Topic
Edge computing
About: Edge computing is a research topic. Over the lifetime, 11657 publications have been published within this topic receiving 148533 citations.
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TL;DR: A new bio-inspired optimization approach called Bees Life Algorithm (BLA) is proposed aimed at addressing the job scheduling problem in the fog computing environment and outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.
Abstract: Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running ap...
202 citations
TL;DR: This study presents a smart agriculture IoT system based on deep reinforcement learning which includes four layers, namely agricultural data collection layer, edge computing layer, agricultural data transmission layer, and cloud computing layer.
202 citations
TL;DR: This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices and discusses why the neuromorphic architectures are useful for edge devices and shows the advantages, drawbacks, and open problems in the field of neuromemristive circuits for edge computing.
Abstract: The volume, veracity, variability, and velocity of data produced from the ever increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks, and open problems in the field of neuromemristive circuits for edge computing.
201 citations
TL;DR: Numerical results indicate that the proposed privacy-preserved pseudonym management scheme effectively enhances location privacy and reduces communication overhead for the vehicles and a hierarchical architecture for the scheme is introduced in F-IoV.
Abstract: As a promising branch of Internet of Things, Internet of Vehicles (IoV) is envisioned to serve as an essential data sensing and processing platform for intelligent transportation systems. In this paper, we aim to address location privacy issues in IoV. In traditional pseudonym systems, the pseudonym management is carried out by a centralized way resulting in big latency and high cost. Therefore, we present a new paradigm named Fog computing supported IoV (F-IoV) to exploit resources at the network edge for effective pseudonym management. By utilizing abundant edge resources, a privacy-preserved pseudonym ( $P^{3}$ ) scheme is proposed in F-IoV. The pseudonym management in this scheme is shifted to specialized fogs at the network edge named pseudonym fogs, which are composed of roadside infrastructures and deployed in close proximity of vehicles. $P^{3}$ scheme has following advantages: 1) context-aware pseudonym changing; 2) timely pseudonym distribution; and 3) reduced pseudonym management overhead. Moreover, a hierarchical architecture for $P^{3}$ scheme is introduced in F-IoV. Enabled by the architecture, a context-aware pseudonym changing game and secure pseudonym management communication protocols are proposed. The security analysis shows that $P^{3}$ scheme provides secure communication and privacy preservation for vehicles. Numerical results indicate that $P^{3}$ scheme effectively enhances location privacy and reduces communication overhead for the vehicles.
200 citations