Where did my 256 GB go? A Measurement Analysis of Storage Consumption on Smart Mobile Devices

This work presents the first-ever detailed and large-scale measurement analysis of storage consumption behavior of applications (apps) on smart mobile devices. We start by carrying out a five-year longitudinal static analysis of millions of Android apps to study the increase in their sizes over time and identify various sources of app storage consumption. Our study reveals that mobile apps have evolved as large monolithic packages that are packed with features to monetize/engage users and optimized for performance at the cost of redundant storage consumption. We also carry out a mobile storage usage study with 140 Android participants. We built and deployed a lightweight context-aware storage tracing tool, called cosmos, on each participant's device. Leveraging the traces from our user study, we show that only a small fraction of apps/features are actively used and usage is correlated to user context. Our findings suggest a high degree of app feature bloat and unused functionality, which leads to inefficient use of storage. Furthermore, we found that apps are not constrained by storage quota limits, and developers freely abuse persistent storage by frequently caching data, creating debug logs, user analytics, and downloading advertisements as needed. Finally, drawing upon our findings, we discuss the need for efficient mobile storage management, and propose an elastic storage design to reclaim storage space when unused. We further identify research challenges and quantify expected storage savings from such a design. We believe our findings will be valuable to the storage research community as well as mobile app developers.

RAID Level 6 and Level 6+ Reliability

Storage systems are built of fallible components but have to provide high degrees of reliability. Besides mirroring and triplicating data, redundant storage of information using erasure-correcting codes is the only possibility to have data survive device failure. We provide here exact formula for the data-loss probability of a disk array composed of several RAID Level 6 stripes. This two-failure tolerant is not only used in practice but can also provide a reference point for the assessment of other data organizations

Broom: Application for non-redundant storage of High Throughput Sequencing data

MotivationThe data generation capabilities of High Throughput Sequencing (HTS) instruments have exponentially increased over the last few years, while the cost of sequencing has dramatically decreased allowing this technology to become widely used in biomedical studies. For small labs and individual researchers, however, storage and transfer of large amounts of HTS data present a significant challenge. The recent trends in increased sequencing quality and genome coverage can be used to reconsider HTS data storage strategies.ResultsWe present Broom, a stand-alone application designed to select and store only high-quality sequencing reads at extremely high compression rates. Written in C++, the application accepts single and paired-end reads in FASTQ and FASTA formats and decompresses data in FASTA format.AvailabilityC++ code available at https://scsb.utmb.edu/labgroups/fofanov/[email protected]

Building an Open Data Repository for a Specialized Research Community: Process, Challenges and Lessons

In 2009, the Institution for Social and Policy Studies (ISPS) at Yale University began building an open access digital collection of social science experimental data, metadata, and associated files produced by ISPS researchers. The digital repository was created to support the replication of research findings and to enable further data analysis and instruction. Content is submitted to a rigorous process of quality assessment and normalization, including transformation of statistical code into R, an open source statistical software. Other requirements included: (a) that the repository be integrated with the current database of publications and projects publicly available on the ISPS website; (b) that it offered open access to datasets, documentation, and statistical software program files; (c) that it utilized persistent linking services and redundant storage provided within the Yale Digital Commons infrastructure; and (d) that it operated in accordance with the prevailing standards of the digital preservation community. In partnership with Yale’s Office of Digital Assets and Infrastructure (ODAI), the ISPS Data Archive was launched in the fall of 2010. We describe the process of creating the repository, discuss prospects for similar projects in the future, and explain how this specialized repository fits into the larger digital landscape at Yale.

NORMALIZATION IN TYPE-2 FUZZY RELATIONAL DATA MODEL BASED ON FUZZY FUNCTIONAL DEPENDENCY USING FUZZY FUNCTIONS

In fuzzy relational databases, the data dependencies, especially the fuzzy functional dependency(ffd) plays an important role in maintaining the consistency of the database and in avoiding the redundant storage of the data. In the past, it has been shown that the type-2 fuzzy relational databases captures impreciseness and incompleteness in data in a better way. The aim of this paper is to provide the concepts for database normalization in a type-2 fuzzy relational database, so that the normalized schemas can be obtained. Here, we deal with the fuzzy functional dependency(ffd) based normalization of type-2 fuzzy relational databases. We use the concepts of fuzzy functions to derive the fuzzy equality and using this fuzzy equality, we define a new definition of fuzzy functional dependency. First we discuss various approaches proposed by the researchers in this context and show why our fuzzy functional dependency is better, as compared to the earlier ffds proposed by the researchers. We call our ffd as non-0 LHS ffd. We identify an anomaly called "spurious ffd" and show that some of the significant contributions proposed by the earlier researchers are suffering from this anomaly, but the non-0 LHS ffd does not suffer from it. Then, we prove that the set of inference rules for the non-0 LHS ffd are sound and complete. We use the definition of non-0 LHS ffd in obtaining the first three normal forms upto BCNF for type-1 and type-2 fuzzy relational schemas. The result of the decomposition and the procedure to obtain the membership value of the decomposed relations is proposed. The associated concepts like the fuzzy key, fuzzy superkey, fuzzy foreign key are defined in terms of non-0 LHS ffd. On the basis of these concepts, we define full ffd, partial ffd etc. In the last, we show that in our case, the relationship of total-ordering between the three normal forms in classical relational databases is also observed.

Spatial Access Method for Flash Memory Embedded Systems

This paper proposed an efficient spatial Access method, called MDR-Tree (Mbr compression and Delayed write operation based R-Tree), that uses the node compression technique and the delayed write operation technique for flash memory embedded systems. The node compression technique of MDR-Tree increased the utilization of flash memory space by compressing the MBR of spatial data using relative coordinates and MBR size. Moreover, the delayed write operation technique reduced the number of write operations in flash memory by temporarily storing spatial data in the buffer and by reflecting them in flash memory at once instead of reflecting the insert, update and delete of spatial data in flash memory for each operation. Especially, the utilization of buffer space was enhanced by preventing the redundant storage of the same spatial data in the buffer.