Nature-inspired Coordination for Complex Distributed Systems 2013/2014


Originating from closed parallel systems, coordination models and technologies gained in expressive power so to deal with complex distributed systems. In particular, nature-inspired models of coordination emerged in the last decade as the most effective approaches to tackle the complexity of pervasive, intelligent, and self-* systems. In this course we first introduce the basic notions of coordination and coordination model, survey the most relevant nature-inspired coordination models, discuss the main open issues, and explore the trends for their future development. 

Location

  • Sala riunioni 2, DISI, Mura A. Zamboni 7, Bologna

Timetable

  • Wednesday 5 February (4 hours, 11-13, 14-16)
  • Wednesday 12 February (4 hours, 11-13, 14-16)
  • Wednesday 19 February (2 hours, 11-13)

Slides

  1. Interaction & Coordination in Distributed Systems (lecture, 05/02/2014)Andrea Omicini (Andrea Omicini)
  2. Tuple-based Coordination of Distributed Systems (lecture, 05/02/2014)Andrea Omicini (Andrea Omicini)
  3. Nature-inspired Models of Coordination (lecture, 12/02/2014)Andrea Omicini (Andrea Omicini)  Examples:
    1. Field-based Coordination (lecture, 29/04/2005) — Franco Zambonelli, Marco Mamei (Franco Zambonelli, Marco Mamei)
    2. Engineering Adaptive Service Ecosystems (lecture, 12/02/2014)Mirko Viroli (Mirko Viroli)
  4. Research Trends in Nature-Inspired Coordination (lecture, 19/02/2014)Andrea Omicini (Andrea Omicini)

PhD Student Tests

  • Angelo Trotta
  • Andrea Borghesi
  • Pankaj Kumar
  • Valeria Vignudelli
  • Liubov Ermolaeva
  • Abel García
  • Tommaso Cavallari
  • Yisleidy Linares Zaila
  • Enrico Gallinucci
  • Stefano Giovanni Rizzo
  • Daniela Loreti

Tags:

Course

— a.y.

2013/2014

— credits

1

— cycle

3rd cycle (phd)

Teachers

— professor

Andrea Omicini

— other professors

Mirko Viroli

Context

— university

Alma Mater Studiorum-Università di Bologna

— campus

Bologna

— department / faculty / school

DISI

— 3rd cycle (phd)

Dottorato di Ricerca in Computer Science and Engineering

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