Solid-state drives (SSDs) are widely used in cloud storage. As the capacity of an SSD has been increasing, it has become common for many virtual machines (VMs) to share a single SSD to maximize resource utilization. However, this sharing can degrade the efficiency of internal operations, such as garbage collection, resulting in increased latencies. Existing literature in this field has mostly focused on interdevice isolation considering the storage device as a black-box entity or presumed an SSD to be shared by up to only eight VMs. In this study, we first analyze a realistic SSD usage environment in cloud systems and identify that block-level data isolation (BDI) should be guaranteed to efficiently scale up the number of VMs in an SSD with minimum latency increases. However, previous schemes cannot work efficiently with BDI when the SSD is shared by dozens of VMs. Based on this analysis, we propose an SSD internal resource management scheme in a cloud environment, called highly VM-scalable SSD (VMS). VMS dynamically partitions physical resources and allocates them to VMs, while the VMs share global buffer blocks to lower latency during abrupt fluctuations of write I/O intensities. Our experimental results show up to 29% of latency reduction. VMS exhibits reduced latencies even in the experiment with 64 VMs, where existing schemes do not function normally.

Recent NAND flash memories provide a partial read operation that can read a page partially and has lower latency than a normal read operation. In order to maximize the benefit of the partial read operation, compression techniques can be applied to improve performance by generating additional partial page requests by compressing pages into smaller ones. Unfortunately, existing compression support SSDs suffer from a huge decompression latency that eventually cancels the benefit of the partial read operation. In this paper, we propose Partial Read-aware SSD (PR-SSD) for fully exploiting partial read operations. In order to mitigate the decompression latency, we propose a new compression algorithm, called Dominant Pattern Compression (DPC), which has extremely low decompression latency. Because uncompressed page requests cannot exploit the partial read operation, we propose split Flash Translation Layer (FTL) that can split the requests into smaller ones and allocate them to different channels for exploiting channel-level parallelism in SSD. Experimental results reveal that PR-SSD can reduce the read response time by 18% on average and also the number of writes and write response time by 29% and 24% on average, respectively

Recent research has revealed that runtime bad blocks are found in the early lifespan of solid state drives. The reduction in overprovisioning space due to runtime bad blocks may well have a negative impact on performance as it weakens the chances of selecting a better victim block during garbage collection. Moreover, previous studies focused on reusing worn-out bad blocks exceeding a program/erase cycle threshold, leaving the problem of runtime bad blocks unaddressed. Based on this observation, we present a salvation scheme for runtime bad blocks. This paper reveals that these blocks can be identified when a page write fails at runtime. Furthermore, we introduce a method to salvage functioning pages from runtime bad blocks. Consequently, the loss in the overprovisioning space can be minimized even after the occurrence of runtime bad blocks. Experimental results show a 26.3% reduction in latency and a 25.6% increase in throughput compared to the baseline at a conservative bad block ratio of 0.45%. Additionally, our results confirm that almost no overhead was observed.

As higher memory bandwidth is required for data-intensive environments, memory compression can be a simple but effective solution to increase memory bandwidth. However, previous intra-block compression techniques do not provide sufficient bandwidth improvement owing to the incompressibility of blocks with diverse data while previous inter-block compression techniques suffer from huge additional memory access overheads or low compression coverages. To overcome the limitations of the previous intra-and inter-block compression techniques, we leverage both the naturally observed low-entropy among blocks and the artificially generated low-entropy resulting from our optimization techniques. Based on these two low-entropies, we propose an Entropy-based Pattern Compression (EPC), which generates an inter-block pattern from the same low-entropy region in numerous blocks and then compresses these blocks by using the selected pattern. Our evaluations show that EPC achieves up to 13% (3% on average) higher speedup and 13% (4% on average) DRAM energy consumption reduction with 160x (20x on average) fewer patterns(groups) compared to the state-of-the-art inter-block compression technique.

Online sales can be influenced significantly by customer reviews, and thus there are several studies on what makes an online review helpful to consumers. However, none of those researches address the review helpfulness in the context of hedonic and utilitarian review types. This study examines how product type (hedonic and utilitarian) moderates the relationship between the level of review type (hedonicity and utilitarianity) and review helpfulness. To test the moderating effects, customer review data for perfume and bar soap product was collected from Amazon.com and analyzed by using a text-mining tool (QDA Miner) and a structural equation modeling software (AMOS 22.0). The results of this study indicate that the product type moderates the impact of the review type on review helpfulness when product type and review type are incongruent. Further, results show that the number of sentences in a customer review affects the review helpfulness when product type is utilitarian.

The increased flash page sizes cause a large number of subpage requests due to the difference in host and flash I/O units. The subpage requests may degrade the space utilization, response time, and lifetime of NAND flash memories. Addressing the subpage issue, a few studies in the past have proposed merging subpages to generate full pages. Although these subpage schemes may improve performance and lifetime, they incur immense DRAM space for storing the sector information of merged pages. Moreover, they do not consider the update frequencies of the subpages for merging and thus an update request to a subpage causes partial page invalidation, which leads to garbage collection (GC) overhead. To address these issues, our proposed scheme considers the update frequencies of the subpages for merging in order to avoid partial page invalidation, which in turn improves the GC efficiency. Further, the proposed scheme uses a sector information table (SIT) in flash pages to store the fine-grained sector information of merged subpages. In the light of experiment results, our scheme, on average, reduces DRAM footprint, flash writes, and block erasures by 29%, 18%, and 13%, respectively.

A solid state drive (SSD) receives requests in multiple of sectors from the host system, which are then mapped to logical pages, the basic I/O units of the flash memory. As the SSD receives requests in sector units, the sectors in a logical page tend to exhibit diverse update frequencies. Therefore, frequent updates to some sectors of a page cause other sectors of the same page to be unnecessarily read and written to other free pages, thereby increasing write amplification and harming the flash memory lifetime. To eliminate unnecessary sector movement and to reduce write amplification, we propose a sector-level classification (SLC) technique. SLC considers the diversity in the update frequencies of sectors and merges sectors with similar update frequencies to generate full, homogeneous pages. Thus, multiple update operations can be converged to a single flash page, thereby reducing write amplification and increasing flash memory lifetime. SLC handles the merged sectors using the proposed shared-page mapping table (SMT), whereas pages whose sectors remain unmerged are handled by a conventional page mapping table. Despite the SMT overhead, SLC does not require excessive resources to accommodate SMT. The capability of SLC is evaluated by a series of experiments, which provides highly encouraging results. It is demonstrated that SLC reduces flash writes, flash reads, block erasures, and flash writes execution time by 42%, 23%, 45%, and 37%, respectively.

During the past decade, the endurance of NAND flash memory has severely deteriorated. The maximum number of program and erase cycles has fallen significantly with emerging of multilevel cell (MLC) and triple-level cell (TLC) technology, and scaling down of the cell size. Wear leveling is a general solution used to alleviate this issue; it enables cells to wear down evenly but it cannot actually mitigate the wearing of the cells. Accordingly, techniques are required to minimize the actual cell degradation. This paper proposesendurance-enhancing lower state encoding. The key insight leveraged by the proposed technique is the data pattern-related characteristic of MLC and TLC NAND flash memories, in which the lower the state of the cells, the lower the occurrence of wear out. Thus, our proposed scheme encodes input data to make the cell state as low as possible in consideration of interpage relation. As a result, the wear out of the memory cells can be minimized and their lifetime is improved by 62.7% in a file type and 43.0% in MySQL. Experimental results indicate that our scheme shows better lifetime improvement than other schemes in most cases.

The manufacturers of NAND flash-based solid-state drives (SSDs) are increasing capacity and throughput by enlarging their page size, which is the minimum I/O unit in the NAND flash chips. Because the host and NAND flash chips have different I/O granularity units, the number of subpage requests increases. However, these subpage requests, especially writes, can cause internal fragmentation and endurance problems. Furthermore, subpage write requests inevitably involve read-modify-write (RMW) operations that increase the write response time because of the out-place-update feature in the NAND flash chips. In this paper, we propose a subpage-aware SSD to increase the lifetime and performance by reducing the number of NAND writes and eliminating unnecessary RMW operations. Our scheme attempts to merge subpage write requests to full page write requests in the write buffer to reduce the number of NAND writes and adds size information to the mapping table to detect unnecessary RMW operations. Our proposed scheme reduces the number of NAND writes by up to 30 and 19 percent on average and the write response time by up to 22 and 13 percent on average.

Most studies on user aggression in virtual worlds have mainly focused on the causes of aggressive behaviour, but only a few have focused on the factors that relieve it. This study was conducted to determine the causes of aggression relaxation and aggravation in virtual worlds, using an approach that significantly differs from that used in previous research. We examined the mechanisms that affect aggravation and relaxation of virtual aggression, and suggested ways to resolve problems with aggression. A survey was conducted with 112 Second Life users to examine how commitment, belief, avatar attachment, desensitisation, and addiction were related to self-control and control disorder, and how the two latter factors affected virtual aggression. The survey also examined how virtual aggression influenced the intention for attacking behaviour in the real world. The results showed that (1) belief is a positive predictor of self-control, which has a negative impact on virtual aggression, (2) addiction is a positive predictor of control disorder, and (3) anger in virtual worlds is significantly connected to aggression in the real world.

Computational models which symbolically represent the abstraction of reality on computers, have won popularity as research tools in organizational studies. However, very few, if any computational models have been used to test theories in the same ways that human experiments generally do. The author introduces a simulation experiment using a computational model of team called "Team-Soar," which mimics a human team experiment that was performed to test a theory of team decision making. The results support the major propositions of the multilevel theory in the same fashion as the ones of the human team experiment. The simulation experiment displays the Team-Soar model's effectiveness as a theory prover.