GMBlock: Optimizing data movement in a block-level storage sharing system over Myrinet

We present gmblock, a block-level storage sharing system over Myrinet which uses an optimized I/O path to transfer data directly between the storage medium and the network, bypassing the host CPU and main memory bus of the storage server. It is device driver independent and retains the protection and isolation features of the OS. We evaluate the performance of a prototype gmblock server and find that: (a) the proposed techniques eliminate memory and peripheral bus contention, increasing remote I/O bandwidth significantly, in the order of 20–200% compared to an RDMA-based approach, (b) the impact of remote I/O to local computation becomes negligible, (c) the performance characteristics of RAID storage combined with limited NIC resources reduce performance. We introduce synchronized send operations to improve the degree of disk to network I/O overlapping. We deploy the OCFS2 shared-disk filesystem over gmblock and show gains for various application benchmarks, provided I/O scheduling can eliminate the disk bottleneck due to concurrent access.     

Design a cloud storage platform for pervasive computing environments

An increasing number of personal electronic handheld devices (e.g., SmartPhone, netbook, MID and etc.), which make up the personal pervasive computing environments, are playing an important role in our daily lives. Data storage and sharing is difficult for these devices due to the data inflation and the natural limitations of mobile devices, such as the limited storage space and the limited computing capability. Since the emerging cloud storage solutions can provide reliable and unlimited storage, they satisfy to the requirement of pervasive computing very well. Thus we designed a new cloud storage platform which includes a series of shadow storage services to address these new data management challenges in pervasive computing environments, which called as “SmartBox”. In SmartBox, each device is associated its shadow storage with a unique account, and the shadow storage acts as backup center as well as personal repository when the device is connected. To facilitate file navigation, all datasets in shadow storage are organized based on file attributes which support the users to seek files by semantic queries. We implemented a prototype of SmartBox focusing on pervasive environments being made up of Internet accessible devices. Experimental results with the deployments confirm the efficacy of shadow storage services in SmartBox.     

Replication management in peer-to-peer cloud storage systems

Data availability represents one of the primary functionalities of any cloud storage system since it ensures uninterrupted access to data. A common solution used by service providers that increase data availability and improve cloud performance is data replication. In this paper, we present a dynamic data replication strategy that is based on a hybrid peer-to-peer cloud architecture. Our proposed strategy selects the most popular data for replication. To determine the proper nodes for storing popular data, we employ not only the feature specifications of storage nodes, but also the relevant structural positions in the cloud network. Our simulation results show the impact of using features such as data popularity, and structural characteristics in improving network performance and balancing the storage nodes, and reducing user response time.

     

Efficient TPA-based auditing scheme for secure cloud storage

In recent years, how to design efficient auditing protocol to verify the integrity of users’ data, which is stored in cloud services provider (CSP), becomes a research focus. Homomorphic message authentication code (MAC) and homomorphic signature are two popular techniques to respectively design private and public auditing protocols. On the one hand, it is not suitable for the homomorphic-MAC-based auditing protocols to be outsourced to third-party auditor (TPA), who has more professional knowledge and computational abilities, although they have high efficiencies. On the other hand, the homomorphic-signature-based ones are very suitable for employing TPA without compromising user’s signing key but have very low efficiency (compared to the former case). In this paper, we propose a new auditing protocol, which perfectly combines the advantages of above two cases. In particular, it is almost as efficient as a homomorphic-MAC-based protocol proposed by Zhang et al. recently. Moreover, it is also suitable for outsourcing to TPA because it does not compromise the privacy of users’ signing key, which can be seen from our security analysis. Finally, numerical analysis and experimental results demonstrate the high-efficiency of our protocol.

     

Future-proof: bunkered data centres and the selling of ultra-secure cloud storage

Abandoned after the Cold War, nuclear bunkers around the world have found afterlives as ultra-secure data storage sites for cloud computing providers. The operators of these bunkered data centres capitalize on the spatial, temporal, and material security affordances of their subterranean fortresses, promoting them as ‘future-proof’ cloud storage solutions. Taking the concept of ‘future-proofing’ as its entry-point, this essay explores how data centre professionals work with the imaginative properties of the bunker to configure data as an object to be securitized. The essay takes the form of an ethnographic tour through a UK-based data bunker. During this tour, threatening data futures and fragile data materialities are conjured in order to secure the conditions of possibility for the bunkered data centre's commercial continuity. Future-proofing, it is argued, provides a conceptual opening onto the entangled imperatives of security and marketing that drive the commercial data storage industry.     

Efficient chameleon hashing-based privacy-preserving auditing in cloud storage

Cloud storage is an important application service in cloud computing, it allows data users to store and access their files anytime, from anywhere and with any device. To ensure the security of the outsourced data, data user needs to periodically check data integrity. In some cases, the identity privacy of data user must be protected. However, in the existing preserving identity privacy protocols, data tag generation is mainly based on complex ring signature or group signature. It brings a heavy burden to data user. To ensure identity privacy of data user, in this paper we propose a novel identity privacy-preserving public auditing protocol by utilizing chameleon hash function. It can achieve the following properties: (1) the identity privacy of data user is preserved for cloud server; (2) the validity of the outsourced data is verified; (3) data privacy can be preserved for the auditor in auditing process; (4) computation cost to produce data tag is very low. Finally, we also show that our scheme is provably secure in the random oracle model, the security of the proposed scheme is related to the computational Diffie–Hellman problem and hash function problem.     

The potential of cloud point system as a novel two-phase partitioning system for biotransformation

Although the extractive biotransformation in two-phase partitioning systems have been studied extensively, such as the water–organic solvent two-phase system, the aqueous two-phase system, the reverse micelle system, and the room temperature ionic liquid, etc., this has not yet resulted in a widespread industrial application. Based on the discussion of the main obstacles, an exploitation of a cloud point system, which has already been applied in a separation field known as a cloud point extraction, as a novel two-phase partitioning system for biotransformation, is reviewed by analysis of some topical examples. At the end of the review, the process control and downstream processing in the application of the novel two-phase partitioning system for biotransformation are also briefly discussed.     

MHB*T based dynamic data integrity auditing in cloud storage

Cluster Computing - Integrity audit technology is proposed to protect data in remote cloud servers from being tampered with. However, the challenge is that the computational complexity is too large...     

A PR-quadtree based multi-dimensional indexing for complex query in a cloud system

The state-of-the-art indexing mechanisms for distributed cloud data management systems can not support complex queries, such as multi-dimensional query and range query. To solve this problem, we propose a multi-dimensional indexing mechanism named PR-Chord to support complex queries. PR-Chord is composed of the global index named PR-Index and the Chord network. The multi-dimensional space formed by the range of the multi-dimensional data is divided into hyper-rectangle spaces equally. The PR-Index is a hierarchical index structure based on the improved PR quadtree to index these spaces. The complex query is transformed into the query of leaf nodes of PR-Index. We design the algorithms of query, insertion and deletion to support complex queries. Since PR-Index does not store the multi-dimensional data, its maintenance cost is zero. PR-Chord has the advantages of load balancing and simple algorithm. The experiment results demonstrate that PR-Chord has good query efficiency.     

Enabling secure auditing and deduplicating data without owner-relationship exposure in cloud storage

The public cloud storage auditing with deduplication has been studied to assure the data integrity and improve the storage efficiency for cloud storage in recent years. The cloud, however, has to store the link between the file and its data owners to support the valid data downloading in previous schemes. From this file-owner link, the cloud server can identify which users own the same file. It might expose the sensitive relationship among data owners of this multi-owners file, which seriously harms the data owners’ privacy. To address this problem, we propose an identity-protected secure auditing and deduplicating data scheme in this paper. In the proposed scheme, the cloud cannot learn any useful information on the relationship of data owners. Different from existing schemes, the cloud does not need to store the file-owner link for supporting valid data downloading. Instead, when the user downloads the file, he only needs to anonymously submit a credential to the cloud, and can download the file only if this credential is valid. Except this main contribution, our scheme has the following advantages over existing schemes. First, the proposed scheme achieves the constant storage, that is, the storage space is fully independent of the number of the data owners possessing the same file. Second, the proposed scheme achieves the constant computation. Only the first uploader needs to generate the authenticator for each file block, while subsequent owners do not need to generate it any longer. As a result, our scheme greatly reduces the storage overhead of the cloud and the computation overhead of data owners. The security analysis and experimental results show that our scheme is secure and efficient.     

Adaptive hybrid storage systems leveraging SSDs and HDDs in HPC cloud environments

Cloud computing should inherently support various types of data-intensive workloads with different storage access patterns. This makes a high-performance storage system in the Cloud an important component. Emerging flash device technologies such as solid state drives (SSDs) are a viable choice for building high performance computing (HPC) cloud storage systems to address more fine-grained data access patterns. However, the bit-per-dollar SSD price is still higher than the prices of HDDs. This study proposes an optimized progressive file layout (PFL) method to leverage the advantages of SSDs in a parallel file system such as Lustre so that small file I/O performance can be significantly improved. A PFL can dynamically adjust chunk sizes and stripe patterns according to various I/O traffics. Extensive experimental results show that this approach (i.e. building a hybrid storage system based on a combination of SSDs and HDDs) can actually achieve balanced throughput over mixed I/O workloads consisting of large and small file access patterns.     

Extractive biodegradation of diphenyl ethers in a cloud point system: Pollutant bioavailability enhancement and surfactant recycling

The biodegradation of diphenyl ethers (DEs) in the environment is limited by their high hydrophobicity. The enhancement of DE bioavailability by a cloud point system (CPS) was investigated in this study. Three CPSs (i.e., Triton X-114, Triton X-114 + Triton X-45, and Brij30 + TMN-3) were tested to promote DE biodegradation. Biocompatibility tests showed that the biodegradation of DE and 4-bromodiphenyl ether (4-BDE) was inhibited by TX-114, unaffected by TX-114 + TX-45, and promoted by Brij30 + TMN-3 over 48 h of cultivation with Cupriavidus basilensis and 4% (w/v) nonionic surfactants. Further optimization with 2% (w/v) Brij30 + TMN-3 yielded residual DE and 4-BDE quantities of 143 and 154 mg/L, respectively, lower than quantities in the control. During degradation, DE content did not decrease in the dilute phase, but sharply decreased in the coacervate phase, indicating that the DEs gradually diffused and transferred from the coacervate phase to the dilute phase for degradation by microbial cells. This behavior also enhanced the bioavailability of DEs in the CPS. By removing the cell-rich dilute phase and adding fresh degradation medium and DE to the coacervate phase, surfactants were successfully recovered and reused twice without affecting DE biodegradation. Results demonstrated that a CPS with 2% (w/v) Brij30 + TMN-3 not only enhanced the bioavailability of DEs, but also decreased the treatment cost through surfactant recycling, which is beneficial for large-scale applications.     

Flexible identity-based remote data integrity checking for cloud storage with privacy preserving property

Cluster Computing - Provable data possession (PDP) protocol is a mechanism that guarantees the integrity of user’s cloud data, and many efficient protocols have been proposed. Many of them...     

Whole cell microbial transformation in cloud point system

Cloud point system, consisting of nonionic surfactant in an aqueous solution, has been developed as a novel medium for whole cell microbial transformation. The basic properties of cloud point system including phase separation and solubilization are introduced. The application of cloud point system for extractive microbial transformation is different from that of water-organic solvent two-phase partitioning system or aqueous two-phase system are discussed, which mainly focus on the biocompatibility of microorganism in a cloud point system and a downstream process of microbial transformation in cloud point system with oil-water-surfactant microemulsion liquid-liquid extraction for surfactant recovery and product separation. Finally, examples of whole cell microbial transformation in cloud point systems, especially in situ extraction of moderate polar substrate/product, are also presented.     

Auto-scaling techniques for IoT-based cloud applications: a review

Cluster Computing - Cloud and IoT applications have inquiring effects that can strongly influence today’s ever-growing internet life along with necessity to resolve numerous challenges for...     

The implementation of a cloud city traffic state assessment system using a novel big data architecture

In order to store and analyze the increasing data in recent years, big data techniques are applied to many fields such as healthcare, manufacturing, telecommunications, retail, energy, transportation, automotive, security, environment, etc. This work implements a city traffic state assessment system in cloud using a novel big data architecture. The proposed system provides the real-time busses location and real-time traffic state, especially the real-time traffic state nearby, through open data, cloud computing, bid data technology, clustering methods, and irregular moving average. With the high-scalability cloud technologies, Hadoop and Spark, the proposed system architecture is first implemented successfully and efficiently. Next, we utilize irregular moving average and clustering methods to find the area of traffic jam. Finally, three important experiments are performed. The first experiment indicates that the computing ability of Spark is better than that of Hadoop. The second experiment applies Spark to process bus location data under different number of executors. In the last experiment, we apply irregular moving average and clustering methods to efficiently find the area of traffic jam in Taiwan Boulevard which is the main road in Taichung city. Based on these experimental results, the provided system services are present via an advanced web technology.     

Valley fever: danger lurking in a dust cloud

Coccidioides immitis and Coccidioides posadasii contribute to the development of Valley Fever. The ability of these fungal pathogens to evade the host immune system creates difficulty in recognition and treatment of this debilitating infection. In this review, we describe the current knowledge of Valley Fever and approaches to improve prevention, detection, and treatment.     

FastStor: improving the performance of a large scale hybrid storage system via caching and prefetching

Storing enormous amount of data on hybrid storage systems has become a widely accepted solution for today’s production level applications in order to trade off the performance and cost. However, how to improve the performance of large scale storage systems with hybrid components (e.g. solid state disks, hard drives and tapes) and complicated user behaviors is not fully explored. In this paper, we conduct an in-depth case study (we call it FastStor) on designing a high performance hybrid storage system to support one of the world’s largest satellite images distribution systems operated by the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) center. We demonstrate how to combine conventional caching policies with innovative current popularity oriented and user-specific prefetching algorithms to improve the performance of the EROS system. We evaluate the effectiveness of our proposed solution using over 5 million real world user download requests provided by EROS. Our experimental results show that using the Least Recently Used (LRU) caching policy alone, we are able to achieve an overall 64 % or 70 % hit ratio on a 100 TB or 200 TB FTP server farm composed of Solid State Disks (SSDs) respectively. The hit ratio can be further improved to 70 % (for 100 TB SSDs) and 76 % (for 200 TB SSDs) if intelligent prefetching algorithms are used together with LRU.