably to reduce the load of each storage node.
Cloud storage is a hot topic in the field of research and applications. At present, there has been a lot of attention on its application in video detection. Through the cloud infrastructure and utilization of virtualization and distributed computing techniques, resources from server clusters are made available to enhance the data redundancy factor and efficiency for document access. As huge cloud storage facility incurs operating expenses so the question rests upon how to be reasonable and efficiently manage cloud storage. The paper first introduce the cloud storage and its architecture, then use the cloud storage construct the traffic video detection system, in accordance with using cloud storage, traffic video detection storage resources are fine tuned and storage efficiency is greatly enhanced.
Public cloud storage services enable organizations to manage data with low operational expenses. However, the benefits come along with challenges and open issues such as security, reliability and the risk to become dependent on a provider for its service. In our previous work, we presented a system that improves availability, confidentiality and reliability of data stored in the cloud. To achieve this objective, we encrypt user's data and make use of the RAID-technology principle to manage data distribution across cloud storage providers. Recently, we conducted a proof-of-concept experiment for our application to evaluate the performance and cost effectiveness of our approach. We observed that our implementation improved the perceived availability and, in most cases, the overall performance when compared with cloud providers individually. We also observed a general trend that cloud storage providers have constant throughput values - whereby the individual throughput performance differs strongly from one provider to another. With this, the experienced transmissions can be utilized to increase the throughput performance of the upcoming data transfers. The aim is to distribute the data across providers according to their capabilities utilizing the maximum of the available throughput capacity. To assess the feasibility of the approach we have to understand how providers handle high simultaneous data transfers. Thus, in this paper we focus on the performance and the scalability evaluation of particular cloud storage providers. To this end, we deployed our application using eight commercial cloud storage repositories in different countries and conducted a set of extensive experiments.
Though a variety of cloud storage services have been offered recently, they have not yet provided users with transparent and cost-effective personal data storage. Services like Google Docs offer easy file access and sharing, but tie storage with internal data formats and specific applications. Meanwhile, services like Drop box offer general-purpose storage. Yet they have not been widely utilized, partly due to their fee-charging nature and long-term service availability concerns. Web-based email services, on the other hand, have been offering growing email storage capacity, reliable service, and powerful search capability, making them appealing as storage resources. In this paper, we examine the efficacy of leveraging web-based email services to build a personal storage cloud. We present EMFS, which aggregates back-end storage by establishing a RAID-like system on top of virtual email disks formed by email accounts. In particular, by replicating data across accounts from different service providers, highly available storage services can be constructed based on already reliable, cloud-based email storage. This paper discusses the design and implementation of EMFS, focusing on unique challenges and opportunities associated with utilizing email services for file transfer and storage, such as email based data organization, metadata format and management, and handling provider-imposed anti-spam usage restrictions. We evaluated EMFS extensively with multiple benchmarks, and compared its performance with NFS, AFS, and a non-free cloud storage service built upon Amazon S3. Our results indicate that while EMFS cannot match the performance of highly optimized distributed file systems with dedicated servers, it performs quite closely to the commercial cloud storage solution.
The increasing popularity of cloud service is leading people to concentrate more on cloud storage than traditional storage. Cloud storage platform is confronted with great challenges as the core infrastructure of all kinds of Internet applications, especially, the security of the out-sourced data (the data that is not stored/retrieved from the tenants' own servers). Thus, to address the security issue, we proposed a metadata and real data separation model of cloud storage named MeSe. Metadata and real data are maintained separately in MeSe, it aims to provide tenants a secured and integrated cloud storage service with two parts of separate servers, the metadata server clusters and data server clusters. Considering tenants' security requirement MeSe based on these two separate server clusters provided a better decision of cloud storage architecture for our tenants. Furthermore, we summarized protection challenges to MeSe and designed a threat model SEEIT, which thoroughly considers the security properties: Single Point of Failure, Eavesdropping, Elevation of Privilege, Information Disclosure and Tampering. SEEIT analyzed all kinds of threats and gave some inspirations that how to implement protection solutions for our metadata and data separation model MeSe.
In order to reduce untrustworthy between cloud users and the underlying cloud storage platform, a novel cloud security storage solution is proposed based on autonomous data storage, management, and access control. The roles of users are re-evaluated, and the knowledge provided by the users is incorporated into the cloud storage model. Both the superiority of the public cloud in large scale data storage and the advantages of the private cloud in privacy preserving can be obtained. The main advantages of our approach include avoiding the superposition of complex security policies and overcoming the mistrust between the users and the platform. Furthermore, our security storage service can be easily integrated into the cooperative cloud computing environment. A prototype system is developed, and a use case is also presented.
In the current era of cloud computing, data stored in the cloud is being generated at a tremendous speed, and thus the cloud storage system has become one of the key components in cloud computing. By storing a substantial amount of data in commodity disks inside the data center that hosts the cloud, the cloud storage system must consider one question very carefully: how do we store data reliably with a high efficiency in terms of both storage overhead and data integrity? Though it is easy to store replicated data to tolerate a certain amount of data losses, it suffers from very low storage efficiency. Conventional erasure coding techniques, such as Reed-Solomon codes, are able to achieve a much lower storage cost with the same level of tolerance against disk failures. However, it incurs much higher repair costs, not to mention even higher access latency. In this sense, designing new coding techniques for cloud storage systems has gained a significant amount of attention in both academia and the industry. In this paper, we examine the existing results of coding techniques for cloud storage systems. Specifically, we present these coding techniques into two categories: regenerating codes and locally repairable codes. These two kinds of codes meet the requirements of cloud storage along two different axes: optimizing bandwidth and I/O overhead. We present an overview of recent advances in these two categories of coding techniques. Moreover, we introduce the main ideas of some specific coding techniques at a high level, and discuss their motivations and performance.
As an emerging technology and business paradigm, Cloud Computing has taken commercial computing by storm. Cloud computing platforms provide easy access to a company's high-performance computing and storage infrastructure through web services. With cloud computing, the aim is to hide the complexity of IT infrastructure management from its users. At the same time, cloud computing platforms provide massive scalability, 99.999% reliability, high performance, and specifiable configurability. These capabilities are provided at relatively low costs compared to dedicated infrastructures. This article gives a quick introduction to cloud storage. It covers the key technologies in Cloud Computing and Cloud Storage, several different types of clouds services, and describes the advantages and challenges of Cloud Storage after the introduction of the Cloud Storage reference model.
This paper presents a novel evaluation study of the Cloud Computing technology, with a focused emphasis on the Cloud Storage mechanisms and the way they are affecting the progress of the present Cloud Services. Considering the exponential growth of the user data and its impact on the Cloud Storage infrastructure, this work provides two major contributions through comprehensive performance evaluations. Firstly, it proposes a unique 10-point performance evaluation framework for existing Cloud Storage infrastructure and applies it for evaluating six major Cloud Storage Service Providers currently in the market. Secondly, it presents a detailed insightful assessment of eighteen most popular Cloud Storage Hardware vendors with respect to the storage technologies being implemented by them. In conclusion, it takes stock of the current trends on optimizing storage infrastructure for Cloud Computing and predicting future research possibilities in this rapidly growing technology.
The young upcoming industry is the cloud storage with lots of potential in terms of growth of storage capacity and the potential of faster retrieval. The architecture of the cloud is designed so as to not only offer unlimited storage capacity, but also has to eliminate the old data backups - created as a part of the constant replication of data. In this paper, the key component is storage-as-a-service solution, that is, the cloud storage is analyzed and comprehended for the storage and retrieval speeds on various free cloud storage sites. The experiments were piloted for files varying in sizes and various time spans. Time spans are deliberated based on network traffic. This paper overall tries to give a snapshot of the data working on different free clouds available. The analysis done gives an identification of the free cloud storage capacity, its performance, betterments and evaluation.
This paper addresses difficulties in mapping blocks onto cloud storage and proposes a novel cost-aware log-structured block I/O management over one of the commercial cloud storage, Amazon S3. The proposed scheme is imbedded in the virtual USB drive architecture that replaces the NAND flash of the USB memory with the capacity-free network storage. The key of the proposed scheme is to perform onto the cloud storage log-structured writes with the optimal number of data blocks that adaptively changes with I/O characteristics (the number of I/O operations and storage size) and cloud storage pricing policy. The proposed scheme also efficiently manages associate metadata by using well-organized data structures and layouts both in the memory and on the cloud storage. Performance analysis shows that the proposed scheme can reduce the total I/O costs significantly up to 54%, as compared with a simple one-to-one mapping scheme.
File distribution and storage in a cloud storage environment is usually handled by storage device providers or physical storage devices rented from third parties. Files can be integrated into useful resources that users are then able to access via centralized management and virtualization. Nevertheless, when the number of files continues to increase, the condition of every storage node cannot be guaranteed by the manager. High volumes of files will result in wasted hardware resources, increased control complexity of the data center, and a less efficient cloud storage system. Therefore, in order to reduce workloads due to duplicate files, we propose the index name servers (INS) to manage not only file storage, data de-duplication, optimized node selection, and server load balancing, but also file compression, chunk matching, real-time feedback control, IP information, and busy level index monitoring. To manage and optimize the storage nodes based on the client-side transmission status by our proposed INS; all nodes must elicit optimal performance and offer suitable resources to clients. In this way, not only can the performance of the storage system be improved, but the files can also be reasonably distributed, decreasing the workload of the storage nodes.
We can now outsource data backups off-site to third-party cloud storage services so as to reduce data management costs. However, we must provide security guarantees for the outsourced data, which is now maintained by third parties. We design and implement FADE, a secure overlay cloud storage system that achieves fine-grained, policy-based access control and file assured deletion. It associates outsourced files with file access policies, and assuredly deletes files to make them unrecoverable to anyone upon revocations of file access policies. To achieve such security goals, FADE is built upon a set of cryptographic key operations that are self-maintained by a quorum of key managers that are independent of third-party clouds. In particular, FADE acts as an overlay system that works seamlessly atop today's cloud storage services. We implement a proof-of-concept prototype of FADE atop Amazon S3, one of today's cloud storage services. We conduct extensive empirical studies, and demonstrate that FADE provides security protection for outsourced data, while introducing only minimal performance and monetary cost overhead. Our work provides insights of how to incorporate value-added security features into today's cloud storage services.
Cloud computing is considered a booming trend in the world of information technology which depends on the idea of computing on demand. Cloud computing platform is a set of scalable data servers, providing computing and storage services. The cloud storage is a relatively basic and widely applied service which can provide users with stable, massive data storage space. Our research concerns with searching in content of different kind of files in the cloud based on ontology, this approach resolves the weaknesses that existed in Google File System that depends on metadata. In this paper, we are proposing new cloud storage architecture based on ontology that can store and retrieve files in the cloud based on its content. Our new architecture was tested on Cloud Storage Simulator and the result shows that the new architecture has better scalability, fault tolerance and performance.
One of the main obstacles hindering wider adoption of storage cloud services is vendor lock-in, a situation in which large amounts of data that are placed in one storage system cannot be migrated to another vendor, e.g., due to time and cost considerations. To prevent this situation we present an advanced on-boarding federation mechanism, enabling a cloud to add a special federation layer to efficiently import data from other storage clouds. This is achieved without being dependent on any special function from the other clouds. We design a generic, modular on-boarding architecture and demonstrate its implementation as part of a VISION Cloud, which is a large scale storage cloud designed for content-centric data. Our system is capable of integrating storage data from various clouds, providing a common global view of storage data. The users can access the data through the new cloud provider immediately after the setup, maintaining the normal operation of applications, so that they do not need to wait for the completion of the data migration process. Finally, we analyze the payment models of existing storage clouds, showing that transferring the data via on-boarding federation with a direct link between clouds can lead to significant time and cost savings.
Nowadays, enterprises and individuals are increasing tending to store their data in the cloud storage systems; yet, these sensitive data will face serious security threats. Currently, cloud storage service providers mainly adopt encryption and authentication to protect sensitive data, and a lot of approaches have been proposed to ensure data security in cloud storage systems. Recently, audio steganography has been regarded as serious attacking measures to threaten cloud storage systems. Nevertheless, little research has been focused on thwarting the Audio steganography Attacks in Cloud Storage Systems. In this paper, we analyze the Audio steganography Attacks in Cloud Storage Systems, and then, we propose and develop StegAD, a novel scheme for defending Audio steganography Attacks. StegAD includes two algorithms, i.e., the enhanced-RS algorithm and the SADI algorithm. The enhanced-RS algorithm is adopted to detect the audio steganographied files, and after that, SADI is applied to infer and compensate the possible hiding positions. To evaluate the performance of StegAD, we perform extensive evaluations on a real platform in terms of detecting, audio quality and interfering intensity. Experimental results show that, our proposed StegAD scheme is very efficient in thwarting the Audio steganography Attacks in Cloud Storage Systems.
We present a fundamentally different approach to improve the security of cloud storage. In contrast to previous methods, our approach introduces third party trusted timestamp and certificate into Cloud storage framework. And user's request is multiply validated. There are three main aspects. (i) Certificate identifies the user's identity; (ii) Trusted timestamp is added to the user's operation request; (iii) Cloud storage system communicates with TSA and Directory server for user information verification. Furthermore, our approach has two important features. First, we use PKI technology to improve cloud storage system security, and through Directory server to authenticate the user certificate status. Second, Cloud storage vets user's operation requests based on trusted timestamps and stores user's operation records, which can provide security services including safety audit, electronic evidence and other services. Our results show that our mechanism can vet and monitor various types of data operations in cloud storage system under the premise of increasing a very small overhead, and the security of cloud storage has greatly enhanced.
We have presented the idea of enabling the cloud storage to support traditional applications. In this way, the applications running in local host can be deployed and running on the cloud storage without any modification. An acceptable solution is to enhance current cloud storage with standard POSIX file system interface. So that it can benefit from the scalable capacity of existing cloud storage and compatible interface of traditional file systems. With this point in mind, we designed and implemented the PosixCloud, a general purpose scalable storage cloud with standard POSIX interface for traditional end users. Similar to other cloud storage systems, the PosixCloud is designed to be chunk based data layout, built on commodity computers, chunk replication for reliability and so on. However, the metadata in our system is managed in distributed database instead of the memory single master. So that the metadata scalability of our system is enhanced and large small files can be handled without introducing high overhead. The paper describes the details of the design and implementation of PosixCloud. Also, we evaluate the POSIX compliance, functionality, data and metadata performance of PosixCloud by both test suits of third parties and customized experiments. The results demonstrate that our system can achieve reasonable performance and meet the storage requirement of most traditional applications.
Cloud computing has taken the limelight with respect to the present industry scenario due to its multi-tenant and pay-as-you-use models, where users need not bother about buying resources like hardware, software, infrastructure, etc. on an permanently basis. As much as the technological benefits, cloud computing also has its downside. By looking at its financial benefits, customers who cannot afford initial investments, choose cloud by compromising on its concerns, like security, performance, estimation, availability, etc. At the same time due to its risks, customers - relatively majority in number, avoid migration towards cloud. Considering this fact, performance and estimation are being the major critical factors for any application deployment in cloud environment; this paper brings the roadmap for an improved performance-centric cloud storage estimation approach, which is based on balanced PCT Free allocation technique for database systems deployment in cloud environment. Objective of this approach is to highlight the set of key activities that have to be jointly done by the database technical team and business users of the software system in order to perform an accurate analysis to arrive at estimation for sizing of the database. For the evaluation of this approach, an experiment has been performed through varied-size PCT Free allocations on an experimental setup with 100000 data records. The result of this experiment shows the impact of PCT Free configuration on database performance. Basis this fact, we propose an improved performance-centric cloud storage estimation approach in cloud. Further, this paper applies our improved performance-centric storage estimation approach on decision support system (DSS) as a case study.
Cloud storage system enables storing of data in the cloud server efficiently and makes the user to work with the data without any trouble of the resources. In the existing system, the data are stored in the cloud using dynamic data operation with computation which makes the user need to make a copy for further updating and verification of the data loss. An efficient distributed storage auditing mechanism is planned which over comes the limitations in handling the data loss. In this paper the partitioning method is proposed for the data storage which avoids the local copy at the user side by using partitioning method. This method ensures high cloud storage integrity, enhanced error localization and easy identification of misbehaving server. To achieve this, remote data integrity checking concept is used to enhance the performance of cloud storage. In nature the data are dynamic in cloud; hence this work aims to store the data in reduced space with less time and computational cost.
Cloud computing is the long dreamed vision of computing as a utility, where data owners can remotely store their data in the cloud to enjoy on-demand high-quality applications and services from a shared pool of configurable computing resources. While data outsourcing relieves the owners of the burden of local data storage and maintenance, it also eliminates their physical control of storage dependability and security, which traditionally has been expected by both enterprises and individuals with high service-level requirements. In order to facilitate rapid deployment of cloud data storage service and regain security assurances with outsourced data dependability, efficient methods that enable on-demand data correctness verification on behalf of cloud data owners have to be designed. In this article we propose that publicly auditable cloud data storage is able to help this nascent cloud economy become fully established. With public audit ability, a trusted entity with expertise and capabilities data owners do not possess can be delegated as an external audit party to assess the risk of outsourced data when needed. Such an auditing service not only helps save data owners¿ computation resources but also provides a transparent yet cost-effective method for data owners to gain trust in the cloud. We describe approaches and system requirements that should be brought into consideration, and outline challenges that need to be resolved for such a publicly auditable secure cloud storage service to become a reality.
Cloud based services, by their nature, are distributed and traditional operation and management processes that often exert centralized control are not suited for cloud services operation and management. This paper introduces a Policy-based Event-driven Service-oriented Architecture (PESA) that enables the manageability of these loosely coupled services distributed across multiple public or private clouds or a hybrid cloud. PESA allows the implementation of policy driven management of service availability, performance, security and risk management. Using the concept of logical and virtual partitioning of the business service fabric into sub-fabrics - islands of services that may span company, geographical, and technological boundaries, public and private clouds, and corporate data centers, we describe conceptual management architecture for policy enforcement. An example describes service availability and performance assurance in a business process implementation using a set of loosely coupled service components in a virtual cloud.
The development of cloud storage services makes companies who outsourced their data to cloud storage server can't control their data by themselves as before. Then comes the security issues, especially the privacy preserving has become a more important security problem. The users always search their documents through keyword in plaintext, which may leak privacy of users in cloud storage environment. In this paper we propose an efficient privacy preserving keyword search scheme in cloud storage, the scheme satisfies the multi-user requirement with low computational overhead and flexible key management. And it is proved to be secure and feasible.
The confidentiality of data is one of the most important issues in cloud storage system. We address the privacy issue of decentralized cloud storage system using threshold cryptography. The major challenge of designing this cloud storage system is to provide a better privacy guarantee. To achieve this goal, we propose a threshold encryption scheme and integrate it with a secure decentralized erasure code to form a secure cloud storage system, where the user generates a secret parameter participated in system encryption and decryption of plaintext blocks in the combine process. Our cloud storage system meets the requirements of data robustness and confidentiality.
Nowadays, subjects of cloud computing, especially cloud storage, are still thought to be new fields with few teaching opportunities. This paper discusses how to realize GET/PUT requests between REST client and servers, utilize CDMI (Cloud Data Management Interface) standard to carry on teaching experiment of cloud storage communication under Linux environment. Practice proves that it is useful to help students understand basic concepts of cloud environment and mechanism of cloud storage, and offer students access to the cloud standard.
Cloud storage is one of the most rapidly growing cloud services, which at the same time also faces serious security challenges. Recently, several cloud-storage service providers started to provide encryption protection to client data in the cloud. However, encryption imposes significant limits on data use. In this paper, we report our design and implementation of an encrypted cloud storage system that supports multi-user secure indices, allowing efficient search among encrypted documents of multiple users. Experiment results show that keyword search can be performed in real time. We believe that our system represents a first step toward providing secure and useful cloud-storage services in practice.
To protect outsourced data in cloud storage against corruptions, adding fault tolerance to cloud storage, along with efficient data integrity checking and recovery procedures, becomes critical. Regenerating codes provide fault tolerance by striping data across multiple servers, while using less repair traffic than traditional erasure codes during failure recovery. Therefore, we study the problem of remotely checking the integrity of regenerating-coded data against corruptions under a real-life cloud storage setting. We design and implement a practical data integrity protection (DIP) scheme for a specific regenerating code, while preserving its intrinsic properties of fault tolerance and repair-traffic saving. Our DIP scheme is designed under a mobile Byzantine adversarial model, and enables a client to feasibly verify the integrity of random subsets of outsourced data against general or malicious corruptions. It works under the simple assumption of thin-cloud storage and allows different parameters to be fine-tuned for a performance-security trade-off. We implement and evaluate the overhead of our DIP scheme in a real cloud storage test bed under different parameter choices. We further analyze the security strengths of our DIP scheme via mathematical models. We demonstrate that remote integrity checking can be feasibly integrated into regenerating codes in practical deployment.
Realizing the transformation from the storage device to the storage service by the application software is the core of cloud storage which is the combination of the application software and the storage device. However, the single cryptogram system cannot satisfy with the requirement of the privacy-preserving in cloud computing. Based on the assumption that the communication is absolute safe, an identity-based distributed encryption scheme is proposed in this paper to ensure the privacy safety of the cloud storage. The proposed scheme is more suitable for the privacy-preserving of mass users.
Cloud storage enables users to remotely store their data and enjoy the on-demand high quality cloud applications without the burden of local hardware and software management. Though the benefits are clear, such a service is also relinquishing users' physical possession of their outsourced data, which inevitably poses new security risks toward the correctness of the data in cloud. In order to address this new problem and further achieve a secure and dependable cloud storage service, we propose in this paper a flexible distributed storage integrity auditing mechanism, utilizing the homomorphic token and distributed erasure-coded data. The proposed design allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of misbehaving server. Considering the cloud data are dynamic in nature, the proposed design further supports secure and efficient dynamic operations on outsourced data, including block modification, deletion, and append. Analysis shows the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server colluding attacks.
With the increasing adoption of cloud computing for data storage, assuring data service reliability, in terms of data correctness and availability, has been outstanding. While redundancy can be added into the data for reliability, the problem becomes challenging in the “pay-as-you-use” cloud paradigm where we always want to efficiently resolve it for both corruption detection and data repair. Prior distributed storage systems based on erasure codes or network coding techniques have either high decoding computational cost for data users, or too much burden of data repair and being online for data owners. In this paper, we design a secure cloud storage service which addresses the reliability issue with near-optimal overall performance. By allowing a third party to perform the public integrity verification, data owners are significantly released from the onerous work of periodically checking data integrity. To completely free the data owner from the burden of being online after data outsourcing, this paper proposes an exact repair solution so that no metadata needs to be generated on the fly for repaired data. The performance analysis and experimental results show that our designed service has comparable storage and communication cost, but much less computational cost during data retrieval than erasure codes-based storage solutions. It introduces less storage cost, much faster data retrieval, and comparable communication cost comparing to network coding-based distributed storage systems.
The paper concentrates on analyzing and discussing data pooling structure, online data pooling partition storage model, structure model of enterprise cloud storage system, proposes the design plans of data control and cloud storage. Storage management control optimized is an effective method that will reduce the working time to large-scale data storage management. Combining storage devices and control management software will provide system data sharing and system high applicability. With cloud storage management control mechanism being applied, those business enterprises could benefit from this.
Nowadays energy-awareness represents a big challenge for cloud computing infrastructures as the adoption of cloud computing become a certain fact and together with the increasing costs for energy, calls for energy-aware methods and techniques. The storage system represents an important factor for energy consumption in a data center. Thus this paper, in the context of cloud storage, reviews the methods and technologies used for energy-aware operation of storage systems in data centers. After surveying relevant literature in this area, this paper presents some of the key research challenges that arise when such energy-saving techniques are extended for use in cloud storage environments.
Cloud computing moves the application software, platform and infrastructure into the large data centers which are maintained at the centralized location. The Cloud Service User (CSU) requests the resources from the cloud for their current requirements without investing the money. It is a pay-as-you-go-basis which means that the CSU pay what they actually consumed. If the Cloud Service Provider (CSP) provides the service to the CSU with high quality then only they improve the business. There are various delivery models available such as SaaS, PaaS and IaaS etc. These models are deployed over the public, private, community and hybrid deployment models for the effective delivery. The existing work focused on the separation of various high-level and low-level services involved in cloud services, which always has an important aspect in the quality of service. The CSU can store the data in the cloud with security, but no awareness of the location is provided in which the data stored. The CSP has to change the location of the data from one location to another location which is unknown by the CSU. Even though, the data with high security at the cloud is available there is no way to identify the location of the data. The proposed work focuses on the location awareness of the data by using the tag which is synchronized in all the location. The CSU can get the notification whenever the data location changes by the CSP. This technique improves the reliability of the cloud storage with the CSU retention. In future the technique will be improved at the maximum level for improving the performance of the cloud computing.
As Cloud services are burgeoning and attractive to HPC developers in virtue of the virtualization technology, how to establish their own dedicated virtual cluster easily become a very important problem. To contribute this issue, Easy Virtual Cluster with Cloud Storage (called VClouster) has been developed by Pervasive Computing Team in the National Center for High-performance Computing (NCHC). Just easy operation, NCHC VClouster helps building a Computing Cloud for HPC numerical simulation. It satisfies various customized demands and has high scalability for virtual machines (VM) so the performance of using Cloud service can be improved. NCHC VClouster system is a friendly design for Cloud users to send their requests, through the user specification it would create a customized and dedicated virtual cluster on demand for different users automatically. The system leverages Cloud toolkit combined with Cloud storage service, then Cloud users do not worry about the transmission of a huge amount of application data. NCHC VClouster also introduces International Certificate Authority (CA) services so that authorized users can easily utilize their virtual machines and integrate more computing resources in same CA organization.
According to the demerits of the traditional cloud storage that there exists superuser, encryption and decryption would take up many client's sources, and the retrieval spends much time and is complex, the paper proposed a security structure of cloud storage based on homomorphic encryption scheme. The structure will reduce the use of client's sources, and is convenient for moving to mobile devices; the homomorphic encryption scheme makes retrieval more efficient; users' data would be more secure because they could not be achieved by superusers in the side of sever; users can operate cloud virtual disk as convenient as local disk. These merits of the structure not only could ensure the data storage's security, but also promote highly the popularization of cloud storage.
In this paper we propose N-Cloud scheme which improves performance, availability, and confidentiality in cloud storage. N-Cloud provides availability by dividing/splitting a file into many chunks, and replicating in a non-overlapping manner these chunks into many cloud storages, based on security and reliability consideration. In this scheme, the chunks of a file can be encrypted concurrently while the encrypted chunks can be uploaded to geographical separated cloud storages in parallel. Same benefit can be achieved for the downloading and decrypting process. It greatly speeds up the processing and transfer. N-Cloud provides confidentiality by dividing/splitting a file into many chunks, encrypting all chunks, and distributing these chunks to many clouds. N-Cloud ensures that no one cloud has the whole file; the scheme will not be compromised unless an attacker breaks into all cloud storage. A preliminary results show significant performance improvement over existing schemes.
In Cloud Storage system, storage systems have to service for large numbers of scattered data access nodes, and data I/O almost are in random access form, in addition, the distribution storage of data result in data transmission between the Cloud nodes increases greatly, then the performance of the cloud storage system was be restricted remarkably. In this paper, we put forward a system for improving access performance in Cloud Storage system. Through the access trace, the process which doing disk I/O should be detected. The processes that are executed contemporaneous should be regarded as a group. Then, the block access sequences belong to same process groups could be mined based on the Frequent Sequence Mining. And the block relation could be obtained. Ultimately, the related blocks could be rearranged to the near location. It could reduce the head moving of disk during access and realize the mapping from random access to sequence access partly. Furthermore, the data could be migrated between the storage nodes according to the block relation and reducing the data transfer through network between nodes. We have also evaluated the benefits of the system. Our result using real system workloads show that with the data rearrange and data transfer, about 10%-20% I/O response time could be reduced.
Cloud storage services enable users to enjoy high-capacity and high-quality storage with less overhead. However, the fact that users no longer have physical possession of the data makes the data integrity protection in cloud storage a very challenging and formidable task. In this paper, we propose a new remote integrality checking scheme for cloud storage that integrate correct checking, dynamic update and privacy preserving. The security and performance analysis shows that this new scheme is provably secure, and can check mass remote file's integrality with constant storage and communication resource for cloud storage users
With the advent of cloud computing, more and more organizations plan to adopt the cloud storage service allowing a data owner to outsource her data to the cloud service provider where the users are provided to access to the outsourced data. However, when the outsourced data are sensitive, the security and privacy of data have to be protected to eliminate the data owner's concerns. Since in cloud storage systems, the data owner and the cloud server are not with the same trust domain, the honest and curious cloud server cannot be relied on to define and enforce the access control policy. To tackle this open problem, existing methods use the cryptographic techniques such as symmetric encryption or traditional public encryption scheme requiring the data owner to encrypt the data and distribute decryption keys to the authorized users, which incur the complicated key distribution and management. In this work, cipher text policy attribute based encryption scheme is presented to achieve fine-grained access control. Furthermore, in the presented scheme, an immediate attribute revocation method is presented to handle the dynamic updates of users' access privileges in cloud storage systems. Security analysis and performance evaluation show the proposed scheme is secure and efficient in cloud storage systems.
With the introduction of cloud storage and cloud servers, it has become easier than ever to backup all your important computer files online. You are now given the flexibility of accessing all your files from anywhere in the world, with the benefit of knowing that all your important pictures, videos, music, files, documents, as well as other programs and data are securely stored and available to you 24 hours a day 7 days a week. With our extensive knowledge of cloud storage and backed up by customer and webmaster reviews we help you chose the best cloud storage service provider for you.
What is the Review Process that you use to find the Best in online storage companies?
Top10CloudStorage.com uses a ten point quality check for each of the reviews that we provide on the website. Our ultimate goal is to assist our readers in finding the best in cloud storage and the most expeditious way in which to do that is to use the same criteria in reviewing each online cloud storage provider. Our experts provide a professional review (an expert look at the company) and then we open up our forum to customers that have used the service and want to rate it themselves. This is how we are able to provide an unbiased opinion and technical look at cloud backup while also offering the sentiment of the consensus of actual customers.
Our professional reviews and customer reviews both use the same ten point look at the cloud online storage company. We highlight what is most important to the consumer, with categories such as how much storage space the company offers, as well as how reliable the cloud file storage company is. Each category receives a score based on a 1 to 5 star system and that is how we determine the overall rating for the company.
Let’s take a look at how Top10CloudStorage.com looks at an online cloud storage provider:
selecting a cloud data storage company that is the least expensive does not mean that the customer is getting the best value for their money. What Top10CloudStorage.com looks for in value is a combination of everything that makes up the cloud storage company and then, how much they charge. This might mean that the customer will see a cloud backup company that charges more for their service, but if they are ranked highly in value for money, then that company also offer superior features, storage space and reliability which, when weighed against the cost, makes up the rating for this online storage category.
this category is based on statistical data related to the uptime of the service. It is expected that cloud storage companies have a 99.9% uptime; however some may fall below that due to unforeseen circumstances. Top10CloudStorage.com believes that the consumer should be made aware of that so that they may make the most informed decision in selecting their online storage service provider.
The Top10CloudStorage.com staff reviewers put cloud storage company customer service departments through a test. This test is conducted as a live phone or live chat customer service request. The time that it takes to get a response and a solution to a problem is rated for speed, helpfulness and efficiency.
Technical Support and customer service are closely related; however this category is a rating of the technical proficiency of the tech support staff. Certainly, it is one thing to have a friendly and helpful tech support agent assisting you and quite another to have one that is all of that and actually solves the problem quickly.
This category is a rating of the amount of features that are offered as well as their usefulness to the consumer. Some cloud storage companies tend to comment on a large number of features that they offer however, those features are not always of a benefit to the consumer. Top10CloudStorage.com keeps a careful eye on this category when reviewing a company.
This category is a comparison of the amount of storage space offered by the company. Storage space also factors into the ‘value for money’ rating.
when testing cloud storage services, Top10CloudStorage.com rates how easy that service is to use. This is compared against a benchmark of general users and technically proficient users. A good rating represents a median between ease of use for general and technical users.
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