Lookup NU author(s): Peter Michalák,
Professor Paul Watson
This is the authors' accepted manuscript of a conference proceedings (inc. abstract) that has been published in its final definitive form by IEEE, 2017.
For re-use rights please refer to the publisher's terms and conditions.
Abstract—The PATH2iot open-source platform presents a new approach to stream processing for Internet of Things applications by automatically partitioning and deploying the computation over the available infrastructure (e.g. cloud, field gateways and sensors) in order to meet non-functional requirements including energy, performance and security. The user gives a high-level declarative description of computation in the form of Event Processing Language queries. These are compiled, optimised,and partitioned to meet the non-functional requirements using database system techniques and cost models extended to meet theneeds of IoT analytics. The paper describes the PATH2iot system, illustrated by a real-world digital healthcare analytics example, with sensor battery life as the main non-functional requirement to be optimised. It shows that the tool can automatically partitionand distribute the computation across a healthcare wearable,a mobile phone and the cloud - increasing the battery life of the smart watch by 416% when compared to other possible allocations. The PATH2iot system can therefore automatically bring the benefits of fog/edge computing to IoT applications.
Author(s): Michalák P, Watson P
Publication type: Conference Proceedings (inc. Abstract)
Publication status: Published
Conference Name: 9th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2017)
Year of Conference: 2017
Online publication date: 28/12/2017
Acceptance date: 07/10/2017
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