Applications of Fog Computing in Video Streaming

The purpose of this paper is to show the viability of fog computing in the area of video streaming in vehicles. With the rise of autonomous vehicles, there needs to be a viable entertainment option for users. The cloud fails to address these options due to latency problems experienced during high internet traffic. To improve video streaming speeds, fog computing seems to be the best option. Fog computing brings the cloud closer to the user through the use of intermediary devices known as fog nodes. It does not attempt to replace the cloud but improve the cloud by allowing faster upload and download of information. This paper explores two algorithms that would work well with vehicles and video streaming. This is simulated using a Java application, and then graphically represented. The results showed that the simulation was an accurate model and that the best algorithm for request history maintenance was the variable model

Hybrid-Vehfog: A Robust Approach for Reliable Dissemination of Critical Messages in Connected Vehicles

Vehicular Ad-hoc Networks (VANET) enable efficient communication between vehicles with the aim of improving road safety. However, the growing number of vehicles in dense regions and obstacle shadowing regions like Manhattan and other downtown areas leads to frequent disconnection problems resulting in disrupted radio wave propagation between vehicles. To address this issue and to transmit critical messages between vehicles and drones deployed from service vehicles to overcome road incidents and obstacles, we proposed a hybrid technique based on fog computing called Hybrid-Vehfog to disseminate messages in obstacle shadowing regions, and multi-hop technique to disseminate messages in non-obstacle shadowing regions. Our proposed algorithm dynamically adapts to changes in an environment and benefits in efficiency with robust drone deployment capability as needed. Performance of Hybrid-Vehfog is carried out in Network Simulator (NS-2) and Simulation of Urban Mobility (SUMO) simulators. The results showed that Hybrid-Vehfog outperformed Cloud-assisted Message Downlink Dissemination Scheme (CMDS), Cross-Layer Broadcast Protocol (CLBP), PEer-to-Peer protocol for Allocated REsource (PrEPARE), Fog-Named Data Networking (NDN) with mobility, and flooding schemes at all vehicle densities and simulation times

A Secure Fog-based Platform for SCADA-based IoT Critical Infrastructure

The rapid proliferation of Internet of Things (IoT) devices, such as smart meters and water valves, into industrial critical infrastructures and control systems has put stringent performance and scalability requirements on modern Supervisory Control and Data Acquisition (SCADA) systems. While cloud computing has enabled modern SCADA systems to cope with the increasing amount of data generated by sensors, actuators and control devices, there has been a growing interest recently to deploy edge datacenters in fog architectures to secure low-latency and enhanced security for mission-critical data. However, fog security and privacy for SCADA-based IoT critical infrastructures remains an under-researched area. To address this challenge, this contribution proposes a novel security “toolbox” to reinforce the integrity, security, and privacy of SCADA-based IoTcritical infrastructure at the fog layer. The toolbox incorporates a key feature: a cryptographic-based access approach to the cloud services using identity-based cryptography and signature schemes at the fog layer. We present the implementation details of a prototype for our proposed Secure Fog-based Platform (SeFoP) and provide performance evaluation results to demonstrate the appropriateness of the proposed platform in a real-world scenario. These results can pave the way towards the development of more secured and trusted SCADA-based IoT critical infrastructure, which is essential to counter cyber threats against next-generation critical infrastructure and industrial control systems. The results from the experiments demonstrate a superior performance of SeFoP, which is around 2.8 seconds when adding 5 virtual machines (VMs), 3.2 seconds when adding 10 VMs, and 112 seconds when adding 1000 VMs compared to Multi-Level user Access Control (MLAC) platform

ROUTER:Fog Enabled Cloud based Intelligent Resource Management Approach for Smart Home IoT Devices

There is a growing requirement for Internet of Things (IoT) infrastructure to ensure low response time to provision latency-sensitive real-time applications such as health monitoring, disaster management, and smart homes. Fog computing offers a means to provide such requirements, via a virtualized intermediate layer to provide data, computation, storage, and networking services between Cloud datacenters and end users. A key element within such Fog computing environments is resource management. While there are existing resource manager in Fog computing, they only focus on a subset of parameters important to Fog resource management encompassing system response time, network bandwidth, energy consumption and latency. To date no existing Fog resource manager considers these parameters simultaneously for decision making, which in the context of smart homes will become increasingly key. In this paper, we propose a novel resource management technique (ROUTER) for fog-enabled Cloud computing environments, which leverages Particle Swarm Optimization to optimize simultaneously. The approach is validated within an IoT-based smart home automation scenario, and evaluated within iFogSim toolkit driven by empirical models within a small-scale smart home experiment. Results demonstrate our approach results a reduction of 12% network bandwidth, 10% response time, 14% latency and 12.35% in energy consumption

A Survey on IoT Fog Resource Monetization and Deployment Models

There has been an immense growth in the number of applications of devices using the Internet of Things (IoT). Fog nodes (FN) are used between IoT devices and cloud computing in fog computing (FC) architecture. Indeed, an IoT application can be fully serviced by local fog servers without propagating IoT data into the cloud core network. FC extends the cloud-computing paradigm to the network edge. This paper surveys fog resources monetization and the wide use of IoT devices in making FC a paramount technology necessary to achieve real-time computation of IoT devices. We looked into the monetization architectures applied by various literature. We found that the decentralization fog monetization architecture stands out since it solves some issues posed by centralized fog monetization architecture, such as QoS and additional fee costs by third parties payment gateway

An efficient indexing model for the fog layer of industrial Internet of Things.

Fog Computing is gaining popularity and is being increasingly deployed in various latency-sensitive application domains including industrial IoTs. However, efficient discovery of services is one of the prevailing issues in the fog nodes of indus-trial IoTs which restrain their efficiencies in availing appropriate services to the clients. To address this issue, this paper proposes a novel effi-cient multilevel index model based on equivalence relation, named the DM-index model, for service maintenance and retrieval in the fog layer of industrial IoTs to eliminate redundancy, narrow the search space, reduce both the traversed number of services and retrieval time, ultimately to improve the service discovery efficiency. The efficiency of the proposed index model has been verified theoretically and evaluated experimentally, which demonstrates that the proposed model is effective in achieving much better service discovery and retrieval performance than the sequential and inverted index models.N/

A secure fog-based platform for SCADA-based IoT critical infrastructure

© 2019 John Wiley & Sons, Ltd. The rapid proliferation of Internet of things (IoT) devices, such as smart meters and water valves, into industrial critical infrastructures and control systems has put stringent performance and scalability requirements on modern Supervisory Control and Data Acquisition (SCADA) systems. While cloud computing has enabled modern SCADA systems to cope with the increasing amount of data generated by sensors, actuators, and control devices, there has been a growing interest recently to deploy edge data centers in fog architectures to secure low-latency and enhanced security for mission-critical data. However, fog security and privacy for SCADA-based IoT critical infrastructures remains an under-researched area. To address this challenge, this contribution proposes a novel security “toolbox” to reinforce the integrity, security, and privacy of SCADA-based IoT critical infrastructure at the fog layer. The toolbox incorporates a key feature: a cryptographic-based access approach to the cloud services using identity-based cryptography and signature schemes at the fog layer. We present the implementation details of a prototype for our proposed secure fog-based platform and provide performance evaluation results to demonstrate the appropriateness of the proposed platform in a real-world scenario. These results can pave the way toward the development of a more secure and trusted SCADA-based IoT critical infrastructure, which is essential to counter cyber threats against next-generation critical infrastructure and industrial control systems. The results from the experiments demonstrate a superior performance of the secure fog-based platform, which is around 2.8 seconds when adding five virtual machines (VMs), 3.2 seconds when adding 10 VMs, and 112 seconds when adding 1000 VMs, compared to the multilevel user access control platform

A Review on Fog Computing Systems

The current decade has witnessed a wide deployment of Internet of Things (IoT) technology in various application domains, and its pervasive role will continue to strengthen in the future. For dealing with a vast number of connected devices and the big data generated by them, an efficient computing platform is required. Fog computing has been proposed as a solution. It is a paradigm extending cloud computing and services to the edge of the network, thus reducing the latency of dynamic decision making and improving real-time performance in general. This paper provides a view on the current state-of-the-art research in the area of fog computing and internet of things (IoT) technology. </p