Program of Graduate Studies | Science and Technology of Electrical and Computer Engineering |
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Subject Area | Software and Information Systems Technologies |
Semester | Fall |
Type | Elective |
ECTS | 7,5 |
Course Instructor |
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Scientific Responsible |
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Title | MLSysOps: Machine Learning for Autonomic System Operation in the Heterogeneous Edge-Cloud Continuum |
Duration | 2023 – 2025 |
Site | https://csl.e-ce.uth.gr/projects/mlsysops |
Department of Electrical and Computer Engineering | |
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Tel. | +30 24210 74967, +30 24210 74934 |
gece ΑΤ e-ce.uth.gr | |
PGS Tel. | +30 24210 74933 |
PGS e-mail | pgsec ΑΤ e-ce.uth.gr |
URL | https://www.e-ce.uth.gr/contact-info/?lang=en |
Program of Graduate Studies | Science and Technology of Electrical and Computer Engineering |
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Subject Area | Software and Information Systems Technologies |
Semester | Fall |
Type | Elective |
ECTS | 7,5 |
Course Instructor |
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The goal of this course is to provide an in-depth view of programming wireless sensor network systems. The following topics are covered: introduction to wireless sensor networks and applications, characteristics and limitations, approaches to self-organization and routing, key programming issues, survey of operating systems and middleware. The course is organized based on a series of assignments for the incremental development of a (simple) middleware with support for the dynamic installation, execution, communication and removal of applications written for a virtual machine that must be implemented as well. Programming is in TinyOS and NesC. Testing and demos are performed using the TOSSIM simulator as well as real Imote2 nodes in the lab. Also, each student presents to the class a research paper assigned by the instructor.