A survey on fog computing for the Internet of Things

Electronics

The Internet of Things (IoT) is a network widely used with the purpose of connecting almost everything, everywhere to the Internet. To cope with this goal, low cost nodes are being used; otherwise, it would be very expensive to expand so fast. These networks are set up with small distributed devices (nodes) that have a power supply, processing unit, memory, sensors, and wireless communications. In the market, we can find different alternatives for these devices, such as small board computers (SBCs), e.g., Raspberry Pi (RPi)), with different features. Usually these devices run a coarse version of a Linux operating system. Nevertheless, there are many scenarios that require enhanced computational power that these nodes alone are unable to provide. In this context, we need to introduce a kind of collaboration among the devices to overcome their constraints. We based our solution in a combination of clustering techniques (building a mesh network using their wireless capabilities); at th...

Sensors

The paradigm of the Internet of everything (IoE) is advancing toward enriching people’s lives by adding value to the Internet of things (IoT), with connections among people, processes, data, and things. This paper provides a survey of the literature on IoE research, highlighting concerns in terms of intelligence services and knowledge creation. The significant contributions of this study are as follows: (1) a systematic literature review of IoE taxonomies (including IoT); (2) development of a taxonomy to guide the identification of critical knowledge in IoE applications, an in-depth classification of IoE enablers (sensors and actuators); (3) validation of the defined taxonomy with 50 IoE applications; and (4) identification of issues and challenges in existing IoE applications (using the defined taxonomy) with regard to insights about knowledge processes. To the best of our knowledge, and taking into consideration the 76 other taxonomies compared, this present work represents the mo...

Sustainability

The Internet of Things (IoT) plays a vital role in interconnecting physical and virtual objects that are embedded with sensors, software, and other technologies intending to connect and exchange data with devices and systems around the globe over the Internet. With a multitude of features to offer, IoT is a boon to mankind, but just as two sides of a coin, the technology, with its lack of securing information, may result in a big bane. It is estimated that by the year 2030, there will be nearly 25.44 billion IoT devices connected worldwide. Due to the unprecedented growth, IoT is endangered by numerous attacks, impairments, and misuses due to challenges such as resource limitations, heterogeneity, lack of standardization, architecture, etc. It is known that almost 98% of IoT traffic is not encrypted, exposing confidential and personal information on the network. To implement such a technology in the near future, a comprehensive implementation of security, privacy, authentication, an...

Studies in Big Data

With the introduction of the concept of Internet of things, a centralized cloud computing was born to counter the lack of processing power and complexity of design of the IoT sensor environment station devices. This worked for a while, but, because of the physical limitations of data transfer speeds over long distances, it has recently been failing to deliver positive results in real time latency-based services. To compliment the cloud's drawbacks and to bring computation close to the nodes (also called Edge Computing) while utilizing every bit of computational power offered by the complete network, fog computing has emerged as a compromise between cloud and edge reducing wastage of resources and increasing communication, relay speeds for the transmission and exchange of Data. Fog Data Analytics is the analysis of the mechanisms and collaborations developed in the network for communication and computation between Edge, Fog, and Cloud layers. The relevance of customization of grounds of comparison for the implementation in different fields warrants a generalization of the judgement criteria i.e., there is no single ideal approach for implementation and thus standardizing the architecture to be implemented is shortsighted and hence a broader explanation is important. This book chapter gives an introduction to Fog Data Analytics, an explanation of the advantages and drawbacks present in the existing system i.e., the motivation for incorporating Fog and methods used to solve some of the issues.

Journal of Cloud Computing

Internet of Things (IoT) has posed new requirements to the underlying processing architecture, specially for real-time applications, such as event-detection services. Complex Event Processing (CEP) engines provide a powerful tool to implement these services. Fog computing has raised as a solution to support IoT real-time applications, in contrast to the Cloud-based approach. This work is aimed at analysing a CEP-based Fog architecture for real-time IoT applications that uses a publish-subscribe protocol. A testbed has been developed with low-cost and local resources to verify the suitability of CEP-engines to low-cost computing resources. To assess performance we have analysed the effectiveness and cost of the proposal in terms of latency and resource usage, respectively. Results show that the fog computing architecture reduces event-detection latencies up to 35%, while the available computing resources are being used more efficiently, when compared to a Cloud deployment. Performanc...

Trends and Innovations in Information Systems and Technologies, 2020

This paper presents an efficient, battery-powered, low-cost, and context-aware IoT edge computing solution tailored for monitoring a real enterprise cooking oil collecting infrastructure. The presented IoT solution allows the collecting enterprise to monitor the amount of oil deposited in specific barrels, deployed country-wide around several partner restaurants. The paper focuses on the specification, implementation, deployment and testing of ESP32 /ESP8266-based end-node components deployed as an edge computing monitoring infrastructure. The achieved low-cost solution guarantees more than a year of battery life, reliable data communication, and enables automatic over-the-air end-node updates. The open-source software libraries developed for this project are shared with the community and may be applied in scenarios with similar requirements.

Journal of Cloud Computing, 2022

Background The Internet of Things (IoT) enables the development of innovative applications in various domains such as healthcare, transportation, and Industry 4.0. Publish-subscribe systems enable IoT devices to communicate with the cloud platform. However, IoT applications need context-aware messages to translate the data into contextual information, allowing the applications to act cognitively. Besides, end-to-end security of publish-subscribe messages on both ends (devices and cloud) is essential. However, achieving security on constrained IoT devices with memory, payload, and energy restrictions is a challenge. Contribution Messages in IoT need to achieve both energy efficiency and secure delivery. Thus, the main contribution of this paper refers to a performance evaluation of a message structure that standardizes the publish-subscribe topic and payload used by the cloud platform and the IoT devices. We also propose a standardization for the topic and payload for publish-subscri...

Wireless Communications and Mobile Computing, 2021

The technological advent in smart sensing devices and the Internet has provided practical solutions in various sectors of networking, public and private sector industries, and government organizations worldwide. This study intends to combine the Internet of Things (IoT) technology with health monitoring to make it personalized and timely through allowing the interconnection between the devices. This work is aimed at exploring various wearable health monitoring modules that people wear to monitor heart rate, blood pressure, pulse, body temperature, and physiological information. The information is acquired using the wireless sensor to create a health monitoring system. The data is integrated using the Internet of Things for processing, connecting, and computing to achieve real-time monitoring. The temperature of three people measured by the temperature thermometer is 36.4, 36.7, and 36.5 (°C), respectively, and the average acquired by the monitoring system of the three people is 36.5...

PeerJ Computer Science, 2021

The Internet of Things (IoT) has penetrating all things and objects around us giving them the ability to interact with the Internet, i.e., things become Smart Things (SThs). As a result, SThs produce massive real-time data (i.e., big IoT data). Smartness of IoT applications bases mainly on services such as automatic control, events handling, and decision making. Consumers of the IoT services are not only human users, but also SThs. Consequently, the potential of IoT applications relies on supporting services such as searching, retrieving, mining, analyzing, and sharing real-time data. For enhancing search service in the IoT, our previous work presents a promising solution, called Cluster Representative (ClRe), for indexing similar SThs in IoT applications. ClRe algorithms could reduce similar indexing by O(K − 1), where K is number of Time Series (TS) in a cluster. Multiple extensions for ClRe algorithms were presented in another work for enhancing accuracy of indexed data. In this ...

Electronics

Technological advancements have made it possible to monitor, diagnose, and treat patients remotely. The vital signs of patients can now be collected with the help of Internet of Things (IoT)-based wearable sensor devices and then uploaded on to a fog server for processing and access by physicians for recommending prescriptions and treating patients through the Internet of Medical Things (IoMT) devices. This research presents the outcome of a survey conducted on healthcare integrated with fog computing and IoT to help researchers understand the techniques, technologies and performance parameters. A comparison of existing research focusing on technologies, procedures, and findings has been presented to investigate several aspects of fog computing in healthcare IoT-based systems, such as increased temporal complexity, storage capacity, scalability, bandwidth, and latency. Additionally, strategies, tools, and sensors used in various diseases such as heart disease, chronic disease, chiku...

AGRIVOLTAICS2021 CONFERENCE: Connecting Agrivoltaics Worldwide

The Internet of Things (IoT) has developed into a major infrastructure that links a large variety of peripherals. It is a technology that helps end-users to access digital content from anywhere. For mission-critical situations, IoT applications must follow stringent performance criteria such as scalability, stability, and privacy. To meet these criteria, IoT needs assistance from related supporting techniques like cloud, edge, virtualization, and 5G technologies. The accuracy and efficacy of two existing IoT models are compared in this study: An existing cloud IoT model, a MEC-based and local edge cloud (EC)IoT model, was simulated using iFogSim. According to the findings, a multi-tier edge-IoT structure capable of maximizing the processing capacity of each of the three tiers is a cost-effective strategy for lowering energy consumption, increasing computing power, and lowering operating costs in critical IT operations.

Cybernetics and Information Technologies

The Fog computing concept has been introduced to aid in the data processing of Internet of things applications using Cloud computing. Due to the profitable benefits of this combination, several papers have lately been published proposing the deployment of Blockchain alongside Fog computing in a variety of fields. A comprehensive evaluation and synthesis of the literature on Blockchain-Fog computing integration applications that have emerged in recent years is required. Although there have been several articles on the integration of Blockchain with Fog computing, the applications connected with this combination are still fragmented and require further exploration. Hence, in this paper, the applications of Blockchain-Fog computing integration are identified using a systematic literature review technique and tailored search criteria generated from the study objectives. This article found and evaluated 144 relevant papers. The findings of this article can be used as a resource for futur...

Sensors

It is well known that power plants worldwide present access to difficult and hazardous environments, which may cause harm to on-site employees. The remote and autonomous operations in such places are currently increasing with the aid of technology improvements in communications and processing hardware. Virtual and augmented reality provide applications for crew training and remote monitoring, which also rely on 3D environment reconstruction techniques with near real-time requirements for environment inspection. Nowadays, most techniques rely on offline data processing, heavy computation algorithms, or mobile robots, which can be dangerous in confined environments. Other solutions rely on robots, edge computing, and post-processing algorithms, constraining scalability, and near real-time requirements. This work uses an edge-fog computing architecture for data and processing offload applied to a 3D reconstruction problem, where the robots are at the edge and computer nodes at the fog....

Research Square (Research Square), 2023

With the development of the Internet of Things (IoT) technology, a vast amount of the IoT data is generated by mobile applications from mobile devices. Cloudlets provide a paradigm that allows the mobile applications and the generated IoT data to be offloaded from the mobile devices to the cloudlets for processing and storage through the access points (APs) in the Wireless Metropolitan Area Networks (WMANs). However, achieving the goal of optimizing resource utilization, latency, and reliability for WMAN with cloudlet Usability is still a challenge, which in this dissertation aims to optimize these targets with cloudlet Usability. In this dissertation, load unloading strategy in wireless networks of urban areas is analyzed and modeled as a multiobjective optimization problem. Multi-objective problem solving is optimized by the NSDE (Nondominated Sorting Differential Evolution) algorithm and the diversity and convergence of the population are ensured through the mutation and crossover operations. In the individual selection phase, NSDE uses the fast nondominated sorting approach and the crowded-comparison operator to ensure that individuals with the relatively best fitness values in the current population can be preserved for the next generation. Finally, the results of the proposed method were compared and evaluated based on the three criteria of resource utilization, latency and reliability with the results obtained from the genetic algorithm and particle swarm accumulation and Hungarian Algorithm. Experimental results show that the proposed method is effective and efficient. The accuracy of the proposed method compared to the Hungarian algorithm with the criteria of resource utilization and latency and reliability are 23.2%, 26.6% and 21.8%, respectively, and compared to the genetic algorithm is 5.8%, 12.4% and 11.3%, respectively.

Future Internet, 2020

The lifelong monitoring and analysis for complex industrial equipment demands a continuously evolvable machine-learning platform. The machine-learning model must be quickly regenerated and updated. This demands the careful orchestration of trainers for model generation and modelets for model serving without the interruption of normal operations. This paper proposes a container-based Continuous Machine-Learning and Serving (CMS) platform. By designing out-of-the-box common architecture for trainers and modelets, it simplifies the model training and deployment process with minimal human interference. An orchestrator is proposed to manage the trainer's execution and enables the model updating without interrupting the online operation of model serving. CMS has been deployed in a 1000 MW thermal power plant for about five months. The system running results show that the accuracy of eight models remains at a good level even when they experience major renovations. Moreover, CMS proved to be a resource-efficient, effective resource isolation and seamless model switching with little overhead.

Real-Time Systems

Technological advances in embedded systems and the advent of fog computing led to improved quality of service of applications of cyber-physical systems. In fact, the deployment of such applications on powerful and heterogeneous embedded systems, such as multiprocessors system-on-chips (MPSoCs), allows them to meet latency requirements and real-time operation. Highly relevant to the industry and our reference case-study, the challenging field of nuclear fusion deploys the aforementioned applications, involving high-frequency control with hard real-time and safety constraints. The use of fog computing and MPSoCs is promising to achieve safety, low latency, and timeliness of such control. Indeed, on one hand, applications designed according to fog computing distribute computation across hierarchically organized and geographically distributed edge devices, enabling timely anomaly detection during high-frequency sampling of time series, and, on the other hand, MPSoCs allow leveraging fog...