Engineering Resilient Collective Adaptive Systems by Self-Stabilisation

Author:

Viroli Mirko1ORCID,Audrito Giorgio2ORCID,Beal Jacob3ORCID,Damiani Ferruccio2ORCID,Pianini Danilo1ORCID

Affiliation:

1. Università di Bologna

2. Università di Torino, Torino, Italy

3. Raytheon BBN Technologies

Abstract

Collective adaptive systems are an emerging class of networked computational systems particularly suited for application domains such as smart cities, complex sensor networks, and the Internet of Things. These systems tend to feature large-scale, heterogeneity of communication model (including opportunistic peer-to-peer wireless interaction) and require inherent self-adaptiveness properties to address unforeseen changes in operating conditions. In this context, it is extremely difficult (if not seemingly intractable) to engineer reusable pieces of distributed behaviour to make them provably correct and smoothly composable. Building on the field calculus, a computational model (and associated toolchain) capturing the notion of aggregate network-level computation, we address this problem with an engineering methodology coupling formal theory and computer simulation. On the one hand, functional properties are addressed by identifying the largest-to-date field calculus fragment generating self-stabilising behaviour, guaranteed to eventually attain a correct and stable final state despite any transient perturbation in state or topology and including highly reusable building blocks for information spreading, aggregation, and time evolution. On the other hand, dynamical properties are addressed by simulation, empirically evaluating the different performances that can be obtained by switching between implementations of building blocks with provably equivalent functional properties. Overall, our methodology sheds light on how to identify core building blocks of collective behaviour and how to select implementations that improve system performance while leaving overall system function and resiliency properties unchanged.

Funder

HyVar

Ateneo/CSP project RunVar

Defense Advanced Research Projects Agency

ICT COST Action

IC1402 ARVI

European Union's Horizon 2020 research

United States Air Force

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Science Applications,Modeling and Simulation

Cited by 72 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3