MQTT-Driven Node Discovery for Integrated IoT-Fog Settings Revisited: The Impact of Advertiser Dynamicity

Venanzi, Riccardo; Kantarcı, Burak; Bellavista, Paolo

doi:10.1109/sose.2018.00013

Cited by 14 publications

(3 citation statements)

References 22 publications

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“…The authors in [23] have introduced an energy efficient fog computing framework in homogeneous fog networks and proposed a low complexity maximal energy efficient task scheduling algorithm to derive the optimal scheduling decision for a task node. In [24] a node discovery approach in IoT-fog environment was proposed. The authors mainly worked on the impact of the dynamicity of the advertiser nodes on device discovery success, which was proved to be 100%, and also sustainability of the batterypowered IoT nodes.…”

Section: Related Workmentioning

confidence: 99%

Centralized and Distributed Architectures for Energy and Delay Efficient Fog Network-Based Edge Computing Services

Bozorgchenani

Tarchi

Corazza

2019

IEEE Trans. on Green Commun. Netw.

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Edge computing techniques allow to exploit the devices at the network borders for computing efforts in order to reduce the centralized cloud requests. A fog network is a feasible solution for implementing edge computing services. Within this scenario, the deployed Fog Nodes (FNs) are able to offload different portions of a single task to the available nodes to be processed at the network edge. However, to partially offload, FNs consume an extra amount of energy for transmission and reception of the tasks while saving energy by not processing the whole task on their own. Moreover, offloading requires an extra transmission and reception time to the task processing time. In this work, the focus is on a partial offloading approach where the trade off between FN energy consumption and task processing delay is considered when estimating the portion to be offloaded to the available devices at the edge of the network by comparing a centralized and a distributed architecture. Simulation results demonstrate the effectiveness of the proposed estimation solutions in terms of FN energy consumption, average task delay and network lifetime.

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Section: Related Workmentioning

confidence: 99%

Centralized and Distributed Architectures for Energy and Delay Efficient Fog Network-Based Edge Computing Services

Bozorgchenani

Tarchi

Corazza

2019

IEEE Trans. on Green Commun. Netw.

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“…The paper [ 22 ] investigates its energy consumption and performance. In the discovery phase, the MQTT server is a Fog node responsible for enabling/disabling the Bluetooth Low Energy (BLE) interfaces of devices, monitoring their trajectories, energy efficiency, and scalability.…”

Section: Related Workmentioning

confidence: 99%

IoT Registration and Authentication in Smart City Applications with Blockchain

Ferreira

Garrocho

Oliveira

et al. 2021

Sensors

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The advent of 5G will bring a massive adoption of IoT devices across our society. IoT Applications (IoT Apps) will be the primary data collection base. This scenario leads to unprecedented scalability and security challenges, with one of the first areas for these applications being Smart Cities (SC). IoT devices in new network paradigms, such as Edge Computing and Fog Computing, will collect data from urban environments, providing real-time management information. One of these challenges is ensuring that the data sent from Edge Computing are reliable. Blockchain has been a technology that has gained the spotlight in recent years, due to its robust security in fintech and cryptocurrencies. Its strong encryption and distributed and decentralized network make it potential for this challenge. Using Blockchain with IoT makes it possible for SC applications to have security information distributed, which makes it possible to shield against Distributed Denial of Service (DDOS). IoT devices in an SC can have a long life, which increases the chance of having security holes caused by outdated firmware. Adding a layer of identification and verification of attributes and signature of messages coming from IoT devices by Smart Contracts can bring confidence in the content. SC Apps that extract data from legacy and outdated appliances, installed in inaccessible, unknown, and often untrusted urban environments can benefit from this work. Our work’s main contribution is the development of API Gateways to be used in IoT devices and network gateway to sign, identify, and authorize messages. For this, keys and essential characteristics of the devices previously registered in Blockchain are used. We will discuss the importance of this implementation while considering the SC and present a testbed that is composed of Blockchain Ethereum and real IoT devices. We analyze the transfer time, memory, and CPU impacts during the sending and processing of these messages. The messages are signed, identified, and validated by our API Gateways and only then collected for an IoT data management application.

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“…Due to this aspect the approaches that make use of this architectural model are focusing less on how the resources are discovered and integrated into the model. Some research directions are already investigating the possibility to switch computations from Cloud to Edge [41] and partially tackles the resource discovery problem in Edge environments [38,39,40], but without emphasizing the case were devices or resources are dynamically added to the ecosystem and how are integrated and related to proper Edge computational nodes.…”

mentioning

confidence: 99%

Service Deployment Challenges in Cloud-to-Edge Continuum

Petcu

2021

SCPE

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This position paper aims to identify the current and future challenges in application, workload or service deployment mechanisms in Cloud-to-Edge environments. We argue that the adoption of the microservices and unikernels on large scale is adding new entries on the list of requirements of a deployment mechanism, but offers an opportunity to decentralize the associated processes and improve the scalability of the applications. Moreover, the deployment in Cloud-to-Edge environment needs the support of federated machine learning.

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MQTT-Driven Node Discovery for Integrated IoT-Fog Settings Revisited: The Impact of Advertiser Dynamicity

Cited by 14 publications

References 22 publications

Centralized and Distributed Architectures for Energy and Delay Efficient Fog Network-Based Edge Computing Services

Centralized and Distributed Architectures for Energy and Delay Efficient Fog Network-Based Edge Computing Services

IoT Registration and Authentication in Smart City Applications with Blockchain

Service Deployment Challenges in Cloud-to-Edge Continuum

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