Self-organising pervasive ecosystems: A crowd evacuation example

Mobile Networks and Applications, 2013

Pervasive service ecosystems are a new paradigm for the design of context-aware systems featuring adaptivity and self-awareness. A theoretical and practical framework has been proposed for addressing these scenarios, taking primary inspirations from natural ecosystems and grounding upon two basic abstractions: "live semantic annotations" (LSAs), which are descriptions stored in infrastructure nodes and wrapping data, knowledge, and activities of humans, devices, and services; and "eco-laws", acting as system rules evolving the population of LSAs as if they were molecules subject to chemical-like reactions. In this paper, we aim at deepening how self-organisation can be injected in pervasive service ecosystems in terms of spatial structures and algorithms for supporting the design of context-aware applications. To this end, we start from an existing classification of self-organisation patterns, and systematically show how they can be supported in pervasive service ecosystems, and be composed to generate a self-organising emergent behaviour. A paradigmatic crowd steering case study is used to demonstrate the effectiveness of our approach.

2011

Abstract This paper grounds on the SAPERE project (Self-Aware PERvasive Service Ecosystems), which aims at proposing a multi-agent framework for pervasive computing, based on the idea of making each agent (service, device, human) manifest its existence in the ecosystem by a Live Semantic Annotation (LSA), and of coordinating agent activities by a small and fixed set of so-called eco-laws, which are sort of chemical-like reactions evolving the distributed population of LSAs.

BioMPE (Bio-inspired Monitoring of Pervasive Environments) is a research project undertaken by the Pervasive and Artificial Intelligence research group at the Department of Informatics, University of Fribourg in Switzerland. The main goal of BioMPE is to build an intelligent and context-aware pervasive computing middleware to address the issues of reliability and dynamic adaptation of P2P overlays that are utilized to conduct monitoring over heterogeneous and ubiquitous networks. Drawing inspiration from nature and in particular from the behavior of ant colonies and swarm intelligence, we employ related selforganization techniques to construct reliable and robust P2P overlays. High-level policy-based management guides the operation and the possible need for adaptation of the monitoring task, in accordance to context information collected from the pervasive environment. In this respect, the key output of the project is the set of protocols, algorithms and mechanisms to enable the provision of reliable P2P overlay network monitoring, adaptation of which is guided by a pervasive computing middleware to reflect varying requirements.

Self-Organising Software, 2011

Software systems are becoming ever more complex, as the capabilities of the software upon which they are based increase. To develop software that is manageable, we must look for novel sources of inspiration, rather than requiring an increasingly costly level of human support. Self-organising software suggests benefits in this direction, and this chapter focuses on a particularly relevant area of inspiration, that of natural systems. Indeed many natural systems are themselves self-organising, despite being often very complicated. We consider natural systems both in the context of non-living (mathematical, physical and chemical) and living (cellular, invertebrate and vertebrate, not excluding human beings) examples. We review some of the causal mechanisms and conditions that are fundamental to self-organisation in natural systems, such as: complexity, evolution, ecological interactions, animal behaviour, as well as the complexities of human behaviour, which has given us insights into phenomena such as small-world networks, epidemics, trust and gossip. In each case, we consider the relevance to self-organising software, and we throughout provide a range of references to applications and to other chapters where particular areas will be developed in more detail. We conclude by considering two application areas which arise frequently in the context of self-organising software, in different contexts: trading in markets, and networks when considered from the perspectives of design, management and robustness.

2012

Future and emerging pervasive computing systems call for new service models and coordination approaches enforcing self-organisation as an inherent property of component interaction. We introduce the concept of a pervasive ecosystem, and present the coordination approach grounded upon it, which revolves around (i) the notion of a distributed and dynamic space of "live semantic annotations" (wrapping data, knowledge, and activities of humans, devices, and services) and (ii) a set of chemical-resembling coordination rules that are applied to such annotations semantically. As an application example we present a simulated scenario of crowd steering in an exhibition centre.

The ambient intelligence scenario depicts electronic environments that are sensitive and responsive to the presence of people. The paper deals with a particular kind of system whose aim is to enhance the everyday experience of people moving inside the related physical environment according to the narrative description of a designer's desiderata. In this kind of situation computer simulation represents a useful way to envision the behaviour of the responsive environments modeled and implemented, without actually bringing them into existence in the real world, in order to evaluate their adherence to the designer's specification. This paper describes the simulation of an adaptive illumination facility, a physical environment endowed with a set of sensors that perceive the presence of humans (or other entities such as dogs, bicycles, cars) and interact with a set of actuators (lights) that coordinate their state to adapt the ambient illumination to the presence and behaviours of its users. The simulation system is used to compare two different selforganization models managing the adaptive illumination system.

The mass deployment of sensors and pervasive computing systems expected in the next few years, will require novel approaches to program and gather information from such systems. Suitable approaches will be general purpose, independent of a specific scenario and sensor deployment, and able to adapt autonomically to different scales and to a number of unforeseen circumstances. This paper focuses on the requirements and issues of upcoming pervasive computing scenario, and surveys current research initiatives to deal with them. In particular researches addressing data retrieval and aggregation, macro-programming, and data integration in pervasive computing infrastructures will be detailed. Overall, the paper illustrates our ideas on collecting information from both sensor systems and Web resources and on linking them together in overlay knowledge network offering applications comprehensive and understandable information about their computational environment.

pervasive.jku.at

In this paper, we present a novel formal agent-based simulation framework (FABS). FABS uses formal specification as a means of clear description of wireless sensor networks (WSNs) sensing a complex adaptive environment. This specification model is then used to develop an agent-based model of both the WSN as well as the environment. As proof of concept, we demonstrate the application of FABS to a boids model of self-organized flocking of animals monitored by a random deployment of proximity sensors.

The design and development of future communications networks call for a careful examination of biological and social systems. New technological developments like self-driving cars, wireless sensor networks, drones swarm, Internet of Things, Big Data, and Blockchain are promoting an integration process that will bring together all those technologies in a large-scale heterogeneous network. Most of the challenges related to these new developments cannot be faced using traditional approaches, and require to explore novel paradigms for building computational mechanisms that allow us to deal with the emergent complexity of these new applications. In this article, we show that it is possible to use biologically and socially inspired computing for designing and implementing self-organizing communication systems. We argue that an abstract analysis of biological and social phenomena can be made to develop computational models that provide a suitable conceptual framework for building new networking technologies: biologically inspired computing for achieving efficient and scalable networking under uncertain environments; socially inspired computing for increasing the capacity of a system for solving problems through collective actions. We aim to enhance the state-of-the-art of these approaches and encourage other researchers to use these models in their future work.