Executing a mobile application using the cloud resources to achieve a higher performance metric than what can be achieved with mobile computing alone (e.g., application response time).
Published in Chapter:
Accessing Big Data in the Cloud Using Mobile Devices
Haoliang Wang (George Mason University, USA), Wei Liu (University of Rochester, USA), and
Tolga Soyata (University of Rochester, USA)
Copyright: © 2014
|Pages: 27
DOI: 10.4018/978-1-4666-5864-6.ch018
Abstract
The amount of data acquired, stored, and processed annually over the Internet has exceeded the processing capabilities of modern computer systems, including supercomputers with multiple-Petaflop processing power, giving rise to the term Big Data. Continuous research efforts to implement systems to cope with this insurmountable amount of data are underway. The authors introduce the ongoing research in three different facets: 1) in the Acquisition front, they introduce a concept that has come to the forefront in the past few years: Internet-of-Things (IoT), which will be one of the major sources for Big Data generation in the following decades. The authors provide a brief survey of IoT to understand the concept and the ongoing research in this field. 2) In the Cloud Storage and Processing front, they provide a survey of techniques to efficiently store the acquired Big Data in the cloud, index it, and get it ready for processing. While IoT relates primarily to sensor nodes and thin devices, the authors study this storage and processing aspect of Big Data within the framework of Cloud Computing. 3) In the Mobile Access front, they perform a survey of existing infrastructures to access the Big Data efficiently via mobile devices. This survey also includes intermediate devices, such as a Cloudlet, to accelerate the Big Data collection from IoT and access to Big Data for applications that require response times that are close to real-time.