Ming Zhang

A caching strategy to improve iSCSI performance

iSCSI is one of the most recent standards that allows SCSI protocols to be carried out over IP networks. However, to encapsulate the SCSI protocol over IP requires a significant amount of overhead traffic for SCSI commands transfers and handshaking over the Internet. In this paper, we propose a caching scheme, called iCache, to improve the iSCSI performance. iCache uses a log disk along with a piece of non-volatile RAM to cache the iSCSI traffic. Through an efficient caching algorithm, iCache can significantly improve performance over current iSCSI systems. Numerical results using popular benchmark program and real world trace have shown dramatic performance gain.

Introducing SCSI-to-IP cache for storage area networks

Data storage plays an essential role in todays fast-growing data-intensive network services. iSCSI is one of the most recent standards that allow SCSI protocols to be carried out over IP networks. However, the disparities between SCSI and IP prevent fast and efficient deployment of SAN (storage area network) over IP. This paper introduces STICS (SCSI-To-IP cache storage), a novel storage architecture that couples reliable and high-speed data caching with low-overhead conversion between SCSI and IP protocols. Through the efficient caching algorithm and localization of certain unnecessary protocol overheads, STICS significantly improves performance over current iSCSI system. Furthermore, STICS can be used as a basic plug-and-play building block for data storage over IP. We have implemented software STICS prototype on Linux operating system. Numerical results using popular PostMark benchmark program and EMCs trace have shown dramatic performance gain over the current iSCSI implementation.

STICS: SCSI-to-IP cache for storage area networks

Abstract Data storage plays an essential role in todays fast-growing data-intensive network services. New standards and products emerge very rapidly for networked data storage. Given the mature Internet infrastructure, the overwhelming preference among the IT community recently is using IP for storage networking because of economy and convenience. iSCSI is one of the most recent standards that allow SCSI protocols to be carried out over IP networks. However, there are many disparities between SCSI and IP in terms of protocols, speeds, bandwidths, data unit sizes, and design considerations that prevent fast and efficient deployment of storage area network (SAN) over IP. This paper introduces SCSI-to-IP cache storage (STICS), a novel storage architecture that couples reliable and high-speed data caching with low-overhead conversion between SCSI and IP protocols. A STICS block consists of one or several storage devices and an intelligent processing unit with CPU and RAM. The storage devices are used to cache and store data while the intelligent processing unit carries out the caching algorithm, protocol conversion, and self-management functions. Through the efficient caching algorithm and localization of certain unnecessary protocol overheads, STICS can significantly improve performance, reliability, and scalability over current iSCSI systems. Furthermore, STICS can be used as a basic plug-and-play building block for data storage over IP. Analogous to “cache memory” invented several decades ago for bridging the speed gap between CPU and memory, STICS is the first-ever “cache storage” for bridging the gap between SCSI and IP making it possible to build an efficient SAN over IP. We have implemented software STICS prototype on Linux operating system. Numerical results using popular benchmarks such as vxbench, IOzone, PostMark, and EMCs trace have shown a dramatic performance gain over the current iSCSI implementation.

SPEK: a storage performance evaluation kernel module for block-level storage systems under faulty conditions

This paper introduces a new benchmark tool, SPEK (storage performance evaluation kernel module), for evaluating the performance of block-level storage systems in the presence of faults as well as under normal operations. SPEK can work on both direct attached storage (DAS) and block level networked storage systems such as storage area networks (SAN). Each SPEK consists of a controller, several workers, one or more probers, and several fault injection modules. Since it runs at kernel level and eliminates skews and overheads caused by file systems, SPEK is highly accurate and efficient. It allows a storage architect to generate configurable workloads to a system under test and to inject different faults into various system components such as network devices, storage devices, and controllers. Available performance measurements under different workloads and faulty conditions are dynamically collected and recorded in SPEK over a spectrum of time. To demonstrate its functionality, we apply SPEK to evaluate the performance of two direct attached storage systems and two typical SANs under Linux with different fault injections. Our experiments show that SPEK is highly efficient and accurate to measure performance for block-level storage systems.

BUCS - a bottom-up cache structure for networked storage servers

This paper introduces a new caching structure to improve server performance by minimizing data traffic over the system bus. The idea is to form a bottom-up caching hierarchy in a networked storage server. The bottom level cache is located on an embedded controller that is a combination of a network interface card (NIC) and a storage host bus adapter (HBA). Storage data coming from or going to a network are cached at this bottom level cache and meta-data related to these data are passed to the host for processing. When cached data exceed the capacity of the bottom level cache, some data are moved to the host RAM that is usually larger than the bottom level cache. This new cache hierarchy is referred to as bottom-up cache structure (BUGS) in contrast to a traditional CPU-centric top-down cache where the top-level cache is the smallest and fastest, and the lower in the hierarchy the larger and slower the cache. Such data caching at the controller level dramatically reduces bus traffic and leads to great performance improvement for networked storages. We have implemented a proof-of-concept prototype using Intels IQ80310 reference board and Linux network block device. Through performance measurements on the prototype implementation, we observed up to 3 times performance improvement of BUCS over traditional systems in terms of response time and system throughput.

Performability evaluation of networked storage systems using N-SPEK

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.

Successor: Proactive cache warm-up of destination hosts in virtual machine migration contexts

In virtualization platforms, host-side storage caches can serve virtual machines (VM) disk I/O requests, which originally target network storage servers. When these requests hit host-side caches, network and disk access latencies are obviated, and thus VMs perceive improved storage performance. VM migration is common in cloud environments, however, VM migration does not transfer host-side cache states. As a result, a newly migrated VM suffers performance degradation until the cache is fully rebuilt. The performance degradation period can be hours long if the cache is naturally warmed up. Employing existing cache warm-up solutions such as migrating host-side cache and Bonfire, VMs may either have a prolonged total migration time or undergo a performance degradation period of tens of minutes due to the warm-up caused storage contention. We propose Successor, which proactively warms up caches of destination hosts before migration completes. Specifically, accessibility of destination hosts during migration enables Successor to parallelize cache warm-up and VM migration. Compared with migrating host-side cache and Bonfire, Successor achieves zero VM-perceived cache warm-up time with low resource costs and performance penalties. We have implemented a prototype of Successor on QEMU/KVM based virtualization platform and verified its efficiency.

A hybrid erasure-coded ECC scheme to improve performance and reliability of solid state drives

The high performance and ever-increasing capacity of flash memory has led to the rapid adoption of Solid-State Disks (SSDs) in mass storage systems. In order to increase disk capacity, multi-level cells (MLC) are used in the design of SSDs, but the use of such SSDs in persistent storage systems raise concerns for users due to the low reliability of such disks. In this paper, we present a hybrid erasure-coded (EECC) architecture that incorporates ECC schemes and erasure codes to improve both performance and reliability. As weak error-correction codes have faster decoding speed than complex error correction codes (ECC), we propose the use of weak-ECC at the segment level rather than complex ECC. To compensate the reduced correction ability of weak-ECC, we use an erasure code that is striped across segments rather than pages or blocks. We use a small sized HDD to store parities so that we can leverage parallelism across multiple devices and remove the parity updates from the critical write path. We carry out simulation experiments based on Disksim to demonstrate that our proposed scheme is able reduce the SSD average read-latency by up to 31.23% and along with tolerance from double chip failures, it dramatically reduces the uncorrectable page error rate.

SPEK: a storage performance evaluation kernel module for block level storage systems

This paper introduces a new benchmark tool, SPEK (storage performance evaluation kernel module), for evaluating the performance of block-level storage systems in the presence of faults as well as under normal operations. SPEK can work on both direct attached storage (DAS) and block level networked storage systems such as storage area networks (SAN). Each SPEK consists of a controller, several workers, one or more probers, and several fault injection modules. Since it runs at kernel level and eliminates skews and overheads caused by file systems, SPEK is highly accurate and efficient. It allows a storage architect to generate configurable workloads to a system under test and to inject different faults into various system components such as network devices, storage devices, and controllers. Available performance measurements under different workloads and faulty conditions are dynamically collected and recorded in SPEK over a spectrum of time. To demonstrate its functionality, we apply SPEK to evaluate the performance of two direct attached storage systems and two typical SANs under Linux with different fault injections. Our experiments show that SPEK is highly efficient and accurate to measure performance for block-level storage systems.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.

A unified, low-overhead framework to support continuous profiling and optimization

We propose a unified, low-overhead framework (ULF) to support continuous system profiling and optimization based on a specifically designed embedded board. Instead of building a new profiling tool from scratch, ULF provides a unified interface to integrate various existing profiling tools and optimizers, and helps to build future tools easily. ULF uses an embedded processor to off-load tasks of post-processing profiling data, which reduces system overhead caused by profiling tools and makes ULF especially suitable for continuous profiling on production systems. By processing the profiling data in parallel and providing feedback promptly, ULF supports on-line optimization. Our case study on I/O profiling demonstrated that ULF-enhanced profiling tool dramatically reduces overhead, making continuous profiling on production systems feasible.