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Provides support to a broad range of industrial applications due to instant response capability It will be located at the edge of network with rich and heterogeneous end-user support According to, a Fog system has the following characteristics: For example, consider IoT devices in the medical domain where the latency of acting on the sensed data could be life-critical.Ĭisco pioneered the delivery of the Fog computing model that extends and brings the Cloud platform closer to end-user’s device to resolve aforementioned issues. Furthermore, such applications generate large volumes of varied data in a high velocity, and by the time data reaches a cloud system for analysis, the chance to inform the IoT device to take reactive action may be gone.
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Latency depends on the speed of Internet connection, resource contention among guest virtual machines (VM) and has been shown to increase with distance. Many cloud services are available in current commercial solutions, but they are not suitable for latency, portability and location-sensitive applications, such as IoT, Wearable computing, Smart Grids, Connected Vehicles and Software-Defined-Networks.
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Ĭloud computing provides many benefits to individuals and organizations through offering highly available and efficient computing resources with an affordable price. This new paradigm is named Fog computing, initially and formally introduced by Cisco. This platform is capable of filtering, aggregating, processing, analysing and transmitting data, and will result in saving time and communication resources. This is achieved by creating a new hierarchically distributed and local platform between the Cloud system and end-user devices, as shown in Fig. The Fog paradigm aims to provide a scalable decentralised solution for this issue. If a server was to become overloaded in a traditional client-server architecture, then many devices could be rendered unusable. This can present scalability and reliability issues when utilising a standard client-server architecture, where data is sensed by the client and processed by the server. These devices need computing resources to process the acquired data however, fast decision processes are also required to maintain a high-level of functionality. IoT devices provide rich functionality, such as connectivity, and the development of new functionality is often data motivated. The Fog computing paradigm is largely motivated by a continuous increase in Internet of Things (IoT) devices, where an ever increasing amount of data (with respect to volume, variety, and velocity ) is generated from an ever-expanding array of devices. This results in the minimisation of data transmission overheads, and subsequently, improves the performance of computing in Cloud platforms by reducing the requirement to process and store large volumes of superfluous data. This paper also determines the impact of those security issues and possible solutions, providing future security-relevant directions to those responsible for designing, developing, and maintaining Fog systems.įog computing is a decentralized computing architecture whereby data is processed and stored between the source of origin and a cloud infrastructure. The majority of Fog applications are motivated by the desire for functionality and end-user requirements, while the security aspects are often ignored or considered as an afterthought. Similar technologies like Edge computing, Cloudlets and Micro-data centres have also been included to provide a holistic review process. This paper surveys existing literature on Fog computing applications to identify common security gaps. This wide range of functionality driven applications intensifies many security issues regarding data, virtualization, segregation, network, malware and monitoring. For example, Internet of Things (IoT) devices are required to quickly process a large amount of data. These features make the Fog platform highly suitable for time and location-sensitive applications. In addition, Fog systems are capable of processing large amounts of data locally, operate on-premise, are fully portable, and can be installed on heterogeneous hardware. It can be described as a cloud-like platform having similar data, computation, storage and application services, but is fundamentally different in that it is decentralized.
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Fog computing is a new paradigm that extends the Cloud platform model by providing computing resources on the edges of a network.