Contributions to Books:
H. Truong, S. Dustdar:
"Sustainability Data and Analytics in Cloud-Based M2M Systems";
in: "Big Data and Internet of Things: A Roadmap for Smart Environments, Volume 546, Series Title: Studies in Computational Intelligence",
N. Bessis, C. Dobre (ed.);
Springer International Publishing,
Recently, cloud computing technologies have been employed for largescale machine-to-machine (M2M) systems, as they could potentially offer better solutions for managing monitoring data of IoTs (Internet of Things) and supporting rich sets of IoT analytics applications for different stakeholders. However, there exist complex relationships between monitored objects, monitoring data, analytics
features, and stakeholders that require us to develop efficient ways to handle these complex relationships to support different business and data analytics processes in large-scale M2M systems. In this chapter, we analyze potential stakeholders and their complex relationships to data and analytics applications in M2M systems for
sustainability governance. Based on that we present techniques for supporting M2M data and process integration, including linking and managing monitored objects,sustainability monitoring data and analytics applications, for different stakeholders who are interested in dealingwith large-scalemonitoring data in M2M environments.
We present a cloud-based data analytics system for sustainability governance that includes a Platform-as-a-Service and an analytics framework. We also illustrate our prototype based on a real-world cloud system for facility monitoring and analytics
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Project Head Schahram Dustdar:
Cloud computing research lab
Created from the Publication Database of the Vienna University of Technology.