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The Second International Conference on Big Data, Small Data, Linked Data and Open Data ALLDATA 2016 February 21 - 25, 2016 - Lisbon, Portugal |
| Tutorials |
T1.
Statistical Methods for System Dependability: Reliability, Availability, Maintainability and Resiliency
Prof. Dr. Andy Snow, Ohio University, USA
Prof. Dr. Gary Weckman, Ohio University, USA
T2. Clouds and Security: A Scrutinized Marriage
Prof. Dr. Carlos Becker Westphall, Federal University of Santa Catarina, Brazil
Prof. Dr. Carla Merkle Westphall, Federal University of Santa Catarina, Brazil
T3. NoSQL Systems for Big Data Management
Prof. Dr. Venkat N. Gudivada, East Carolina University-Greenville, USA
Details
T1.
Statistical Methods for System Dependability: Reliability, Availability, Maintainability and Resiliency
Prof. Dr. Andy Snow, Ohio University, USA
Prof. Dr. Gary Weckman, Ohio University, USA
I. Overview
The goal of this tutorial is to provide attendees a working knowledge of the statistical methods used to assess complex system dependability. The dependability attributes reliability, availability, maintainability, and resiliency, are covered. Empirical techniques of assessing and forecasting these attributes are provided along with examples of using actual outage data.
II. List of Tutorial Modules and Content
- A. Hazards
- Threats (natural and manmade)
- Vulnerabilities
- Faults Taxonomy
- Service Outages
- Single Points of Failure
- Over-Concentration
- Risk as a f(Severity, Likelihood)
- Protection through fault prevention, tolerance, removal, and forecasting
- Best Practices
- B. Dependability Attributes: Reliability, Availability, Maintainability and Resiliency
- Point Processes:
- Homogeneous Poisson Process (HPP)
- Renewal Processes (RP)
- Branching Poisson Processes (BPP)
- Non-Homogenous Poisson Process (NHPP)
- Reliability – f (MTTF)
- Maintainability – f (MTTR)
- Availability – f ( MTTF, MTTR)
- Resiliency – f ( MTTF, MTTR, Severity)
- User and Service Provider Perspectives of Dependability
- C. Statistical Dependability Assessments & Forecasting
- Data Collection Requirements
- Outage Cause Classification and Analysis (trigger, direct, and root causes)
- Trend Assessments (Graphical, Laplace, Lewis-Robinson, Mil-Handbook tests)
- Poisson Regression, Simulation and Artificial Neural Networks
- IT and Telecom Case Studies
T2. Clouds and Security: A Scrutinized Marriage
Prof. Dr. Carlos Becker Westphall, Federal University of Santa Catarina, Brazil
Prof. Dr. Carla Merkle Westphall, Federal University of Santa Catarina, Brazil
- Introduction
- Motivation
- Cloud security challenges and problems
- Basic concepts
- Cloud computing
- Security
- Identity and access management
- Privacy
- Trust management and federations
- Related work and Technologies
- Research questions
- Research proposals
- Current Technologies
- Conclusion
T3. NoSQL Systems for Big Data Management
Prof. Dr. Venkat N. Gudivada, East Carolina University-Greenville, USA
Database Management Systems (DBMS) are the backbone of almost all software applications. Until recently, Relational Database Management Systems (RDBMS) have been the de facto standard for managing all types of data. They have been used regardless of whether or not a natural fit existed between RDBMS features and software applications requirements. However, during the last few years a credible challenge to the deeply entrenched RDBMS dominance was triggered by the special requirements Big Data applications. Over 90% of Big Data is non-relational and unstructured, and is unprecedented in scale and complexity. These events have brought to the fore the inadequacy of RDBMS in meeting the data management needs of Big Data applications.
To address the above needs, a bewildering array of new database management products have emerged in the last few years. They are referred to by various names including NoSQL, NewSQL, and non-RDBMS. Currently, there are over 250 such systems and new ones are introduced frequently. We classify them into the following broad categories: Relational, Column Relational, RDF Stores, Native XML, Object-oriented, Search Engines, Key-Value, Column-oriented, Document-oriented, Graph, NewSQL, CMS, Multivalue, and Navigational.
This two-hour tutorial will provide an overview of NoSQL systems and demonstrate solutions to three practical problems using Spark, MongoDB, and Neo4j. The tutorial is organized as:
Special needs of Big Data applications (10 min)
Technical Enablers of NoSQL Systems (10 min)
An Overview of NoSQL Systems (5 min)
Hadoop Ecosystem and Spark (30 min)
Break (5 min)
Document Databases -- MongoDB (30 min)
Graph Databases -- Neo4j (30 min)
Participants are encouraged to bring their laptop computers for hands-on exploration of Spark, MongoDB, and Neo4j.
