ECAS 2019

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4th eCAS Workshop on Engineering Collective Adaptive Systems
Umeå, Sweden, 16/06/2019

Modern software systems are becoming more and more collective and are composed of many distributed and heterogeneous entities. These systems operate under continuous perturbations making manual adjustments infeasible. For a collective system to be resilient, its adaptation must also be collective, in the sense that multiple entities must adapt in a way that addresses critical runtime conditions while preserving the benefits of collaborative interdependencies. Decision- making in such systems is distributed and possibly highly dispersed, and interaction between the entities may lead to the emergence of unexpected phenomena.

In such systems, a new approach for adaptation is needed to allow:  multiple entities to collectively adapt with (ii) negotiations to decide which collective changes are best. Collective adaptation also raises a second important challenge: Which parts of the system (things, services, people) should be engaged in an adaptation? This is nontrivial, as multiple solutions to the same problem may be generated at different levels. The challenge is to understand these levels and create mechanisms to decide the right scope for an adaptation for a given problem.

This workshop solicits papers that address new methodologies, theories and principles that can be used to develop a better understanding of the fundamental factors underpinning the operation of such systems, so that they can be better designed, built, and analyzed, as well as case studies and applications showing such approaches in action. Interdisciplinary work is particularly welcomed.

topics of interest
  • Novel theories relating to operating principles of CAS
  • Novel design principles for building CAS systems
  • Insights into the short and long-term adaptation of CAS systems
  • Insights into emergent properties of CAS
  • Insights into general properties of large scale, distributed CAS
  • Decision-making approaches in CAS
  • Methodologies for studying, analyzing, and building CAS
  • Frameworks for analyzing or developing CAS case studies
  • Languages, platforms, APIs and other tools for CAS
  • Scenarios, case studies, and experience reports of CAS in different contexts (e.g., Smart Mobility, Smart Energy/Smart Grid, Smart Buildings, traffic management, emergency response, etc.)