2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)最新文献_第3页

Performance Comparison of Simple Reflex Agents Using Stigmergy with Model-Based Agents in Self-Organizing Transportation 基于Stigmergy的简单反射因子与基于模型的因子在自组织运输中的性能比较

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00071

Sebastian Schmid, Daniel Schraudner, A. Harth

引用次数: 4

An anytime algorithm for dynamic multi-agent task allocation problems 动态多智能体任务分配问题的任意时间算法

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00065

Qinyuan Li, Minyi Li, Bao Quoc Vo, R. Kowalczyk

引用次数: 1

Distributed Constraint Optimization for Task Allocation in Self-Adaptive Manufacturing Systems 自适应制造系统任务分配的分布式约束优化

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00034

Joseph Hirsch, Martin Neumayer, Hella Ponsar, Oliver Kosak, W. Reif

{"title":"Distributed Constraint Optimization for Task Allocation in Self-Adaptive Manufacturing Systems","authors":"Joseph Hirsch, Martin Neumayer, Hella Ponsar, Oliver Kosak, W. Reif","doi":"10.1109/ACSOS-C52956.2021.00034","DOIUrl":"https://doi.org/10.1109/ACSOS-C52956.2021.00034","url":null,"abstract":"Adaptive manufacturing systems consist of many autonomous agents working together in an ever-changing environment. Therefore, collectively deciding which agent performs what task is a key issue and widely studied. However, many approaches towards this issue assume (partially) centralized control, require implementing proprietary algorithms, or cannot provide any guarantees regarding their runtime or communication overhead. To address these problems, we investigate the use of distributed constraint optimization (DCOP) in this context: We present a DCOP model built on freely available algorithms to distribute the problem among the agents that cooperate to solve it. Furthermore, we compare this decentralized approach to a centralized one by measuring the runtime in a set of system configurations with an increasing number of agents. While the DCOP approach works well in small system configurations, our results indicate poor scalability compared to the central approach when increasing the number of agents. We conclude that, although the DCOP approach has desirable properties, it is unsuitable for larger practical applications with dozens or hundreds of agents.","PeriodicalId":268224,"journal":{"name":"2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121019266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Six Software Engineering Principles for Smarter Cyber-Physical Systems 智能网络物理系统的六个软件工程原则

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00058

Danny Weyns, T. Bures, R. Calinescu, Barnaby Craggs, J. Fitzgerald, D. Garlan, B. Nuseibeh, L. Pasquale, A. Rashid, I. Ruchkin, B. Schmerl

{"title":"Six Software Engineering Principles for Smarter Cyber-Physical Systems","authors":"Danny Weyns, T. Bures, R. Calinescu, Barnaby Craggs, J. Fitzgerald, D. Garlan, B. Nuseibeh, L. Pasquale, A. Rashid, I. Ruchkin, B. Schmerl","doi":"10.1109/ACSOS-C52956.2021.00058","DOIUrl":"https://doi.org/10.1109/ACSOS-C52956.2021.00058","url":null,"abstract":"Cyber-Physical Systems (CPS) integrate computational and physical components. With the digitisation of society and industry and the progressing integration of systems, CPS need to become “smarter” in the sense that they can adapt and learn to handle new and unexpected conditions, and improve over time. Smarter CPS present a combination of challenges that existing engineering methods have difficulties addressing: intertwined digital, physical and social spaces, need for heterogeneous modelling formalisms, demand for context-tied cooperation to achieve system goals, widespread uncertainty and disruptions in changing contexts, inherent human constituents, and continuous encounter with new situations. While approaches have been put forward to deal with some of these challenges, a coherent perspective on engineering smarter CPS is lacking. In this paper, we present six engineering principles for addressing the challenges of smarter CPS. As smarter CPS are software-intensive systems, we approach them from a software engineering perspective with the angle of self-adaptation that offers an effective approach to deal with run-time change. The six principles create an integrated landscape for the engineering and operation of smarter CPS.","PeriodicalId":268224,"journal":{"name":"2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131401375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Augmented Collective Digital Twins for Self-Organising Cyber-Physical Systems 自组织网络物理系统的增强集体数字孪生

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00051

Roberto Casadei, Andrea Placuzzi, Mirko Viroli, Danny Weyns

{"title":"Augmented Collective Digital Twins for Self-Organising Cyber-Physical Systems","authors":"Roberto Casadei, Andrea Placuzzi, Mirko Viroli, Danny Weyns","doi":"10.1109/ACSOS-C52956.2021.00051","DOIUrl":"https://doi.org/10.1109/ACSOS-C52956.2021.00051","url":null,"abstract":"Context. Self-organising and collective computing approaches are increasingly applied to large-scale cyber-physical systems (CPS), enabling them to adapt and cooperate in dynamic environments. Also, in CPS engineering, digital twins are often leveraged to provide synchronised logical counterparts of physical entities, whereas in sensor networks the different-but-related concept of virtual device is used e.g. to abstract groups of sensors. Vision. We envision the design concept of “augmented collective digital twin” that captures digital twins at a collective level extended with purely virtual devices. We argue that this concept can foster the engineering of self-organising CPS by providing a holistic, declarative, and integrated system view. Method. From a review and proposed taxonomy of logical devices comprehending both digital twins and virtual devices, we reinterpret a meta-model for self-organising CPSs and discuss how it can support augmented collective digital twins. We illustrate the approach in a crowd-aware navigation scenario, where virtual devices are opportunistically integrated into the system to enhance spatial coverage, improving navigation capabilities. Conclusion. By integrating physical and virtual devices, the novel notion of augmented collective digital twin paves the way to self-improving system functionality and intelligent use of resources in self-organising CPSs. Conclusion. By integrating physical and virtual devices, the novel notion of augmented collective digital twin paves the way to self-improving system functionality and intelligent use of resources in self-organising CPSs.","PeriodicalId":268224,"journal":{"name":"2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)","volume":"26 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122585877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Novel Technique for Mapping Jammed Areas in Connected and Autonomous Vehicles (CAVs) 一种新的车联网与自动驾驶车辆拥堵区域映射技术

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00044

Md. Shahzad Alam, Abiral Acharya, Jared Oluoch

{"title":"A Novel Technique for Mapping Jammed Areas in Connected and Autonomous Vehicles (CAVs)","authors":"Md. Shahzad Alam, Abiral Acharya, Jared Oluoch","doi":"10.1109/ACSOS-C52956.2021.00044","DOIUrl":"https://doi.org/10.1109/ACSOS-C52956.2021.00044","url":null,"abstract":"It is envisioned that in future, Connected and Autonomous Vehicles (CAV s) will be linked through Vehicular Ad Hoc Networks (VANETs) to enable real-time sharing of traffic information known as beacons. Due to their ephemeral and high mobility nature, VANETs are prone to jamming attacks. In this paper, we propose a solution that combines Centroid Localization (CL) and Graham Scan's Hull algorithms to detect an attacker and map the jammed area in a VANET environment. Specifically, 1) we present a universal information collection mechanism for individual vehicles in the network regardless of their proximity to the RoadSide Units (RSUs); 2) we use associative law of set theory to accumulate vehicle subgroups and obtain a complete information of the network; and 3) we present different jamming attack scenarios with varying radii and x,y coordinates. Simulation results with IEEE 802.11p demonstrate that on average, our proposed technique achieves an average of 98.5% accuracy, 89.4% average precision-recall (APR), and 93.9% area under curve (AUC) receiver operating characteristics (ROC) score.","PeriodicalId":268224,"journal":{"name":"2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C)","volume":"1 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116676275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Bayesian Optimization-Based Analysis and Planning Approach for Self-Adaptive Cyber-Physical Systems 基于贝叶斯优化的自适应信息物理系统分析与规划方法

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00077

A. Petrovska, Julianne Weick

引用次数: 1

5th Workshop on Self-Aware Computing (SeAC 2021) [Organizing Committee and Program Committee] 第五届自我感知计算研讨会(SeAC 2021)[筹委会及计划委员会]

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/acsos-c52956.2021.00015

引用次数: 0

Assessment of Configuration Stability and Variability in Collections of Self-Adaptive Systems 自适应系统集合中构型稳定性和变异性的评估

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00038

Sven Tomforde, Martin Goller

引用次数: 3

AI - Based On The Fly Design of Experiments in Physics and Engineering 基于人工智能的物理与工程实验设计

2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) Pub Date : 2021-09-01 DOI: 10.1109/ACSOS-C52956.2021.00048

Kristina Dingel, A. Liehr, M. Vogel, S. Degener, David Meier, Thoralf Niendorf, Arno Ehresmann, B. Sick

引用次数: 3