scholarly journals RocksDB: Evolution of Development Priorities in a Key-value Store Serving Large-scale Applications

2021 ◽  
Vol 17 (4) ◽  
pp. 1-32
Author(s):  
Siying Dong ◽  
Andrew Kryczka ◽  
Yanqin Jin ◽  
Michael Stumm
Keyword(s):  
Large Scale ◽  
Future Research ◽  
Solid State Drives ◽  
Open Problems ◽  
Failure Handling ◽  
Data Formats ◽  
Data Corruption ◽  
Write Amplification ◽  
Protection Mechanisms ◽  
Integrity Protection

This article is an eight-year retrospective on development priorities for RocksDB, a key-value store developed at Facebook that targets large-scale distributed systems and that is optimized for Solid State Drives (SSDs). We describe how the priorities evolved over time as a result of hardware trends and extensive experiences running RocksDB at scale in production at a number of organizations: from optimizing write amplification, to space amplification, to CPU utilization. We describe lessons from running large-scale applications, including that resource allocation needs to be managed across different RocksDB instances, that data formats need to remain backward- and forward-compatible to allow incremental software rollouts, and that appropriate support for database replication and backups are needed. Lessons from failure handling taught us that data corruption errors needed to be detected earlier and that data integrity protection mechanisms are needed at every layer of the system. We describe improvements to the key-value interface. We describe a number of efforts that in retrospect proved to be misguided. Finally, we describe a number of open problems that could benefit from future research.

Flash-Based Storage Deduplication Techniques

2019 ◽  
Vol 10 (3) ◽  
pp. 32-48 ◽  
Author(s):  
Ilya A. Chernov ◽  
Evgeny Ivashko ◽  
Dmitry Kositsyn ◽  
Vadim Ponomarev ◽  
Alexander Rumyantsev ◽  
...  
Keyword(s):  
Experimental Comparison ◽  
Storage Device ◽  
Future Research ◽  
Data Deduplication ◽  
Solid State Drives ◽  
Open Problems ◽  
Storage Devices ◽  
Survey Paper ◽  
Active Research ◽  
High Level

Exponential growth of the amount of data stored worldwide together with high level of data redundancy motivates the active development of data deduplication techniques. The overall increasing popularity of solid-state drives (SSDs) as primary storage devices forces the adaptation of deduplication techniques to technical peculiarities of this type of storage (such as write amplification and wearout), implying active research in SSD-equipped storage data deduplication subdomain. In this survey paper the authors summarize the recent results on deduplication in SSD-enhanced storage, providing a novel taxonomy of the techniques. They classify the techniques on the basis of storage device complexity, starting from a sub-device level up to the storage network. Linux deduplication implementations are discussed, and the results of experimental comparison of several widely used tools are presented. Finally, the authors briefly outline open problems in the field and possible points of future research.

scholarly journals Structure-preserving deep learning

2021 ◽  
pp. 1-49
Author(s):  
E. CELLEDONI ◽  
M. J. EHRHARDT ◽  
C. ETMANN ◽  
R. I. MCLACHLAN ◽  
B. OWREN ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Large Scale ◽  
Computational Effort ◽  
Model Complexity ◽  
Future Research ◽  
Learning Methods ◽  
Open Problems ◽  
Mathematical Problems ◽  
Made In

Over the past few years, deep learning has risen to the foreground as a topic of massive interest, mainly as a result of successes obtained in solving large-scale image processing tasks. There are multiple challenging mathematical problems involved in applying deep learning: most deep learning methods require the solution of hard optimisation problems, and a good understanding of the trade-off between computational effort, amount of data and model complexity is required to successfully design a deep learning approach for a given problem.. A large amount of progress made in deep learning has been based on heuristic explorations, but there is a growing effort to mathematically understand the structure in existing deep learning methods and to systematically design new deep learning methods to preserve certain types of structure in deep learning. In this article, we review a number of these directions: some deep neural networks can be understood as discretisations of dynamical systems, neural networks can be designed to have desirable properties such as invertibility or group equivariance and new algorithmic frameworks based on conformal Hamiltonian systems and Riemannian manifolds to solve the optimisation problems have been proposed. We conclude our review of each of these topics by discussing some open problems that we consider to be interesting directions for future research.

Change of Attitude, Technology and Practice: Identifying the Change for Increased Value Creation with Customer Co-creation

2017 ◽  
Vol 5 (1) ◽  
pp. 70-82
Author(s):  
Soumi Paul ◽  
Paola Peretti ◽  
Saroj Kumar Datta
Keyword(s):  
Social Media ◽  
New Product Development ◽  
Value Creation ◽  
Large Scale ◽  
Customer Orientation ◽  
Customer Relationships ◽  
Future Research ◽  
Management Competencies ◽  
Business Decisions ◽  
Prime Concern

Building customer relationships and customer equity is the prime concern in today’s business decisions. The emergence of internet, especially social media like Facebook and Twitter, changed traditional marketing thought to a great extent. The importance of customer orientation is reflected in the axiom, “The customer is the king”. A good number of organizations are engaging customers in their new product development activities via social media platforms. Co-creation, a new perspective in which customers are active co-creators of the products they buy and use, is currently challenging the traditional paradigm. The concept of co-creation involving the customer’s knowledge, creativity and judgment to generate value is considered not only an upcoming trend that introduces new products or services but also fitting their need and increasing value for money. Knowledge and innovation are inseparable. Knowledge management competencies and capacities are essential to any organization that aspires to be distinguished and innovative. The present work is an attempt to identify the change in value creation procedure along with one area of business, where co-creation can return significant dividends. It is on extending the brand or brand category through brand extension or line extension. This article, through an in depth literature review analysis, identifies the changes in every perspective of this paradigm shift and it presents a conceptual model of company-customer-brand-based co-creation activity via social media. The main objective is offering an agenda for future research of this emerging trend and ensuring the way to move from theory to practice. The paper acts as a proposal; it allows the organization to go for this change in a large scale and obtain early feedback on the idea presented. 

Overview of Subsynchronous Oscillation in Grid-connected Wind Farm

2020 ◽  
Vol 13 (7) ◽  
pp. 969-979
Author(s):  
Xu Pei-Zhen ◽  
Lu Yong-Geng ◽  
Cao Xi-Min
Keyword(s):  
Power Systems ◽  
Wind Turbine ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Induction Generator ◽  
Future Research ◽  
Stable Operation ◽  
Subsynchronous Oscillation ◽  
Different Types

Background: Over the past few years, the subsynchronous oscillation (SSO) caused by the grid-connected wind farm had a bad influence on the stable operation of the system and has now become a bottleneck factor restricting the efficient utilization of wind power. How to mitigate and suppress the phenomenon of SSO of wind farms has become the focus of power system research. Methods: This paper first analyzes the SSO of different types of wind turbines, including squirrelcage induction generator based wind turbine (SCIG-WT), permanent magnet synchronous generator- based wind turbine (PMSG-WT), and doubly-fed induction generator based wind turbine (DFIG-WT). Then, the mechanisms of different types of SSO are proposed with the aim to better understand SSO in large-scale wind integrated power systems, and the main analytical methods suitable for studying the SSO of wind farms are summarized. Results: On the basis of results, using additional damping control suppression methods to solve SSO caused by the flexible power transmission devices and the wind turbine converter is recommended. Conclusion: The current development direction of the SSO of large-scale wind farm grid-connected systems is summarized and the current challenges and recommendations for future research and development are discussed.

scholarly journals ‘CTRL’: an online, Dynamic Consent and participant engagement platform working towards solving the complexities of consent in genomic research

2021 ◽  
Author(s):  
Matilda A. Haas ◽  
Harriet Teare ◽  
Megan Prictor ◽  
Gabi Ceregra ◽  
Miranda E. Vidgen ◽  
...  
Keyword(s):  
Large Scale ◽  
Genomic Medicine ◽  
International Standards ◽  
Security And Privacy ◽  
Genomic Research ◽  
Return Of Results ◽  
Future Research ◽  
Design And Development ◽  
Participant Engagement ◽  
Dynamic Consent

AbstractThe complexities of the informed consent process for participating in research in genomic medicine are well-documented. Inspired by the potential for Dynamic Consent to increase participant choice and autonomy in decision-making, as well as the opportunities for ongoing participant engagement it affords, we wanted to trial Dynamic Consent and to do so developed our own web-based application (web app) called CTRL (control). This paper documents the design and development of CTRL, for use in the Australian Genomics study: a health services research project building evidence to inform the integration of genomic medicine into mainstream healthcare. Australian Genomics brought together a multi-disciplinary team to develop CTRL. The design and development process considered user experience; security and privacy; the application of international standards in data sharing; IT, operational and ethical issues. The CTRL tool is now being offered to participants in the study, who can use CTRL to keep personal and contact details up to date; make consent choices (including indicate preferences for return of results and future research use of biological samples, genomic and health data); follow their progress through the study; complete surveys, contact the researchers and access study news and information. While there are remaining challenges to implementing Dynamic Consent in genomic research, this study demonstrates the feasibility of building such a tool, and its ongoing use will provide evidence about the value of Dynamic Consent in large-scale genomic research programs.

scholarly journals Cyberstalking Victimization Model Using Criminological Theory: A Systematic Literature Review, Taxonomies, Applications, Tools, and Validations

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1670
Author(s):  
Waheeb Abu-Ulbeh ◽  
Maryam Altalhi ◽  
Laith Abualigah ◽  
Abdulwahab Ali Almazroi ◽  
Putra Sumari ◽  
...  
Keyword(s):  
Data Analysis ◽  
Structural Equation ◽  
Large Scale ◽  
Review Paper ◽  
Essential Element ◽  
Routine Activities ◽  
Criminological Theory ◽  
Equation Modeling ◽  
Future Research ◽  
Proposed Model

Cyberstalking is a growing anti-social problem being transformed on a large scale and in various forms. Cyberstalking detection has become increasingly popular in recent years and has technically been investigated by many researchers. However, cyberstalking victimization, an essential part of cyberstalking, has empirically received less attention from the paper community. This paper attempts to address this gap and develop a model to understand and estimate the prevalence of cyberstalking victimization. The model of this paper is produced using routine activities and lifestyle exposure theories and includes eight hypotheses. The data of this paper is collected from the 757 respondents in Jordanian universities. This review paper utilizes a quantitative approach and uses structural equation modeling for data analysis. The results revealed a modest prevalence range is more dependent on the cyberstalking type. The results also indicated that proximity to motivated offenders, suitable targets, and digital guardians significantly influences cyberstalking victimization. The outcome from moderation hypothesis testing demonstrated that age and residence have a significant effect on cyberstalking victimization. The proposed model is an essential element for assessing cyberstalking victimization among societies, which provides a valuable understanding of the prevalence of cyberstalking victimization. This can assist the researchers and practitioners for future research in the context of cyberstalking victimization.

scholarly journals Climate Change Sustainability: From Bargaining to Cooperative Balanced Approach

Games ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 45
Author(s):  
Tiziana Ciano ◽  
Massimiliano Ferrara ◽  
Mariangela Gangemi ◽  
Domenica Stefania Merenda ◽  
Bruno Antonio Pansera
Keyword(s):  
Climate Change ◽  
Cooperative Game Theory ◽  
Research Field ◽  
Future Research ◽  
Open Problems ◽  
Cooperative Approach ◽  
Change Dynamics ◽  
Bargaining Solutions ◽  
Balanced Approach ◽  
Competitive Bargaining

This work aims to provide different perspectives on the relationships between cooperative game theory and the research field concerning climate change dynamics. New results are obtained in the framework of competitive bargaining solutions and related issues, moving from a cooperative approach to a competitive one. Furthermore, the dynamics of balanced and super-balanced games are exposed, with particular reference to coalitions. Some open problems are presented to aid future research in this area.

scholarly journals Large-Scale Object Monitoring in Internet-of-Things: Energy-Efficient Perspectives

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 461
Author(s):  
Yongbin Yim ◽  
Euisin Lee ◽  
Seungmin Oh
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Future Research ◽  
Technological Evolution ◽  
Node Density ◽  
Mobile Objects ◽  
Research Challenges ◽  
Energy Efficient Communication ◽  
Efficient Communication ◽  
Architectural Principles

Recently, the demand for monitoring a certain object covering large and dynamic scopes such as wildfires, glaciers, and radioactive contaminations, called large-scale fluid objects (LFOs), is coming to the fore due to disasters and catastrophes that lately happened. This article provides an analytic comparison of such LFOs and typical individual mobile objects (IMOs), namely animals, humans, vehicles, etc., to figure out inherent characteristics of LFOs. Since energy-efficient monitoring of IMOs has been intensively researched so far, but such inherent properties of LFOs hinder the direct adaptation of legacy technologies for IMOs, this article surveys technological evolution and advances of LFOs along with ones of IMOs. Based on the communication cost perspective correlated to energy efficiency, three technological phases, namely concentration, integration, and abbreviation, are defined in this article. By reviewing various methods and strategies employed by existing works with the three phases, this article concludes that LFO monitoring should achieve not only decoupling from node density and network structure but also trading off quantitative reduction against qualitative loss as architectural principles of energy-efficient communication to break through inherent properties of LFOs. Future research challenges related to this topic are also discussed.

scholarly journals Enhanced Wastewater Treatment by Immobilized Enzymes

2021 ◽  
Author(s):  
Jakub Zdarta ◽  
Katarzyna Jankowska ◽  
Karolina Bachosz ◽  
Oliwia Degórska ◽  
Karolina Kaźmierczak ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Process Optimization ◽  
Organic Pollutants ◽  
Large Scale ◽  
Removal Rate ◽  
Immobilized Enzymes ◽  
Future Research ◽  
Process Conditions ◽  
Removal Rates ◽  
Catalytic Cycles

Abstract Purpose of Review In the presented review, we have summarized recent achievements on the use of immobilized oxidoreductases for biodegradation of hazardous organic pollutants including mainly dyes, pharmaceuticals, phenols, and bisphenols. In order to facilitate process optimization and achievement of high removal rates, effect of various process conditions on biodegradation has been highlighted and discussed. Recent Findings Current reports clearly show that immobilized oxidoreductases are capable of efficient conversion of organic pollutants, usually reaching over 90% of removal rate. Further, immobilized enzymes showed great recyclability potential, allowing their reuse in numerous of catalytic cycles. Summary Collected data clearly indicates immobilized oxidoreductases as an efficient biocatalytic tools for removal of hazardous phenolic compounds, making them a promising option for future water purification. Data shows, however, that both immobilization and biodegradation conditions affect conversion efficiency; therefore, process optimization is required to achieve high removal rates. Nevertheless, we have demonstrated future trends and highlighted several issues that have to be solved in the near-future research, to facilitate large-scale application of the immobilized oxidoreductases in wastewater treatment.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

Sign in / Sign up

Export Citation Format

Share Document