Green Internet of Things for Enterprises
Koduru Suresh1, PVGD Prasad Reddy2, Padala Pushkal3

1Koduru Suresh*, CSSE, Andhra University, Visakhapatnam, India.
2PVGD Prasad Reddy, CSSE, Andhra University, Visakhapatnam, India.
3Padala Pushkal, CSE, NIE, Mysore, India.
Manuscript received on July 10, 2019. | Revised Manuscript received on August 20, 2019. | Manuscript published on August 30, 2019. | PP: 4679-4681 | Volume-8 Issue-6, August 2019. | Retrieval Number: F9153088619/2019©BEIESP | DOI: 10.35940/ijeat.F9153.088619
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: Today digital transformation is playing a key role in many intelligent enterprises. Due to this there is a tremendous data exchange between internet of things which results in higher demand of bandwidth over communication network. Hence there is a need to utilize the bandwidth effectively which aids in reducing the greenhouse gas emissions in internet of things. Reducing the data size is one aspect that can be considered, to wisely utilize the network bandwidth. In this paper, a novel GWOICT (Grey Wolf Optimizer for Information and Communication Technology) algorithm is developed using jpeg baseline compression algorithm and grey wolf optimizer to reduce the size of images that enables to reduce the CO2 emissions while transferring data over a network of objects. The proposed technique has shown better results in terms of compressing the images and reducing CO2 emissions over the network for driving towards green internet of things in an enterprise.
Keywords: Green Internet of Things, Grey Wolf Optimization, Image Compression, CO2 Emissions.