17 - Nature-inspired Coordination for Complex Distributed Systems

Originating from closed parallel systems, coordination models and technologies gained in expressive power so to deal with open 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 talk we survey the most relevant nature-inspired coordination models, discuss the main open issues, and explore the trends for their future development

An Overview of Recent Progress in the Study of Distributed Multi-agent Coordination

This article reviews some main results and progress in distributed multi-agent coordination, focusing on papers published in major control systems and robotics journals since 2006. Distributed coordination of multiple vehicles, including unmanned aerial vehicles, unmanned ground vehicles and unmanned underwater vehicles, has been a very active research subject studied extensively by the systems and control community. The recent results in this area are categorized into several directions, such as consensus, formation control, optimization, task assignment, and estimation. After the review, a short discussion section is included to summarize the existing research and to propose several promising research directions along with some open problems that are deemed important for further investigations

The Evolutionary Price of Anarchy: Locally Bounded Agents in a Dynamic Virus Game

The Price of Anarchy (PoA) is a well-established game-theoretic concept to shed light on coordination issues arising in open distributed systems. Leaving agents to selfishly optimize comes with the risk of ending up in sub-optimal states (in terms of performance and/or costs), compared to a centralized system design. However, the PoA relies on strong assumptions about agents\u27 rationality (e.g., resources and information) and interactions, whereas in many distributed systems agents interact locally with bounded resources. They do so repeatedly over time (in contrast to "one-shot games"), and their strategies may evolve. Using a more realistic evolutionary game model, this paper introduces a realized evolutionary Price of Anarchy (ePoA). The ePoA allows an exploration of equilibrium selection in dynamic distributed systems with multiple equilibria, based on local interactions of simple memoryless agents. Considering a fundamental game related to virus propagation on networks, we present analytical bounds on the ePoA in basic network topologies and for different strategy update dynamics. In particular, deriving stationary distributions of the stochastic evolutionary process, we find that the Nash equilibria are not always the most abundant states, and that different processes can feature significant off-equilibrium behavior, leading to a significantly higher ePoA compared to the PoA studied traditionally in the literature

Active distribution power system with multi-terminal DC links

A fast power restoration operational scheme and relevant stabilizing control is proposed for active distribution power systems with multi-terminal DC network in replacement of the conventional normal open switches. A 9-feeder benchmark distribution power system is established with a 4-terminal medium power DC system injected. The proposed power restoration scheme is based on the coordination among distributed control among relays, load switches, voltage source converters and autonomous operation of multi-terminal DC system. A DC stabilizer is proposed with virtual impedance method to damp out potential oscillation caused by constant power load terminals. The proposed system and controls are validated by frequency domain state space model and time domain case study with Matlab/Simulink

Self-Adaptation in Highly Distributed Dynamic Systems: part of Report from the GI Dagstuhl Seminar 14433: Software Engineering for Self-Adaptive Systems

International audienceThis breakout group focused on identifying the challenges of performing self-adaptation in highly distributed dynamic systems. This is a pressing issue in self-adaptive systems research, as proposed ``smart" systems are increasingly built out of disparate entities (sensors and actuators) that feature a close connection to the physical world -- so-called cyber-physical systems (CPSs). Examples are numerous: intelligent vehicle navigation, fleets of autonomous robots, emergency coordination systems, to mention just a few. CPSs are typically distributed at the physical space and feature no firm boundaries -- they are open-ended. They are composed of loosely connected entities, that are often mobile. Grafting such systems with self-adaptive capabilities is a distinct challenge, which projects itself in all phases of the autonomic loop

Enabling Information Gathering Patterns for Emergency Response with the OpenKnowledge System

Today's information systems must operate effectively within open and dynamic environments. This challenge becomes a necessity for crisis management systems. In emergency contexts, in fact, a large number of actors need to collaborate and coordinate in the disaster scenes by exchanging and reporting information with each other and with the people in the control room. In such open settings, coordination technologies play a crucial role in supporting mobile agents located in areas prone to sudden changes with adaptive and flexible interaction patterns. Research efforts in different areas are converging to devise suitable mechanisms for process coordination: specifically, current results on service-oriented computing and multi-agent systems are being integrated to enable dynamic interaction among autonomous components in large, open systems. This work focuses on the exploitation and evaluation of the OpenKnowledge framework to support different information-gathering patterns in emergency contexts. The OpenKnowledge (OK) system has been adopted to model and simulate possible emergency plans. The Lightweight Coordination Calculus (LCC) is used to specify interaction models, which are published, discovered and executed by the OK distributed infrastructure in order to simulate peer interactions. A simulation environment fully integrated with the OK system has been developed to: (1) evaluate whether such infrastructure is able to support different models of information-sharing, e.g., centralized and decentralized patterns of interaction; (2) investigate under which conditions the OK paradigm, exploited in its decentralized nature, can improve the performance of more conventional centralized approaches. Preliminary results show the capability of the OK system in supporting the two afore-mentioned patterns and, under ideal assumptions, a comparable performance in both cases