Exploring Container Virtualization in IoT Clouds

Celesti, Antonio; Mulfari, Davide; Fazio, Maria; Villari, Massimo; Puliafito, Antonio

doi:10.1109/smartcomp.2016.7501691

Cited by 92 publications

(46 citation statements)

References 6 publications

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“…The IoT cloud also includes various servers with virtual storage and processing capabilities, and the senor and actuator with virtual sensing and actuating capabilities. Through this, the IoT cloud collects information from all the sensors in the cloud and analyzes the collected information in an integrative way to derive the results, thereby providing various services to the user according to the result obtained [20][21][22]. However, the sensor and actuator with limited network environments have limitations in directly interacting with the IoT cloud.…”

Section: Iot Application Protocolmentioning

confidence: 99%

Sleep Information Gathering Protocol Using CoAP for Sleep Care

Choi

Kang

Lee

2017

Entropy

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There has been a growing interest in sleep management recently, and sleep care services using mobile or wearable devices are under development. However, devices with one sensor have limitations in analyzing various sleep states. If Internet of Things (IoT) technology, which collects information from multiple sensors and analyzes them in an integrated manner, can be used then various sleep states can be more accurately measured. Therefore, in this paper, we propose a Smart Model for Sleep Care to provide a service to measure and analyze the sleep state using various sensors. In this model, we designed and implemented a Sleep Information Gathering Protocol to transmit the information measured between physical sensors and sleep sensors. Experiments were conducted to compare the throughput and the consumed power of this new protocol with those of the protocols used in the existing service-we achieved the throughput of about two times and 20% reduction in power consumption, which has confirmed the effectiveness of the proposed protocol. We judge that this protocol is meaningful as it can be applied to a Smart Model for Sleep Care that incorporates IoT technology and allows expanded sleep care if used together with services for treating sleep disorders.

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Section: Iot Application Protocolmentioning

confidence: 99%

Sleep Information Gathering Protocol Using CoAP for Sleep Care

Choi

Kang

Lee

2017

Entropy

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“…Microservice can be implemented using container technology [17], where only one or few processes run inside a single container. Docker containers provide a lightweight, low overhead and fast technology empowering the usage of microservice architectures [9]. When the microservices are smaller enough and could be managed locally, they can be referred as nanoservices [1].…”

Section: B Container-based Microservice Architecturesmentioning

confidence: 99%

“…The local IoT-layer generally has less resources, such as the minimal availability of hardware resources, limited network access and highly variable device environment, among others. Docker container based solutions are becoming popular to provide virtualized services for resource-constrained IoT systems [9]. This paper presents the implementation behind the gadgetfree IoT edge architecture introduced in [1], and provides a detailed evaluation for it.…”

Section: Introductionmentioning

confidence: 99%

Docker Enabled Virtualized Nanoservices for Local IoT Edge Networks

Islam

Harjula

Kumar

et al. 2019

2019 IEEE Conference on Standards for Communications and Networking (CSCN)

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Edge computing is a novel computing paradigm moving server resources closer to end-devices. It helps unleashing the full potential of high-performance access networks with respect to ultra-low latency and transfer rate and improve resilience to problems at core networks and data centers. Multiaccess Edge Computing (MEC), is a standard solution by European Telecommunications Standards Institute (ETSI) for access network-level edge computing. MEC, operating at access network level, is an ideal solution for the most cases. However, there are still some challenges to address: first is related to the vulnerability to access network problems and the second is about the high load inflicted to access networks and MEC servers. This is a particular issue in massive-scale Internet of Things (IoT) use cases, where numerous sensors may produce high amounts of data, or where critical system functionalities must be ensured also during access network problems. In this paper, we study the feasibility of bringing some edge functions to the local level as virtualized and dynamically deployable components utilizing local hardware capacity. For the study, we have implemented a local edge networking prototype based on local microservices, called nanoservices, implemented using Docker containers and deployed using Docker Swarm-based orchestration. Since IoT networks typically consist of constrained-capacity devices, our focus is in optimizing the resources of the proposed nanoservices.

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“…Celesti et al [5] and Mulfari et al [6] proposed applying container-based virtualization [7] to IoT devices for resolving the management issue. Container-based virtualization allows multiple execution environments (containers) to run concurrently on an operating system (OS) and simplifies the packaging, distribution, installation, and execution of IoT devices.…”

Section: Introductionmentioning

confidence: 99%

“…To utilize such advantages of containers, previous studies [5,6,12,13] deployed containers to IoT devices and conducted performance evaluation to compare the performance of containers with the native environment. However, they did not conduct detailed network performance analysis of containers on IoT devices.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Container Virtualization on Network Performance of IoT Devices

Lee

Kim

2018

Mobile Information Systems

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Container-based virtualization offers advantages such as high performance, resource efficiency, and agile environment. ese advantages make Internet of ings (IoT) device management easy. Although container-based virtualization has already been introduced to IoT devices, the different network modes of containers and their performance issues have not been addressed. Since the network performance is an important factor in IoT, the analysis of the container network performance is essential. In this study, we analyze the network performance of containers on an IoT device, Raspberry Pi 3. e results show that the network performance of containers is lower than that of the native Linux, with an average performance difference of 6% and 18% for TCP and UDP, respectively. In addition, the network performance of containers varies depending on the network mode. When a single container runs, bridge mode achieves higher performance than host mode by 25% while host mode shows better performance than bridge mode by 45% in the multicontainer environment.

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Exploring Container Virtualization in IoT Clouds

Cited by 92 publications

References 6 publications

Sleep Information Gathering Protocol Using CoAP for Sleep Care

Sleep Information Gathering Protocol Using CoAP for Sleep Care

Docker Enabled Virtualized Nanoservices for Local IoT Edge Networks

The Impact of Container Virtualization on Network Performance of IoT Devices

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