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Top1. Introduction
The primary goal of the IoT is to bring everything online so that human participation is decreased, and the process becomes automated. IoT was initially proposed in 1999 by Kevin Ashton (Ashton, 2009), since then it has been gaining popularity and benefiting every aspect of human life. Smart cities (smart houses, smart buildings, smart surveillance) (Gharaibeh et al., 2017), smart healthcare (smart wearables, personal monitoring) (Catarinucci et al., 2015), commercial (shopping, retail), industrial automation (particularly production) (Atzori et al., 2010), and even agriculture (Elijah et al., 2018)(Brewster et al., 2017) have all benefited from the IoT in recent years. IoT is becoming increasingly important in today's digital age, resulting in a rapid increase in the number of connected devices (Middleton et al., 2015). Such widely distributed IoT devices at the network's edge will generate massive amounts of data. Increased bandwidth usage, delay, and network congestion are anticipated as a result of processing, analyzing, storing, and transmitting these huge amounts of data in the centralized cloud (Shi et al., 2016)(Shi & Dustdar, 2016). Furthermore, because cloud servers are located far from IoT end-user devices, cloud computing cannot meet the needs of IoT applications that demand real-time response, such as fire alarm warning systems, healthcare, and self-driving cars (Bangui et al., 2018)(Dastjerdi & Buyya, 2016).
Edge computing, which delivers services closer to IoT end-users, has become a popular paradigm in recent years for reducing network congestion. In edge computing, end-user IoT data is processed at the edge of the network as near to the originating source as possible. By providing services closer to IoT end-users, edge computing is serving real-time IoT applications without the need for high-speed Internet access (Satyanarayanan, 2017). Compared to cloud computing, edge computing offers advantages such as reduced network congestion, real-time response, and privacy. Edge computing architecture is displayed in Figure 1, which consists of three layers, namely the device layer, the edge computing layer, and the cloud computing layer.
Figure 1.
Edge computing architecture
Device Layer
The device layer includes all IoT devices such as sensors and actuators, security cameras, tablets, and mobile phones etc. All connected devices at this layer have a ubiquitous presence on the Internet.
Edge Computing Layer
At this layer edge nodes such as dedicated hardware, switches, routers, and small data centers act on the raw data. Edge nodes located at the edge computing layer are devices that can direct network traffic and have limited computing power. The data produced by the device layer is no longer transferred directly to the cloud computing layer but is instead processed and analyzed locally at the edge computing layer, providing real-time feedback to the end user.