A network approach for managing and processing big cancer data in clouds

Translational cancer research requires integrative analysis of multiple levels of big cancer data to identify and treat cancer. In order to address the issues that data is decentralised, growing and continually being updated, and the content living or archiving on different information sources partially overlaps creating redundancies as well as contradictions and inconsistencies, we develop a data network model and technology for constructing and managing big cancer data. To support our data network approach for data process and analysis, we employ a semantic content network approach and adopt the CELAR cloud platform. The prototype implementation shows that the CELAR cloud can satisfy the on-demanding needs of various data resources for management and process of big cancer data

Designing a Modern Software Engineering Training Program with Cloud Computing

The software engineering industry is trending towards cloud computing. For our project, we assessed the various tools and practices used in modern software development. The main goals of this project were to create a reference model for developing cloud-based applications, to program a functional cloud-based prototype, and to develop an accompanying training manual. These materials will be incorporated into the software engineering courses at WPI, namely CS 3733 and CS 509

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

Security Implications of Adopting a New Data Storage and Access Model in Big Data and Cloud Computing

This article examines the security implications of using cloud computing and Big Data. It employs a mixed methodology of qualitative and quantitative research and takes a critical realist epistemological approach. The objective is to identify the components of a theory for predicting and explaining [1, 4] the security implications associated with adopting the services provided by cloud computing and Big Data. The integration of various information sources and the widespread use of computing across diverse fields have resulted in a significant increase in data volume, scale, quantity, and diversity. Consequently, data management, storage, retrieval, and access have undergone significant changes. The latest developments in IT have brought forth novel technologies such as Cloud Computing and Big Data. Big Data comprises of technologies that rely on NoSQL (Not only SQL) databases, which enable the growth of data volumes, numbers, and types on a large scale. The new NoSQL systems are seen as solutions for meeting scalability requirements of large IT firms. Multiple open-source and pay-as-you-go NoSQL models are available for purchase