Heeseung Jo

A superblock-based flash translation layer for NAND flash memory

In NAND flash-based storage systems, an intermediate software layer called a flash translation layer (FTL)is usually employed to hide the erase-before-write characteristics of NAND flash memory. This paper proposes a novel superblockbased FTL scheme, which combines a set of adjacent logical blocks into a superblock. In the proposed FTL scheme, superblocks are mapped at coarse granularity,while pages inside the superblock are mapped freely at fine granularity to any location in several physical blocks. To reduce extra storage and flash memory operations, the fine-grain mapping information is stored in the spare area of NAND flash memory. This hybrid mapping technique has the flexibility provided by fine-grain address translation, while reducing the memory overhead to the level of coarse-grain address translation. Our experimental results show that the proposed FTL scheme decreases the garbage collection overhead up to 40% compared to previous FTL schemes.

FAB: flash-aware buffer management policy for portable media players

This paper presents a novel buffer management scheme for portable media players equipped with flash memory. Though flash memory has various advantages over magnetic disks such as small and lightweight form factor, solid-state reliability, low power consumption, and shock resistance, its physical characteristics imposes several limitations. Most notably, it takes relatively long time to write data in flash memory and the data cannot be overwritten before being erased first. Since an erase operation is performed as a unit of larger block, the employed strategy for mapping logical blocks onto physical pages affects real performance of flash memory. This article suggests a flash-aware buffer management scheme that reduces the number of erase operations by selecting a victim based on its page utilization rather than based on the traditional LRU policy. Our scheme effectively minimizes the number of write and erase operations in flash memory, reducing the total execution time by 17% compared to the LRU policy.

Task-aware virtual machine scheduling for I/O performance.

The use of virtualization is progressively accommodating diverse and unpredictable workloads as being adopted in virtual desktop and cloud computing environments. Since a virtual machine monitor lacks knowledge of each virtual machine, the unpredictableness of workloads makes resource allocation difficult. Particularly, virtual machine scheduling has a critical impact on I/O performance in cases where the virtual machine monitor is agnostic about the internal workloads of virtual machines. This paper presents a task-aware virtual machine scheduling mechanism based on inference techniques using gray-box knowledge. The proposed mechanism infers the I/O-boundness of guest-level tasks and correlates incoming events with I/O-bound tasks. With this information, we introduce partial boosting, which is a priority boosting mechanism with task-level granularity, so that an I/O-bound task is selectively scheduled to handle its incoming events promptly. Our technique focuses on improving the performance of I/O-bound tasks within heterogeneous workloads by lightweight mechanisms with complete CPU fairness among virtual machines. All implementation is confined to the virtualization layer based on the Xen virtual machine monitor and the credit scheduler. We evaluate our prototype in terms of I/O performance and CPU fairness over synthetic mixed workloads and realistic applications.

A group-based wear-leveling algorithm for large-capacity flash memory storage systems

Although NAND flash memory has become one of the most popular storage media for portable devices, it has a serious problem with respect to lifetime. Each block of NAND flash memory has a limited number of program/erase cycles, usually 10,000-100,000, and data in a block become unreliable after the limit. For this reason, distributing erase operations evenly across the whole flash memory media is an important concern in designing flash memory storage systems.In this paper, we propose a memory-efficient group-based wear-leveling algorithm. Our group-based algorithm achieves a small memory footprint by grouping several logically sequential blocks and managing only the summary information for each group. We also propose an effective group summary structure and a method to reduce unnecessary wear-leveling operations in order to enhance the wear-leveling performance. The evaluation results show that our group-based algorithm consumes only 8.75% of memory space compared to the previous scheme that manages per-block information, while showing roughly the same wear-leveling performance.

Superblock FTL: A superblock-based flash translation layer with a hybrid address translation scheme

In NAND flash-based storage systems, an intermediate software layer called a Flash Translation Layer (FTL) is usually employed to hide the erase-before-write characteristics of NAND flash memory. We propose a novel superblock-based FTL scheme, which combines a set of adjacent logical blocks into a superblock. In the proposed Superblock FTL, superblocks are mapped at coarse granularity, while pages inside the superblock are mapped freely at fine granularity to any location in several physical blocks. To reduce extra storage and flash memory operations, the fine-grain mapping information is stored in the spare area of NAND flash memory. This hybrid address translation scheme has the flexibility provided by fine-grain address translation, while reducing the memory overhead to the level of coarse-grain address translation. Our experimental results show that the proposed FTL scheme significantly outperforms previous block-mapped FTL schemes with roughly the same memory overhead.

Energy Reduction in Consolidated Servers through Memory-Aware Virtual Machine Scheduling

Increasing energy consumption in server consolidation environments leads to high maintenance costs for data centers. Main memory, no less than processor, is a major energy consumer in this environment. This paper proposes a technique for reducing memory energy consumption using virtual machine scheduling in multicore systems. We devise several heuristic scheduling algorithms by using a memory power simulator, which we designed and implemented. We also implement the biggest cover set first (BCSF) scheduling algorithm in the working server system. Through extensive simulation and implementation experiments, we observe the effectiveness of the memory-aware virtual machine scheduling in saving memory energy. In addition, we find out that power-aware memory management is essential to reduce the memory energy consumption.

XHive: Efficient Cooperative Caching for Virtual Machines

Since a virtual machine independently uses its own caching policy, redundant disk operations exacerbate the I/O virtualization overhead when virtual machines access large amounts of data on shared storage. This paper presents XHive, an efficient cooperative caching system that is implemented at the virtualization layer, for consolidated environments. Our proposed scheme globally manages buffer caches of consolidated virtual machines in order to accommodate a shared working set in machine memory. A singlet, which is a block cached solely by a virtual machine, is preferentially given more chances to be cached in machine memory by XHive, when it is evicted by a guest operating system. For efficient use of limited memory, singlets are cached in memory that is collaboratively donated from idle memory of virtual machines. Our evaluation shows that XHive significantly reduces disk I/O operations for shared working sets, thereby achieving high read performance and scalability. Improved scalability enables a high degree of workload consolidation with respect to virtual machines that have shared working sets.

SSD-HDD-hybrid virtual disk in consolidated environments

With the prevalence of multi-core processors and cloud computing, the server consolidation using virtualization has increasingly expanded its territory, and the degree of consolidation has also become higher. As a large number of virtual machines individually require their own disks, the storage capacity of a data center could be exceeded. To address this problem, copy-on-write storage systems allow virtual machines to initially share a template disk image. This paper proposes a hybrid copy-on-write storage system that combines solid-state disks and hard disk drives for consolidated environments. In order to take advantage of both devices, the proposed scheme places a read-only template disk image on a solid-state disk, while write operations are isolated to the hard disk drive. In this hybrid architecture, the disk I/O performance benefits from the fast read access of the solid-state disk, especially for random reads, precluding write operations from the degrading flash memory performance. We show that the hybrid virtual disk, in terms of performance and cost, is more effective than the pure copy-on-write disks for a highly consolidated system.

Transparently bridging semantic gap in CPU management for virtualized environments

Consolidated environments are progressively accommodating diverse and unpredictable workloads in conjunction with virtual desktop infrastructure and cloud computing. Unpredictable workloads, however, aggravate the semantic gap between the virtual machine monitor and guest operating systems, leading to inefficient resource management. In particular, CPU management for virtual machines has a critical impact on I/O performance in cases where the virtual machine monitor is agnostic about the internal workloads of each virtual machine. This paper presents virtual machine scheduling techniques for transparently bridging the semantic gap that is a result of consolidated workloads. To enable us to achieve this goal, we ensure that the virtual machine monitor is aware of task-level I/O-boundedness inside a virtual machine using inference techniques, thereby improving I/O performance without compromising CPU fairness. In addition, we address performance anomalies arising from the indirect use of I/O devices via a driver virtual machine at the scheduling level. The proposed techniques are implemented on the Xen virtual machine monitor and evaluated with micro-benchmarks and real workloads on Linux and Windows guest operating systems.

Transparent Fault Tolerance of Device Drivers for Virtual Machines

In a consolidated server system using virtualization, physical device accesses from guest virtual machines (VMs) need to be coordinated. In this environment, a separate driver VM is usually assigned to this task to enhance reliability and to reuse existing device drivers. This driver VM needs to be highly reliable, since it handles all the I/O requests. This paper describes a mechanism to detect and recover the driver VM from faults to enhance the reliability of the whole system. The proposed mechanism is transparent in that guest VMs cannot recognize the fault and the driver VM can recover and continue its I/O operations. Our mechanism provides a progress monitoring-based fault detection that is isolated from fault contamination with low monitoring overhead. When a fault occurs, the system recovers by switching the faulted driver VM to another one. The recovery is performed without service disconnection or data loss and with negligible delay by fully exploiting the I/O structure of the virtualized system.