SPEK: A Storage Performance Evaluation Kernel Module for Block-Level Storage Systems under Faulty Conditions

In this paper we introduce SPEK (storage performance evaluation kernel module), a benchmarking tool for measuring and characterizing raw performance of data storage systems at block level. It can be used for both DAS (direct attached storage) and block level networked storage systems. Each SPEK tool consists of a controller, several workers, and one or more probers. Each worker is a kernel module generating I/O requests to lower level SCSI layer directly. Compared to traditional file system I/O and disk I/O benchmarking tools, SPEK is highly accurate and efficient since it runs at kernel level and eliminates file system overheads. It is specially suitable for accurately measuring raw performance of data storages at block level without influence of file system cache or buffer cache. Using SPEK, a user can easily simulate realistic workloads and produce detailed profiling data for networked storage as well as DAS. We have built a prototype on Linux and our experiments have demonstrated its accuracy and efficiency in measuring block level storage systems.

This paper introduces a new benchmark tool for evaluating performance and availability (performability) of networked storage systems, specifically storage area network (SAN) that is intended for providing block-level data storage with high performance and availability. The new benchmark tool, named N-SPEK (Networked-Storage Performability Evaluation Kernel module), consists of a controller, several workers, one or more probers, and several fault injection modules. N-SPEK is highly accurate and efficient since it runs at kernel level and eliminates skews and overheads caused by file systems. It allows a SAN architect to generate configurable storage workloads to the SAN under test and to inject different faults into various SAN components such as network devices, storage devices, and controllers. Available performances under different workloads and failure conditions are dynamically collected and recorded in the N-SPEK over a spectrum of time. To demonstrate its functionality, we apply N-SPEK to evaluate the performability of a specific iSCSI-based SAN under Linux environment. Our experiments show that N-SPEK not only efficiently generates quantitative performability results but also reveals a few optimization opportunities for future iSCSI implementations.

Living in the age of digital transformation, companies and individuals are moving to public and private clouds to store and retrieve information, hence the need to store and retrieve data is exponentially increasing. Existing storage technologies such as DAS are facing a big challenge to deal with these huge amount of data. Hence, newer technologies should be adopted. Storage Area Network (SAN) is a distributed storage technology that aggregates data from several private nodes into a centralized secure place. Looking at SAN from a security perspective, clearly physical security over multiple geographical remote locations is not adequate to ensure a full security solution. A SAN security framework needs to be developed and designed. This work investigates how SAN protocols work (FC, ISCSI, FCOE). It also investigates about other storages technologies such as Network Attached Storage (NAS) and Direct Attached Storage (DAS) including different metrics such as: IOPS (input output per second), Throughput, Bandwidths, latency, cashing technologies. This research work is focusing on the security vulnerabilities in SAN listing different attacks in SAN protocols and compare it to other such as NAS and DAS. Another aspect of this work is to highlight performance factors in SAN in order to find a way to improve the performance focusing security solutions aimed to enhance the security level in SAN.

With the popularization of network applications, more and more devices can be connected to the network, and the amount of data generated is increasing. The problem of secure data storage is becoming more and more prominent. The storage of data is becoming larger and more complex. It has moved from simple independent storage to the cloud. The storage system has become an important network component independent of the server. The performance of the storage system directly affects the performance of the network and directly affects the user experience of network applications. This article discusses the mainstream storage technology solutions, namely Direct Attached Storage (DAS), Storage Area Network (SAN) and Network Attached Storage (NAS). The three solutions have their own characteristics and are suitable for different application scenarios and requirements. In this paper, network attached storage (NAS) is taken as an example, and a specific storage application deployment plan is given in combination with application requirements.

Due to the excitement of Internet and high bandwidth, there are more and more multimedia applications involving digital industry. However the storage and the real-time of the conventional storage architecture cannot cater for the requirements of continuous media. The most important storage architecture used in past is Direct Attached Storage (DAS) and RAID cabinet, and recently, both Network Attached Storage (NAS) and Storage Area Networks (SAN) are the alterative storage network topology. But as for the multimedia characters, there need more storage capacity and more simultaneous streams. In this paper, we have introduced a novel concept 'Unified Storage Network' (USN) to build efficient SAN over IP, to bridge the gap of NAS and SAN, furthermore to resolve the scalability problem of storage for multimedia applications.

The ever-increasing demand for fast and reliable data storage has caused dramatic changes in the storage model. Direct attached storage (DAS) architecture, also known as server-centric architecture, is being replaced by the storage area network (SAN), leading to storage-centric architecture. In SAN storage devices exist completely independent of any computer (servers in particular). Multiple servers can access the same storage device without involvement of other servers. Recently, companies have been able to implement storage integration/sharing, remote backup/restoral, near-real-time disk mirroring/replication, and the like, using a new SAN architecture known as distributed storage area network (DSAN). The DSAN is multiple SANs interconnected using existing Internet Protocol (IP) networks to distribute storage over wide geographical areas. Even though DSANs provide additional capabilities to a SAN, the end-to-end latency (ETEL) due to large physical cable lengths (IP networks) imposes limitations on enterprise class application performance. DSANs can also be implemented using IP storage solutions that provide direct links between servers and storages, eliminating translation of fibre channel protocol frames to IP packets. This paper examines the effect of ETEL in DSAN on the performance of an enterprise class application with real-time application replication like Microsoft Exchange Server 2003. This investigation in done in two parts: disk subsystem (DS) characterization using Jetstress benchmarking software and the performance of Microsoft Exchange using LoadSim 2003 benchmarking software. Preliminary results were presented in [1].

The proliferation of machine-to-machine (M2M) communication is exponentially increasing the amount of unstructured data that is generated in the digital universe. It is estimated that Facebook generates roughly about 1 TB of data every day, and most of it is unstructured data. The storage infrastructures like storage area networks (SANs) and network-attached storage (NAS) are not designed to store and process unstructured data. Hence, it is the need of the day to design storage devices and networks which are robust enough to scale and accommodate huge amount of unstructured data without causing any performance impact. However, any present-day storage infrastructure that is designed to handle big data uses the traditional storage technologies like NAS and SAN as their underlying foundation. Hence, it is impossible to understand big data storage platforms without proper understanding of underlying technologies. In this chapter, we are explaining the foundations of storage technologies in the beginning, and later on, we are doing a deep dive to understand how their design has been transformed in such a way that they can store and process big data. In most of the scenarios, multiple storage platforms are combined, and then some kind of enhancement is added to make them compatible to handle big data. In the first half of the chapter, we are examining the storage technologies like direct-attached storage (DAS), NAS, and SAN. We are also analyzing their suitability for processing big data. In the second half of the chapter, we are focusing on the latest storage technologies which have been designed and optimized for big data processing like Panasas file system, Luster file system, GFS, and HDFS.KeywordsBig data Storage Cloud Hadoop Storage area network Network -attached storageFiber Channel Object -based storagePanasas

SCSI is a newly emerging protocol with the goal of implementing the Storage Area Network (SAN) technology over TCP/IP,where enables to access to remote data that in attached storage disks storages - Direct Attached Storage(DAS) over IP-networked. Also it's brings economy and convenience whereas it also raises performance and reliability issues. This paper investigates about possibility , using storage technology of the SANs, and iSCSI-SAN protocol,in local system PC, to improve access to attached storage disks storages in local system, with using iSCSI-SANs as virtual storage, is rather than DAS storage in local system of PC. Explicates after experiment procedure is that improving throughput of iSCSI-SANs was better than attached storage disks storages - DAS in local system . This means is that it can use iSCSI-SANs in local system of PC as attache storage disks storages as DAS , without cost , high performance, and easy control.

With the fast growth of data in multispectral image processing, the traditional storage architecture was challenged. It is currently being replaced by Storage Area Networks (SAN), which makes storage devices externalized from servers. A SAN is a separate network for storage, isolated from the messaging network and optimized for the movement of data between servers and storage devices. Nowadays, most of current SAN use Fibre Channel to move data between servers and storage devices (FC-SAN), but because of the drawbacks of the FC-SAN: for interoperability, lack of skilled professional and management tools, high implementation cost and so on, the development and application of FC-SAN was obstructed. In this paper, we introduce an IP-based Storage Area Networks architecture, which has the good qualities of FC- SAN but overcomes the shortcoming of it. The principle is: use IP technology to move data between servers and storage devices, build a SAN with the IP-based network devices (not the FC-based network device), and through the switch, SAN is attached to the LAN(Local Area Network) through multiple access. Especially, these storage devices are acted as commercial NAS devices and PC.

Storage systems are the next frontier for providing protection against intrusion. Since storage systems see changes to persistent data, several types of intrusions can be detected by storage systems. Intrusion detection (ID) techniques can be deployed in various storage systems. In this paper, we study how intrusions can be detected at the block storage level and in SAN environments. We propose novel approaches for storage-based intrusion detection and discuss how features of state-of-the-art block storage systems can be used for intrusion detection and recovery of compromised data. In particular we present two prototype systems. First we present a real time intrusion detection system (IDS), which has been integrated within a storage management and virtualization system. In this system incoming requests for storage blocks are examined for signs of intrusions in real time. We then discuss how intrusion detection schemes can be deployed as an appliance loosely coupled with a SAN storage system. The major advantage of this approach is that it does not require any modification and enhancement to the storage system software. In this approach, we use the space and time efficient point-in-time copy operation provided by SAN storage devices. We also present performance results showing that the impact of ID on the overall storage system performance is negligible. Recovering data in compromised systems is also discussed.

The Performance Analysis of GlusterFS In Virtual Storage

Is cloud storage ready? Performance comparison of representative IP-based storage systems

Archiving and retrieval of experimental data using SAN based centralized storage system for SST-1

On the basis of introducing the function of information storage system, this paper analyzes the advantages and disadvantages of three kinds of traditional information resource storage systems: Direct Attached Storage (DAS), network attached storage (NAS) and storage area network (SAN) ct-Based Storage). Compared with the traditional storage mode, the storage system is intelligent because of the introduction of the concept of object. With the further development of object storage, this storage mode can realize all the functions of block or file, and also has the intelligent mechanism of self-management and self adaptation that block and file storage system do not have.

By merging network and channel interfaces, resulting interfaces allow multiple computers to physically share storage devices. A storage area network (SAN) is a high-speed special-purpose network (or subnetwork) that interconnects different kinds of data storage devices with associated data servers on behalf of a larger network of users. In SAN, computers service local file requests directly from shared storage devices. Direct device access eliminates the server machines as bottlenecks to performance and availability. Communication is unnecessary between computers, since each machine views the storage as being locally attached. SAN provides us to very large physical storage up to 64-bit address space, but traditional file systems can't adapt to the file system for SAN because they have the limitation of scalability. In this paper, we present architectures and features of SANtopia that allows multiple machines to access and share disk and tape devices on a Fibre Channel or SCSI storage network in Linux system. It performs well as a local file system, as a traditional network file system running over IP environments, and as a high performance cluster file system running over storage area networks like Fibre Channel. SANtopia provides a key cluster enabling technology for Linux, helping to bring the availability, scalability, and load balancing benefits of clustering to Linux.