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End-to-End Design for Self-Reconfigurable Heterogeneous Robotic Swarms [article]

Jorge Peña Queralta, Li Qingqing, Tuan Nguyen Gia, Hong-Linh Truong, Tomi Westerlund
2020 arXiv   pre-print
Multiple challenges remain in complex scenarios where a large amount of data needs to be processed in real-time and high degrees of situational awareness are required.  ...  We address this by bringing elastic computing techniques and dynamic resource management from the edge-cloud computing domain to the swarm robotics domain.  ...  This concept serves as the basis for abstracting edge resources and building dynamic management models on top of them.  ... 
arXiv:2004.13997v1 fatcat:a2m73kad7bcq5oxcaes34q4vwa

Brainware Computing: Concepts, Scopes and Challenges

Eui-Nam Huh, Md Imtiaz Hossain
2021 Applied Sciences  
In this paper, instead of focusing on SOA and Robot as a Service (RaaS) model, we propose a novel computing architecture, addressed as Brainware Computing, for driving multiple domain-specific brains one-at-a-time  ...  for deploying brain and a new computing model with more scalability and flexibility.  ...  Acknowledgments: A lot of thanks goes to the colleagues for effective contributions to this proposal.  ... 
doi:10.3390/app11115303 fatcat:npzy45ztfrgppobbcemedoeova

Data Capsule: Representation of Heterogeneous Data in Cloud-Edge Computing

Ion-Dorinel Filip, Andrei Vlad Postoaca, Radu-Dumitru Stochitoiu, Darius-Florentin Neatu, Catalin Negru, Florin Pop
2019 IEEE Access  
The architecture includes multiple processing platforms. We evaluate the proposed model in edge-cloud computing platforms designed for robots that run machine learning tasks.  ...  Some of those requirements came from the fact that the robots are involved in highly dynamic environments and have to execute complex decision algorithms in real-time, while other requirements ask for  ...  ACKNOWLEDGMENT The authors would like to thank the reviewers for their time and expertise, constructive comments and valuable insight.  ... 
doi:10.1109/access.2019.2910584 fatcat:22d5d46tefgbbb6kvfm2sivxfu

Enhancing Autonomy with Blockchain and Multi-Access Edge Computing in Distributed Robotic Systems [article]

Jorge Peña Queralta, Li Qingqing, Zhuo Zou, Tomi Westerlund
2020 arXiv   pre-print
Blockchains will enable a transparent and secure way of providing services and managing resources at the Multi-Access Edge Computing (MEC) layer.  ...  We overview the state-of-the-art in MEC slicing, distributed robotic systems and blockchain technology to define a framework for services the MEC layer that will enhance the autonomous operations of connected  ...  ACKNOWLEDGEMENTS This work was supported by the Academy of Finland's AutoSOS project with grant number 328755, the NSFC grant number 61876039, and the Shanghai Platform for Neuromorphic and AI Chips (NeuHeilium  ... 
arXiv:2007.01156v1 fatcat:rmwqquu2qbhwlonqxrrestzc4u

Service-Oriented Real-Time Smart Job Shop Symmetric CPS Based on Edge Computing

Chuang Wang, Yi Lv, Qiang Wang, Dongyu Yang, Guanghui Zhou
2021 Symmetry  
First, the CPS and MEC for a service-oriented production process are analyzed. Secondly, based on MEC middleware, a CPS architecture model of a smart job shop is established.  ...  Real-time acquisition of production data and rapid response to changes in the external environment are the keys to ensuring the symmetry of the CPS.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym13101839 fatcat:53mrwscrffen3hklivusfuihbe

Internet of Robotic Things Intelligent Connectivity and Platforms

Ovidiu Vermesan, Roy Bahr, Marco Ottella, Martin Serrano, Tore Karlsen, Terje Wahlstrøm, Hans Erik Sand, Meghashyam Ashwathnarayan, Micaela Troglia Gamba
2020 Frontiers in Robotics and AI  
These new applications accelerate the development of autonomous system design paradigms and the proliferation of the Internet of Robotic Things (IoRT).  ...  The continuous, real-time interaction with the environment makes perception, location, communication, cognition, computation, connectivity, propulsion, and integration of federated IoRT and digital platforms  ...  The digital model is extended for real-time communication with the physical system for performance optimization on a system level using a cloud-based service with real-time performance metrics, optimization  ... 
doi:10.3389/frobt.2020.00104 pmid:33501271 pmcid:PMC7805974 fatcat:oejpeyynjndnxcq7jsdcotv7ua

An Overview of Federated Learning at the Edge and Distributed Ledger Technologies for Robotic and Autonomous Systems [article]

Yu Xianjia, Jorge Peña Queralta, Jukka Heikkonen, Tomi Westerlund
2021 arXiv   pre-print
At the same time, advances in deep learning (DL) have significantly raised the degree of autonomy and level of intelligence of robotic and autonomous systems.  ...  Autonomous systems are becoming inherently ubiquitous with the advancements of computing and communication solutions enabling low-latency offloading and real-time collaboration of distributed devices.  ...  In [90] , the authors introduced a FL-based online reinforcement transfer learning process for real-time perception, with a demonstration through a collision avoidance system simulated in Airsim.  ... 
arXiv:2104.10141v2 fatcat:x4mysoxyzzagpjxpzmpxu2af4q

Recent Advances in Evolving Computing Paradigms: Cloud, Edge, and Fog Technologies

Nancy A Angel, Dakshanamoorthy Ravindran, P M Durai Raj Vincent, Kathiravan Srinivasan, Yuh-Chung Hu
2021 Sensors  
the security and management of resources.  ...  The newest drift is moving computational and storage resources to the edge of the network, involving a decentralized distributed architecture.  ...  The key feature of fog computing and edge computing models is the potential to quickly store and process data, benefiting real-time applications and playing a crucial part in efficient business operations  ... 
doi:10.3390/s22010196 pmid:35009740 pmcid:PMC8749780 fatcat:syxfgjxg45hkvbgny4hxlxas4e

Fogification of industrial robotic systems: research challenges

Shaik Mohammed Salman, Thomas Nolte, Moris Behnam, Vaclav Struhar, Alessandro V. Papadopoulos
2019 Zenodo  
Robotics and Industrial Automation.  ...  leading to these results has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 764785, FORA-Fog Computing for  ...  Resource Estimation and Workload Optimization To ensure real-time performance, a proper analysis of the system must be done to estimate the resources necessary for an application.  ... 
doi:10.5281/zenodo.5851068 fatcat:wfyy746lvjcvfjwb2jrjqyxq2y

IEEE Access Special Section Editorial: Edge Computing and Networking for Ubiquitous AI

Victor C. M. Leung, Xiaofei Wang, Abbas Jamalipour, Xu Chen, Samia Bouzefrane
2021 IEEE Access  
multiplications for a subset of kernel weights in a convolutional neural network (CNN) layer.  ...  Another is how edge computing supports AI in a networking environment. For example, AI training and inference can be efficiently enabled by a multitude of computing resources from edge computing.  ...  ''Intelligent search and find system for robotic platform based on smart edge computing service,'' by Barnawi et al., proposes a heterogeneous robotic system to facilitate the development of advanced  ... 
doi:10.1109/access.2021.3090143 fatcat:mdgmfeph6zcrzc6z7w7xjg3iua

Mobile Edge Cloud: Opportunities and Challenges [article]

Sayed Chhattan Shah
2018 arXiv   pre-print
The real-time requirements associated with the internet of things and cyber-physical system applications make the problem even more challenging.  ...  The executions of these algorithms require a vast amount of computing and storage resources.  ...  create a real-time and energy efficient mobile edge cloud.  ... 
arXiv:1811.01929v1 fatcat:moa7c7l335hoffll5allfselu4

Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges [article]

Lei Lei, Yue Tan, Kan Zheng, Shiwen Liu, Kuan Zhang, Xuemin Shen
2020 arXiv   pre-print
In this paper, we first provide a tutorial of DRL, and then propose a general model for the applications of RL/DRL in AIoT.  ...  The Autonomous Control System (ACS), on the other hand, performs control functions on the physical systems without external intervention over an extended period of time.  ...  A similar system model is considered in [84] , where a DQN-based scheme is proposed to allocate computation and communication resources for an edge computing system with multiple edge servers and mobile  ... 
arXiv:1907.09059v3 fatcat:z7yksnu4wve7norrjijnu43kvi

Zero-Touch Network on Industrial IoT: An End-to-End Machine Learning Approach [article]

Shih-Chun Lin, Chia-Hung Lin, Wei-Chi Chen
2022 arXiv   pre-print
To unbound the potential of smart factory, this paper develops zero-touch network systems for intelligent manufacturing and facilitates distributed AI applications in both training and inferring stages  ...  in a large-scale manner.  ...  Balance between Training Speed and Accuracy Owing to the usage of multiple AI/ML models for non/near real-time RAN optimization in our framework, a balance should be found between the training time and  ... 
arXiv:2204.12605v1 fatcat:zvdtpobsdnbuzn6ky5zx2c2xca

Cloud-based Cyber-Physical Robotic Mobile Fulfillment Systems: A Case Study of Collision Avoidance

K.L. Keung, C.K.M. Lee, P. Ji, K.K.H. Ng
2020 IEEE Access  
The rapid development and implementation of the Internet of Things (IoT) and Cyber-Physical Systems (CPS) in the engineering and manufacturing field have embraced a virtual identity to ensure nearly real-time  ...  INDEX TERMS Robotic mobile fulfillment system, Cyber-physical systems, Internet of Things, collision avoidance. This work is licensed under a Creative Commons Attribution 4.0 License.  ...  [39] presented a collection of path planning algorithms for real-time movement of multiple mobile robots across the RMFS. B.  ... 
doi:10.1109/access.2020.2992475 fatcat:6hpoaorrrzainpexgs4dfdbhdu

Deep Learning at the Mobile Edge: Opportunities for 5G Networks

Miranda McClellan, Cristina Cervelló-Pastor, Sebastià Sallent
2020 Applied Sciences  
In this paper, we discuss the state of the art for ML within mobile edge computing and the advances needed in automating adaptive resource allocation, mobility modeling, security, and energy efficiency  ...  Together, mobile edge computing and ML enable seamless automation of network management to reduce operational costs and enhance user experience.  ...  These ask offloading systems respond to changes in real-time demand for computation and supporting resources at the mobile edge computing nodes.  ... 
doi:10.3390/app10144735 fatcat:ytrnh35x6zbxbki3zg435xqacu
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