Edge computing

About: Edge computing is a research topic. Over the lifetime, 11657 publications have been published within this topic receiving 148533 citations.

Fog Computing Architecture, Evaluation, and Future Research Directions

Abstract: IoT has been gaining a lot of attention in recent years. In fact, the number of connected devices has already surpassed the total population on Earth. Current developments in various technologies have paved the way for many IoT services that are now being deployed in different sectors. IoT can extend its scope and service provisioning capabilities with the integration of the cloud computing paradigm. Similarly, cloud cannot only access underlying IoT nodes and provide them with cloud services, but can also create further enhanced services based on the data collected from IoT nodes. However, IoT and sensor networks on the ground are often far from the cloud, which is normally accessible via the Internet. Some services require fast response and a great deal of pre-processing and filtering, and may also have security and privacy requirements. For all such cases, middleware, also known as fog, is required between the cloud and IoT devices. We present cloud-IoT integration issues followed by a comparison between fog and cloud computing. We evaluate the performance of fog computing using performance metrics such as processing delay, processing costs, and processing power, and derive the performance gains obtained in comparison to a cloud computing only approach. Finally, we identify some future research directions for fog computing.

A Smart Manufacturing Service System Based on Edge Computing, Fog Computing, and Cloud Computing

Abstract: The state-of-the-art technologies in new generation information technologies (New IT) greatly stimulate the development of smart manufacturing. In a smart manufacturing environment, more and more devices would be connected to the Internet so that a large volume of data can be obtained during all phases of the product lifecycle. Cloud-based smart manufacturing paradigm facilitates a new variety of applications and services to analyze a large volume of data and enable large-scale manufacturing collaboration. However, different factors, such as the network unavailability, overfull bandwidth, and latency time, restrict its availability for high-speed and low-latency real-time applications. Fog computing and edge computing extended the compute, storage, and networking capabilities of the cloud to the edge, which will respond to the above-mentioned issues. Based on cloud computing, fog computing, and edge computing, in this paper, a hierarchy reference architecture is introduced for smart manufacturing. The architecture is expected to be applied in the digital twin shop floor, which opens a bright perspective of new applications within the field of manufacturing.

Blockchain-Based Anonymous Authentication With Key Management for Smart Grid Edge Computing Infrastructure

Abstract: Achieving low latency and providing real-time services are two of several key challenges in conventional cloud-based smart grid systems, and hence, there has been an increasing trend of moving to edge computing. While there have been a number of cryptographic protocols designed to facilitate secure communications in smart grid systems, existing protocols generally do not support conditional anonymity and flexible key management. Thus, in this article, we introduce a blockchain-based mutual authentication and key agreement protocol for edge-computing-based smart grid systems. Specifically, leveraging blockchain, the protocol can support efficient conditional anonymity and key management, without the need for other complex cryptographic primitives. The security analysis shows that the protocol achieves reasonable security assurance, and the comparative summary for security and efficiency also suggests the potential of the proposed protocol in a smart grid deployment.

A Systematic Survey of Industrial Internet of Things Security: Requirements and Fog Computing Opportunities

Abstract: A key application of the Internet of Things (IoT) paradigm lies within industrial contexts. Indeed, the emerging Industrial Internet of Things (IIoT), commonly referred to as Industry 4.0, promises to revolutionize production and manufacturing through the use of large numbers of networked embedded sensing devices, and the combination of emerging computing technologies, such as Fog/Cloud Computing and Artificial Intelligence. The IIoT is characterized by an increased degree of inter-connectivity, which not only creates opportunities for the industries that adopt it, but also for cyber-criminals. Indeed, IoT security currently represents one of the major obstacles that prevent the widespread adoption of IIoT technology. Unsurprisingly, such concerns led to an exponential growth of published research over the last few years. To get an overview of the field, we deem it important to systematically survey the academic literature so far, and distill from it various security requirements as well as their popularity. This paper consists of two contributions: our primary contribution is a systematic review of the literature over the period 2011–2019 on IIoT Security, focusing in particular on the security requirements of the IIoT. Our secondary contribution is a reflection on how the relatively new paradigm of Fog computing can be leveraged to address these requirements, and thus improve the security of the IIoT.

Double Auction-Based Resource Allocation for Mobile Edge Computing in Industrial Internet of Things

Abstract: Mobile edge computing (MEC) yields significant paradigm shift in industrial Internet of things (IIoT), by bringing resource-rich data center near to the lightweight IIoT mobile devices (MDs). In MEC, resource allocation and network economics need to be jointly addressed to maximize system efficiency and incentivize price-driven agents, whereas this joint problem is under the locality constraints, i.e., an edge server can only serve multiple IIoT MDs in the vicinity constrained by its limited computing resource. In this paper, we investigate the joint problem of network economics and resource allocation in MEC where IIoT MDs request offloading with claimed bids and edge servers provide their limited computing service with ask prices. Particularly, we propose two double auction schemes with dynamic pricing in MEC, namely a breakeven-based double auction (BDA) and a more efficient dynamic pricing based double auction (DPDA), to determine the matched pairs between IIoT MDs and edge servers, as well as the pricing mechanisms for high system efficiency, under the locality constraints. Through theoretical analysis, both algorithms are proved to be budget-balanced, individual profit, system efficient, and truthful. Extensive simulations have been conducted to evaluate the performance of the proposed algorithms and the simulation results indicate that the proposed DPDA and BDA can significantly improve the system efficiency of MEC in IIoT.