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 Telecom Dsl

The amount of data in our world has shown exponential growth in recent years. This creates a very large collection of data sets –so called big data- in many organizations. Enterprises want to process their own big data to generate values from data to improve productivity innovation and customer relationship better than their competitors. However big data is so large and complex that it becomes difficult to process using traditional database management techniques. in this paper we present a system which can be used to analyses for big data of telecom industries. -- Abstract'tan.Son yıllarda dünyamızdaki veri miktarı katlanarak artmaktadır. Bu durum şirketler içerisinde büyük veri olarak adlandırılan yapıların ortaya çıkmasına neden olmaktadır. Günümüz şirketleri rakiplerinin önüne geçebilmek adına gerekli olan verimlilik, yenilik ve müşteri ilişkileri gibi analiz sonuçlarını kendi bünyelerinde bulunan verileri işleyerek elde etmek isterler. Ancak büyük veri gerçek anlamda çok büyük ve karmaşık olduğundan ötürü geneleksel veri yönetim sistemleri ile işlenmesi imkansız denecek kadar zordur. Bu çalışmada size telekom firmaları için geliştirilmiş olan büyük veri sistemini sunacağız. Sistemimiz üç ana bölümden oluşmaktadır: DSL adı verilen Telekom alanına özgü bir dil, Map Reduce programlama modeli içeren paralel programlama platform ve sonuçların kullanıcıya sunulduğu bir arayüz. Bu üç ana bölüm birbirleri ile dağıtık dosya tanımlayıcısı olarak adlandırdığımız -DFD- framework?ü kullanarak haberleşmektedir. Önermiş olduğumuz DSL çözümümüz telekom firmalarına özgü telefon kayıtları, ağ kayıtları, link analizleri gibi verilerin paralel olarak işlenmesine olanak sağlar. Ayrıca veri merkezinde dağıtık yapıda bulanan cihazlar üzerinde işlemlerin paralel olarak çözümlenmesini sağlar. Web tabanlı sonuç gösterim ara yüzü ile işlenen verilerin efektif olarak gösterilmesi amaçlanmıştır. Tanımlamış olduğumuz DSL dili, SQL dilinden oldukça basit bir dildir. Kullanıcının dosyalar üzerinde herhangi bir paralel işlem yaptırması için Map Reduce tekniklerini içeren C, Java gibi kodları yazmasına gerek olmamaktadır. Aynı dil ile sonuç gösterimini kullanmak mümkündür

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. hi 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.UNC Charlotte; Eastern Mediterranean Univ; IEEE; IEEE Commun Soc; NUS

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