Towards a data‐driven IoT software architecture for smart city utilities. (10th April 2018)

• Record Type: Journal Article
• Authors: Simmhan, Yogesh; Ravindra, Pushkara; Chaturvedi, Shilpa; Hegde, Malati; Ballamajalu, Rashmi
• Is Part Of: Software, practice & experience. Volume 48:Number 7(2018)
• Page Start: 1390
• Page End: 1416
• Publication Date: 2018-04-10
• Subjects: big data platforms -- cloud computing -- information integration -- Internet of things -- smart cities -- stream processing -- wireless sensor networks; Computer software -- Periodicals; Computer programming -- Periodicals; Computer programs -- Periodicals; 005.3
• DOI: 10.1002/spe.2580
• Languages: English
• ISSNs: 0038-0644

Abstract

Summary: The Internet of things (IoT) is emerging as the next big wave of digital presence for billions of devices on the Internet. Smart cities are a practical manifestation of IoT, with the goal of efficient, reliable, and safe delivery of city utilities like water, power, and transport to residents, through their intelligent management. A data‐driven IoT software platform is essential for realizing manageable and sustainable smart utilities and for novel applications to be developed upon them. Here, we propose such service‐oriented software architecture to address 2 key operational activities in a smart utility: the IoT fabric for resource management and the data and application platform for decision‐making . Our design uses Open Web standards and evolving network protocols, cloud and edge resources, and streaming big data platforms. We motivate our design requirements using the smart water management domain; some of these requirements are unique to developing nations. We also validate the architecture within a campus‐scale IoT testbed at the Indian Institute of Science, Bangalore and present our experiences. Our architecture is scalable to a township or city while also generalizable to other smart utility domains. Our experiences serve as a template for other similar efforts, particularly in emerging markets and highlight the gaps and opportunities for a data‐driven IoT software architecture for smart cities.