Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Autonomic Cloud Computing: Open Challenges and Architectural Elements

As Clouds are complex, large-scale, and heterogeneous distributed systems, management of their resources is a challenging task. They need automated and integrated intelligent strategies for provisioning of resources to offer services that are secure, reliable, and cost-efficient. Hence, effective management of services becomes fundamental in software platforms that constitute the fabric of computing Clouds. In this direction, this paper identifies open issues in autonomic resource provisioning and presents innovative management techniques for supporting SaaS applications hosted on Clouds. We present a conceptual architecture and early results evidencing the benefits of autonomic management of Clouds.Comment: 8 pages, 6 figures, conference keynote pape

Cloud Storage and Bioinformatics in a private cloud deployment: Lessons for Data Intensive research

This paper describes service portability for a private cloud deployment, including a detailed case study about Cloud Storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). Our Cloud Storage design and deployment is based on Storage Area Network (SAN) technologies, details of which include functionalities, technical implementation, architecture and user support. Experiments for data services (backup automation, data recovery and data migration) are performed and results confirm backup automation is completed swiftly and is reliable for data-intensive research. The data recovery result confirms that execution time is in proportion to quantity of recovered data, but the failure rate increases in an exponential manner. The data migration result confirms execution time is in proportion to disk volume of migrated data, but again the failure rate increases in an exponential manner. In addition, benefits of CCAF are illustrated using several bioinformatics examples such as tumour modelling, brain imaging, insulin molecules and simulations for medical training. Our Cloud Storage solution described here offers cost reduction, time-saving and user friendliness

Security aspects in cloud based condition monitoring of machine tools

In the modern competitive environments companies must have rapid production systems that are able to deliver parts that satisfy highest quality standards. Companies have also an increased need for advanced machines equipped with the latest technologies in maintenance to avoid any reduction or interruption of production. Eminent therefore is the need to monitor the health status of the manufacturing equipment in real time and thus try to develop diagnostic technologies for machine tools. This paper lays the foundation for the creation of a safe remote monitoring system for machine tools using a Cloud environment for communication between the customer and the maintenance service company. Cloud technology provides a convenient means for accessing maintenance data anywhere in the world accessible through simple devices such as PC, tablets or smartphones. In this context the safety aspects of a Cloud system for remote monitoring of machine tools becomes crucial and is, thus the focus of this pape

InterCloud: Utility-Oriented Federation of Cloud Computing Environments for Scaling of Application Services

Cloud computing providers have setup several data centers at different geographical locations over the Internet in order to optimally serve needs of their customers around the world. However, existing systems do not support mechanisms and policies for dynamically coordinating load distribution among different Cloud-based data centers in order to determine optimal location for hosting application services to achieve reasonable QoS levels. Further, the Cloud computing providers are unable to predict geographic distribution of users consuming their services, hence the load coordination must happen automatically, and distribution of services must change in response to changes in the load. To counter this problem, we advocate creation of federated Cloud computing environment (InterCloud) that facilitates just-in-time, opportunistic, and scalable provisioning of application services, consistently achieving QoS targets under variable workload, resource and network conditions. The overall goal is to create a computing environment that supports dynamic expansion or contraction of capabilities (VMs, services, storage, and database) for handling sudden variations in service demands. This paper presents vision, challenges, and architectural elements of InterCloud for utility-oriented federation of Cloud computing environments. The proposed InterCloud environment supports scaling of applications across multiple vendor clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that federated Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.Comment: 20 pages, 4 figures, 3 tables, conference pape