A software analysis tool for energy and time-aware function placement on the edge

Γιάννος, Γαβριηλίδης; Giannos, Gavriilidis

dc.contributor.author	Γιάννος, Γαβριηλίδης	el
dc.contributor.author	Giannos, Gavriilidis	en
dc.date.accessioned	2022-06-07T11:06:05Z
dc.date.available	2022-06-07T11:06:05Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/55253
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.22951
dc.rights	Default License
dc.subject	Διαχείριση πόρων	el
dc.subject	Κυβερνήτες	el
dc.subject	Ενορχήστρωση πακέτων	el
dc.subject	Διαδίκτυο των πραγμάτων	el
dc.subject	Μηχανική μάθηση	el
dc.subject	Resource management	en
dc.subject	Kubernetes	en
dc.subject	Container orchestration	en
dc.subject	Internet of things	en
dc.subject	Machine learning	en
dc.title	A software analysis tool for energy and time-aware function placement on the edge	en
heal.type	bachelorThesis
heal.classification	Computer science	en
heal.language	el
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2022-02-03
heal.abstract	In this thesis, we present a tool that proposes a way in which the individual functions of a monolithic code could run in a serverless environment, so that given a maximum runtime threshold, the minimum possible energy consumption in devices is achieved. These devices consist our serverless infrastructure (cluster), they are orchestrated by Kubernetes and the deployment of our code is managed by a scalable, fault-tolerant event-driven serverless platform called OpenFaaS. Our tool uses machine learning techniques for energy and time predictions and analyzes (profiles) the code file given in terms of memory allocation and the run-time required for each of its individual functions. The utilization of this information and the decision for the final proposal is achieved with the help of our self-developed minimization algorithm with approximate solution.	en
heal.advisorName	Σούντρης, Δημήτριος	el
heal.committeeMemberName	Τσανάκας, Παναγιώτης	el
heal.committeeMemberName	Πνευματικάτος, Διονύσιος	el
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών. Τομέας Τεχνολογίας Πληροφορικής και Υπολογιστών. Εργαστήριο Μικροϋπολογιστών και Ψηφιακών Συστημάτων VLSI	el
heal.academicPublisherID	ntua
heal.numberOfPages	96 σ.	el
heal.fullTextAvailability	false