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21st International Conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)

作者： Qiao, Yuansong Nolan, Robert Gill, Saul Fang, Guiming Lee, Brian Athlone Inst Technol Software Res Inst Athlone Ireland Chinese Acad Sci Inst Software Beijing Peoples R China

ISBN: (纸本)9781538634585

The enormous number of things connected to the Internet requires a flexible macro-programming platform to efficiently organize functions and process data. Fog or Edge computing is an emerging architecture to fill the gaps between things and cloud through providing computing, storage and forwarding services close to the end devices. This paper presents ThingNet - a micro-service based macro-programming platform to enable distributed data routing and processing across IoT devices, edges and central cloud. Application providers can deploy, modify, migrate and scale application logic over underlying infrastructures. An application level service function chaining is designed to enable data flow programming. The service functions can be shared by multiple data flows to reduce resource utilisation. The platform is implemented based on open source platforms including Kubernetes and MiNifi. ThingNet has been verified through a proof of concept testbed including Raspberry Pis, Intel NUCs, and Openstack VMs.

关键词： IoT macro-programming Micro-service Fog Computing Edge Computing

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PICO-MP: De-Centralised macro-programming for Wireless Sensor and Actuator Networks 32

PICO-MP: De-Centralised Macro-Programming for Wireless Senso...

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32nd IEEE International Conference on Advanced Information Networking and Applications (AINA)

作者： Dulay, Naranker Micheletti, Matteo Mostarda, Leonardo Piermarteri, Andrea Imperial Coll London Dept Comp London England Univ Camerino Comp Sci Dept Camerino Italy

ISBN: (纸本)9781538621950

macro-programming advocates the use of high-level abstractions to specify distributed systems as a whole. However, macro-programming implementations are often centralised. In this paper we present PICO-MP, the first fully decentralised macro-programming middleware for wireless sensor and actuator network (WSAN) applications. PICO-MP incorporates a novel publish-subscribe service that can correlate events scattered across a WSAN using global formulae specifications that are automatically checked in a distributed fashion. PICO-MP has been implemented for the TinyOS operating system and validated on a case study that uses global formulae to improve energy efficiency (lifetime) of the implementation.

关键词： Wireless Sensor and Actuator Networks Distributed Computation macro-programming Publish / Subscribe Paradigm Energy Efficiency

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Declarative macro-programming of Collective Systems with Aggregate Computing: An Experience Report 24

Declarative Macro-Programming of Collective Systems with Agg...

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26th International Conference on Principles and Practice of Declarative programming (PPDP)

作者： Casadei, Roberto Viroli, Mirko Univ Bologna Cesena Italy

ISBN: (纸本)9798400709692

Massive deployments of devices across all kinds of environments pose the need for engineering their collaborative, macro-level behaviour. To address this challenge, so-called macro-programming approaches have emerged. A prominent nature-inspired example of macro-programming is aggregate computing. In aggregate computing, macroscopic and self-organising behaviour is declared as a functional manipulation of computational fields. Fields are macro-level abstractions mapping devices to values over time, whose computation details, typically based on an execution model of asynchronous sense-compute-interact rounds, are abstracted. In more than ten years of research, multiple software engineering concerns in aggregate computing systems have been investigated, addressing aspects at the level of the language, execution dynamics, middle-ware, and deployment. Arguably, the enabling factor for many of such investigations and results is precisely the declarative nature of the aggregate computing paradigm. In this experience report, we analyse aggregate computing through the lenses of declarative programming, and draw significant insights and perspectives related to the engineering of complex adaptive systems.

关键词： collective adaptive systems macro-programming aggregate computing declarative programming self-organisation

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System-wide IoT design and programming: Patterns for decentralised collective processes

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INTERNET OF THINGS 2025年 29卷

作者： Casadei, Roberto Univ Bologna Dept Comp Sci & Engn Alma Mater Studiorum Via Univ 50 I-47521 Cesena Italy

The Internet of Things promotes a view of large-scale deployments of devices able to compute, communicate, and interact with their surrounding environment. In this context, one significant challenge revolves around designing and programming collective processes, i.e., durable activities involving the collaboration of large groups of devices. Examples of collective processes include distributed sensing, collective decision-making, collective movement/transport, and adaptive maintenance of system-level structures. To address the issues involved in developing such kinds of system-wide behaviours, research has proposed multiple approaches, abstractions, and algorithmic solutions. In particular, the approach of aggregate processes has emerged as a promising formal technique for programming collective processes by a macro-level perspective while supporting decentralisation, abstraction, and resilience. In order to characterise (i) previous work on aggregate processes, (ii) the usages and applications that this technique may foster, and (iii) draw general design insights in the realm of collective computing, this article provides a characterisation of common problems and solutions based on aggregate processes. What results is a catalogue of design patterns for decentralised collective processes. Specifically, we provide a taxonomy of patterns, describe each pattern in a schematic form, and discuss the implications for the design of collective processes for the Internet of Things and related scenarios.

关键词： Internet of Things Collective intelligence Distributed computing Decentralised systems macro-programming Design patterns

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EasiSMP:A Resource-Oriented programming Framework Supporting Runtime Propagation of RESTful Resources

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Journal of Computer Science & Technology 2014年第2期29卷 194-204页

作者：邱杰凡李栋石海龙侯陈达崔莉 Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences

In order to simplify programming for building sensor networks, macro-programming methods have been pro- posed in prior work. Most of them are designed for the dedicated networks and specific scenarios where devices are mostly homogeneous. Nevertheless the methods rarely consider those shared networks which are composed of heterogeneous de- vices, e.g., sensors, actuators, mobile devices, and share resources among themselves. In this paper, we present EasiSMP, a resource-oriented programming framework for these shared networks and generic application scenarios. In this framework, the devices and their functionalities are abstracted into RESTful virtual resources （VRs） each of which is labelled by a uni- form resource identifier （URI）. The post-deployment VR can be globally accessed and reused to propagate new resource（s） at runtime. To support the resource propagation, programming primitives are proposed and a virtual resource engine （VRE） is studied. To perform evaluation, EasiSMP is deployed into a relic monitoring network. Experimental results show that programming using Ea-siSMP is concise, and the average deployment overhead is decreased by up to 27% compared with the node-level programming.

关键词： macro-programming RESTful virtual resource resource propagation cloud-sea computing

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Collective Abstractions and Platforms for Large-Scale Self-Adaptive IoT 3

Collective Abstractions and Platforms for Large-Scale Self-A...

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3rd IEEE International Workshops on Foundations and Applications of Self* Systems (FAS*W)

作者： Casadei, Roberto Viroli, Mirko Univ Bologna Dept Comp Sci & Engn Alma Mater Studiorum Cesena Italy

ISBN: (纸本)9781538651759

On the way to the materialisation of the pervasive computing vision, the technological progress swelling from mobile computing and the Internet of Things (IoT) domain is already rich of missed opportunities. Firstly, coordinating large numbers of heterogeneous situated entities to achieve system-level goals in a resilient and self-adaptive way is complex and requires novel approaches to be seamlessly injected into mainstream distributed computing models. Secondly, achieving effective exploitation of computer resources is difficult, due to operational constraints resulting from current paradigms and uncomprehensive software infrastructures which hinder flexibility, adaptation, and smooth coordination of computational tasks execution. Indeed, building dynamic, context-oriented applications in small- or large-scale IoT with traditional abstractions is hard: even harder is to achieve opportunistic, QoS- and QoE-driven application task management across available hardware and networking infrastructure. In this insight paper, we analyse by the collective adaptation perspective the key directions of the impelling paradigm shift urged by forthcoming large-scale IoT scenarios. Specifically, we consider how collective abstractions and platforms can synergistically assist in such a transformation, by better capturing and enacting a notion of "collective service" as well as the dynamic, opportunistic, and context-driven traits of space-time-situated computations.

关键词： collective adaptive systems Internet of Things distributed coordination macro-programming

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Software Engineering for Collective Cyber-Physical Ecosystems

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ACM Transactions on Software Engineering and Methodology 1000年

作者： Roberto Casadei Gianluca Aguzzi Giorgio Audrito Ferruccio Damiani Danilo Pianini Giordano Scarso Gianluca Torta Mirko Viroli Università di Bologna Italy Università di Torino Italy

Today's distributed and pervasive computing addresses large-scale cyber-physical ecosystems, characterised by dense and large networks of devices capable of computation, communication and interaction with the environment and people. While most research focuses on treating these systems as “composites” (i.e., heterogeneous functional complexes), recent developments in fields such as self-organising systems and swarm robotics have opened up a complementary perspective: treating systems as “collectives” (i.e., uniform, collaborative, and self-organising groups of entities). This article explores the motivations, state of the art, and implications of this “collective computing paradigm” in software engineering. In particular, it discusses its peculiar challenges, implied by characteristics like distribution, situatedness, large scale, and cooperative nature. These challenges outline significant directions for future research in software engineering, touching on aspects such as macro-programming, collective intelligence, self-adaptive middleware, learning/synthesis of collective behaviour, human involvement, safety and security in collective cyber-physical ecosystems.

关键词： cyber-physical ecosystems collective adaptive systems swarm intelligence macro-programming edge-cloud continuum multi-agent systems distributed artificial intelligence

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