Big Data Analytics for Wireless and Wired Network Design: A Survey

Currently, the world is witnessing a mounting avalanche of data due to the increasing number of mobile network subscribers, Internet websites, and online services. This trend is continuing to develop in a quick and diverse manner in the form of big data. Big data analytics can process large amounts of raw data and extract useful, smaller-sized information, which can be used by different parties to make reliable decisions. In this paper, we conduct a survey on the role that big data analytics can play in the design of data communication networks. Integrating the latest advances that employ big data analytics with the networks’ control/traffic layers might be the best way to build robust data communication networks with refined performance and intelligent features. First, the survey starts with the introduction of the big data basic concepts, framework, and characteristics. Second, we illustrate the main network design cycle employing big data analytics. This cycle represents the umbrella concept that unifies the surveyed topics. Third, there is a detailed review of the current academic and industrial efforts toward network design using big data analytics. Forth, we identify the challenges confronting the utilization of big data analytics in network design. Finally, we highlight several future research directions. To the best of our knowledge, this is the first survey that addresses the use of big data analytics techniques for the design of a broad range of networks

Big Data Platform Development With a Domain Specific Language for Telecom Industries

This paper introduces a system that offer a special big data analysis platform with Domain Specific Language for telecom industries. This platform has three main parts that suggests a new kind of domain specific system for processing and visualization of large data files for telecom organizations. These parts are Domain Specific Language (DSL), Parallel Processing/Analyzing Platform for Big Data and an Integrated Result Viewer. In addition to these main parts, Distributed File Descriptor (DFD) is designed for passing information between these modules and organizing communication. To find out benefits of this domain specific solution, standard framework of big data concept is examined carefully. Big data concept has special infrastructure and tools to perform for data storing, processing, analyzing operations. This infrastructure can be grouped as four different parts, these are infrastructure, programming models, high performance schema free databases, and processing-analyzing. Although there are lots of advantages of Big Data concept, it is still very difficult to manage these systems for many enterprises. Therefore, this study suggest a new higher level language, called as DSL which helps enterprises to process big data without writing any complex low level traditional parallel processing codes, a new kind of result viewer and this paper also presents a Big Data solution system that is called Petaminer. © 2013 IEEE