TITLE:
Managing Computing Infrastructure for IoT Data
AUTHORS:
Sapna Tyagi, Ashraf Darwish, Mohammad Yahiya Khan
KEYWORDS:
Big Data, Cloud Computing, Data Analytics, Elastic Scalability, Heterogeneous Computing, GPU, PCM, Massive Data Processing
JOURNAL NAME:
Advances in Internet of Things,
Vol.4 No.3,
July
29,
2014
ABSTRACT:
Digital data have become a torrent engulfing every area of business, science and engineering disciplines, gushing into every economy, every organization and every user of digital technology. In the age of big data, deriving values and insights from big data using rich analytics becomes important for achieving competitiveness, success and leadership in every field. The Internet of Things (IoT) is causing the number and types of products to emit data at an unprecedented rate. Heterogeneity, scale, timeliness, complexity, and privacy problems with large data impede progress at all phases of the pipeline that can create value from data issues. With the push of such massive data, we are entering a new era of computing driven by novel and ground breaking research innovation on elastic parallelism, partitioning and scalability. Designing a scalable system for analysing, processing and mining huge real world datasets has become one of the challenging problems facing both systems researchers and data management researchers. In this paper, we will give an overview of computing infrastructure for IoT data processing, focusing on architectural and major challenges of massive data. We will briefly discuss about emerging computing infrastructure and technologies that are promising for improving massive data management.