Evaluation of metaheuristic optimization based data aggregation scheme for fog enabled IOT environment

Abstract

newlineInternet of Things (IoT) is becoming a novel device to device communication technology nowadays. However, due to the miniaturized hardware, limited functioning capability and memory capacity IoT faces several challenging issues. Sensors and WSN are becoming the major components for constructing IoT. Since sensor nodes are working with battery power, it becomes very tough to execute the critical processes that consume more energy. Therefore, it is very much essential to remove the duplicate data before communicating to the base station. Fog computing is a promising technology that has been emerged to handle the growth of smart devices as well as the popularity of latency-sensitive and location-awareness Internet of Things (IoT) services. After the emergence of IoT-based services, the industry of internet-based devices has grown. The number of these devices has raised from millions to billions, and it is expected to increase further in the near future. In fog computing, distributed fog server closeness to the terminal devices allows upcoming and outgoing data to be transmitted effectually. But the increasing size of fog enabled IoT environments leads to the design of effective routing schemes to accomplish minimum delay and bandwidth. Thus, additional challenges will be added to the traditional centralized cloud-based architecture as it will not be able to handle that growth and to support all connected devices in real-time without affecting the user experience. At the same time, data aggregation is employed to gather the data and accumulate it for removing repetitive data and conserving energy. Conventional data aggregation models for Fog enabled IoT environments possess high computational complexity and communication cost. The goal of data aggregation is to reduce quantity of data dissemination and extend iv lifetime. The Compressed Sensing (CS) theory is employed in the fog enabled IoT environment. Therefore, in order to resolve the issues and improve the lifetime of the network. With the above limi