Prerequisites for Participation

• Knowledge of Algorithmics.
• Fundamentals of Distributed Systems and Networks.

Intended Learning Outcomes

Students who have successfully finished this module will will have quite good knowledges on specific problems and protocoles related to Autonomic Networks, namely:

• Sensor Networks (routing, overlays, architectures, etc)
• Delay-Tolerant Network
• Mobility Tolerance
• Active/Passive Mobility / Robot Networks
• Fault Tolerance in Dynamic Distributed Networks
• Self-* Properties

Content

Module ANET (Autonomic NETworks) covers main scientific and technological issues of autonomous and ubiquitous networks. Principles, techniques, and examples related to the design of such networks are introduced, sometimes through similarities and differences with classical networks.  Various aspects of self-* attributes are discussed, such as self-stabilization, self-configuration, self-organization, self-management, self-optimization, self-adaptiveness, etc.  Passive mobility and proactive mobility are addressed and applied to networks in general and more specifically, to sensor networks, swarms of robots, MANET, and VANET.

Teaching and Learning Methods

• 2h weekly hours lecture
• 2h weekly hours integrated interactive tutorials (problem solving, assignments discussion, lab sessions)

Assessment and Grading Procedures

Paper review (20%), Labs/Practical class reports (20%), and Final written exam (60%)

Workload calculation (contact hours, homework, exam preparation,..)

• 4h weekly contact hours x 14 weeks = 56 h
• 5h weekly hours preparation and afterwork x 14 weeks = 70 h
• Exams preparation: 24h
• Total: 150 h

Frequency and dates

Offered every Fall semester:

• Classes start mid-September and end end-January;
• Final exam at the beginning of February;
• Makeup exam for those who failed the first session in next September.

Max. Number of Participants

30

Enrolment Procedures

Request to the head of CNI program

Recommended Reading, Course Material

• Algorithms for Sensor and Ad Hoc Networks: Advanced Lectures. D. Wagner and R. Wattenhofer (Eds.), Springer-Verlag, 2007.
  
• Fundamentals of Wireless Sensor Networks: Theory and Practice. W. Dargie and C. Poellabauer, Wiley, 2011.
  
• Handbook of Sensor Networks: Algorithms and Architectures. I. Stojmenovic, Wiley, 2005.
  
• Wireless Sensor Networks: Technology, Protocols, and Applications. K. Sohraby, D. Minoli, and T. Znati, Willey, 2007.
  
• Distributed Computing by Mobile Entities: Current Research in Moving and Computing.  P.Flocchini, G. Prencipe, and N. Santoro, Lecture Notes in Computer Science Book 11340, Springer.
  
• Introduction to Distributed Self-Stabilizing Algorithms. Karine Altisen, Stéphane Devismes, Swan Dubois, and Franck Petit. Synthesis Lectures on Distributed Computing Theory, Morgan & Claypool Publishers, 2019.
  
• Distributed Computing: a locality sensitive approach. D. Peleg, Siam Monographs, 2000.