Abstract

The current global emphasis on "Internet of Things (IoT)" have highlighted the extreme importance of sensor-based intelligent and ubiquitous systems which are more commonly known as "cyber-physical systems." The technology has the potential to create a network of smart devices and things to an extent that has never been envisaged before, far outnumbering the number of devices connected in the Internet as we know today. The sheer number of such connected ubiquitous devices is likely to give rise to a hitherto unforeseen volume of data of different types with a demand for execution of analytical algorithms over the data. On the success of these analytic processes will depend the actual "smartness" of the "Intelligent Infrastructures" which now form the crux of the IoT paradigm. We have seen the advent of cloud-based paradigms to analyse the data in a data-parallel fashion within large data centres which now form the basis of the "big-data" problem. But apart from the servers in the data centres, we potentially have a huge pool of compute resources if we think about the smart devices in and around our homes collectively, which remain relatively idle. In this paper, we present a proposal with some emulated experimental results where we claim that in an IoT framework, the smart devices such as mobile phones, home gateways etc. can be utilised for execution of dataparallel analytic jobs. This is effectively a work-in-progress and it is acknowledged that there will be further challenges for real devices. Future research will attempt to consider these challenges.

Keywords

Computer scienceBig dataCloud computingInternet of ThingsData scienceAnalyticsServerUbiquitous computingComputer securityMobile deviceWorld Wide WebHuman–computer interactionData mining

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Publication Info

Year
2014
Type
article
Pages
565-570
Citations
62
Access
Closed

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Arijit Mukherjee, Himadri Sekhar Paul, S. Dey et al. (2014). ANGELS for distributed analytics in IoT. , 565-570. https://doi.org/10.1109/wf-iot.2014.6803230

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DOI
10.1109/wf-iot.2014.6803230