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Instead of sensor nodes transferring all raw data to cloud computing, FNs can receive raw data from WSNs, aggregate it, do pre-processing, and store it temporarily.
FREMONT, CA: Wireless sensor networks (WSNs) of the next generation are expected to be used in the Internet of Things (IoT), which has completely transformed the existing technological landscape. Electronic gadgets like home appliances, medical equipment, different kinds of sensor nodes, and cameras may connect and interact with each other through the Internet. As a result, such devices have some limits, such as power, storage, computing power, and bandwidth.
The heterogeneity of the networks is created by the deployment of diverse types of sensor nodes in the areas of interest. Sensor components having varied capacities, like hardware specifications, identification, sensing type, communication capabilities, mode of operation, sensing rate, and frequency, make up heterogeneous sensor networks.
The network's heterogeneity allows for more outstanding deployment options while lowering overhead. The sensor nodes in the proposed scheme are divided into two types: low-end and high-end. The low-end nodes are standard sensor nodes with restricted processing and sensing capabilities, and they are in charge of data collection and transmission.
Sensors with high processing power, extensive communication ranges, and high throughput comprise the high-end nodes. Load balancing and network lifetime utilization can be achieved in a network with various sensor nodes. WSNs are widely utilized in modern society, notably for environmental monitoring in hydraulic power plants, car manufacture in the automobile sector, thermal energy in greenhouses, and forest monitoring. Sensor nodes in traditional WSNs send their raw data to a base station for analysis and storage.
WSNs can now send raw data to the cloud for processing and storage because to recent advancements in IoT technologies. This operation necessitates a lot of network traffic and depletes the energy of sensor nodes. Rather than sending the massive amount of sensed data created by the sensor nodes across the network and then processing it on a cloud computing platform, fog computing allows some processing to be done locally to the sensor networks. Networking devices like routers, proxy servers, set-top boxes, and gateways make up fog computing.
Such devices have more processing and storage capacity than sensor nodes. To acquire sensed data from nodes, they can be positioned between sensor nodes and cloud computing. This technology will reduce energy dissipation in sensor nodes during transmission and offer WSNs with low latency, position awareness, and high bandwidth. Cisco used the phrase "fog computing" to describe a method of overcoming cloud computing's constraints. Fog computing brings services closer to the people who utilize them. It is made up of fog nodes (FNs) that deliver resources at the network's edge. They have a lot of processing power and storage, and they can act as fog servers on the network.
The new technology is deployed at the network's edge. It provides end-users with various advantages, including effective network bandwidth usage, data security, fewer blockages, network latency reduction, improved dependability of transmitted sensed data, and faster analysis. To solve some of the limits of WSNs and take advantage of the advantages of fog computing, it has been integrated into the architectural model.
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