Distributed Intelligence at the Edge on IoT Networks

Alam, Tanweer; Rababah, Baha; Ali, Arshad; Qamar, Shamimul

doi:10.33166/aetic.2020.05.001

Cited by 11 publications

(7 citation statements)

References 90 publications

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“…Theoretically, it is in line with the concept was developed (Lai, 2017). TAM focuses on the perceived usefulness of the core concept that represents the user's subjective perception of IT in the performance capacity of completing various tasks (Alam et al, 2020). Individual subjective perceptions of the ease of IT systems impact profits, which indirectly have a rapid impact on technology users.…”

Section: Discussionmentioning

confidence: 99%

The Study of Perceived Risk and E-Service Convenience Towards Satisfaction and Trust of Online Academic Users in Indonesia

2021

International Journal of Media and Information Literacy

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The modernization in information technology (IT) has influenced the changes in the education industry. IT Utilization has provided users with many benefits. There are issues of security and privacy arising. This exploration examines the perceived risk and the e-service convenience of the satisfaction and trust of academic-online users at the University of Indonesia. Data collected by distributing the questionnaires to 220 respondents at two state universities and one private university in Indonesia. The sampling method applied from the convenience and purposive sampling technique, which is distributed to users, namely students, lecturers, and administrative staff. The data analyzed using path analysis. A results show that decision convenience, transaction convenience, and post-benefit convenience have a significant effect on academic-online user satisfaction. There is no influence of other factors such as perceived risk, access convenience, and benefit convenience on user satisfaction academic-online at college. This research also proves that satisfaction has a positive influence on user trust.

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Section: Discussionmentioning

confidence: 99%

The Study of Perceived Risk and E-Service Convenience Towards Satisfaction and Trust of Online Academic Users in Indonesia

2021

International Journal of Media and Information Literacy

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“…These edge devices process, filter, and analyze the incoming data in real-time, extracting actionable insights and making autonomous decisions based on predefined rules or machine learning algorithms. The processed data may then be transmitted to centralized cloud servers for further analysis, long-term storage, or integration with other enterprise systems (Alam, et al, 2020;Porambage, et al, 2018). The conceptual framework of edge computing within IoT emphasizes the importance of proximity, scalability, and autonomy in enabling efficient data processing, low-latency communication, and seamless integration with existing IT infrastructure (Angel, et al, 2021;Douch, et al, 2022).…”

Section: Integration Of Edge Computing and Iotmentioning

confidence: 99%

Current state and prospects of edge computing within the Internet of Things (IoT) ecosystem

Enoch Oluwademilade Sodiya,

Uchenna Joseph Umoga,

Alexander Obaigbena

et al. 2024

Int. J. Sci. Res. Arch.

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The burgeoning growth of the Internet of Things (IoT) has prompted a paradigm shift in computing architectures, leading to the emergence and rapid evolution of edge computing. This review delves into the current state and prospects of edge computing within the IoT ecosystem, exploring its significance, challenges, and future potential. Edge computing, characterized by decentralized data processing at or near the source of data generation, has gained substantial traction owing to its ability to address critical concerns such as latency, bandwidth consumption, and privacy issues inherent in centralized cloud-based systems. By enabling data processing closer to the point of collection, edge computing minimizes latency and ensures real-time responses, making it indispensable for latency-sensitive applications like industrial automation, autonomous vehicles, and healthcare. The integration of edge computing with IoT devices has facilitated the creation of distributed computing architectures capable of handling massive data volumes generated by interconnected devices. This convergence enables efficient data aggregation, analysis, and decision-making at the network's edge, reducing the burden on centralized cloud infrastructure and optimizing resource utilization. Despite its numerous advantages, edge computing faces several challenges, including resource constraints, security vulnerabilities, and interoperability issues. Resource-constrained edge devices often lack the computational power and storage capacity required for complex analytics, necessitating innovative approaches to resource management and workload distribution. Moreover, the distributed nature of edge environments introduces new security risks, necessitating robust security measures to safeguard sensitive data and mitigate cyber threats. Looking ahead, the prospects of edge computing within the IoT ecosystem are promising, with advancements in edge hardware, software, and networking technologies driving innovation and adoption. Edge computing is poised to play a pivotal role in enabling the next wave of IoT applications, ranging from smart cities and autonomous systems to immersive experiences and personalized services. However, realizing the full potential of edge computing requires concerted efforts from industry stakeholders to address existing challenges and foster ecosystem-wide collaboration. The convergence of edge computing and IoT holds immense potential to revolutionize industries, reshape computing architectures, and empower a new era of intelligent, responsive, and decentralized systems.

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“…In addition, it brings together the industry to deliver high-level smart application-type applications such as emergency control, safety control, and transfer as well as property, health, and environmental management [48]. It also brings together the industry to deliver strategic management for all smart-type solutions [49].…”

Section: Application Layermentioning

confidence: 99%

Internet of things: review, architecture and applications

Alam

2022

Comput Sci Inf Technol

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Devices linked to the internet of things (IoT) may communicate with one another in several settings. Furthermore, rather of relying on an existing centralized system, users may develop their own network by using wireless capabilities. This kind of network is known as a wireless mobile ad hoc network. The mobile ad-hoc network (MANET) enables IoT devices to connect with one another in an unstructured networked environment. IoT devices may connect, establish linkages, and share data on a continuous basis. In this system, the cloud's purpose is to store and analyze data acquired from IoT devices. One of the most significant challenges in cloud computing has been identified as information security, and its resolution will result in an even bigger increase in cloud computing usage and popularity in the future. Finally, the goal of this project is to create a framework for facilitating communication between IoT devices in a Cloud and MANET context. Our major contribution is a ground-breaking research initiative that combines cloud computing with the MANET and connects the internet of things. This research might be used to the IoT in the future.

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Distributed Intelligence at the Edge on IoT Networks

Cited by 11 publications

References 90 publications

The Study of Perceived Risk and E-Service Convenience Towards Satisfaction and Trust of Online Academic Users in Indonesia

The Study of Perceived Risk and E-Service Convenience Towards Satisfaction and Trust of Online Academic Users in Indonesia

Current state and prospects of edge computing within the Internet of Things (IoT) ecosystem

Internet of things: review, architecture and applications

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