EBDS: An energy-efficient big data-based secure framework using Internet of Things for green environment

The Internet of Things (IoT) has a rapid growth in the development of smart and green environments. The IoT-based physical objects are interconnected with sensors, actuators, and data centers to gather, process and store the environmental data. The collected data is further utilized for post analysis and smarter decisions by the Base Station (BS). However, the limited resources of IoT-based sensors in terms of energy, processing, and transmission power place pressure on the development of green societies. Moreover, the IoT-based network also connects with big data using the Internet to manipulate and store a huge amount of data on the cloud. Therefore, along with the decreasing of energy consumption, security, and data integrity is other research concerns. Accordingly, an energy-efficient and big data-based secure framework using the Internet of Things for a green environment is presented. Firstly, the IoT-based sensors are connecting for data gathering and perform data routing using the Dijkstra-based optimal algorithm. Such a proposed algorithm imposes lower overheads and minimizes energy consumption in finding the most reliable and least transmission distance routes. Secondly, it also secures the generated big data from network attackers and maintains the consistency of the green environment. The experimental results reveal the EBDS framework increases the performance of green environment for energy consumption by 16%, packet drop ratio by 33%, network throughput by 13%, end-to-end delay by 15.5%, and route stability by 16% in non-uniform data traffic as compared to other work. (C) 2020 Elsevier B.V. All rights reserved.