M.Tech, B-Tech

Dhivvya J. P. currently serves as Assistant Professor at the Department of Computer Science Engineering at Amrita School of Engineering, Amritapuri. She pursued her B. Tech. in Computer Science and Engineering  in 2007 and M. Tech. in Wireless Networks & Applications from Amrita Vishwa Vidyapeetham in 2017.


  • Instructor Excellence Advanced 2013 by Cisco
  • Instructor Excellence Expert 2015 by Cisco
  • Instructor Excellence Expert 2017 by Cisco
  • Instructor Excellence Expert 2018 by Cisco
  • Women in Networking 2018 by Cisco


Publication Type: Conference Paper

Year of Publication Title


K. Adarsh, Akshay, K. M. P., J. P. Dhivvya, Harikrishna, K. J., Simi, S., and Rao, S. N., “Analysis of Long Range Wi-Fi Backhaul Link in Maritime Environment”, in 2018 International Conference on Communication and Signal Processing (ICCSP), Chennai, India, 2018.[Abstract]

Marine fishermen in developing countries like India do not have an economically viable mode of communication during their long fishing trip which covers a distance more than 40 to 50km range. Project OceanNet fills this gap by including a novel heterogeneous network and provides a cost-effective solution of over the sea communication. The purpose of this work is to analyse the link quality of Long Range (LR) Wi-Fi backhaul link used in OceanNet, which is significant in improving the overall network throughput. This work compares and analyzes the link quality parameters of the hardware test bed with the results obtained from sea trial. This analysis is useful to develop a simulation platform for carrying out successful tests in improving the overall network performance.

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J. P. Dhivvya, Rao, S. N., and Simi, S., “Analysis of optimal backhaul link selection in a novel maritime communication network”, in 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET), Chennai, India, 2017.[Abstract]

Offshore fishing is serving as a major livelihood for millions of people around the world. OceanNet project aims at developing an effective, low-cost, long range communication system to provide internet connectivity at the sea. Wireless Backhaul network is formed by connecting Base Station (BS) in the shore to the Adaptive Backhaul Equipment (ABE) in the boats. The fishermen fishing in a particular fishing zone form a cluster. A mesh network is formed in the clusters to improve the connectivity. In this work, OceanNet Backhaul Link Selection (OBLS) algorithm is implemented in a hardware test-bed that models the OceanNet topology to assess the feasibility of using this in the off-shore boats. It also proposes and implements a controller as a static node in the Base Station network which analyzes the connectivity based on signal strength, noise floor and link quality and selects the best backhaul links by redirecting the route from Access Routers to the ABE having good Signal-to-noise (SNR) ratio to reach the Base Station. The throughput tests analyzed demonstrate that the packet delivery ratio is improved to a large extent after the application of the OBLS algorithm.

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J. P. Dhivvya, Jayakrishnan, V. M., Thomas, E. K., Dr. Maneesha V. Ramesh, and Divya, P., “Towards Energy Conservation in Campus using Wireless Sensor Network”, in 2017 IEEE Global Humanitarian Technology Conference (GHTC), 2017.[Abstract]

Educational institutions, should set a role model, in the reduction of the carbon foot print, to protect mother earth. In this paper we focus on designing a Wireless Sensor Network (WSN) based system, which can efficiently conserve the energy of class rooms and labs. We have identified temperature, light, pressure sensors to be utilized for this application. Infra Red receiver and transmitter is used to detect an event whether a person is leaving the room or not. Server room is checked for humidity, temperature, smoke by an integrated sensor, which sends the sensed data to the cloud. So all the sensors send the data periodically to the cloud, which processes the collected data and send the triggered response to the necessary output device and message the facility manager to take administrative actions. The status of each room in each floor is ultimately received at the central monitoring station at the ground floor of the building. The proposed system is designed in such a manner, it can be replicated cost-efficiently in multiple buildings within a campus by using low cost sensors and with the existing communication devices. Therefore this Green Campus System (GCS) design based on wireless sensor networks help in meeting the target of sustainable cities by reducing the overall energy consumption and improving the efficiency in the energy resource management

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J. P. Dhivvya, Rao, S. N., and Simi, S., “Towards maximizing throughput and coverage of a novel heterogeneous maritime communication network”, in Proceedings of the International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2017, vol. Part F129153.[Abstract]

Marine fishermen are unable to economically communicate either with other boats over the ocean or with the people on the shore due to the shortcomings in the available cellular and satellite communication. Project OceanNet bridges this gap to deploy a heterogeneous wireless communication system to provide internet access to the fishermen's smart phones in the boat helping them to reach out for help in critical situations. This work involves designing a wireless multi-hop backhaul network to extend the coverage and to improve the connectivity through an ad hoc mesh network between the access routers in different boats. Selecting the best path from the fishermen's end devices in the heterogeneous network can increase the throughput. The design and implementation of an elimination algorithm is dicussed to spectacle the improvement of the throughput and coverage. The algorithm is based on the analysis of the quality of various types of links using Signal-to-noise ratio(SNR) and Expected Transmission Count(ETX) metrics. The performance analysis in hardware test bed prove that the packet delivery ratio is substantially improved by the proposed path selection algorithm in the network. © 2017 Copyright is held by the owner/author(s).

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