Development of a Survivable Cloud Multi-Robot Framework for Heterogeneous Environments

Osunmakinde, Isaac Olusegun; Ramharuk, Vikash

doi:10.5772/58891

Cited by 18 publications

(4 citation statements)

References 15 publications

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“…Emerging EVC platforms, such as Zoom, use cloud-based technology that involves the use of anytime anywhere platform-independent applications through the Internet, without requiring organizationwide installation or upfront infrastructure capital investment (Sousa & Rocha, 2019). The application providers develop, maintain, and update the application, which allows for a reduction of costs to its end-users (Osunmakinde & Ramharuk, 2014). 2020 has brought with it unprecedented changes to the global business landscape.…”

Section: Introductionmentioning

confidence: 99%

Reading Between the Lines: Understanding Customer Experience With Disruptive Technology Through Online Reviews

Robertson

Ferreira

Paschen

2021

Australasian Marketing Journal

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A customer’s experience with a brand, as evidenced in online customer reviews, has attracted multidisciplinary scholarly attention. Customer experience plays an important role as an antecedent to brand engagement, brand adoption, and eventual brand loyalty. Thus, it is important for businesses to understand their customers’ experiences so that they can make changes as necessary. The COVID-19 pandemic has brought unprecedented changes to the business landscape, forcing businesses to move online, with many utilizing enterprise video conferencing (EVC) to maintain daily operations. To ensure efficient digitization, many turned to the online reviews of others’ experiences with EVC before engaging with it themselves. This research examined how the customer experience is portrayed through emotional tone and word choice in online reviews for the EVC platform Zoom. Using computerized text analysis, key differences were found in the emotional tone and word choice for low- and high-rated reviews. The complexity and emotionality expressed in reviews have implications on the usability of the review for others. The results from this study suggest that online customer reviews with a high rating express a higher level of expertise and confidence than low-rated reviews. Given the potential dissemination and impact, digital marketers may be well advised to first and foremost respond to online reviews that are high in emotional tone.

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Section: Introductionmentioning

confidence: 99%

Reading Between the Lines: Understanding Customer Experience With Disruptive Technology Through Online Reviews

Robertson

Ferreira

Paschen

2021

Australasian Marketing Journal

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“…Therefore, over the last few years, plenteous research has been conducted in this area. Initial studies such as [113], [135], [219], [220] give particular attention to the infrastructure and framework for offloading in multiagent cloud robotics. Platforms to support offloading the computeintensive tasks from the robotic network to cloud and edge resources are also furnished in [114], [136].…”

Section: B Computation Offloadingmentioning

confidence: 99%

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

Afrin

Jin

Rahman

et al. 2021

IEEE Commun. Surv. Tutorials

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Robotic applications nowadays are widely adopted to enhance operational automation and performance of real-world Cyber-Physical Systems (CPSs) including Industry 4.0, agriculture, healthcare, and disaster management. These applications are composed of latency-sensitive, data-heavy, and compute-intensive tasks. The robots, however, are constrained in the computational power and storage capacity. The concept of multi-agent cloud robotics enables robotto-robot cooperation and creates a complementary environment for the robots in executing large-scale applications with the capability to utilize the edge and cloud resources. However, in such a collaborative environment, the optimal resource allocation for robotic tasks is challenging to achieve. Heterogeneous energy consumption rates and application of execution costs associated with the robots and computing instances make it even more complex. In addition, the data transmission delay between local robots, edge nodes, and cloud data centres adversely affects the real-time interactions and impedes service performance guarantee. Taking all these issues into account, this paper comprehensively surveys the state-of-the-art on resource allocation and service provisioning in multi-agent cloud robotics. The paper presents the application domains of multi-agent cloud robotics through explicit comparison with the contemporary computing paradigms and identifies the specific research challenges. A complete taxonomy on resource allocation is presented for the first time, together with the discussion of resource pooling, computation offloading, and task scheduling for efficient service provisioning. Furthermore, we highlight the research gaps from the learned lessons, and present future directions deemed beneficial to further advance this emerging field.

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“…Most modern robotic systems employ a distributed system architecture that is composed of sophisticated control software synchronizing tasks on multiple controllers that are connected through an underlying network. Some examples are multirobot systems in heterogeneous environments [2], cloud-based frameworks [3], and industrial robots for largescale automation systems [4].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Characteristics of ROS 2.0 in Multiagent Robot Systems: An Empirical Study

2020

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Due to its ease of use and flexibility, the robot operating system (ROS) is increasingly becoming the most popular middleware for robot applications, even in multiagent systems. Since ROS 1.0 does not satisfy real-time requirements, ROS 2.0 was developed, and it improved the communication stack with the real-time data distribution service (DDS) protocol. However, the actual performance level to be expected is still unknown and can largely depend on the operating system and the kernel being used, the DDS distribution, and the overall software load of the system. In this paper, we present an empirical study that evaluates the real-time performance of ROS 2.0 in both the system and communication software layers. In the system layer, the deterministic behavior of the ROS 2.0 nodes is thoroughly observed with regard to whether the tasks are schedulable and can function within the specified temporal deadline. In the communication layer, special attention is devoted to the rate of data loss and the overall latency of messages between nodes. Experiments are performed in various working conditions; for example, the system load is increased to define the real-time performance of the tasks. For reference, the results are compared with the those from the traditional ROS variation. Moreover, we implement a multiagent service robot system to verify the suitability of ROS 2.0 for real-world applications. Our results show that the application of ROS 2.0 is more suitable than that of ROS 1.0 in terms of real-time performance.

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Development of a Survivable Cloud Multi-Robot Framework for Heterogeneous Environments

Cited by 18 publications

References 15 publications

Reading Between the Lines: Understanding Customer Experience With Disruptive Technology Through Online Reviews

Reading Between the Lines: Understanding Customer Experience With Disruptive Technology Through Online Reviews

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

Real-Time Characteristics of ROS 2.0 in Multiagent Robot Systems: An Empirical Study

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