Engineering self-organizing urban superorganisms

Progresses in ubiquitous, embedded, and social networking and computing make possible for people in urban areas to dynamically interact with each other and with ICT devices around. This can result in a system with a very large number of agents working together in an orchestrated and self-organizing way to achieve specific urban-level goals, i.e., as if they were a “superorganism”. In this paper, we sketch the future vision of urban superorganisms and overview some emerging application areas heading towards the vision. Following, we identify the key challenges in engineering self-organizing multi-agent systems that can work as a superorganism, i.e., seamlessly involving ICT agents and human agents so to achieve some required urban level goals. Finally, we introduce the reference architecture for an infrastructure to support our future vision of self-organizing urban superorganisms

Engineering environment-mediated coordination via nature-inspired laws

SAPERE is a general multiagent framework to support the development of self-organizing pervasive computing services. One of the key aspects of the SAPERE approach is to have all interactions between agents take place in an indirect way, via a shared spatial environment. In such environment, a set of nature-inspired coordination laws have been defined to rule the coordination activities of the application agents and promote the provisioning of adaptive and self-organizing services

Key Abstractions for IoT-Oriented Software Engineering

Despite the progress in Internet of Things (IoT) research, a general software engineering approach for systematic development of IoT systems and applications is still missing. A synthesis of the state of the art in the area can help frame the key abstractions related to such development. Such a framework could be the basis for guidelines for IoT-oriented software engineering

A Self-Reconfigurable Framework for Context Awareness

Urban environments are increasingly pervaded by ICT devices. Soon, citizens and technologies could collaboratively constitute large-scale socio-technical organisms supporting both individual and collective awareness. This paper illustrates a modern awareness framework designed to deal with the complexity of this scenario. The framework is able to collect and classify data streams in a modular way by supporting service oriented, reconfigurable components. Furthermore, we evaluate an innovative meta-classifcation scheme based on state-automata for (i) improving energy efficiency, (ii) improving classification accuracy and (iii) improving software engineering of aware systems, without affecting the overall performance

Patterns for self-adaptive systems: agent-based simulations

Self-adaptive systems are distributed computing systems that can adapt their behavior and structure to different kinds of conditions. This adaptation does not concern the single components only, but the entire system. In a previous work we have identified several patterns for self-adaptation, classifying them by means of a taxonomy, which aims at being a support for developers of self-adaptive systems. Starting from that theoretical work, we have simulated the described self-adaptation patterns, in order to better understand the concrete and real features of each pattern. The contribution of this paper is to report about the simulation work of three patterns as examples, detailing how it was carried out, in order to provide a further support for the developers

The Socio-Technical Superorganism Vision

Abstract We sketch the future vision of socio-technical superorganisms and overview two emerging application area heading towards the vision. Following, we identify the key challenges in engineering self-organizing ICT systems that can work as a superorganism

XLearn : learning activity labels across heterogeneous datasets

Sensor-driven systems often need to map sensed data into meaningfully labelled activities to classify the phenomena being observed. A motivating and challenging example comes from human activity recognition in which smart home and other datasets are used to classify human activities to support applications such as ambient assisted living, health monitoring, and behavioural intervention. Building a robust and meaningful classifier needs annotated ground truth, labelled with what activities are actually being observed—and acquiring high-quality, detailed, continuous annotations remains a challenging, time-consuming, and error-prone task, despite considerable attention in the literature. In this article, we use knowledge-driven ensemble learning to develop a technique that can combine classifiers built from individually labelled datasets, even when the labels are sparse and heterogeneous. The technique both relieves individual users of the burden of annotation and allows activities to be learned individually and then transferred to a general classifier. We evaluate our approach using four third-party, real-world smart home datasets and show that it enhances activity recognition accuracies even when given only a very small amount of training data.PostprintPeer reviewe

Towards User-Aware Service Composition

Our everyday life is more and more supported by the information technology in general and specific services provided by means of our electronic devices. The AMBIT project (Algorithms and Models for Building context-dependent Information delivery Tools) aims at providing a support to develop services that are automatically tailored based on the user profile. However, while the adaptation of the single services is the first step, the next step is to achieve adaptation in the composition of different services. In this paper, we explore how services can be composed in a user-aware way, in order to decide the composition that better meets users’ requirements. That is, we exploit the user profile not only to provide her customized services, but also to compose them in a suitable way

An Argumentation-based Perspective over the Social IoT

The crucial role played by social interactions between smart objects in the Internet of Things is being rapidly recognized by the Social Internet of Things (SIoT) vision. In this paper, we build upon the recently introduced vision of Speaking Objects – “things” interacting through argumentation – to show how different forms of human dialogue naturally fit cooperation and coordination requirements of the SIoT. In particular, we show how speaking objects can exchange arguments in order to seek for information, negotiate over an issue, persuade others, deliberate actions, and so on, namely, striving to reach consensus about the state of affairs and their goals. In this context, we illustrate how argumentation naturally enables such a form of conversational coordination through practical examples and a case study scenario