QoS-Aware Robotic Streaming Workflow Allocation in Cloud Robotics Systems

Chen, Wuhui; Yaguchi, Yuichi; Naruse, Keitaro; Watanobe, Yutaka; Nakamura, Keita

doi:10.1109/tsc.2018.2803826

Cited by 54 publications

(32 citation statements)

References 40 publications

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“…On the other side, the experimentation in the real scenario shows the efficiency of the approach with concrete agents due to the higher number of challenges, which are discarded in the simulated scenario. It is often the case that cloud-based applications' performances are affected by network glitches, bandwidth fluctuations which provoke irregular robot mobility [11]. Testing the communication layer in both kinds of scenarios provides precise evidence of its efficiency.…”

Section: Discussionmentioning

confidence: 99%

“…Among the several cloud-based applications proposed in the literature, the challenges of bi-directional visibility and communication among agents (i.e., robots and cloud resources) are often underestimated or based on non-"plug-and-play" solutions such as VPNs. Besides, in [11], the authors state three challenges of computation offloading:…”

Section: Related Workmentioning

confidence: 99%

“…Beyond these specific applications, several works focus on the definition and implementation of the architecture for communication and interaction between physical robots and virtual resources hosted on cloud infrastructure [10][11][12][13][14]. Different solutions have been provided, but the problem of bi-directional communication among agents (i.e., from a user interface to a mobile robot platform and vice-versa) on different networks is often not addressed or underestimated.…”

Section: Introductionmentioning

confidence: 99%

“…Summary of other available solutions in the current state of the art. [11] QoS-aware robotic streaming work-flow allocation algorithm Problem of agents' visibility not included [12] Problem formally described as Stackelberg game…”

mentioning

confidence: 99%

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A Plug and Play Transparent Communication Layer for Cloud Robotics Architectures

2020

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The cloud robotics paradigm aims at enhancing the abilities of robots by using cloud services, but it still poses several challenges in the research community. Most of the current literature focuses on how to enrich specific robotic capabilities, overlooking how to effectively establish communication between the two fields. Our work proposes a "plug-and-play" solution to bridge the communication gap between cloud and robotic applications. The proposed solution is designed based on the mature WebSocket technology and it can be extended to any ROS-based robotic platform. The main contributions of this work are the definition of a reliable autoconnection/autoconfiguration mechanism as well as to outline a scalable communication layer that allows the effective control of multiple robots from multiple users. The "plug-and-play" solution was evaluated in both simulated and real scenarios. In the first case, the presence of users and robots was simulated with Robot Operating System (ROS) nodes running on five machines. In the real scenario, three non-expert users teleoperated, simultaneously, three remote robots by using the proposed communication layer with different networking protocols. Results confirmed the reliability at different levels: at startup (success_rate = 100%); during high-rate communications (message_lost = 0%); in performing open-loop spiral trajectories with enhancement, with respect to similar works; and in the quality of simultaneous teleoperations.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A Plug and Play Transparent Communication Layer for Cloud Robotics Architectures

2020

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“…Apart from combining cloud and the robot networks, they also provide additional security features in their framework. Moreover, in other recent works (Rahman et al, 2017 ; Chen et al, 2018 ; Hong et al, 2019 ) computation offloading in robotics has been used. Therefore, improving the performance of mobile robots as well as providing a cloud-based energy-efficient alternative.…”

Section: Related Workmentioning

confidence: 99%

A Self-Aware and Scalable Solution for Efficient Mobile-Cloud Hybrid Robotics

2020

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Backed by the virtually unbounded resources of the cloud, battery-powered mobile robotics can also benefit from cloud computing, meeting the demands of even the most computationally and resource-intensive tasks. However, many existing mobile-cloud hybrid (MCH) robotic tasks are inefficient in terms of optimizing trade-offs between simultaneously conflicting objectives, such as minimizing both battery power consumption and network usage. To tackle this problem we propose a novel approach that can be used not only to instrument an MCH robotic task but also to search for its efficient configurations representing compromise solution between the objectives. We introduce a general-purpose MCH framework to measure, at runtime, how well the tasks meet these two objectives. The framework employs these efficient configurations to make decisions at runtime, which are based on: (1) changing of the environment (i.e., WiFi signal level variation), and (2) itself in a changing environment (i.e., actual observed packet loss in the network). Also, we introduce a novel search-based multi-objective optimization (MOO) algorithm, which works in two steps to search for efficient configurations of MCH applications. Analysis of our results shows that: (i) using self-adaptive and self-aware decisions, an MCH foraging task performed by a battery-powered robot can achieve better optimization in a changing environment than using static offloading or running the task only on the robot. However, a self-adaptive decision would fall behind when the change in the environment happens within the system. In such a case, a self-aware system can perform well, in terms of minimizing the two objectives. (ii) The Two-Step algorithm can search for better quality configurations for MCH robotic tasks of having a size from small to medium scale, in terms of the total number of their offloadable modules.

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