Dnyanesh Mantri

Dr. Dnyanesh Mantri

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Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2015 in Computers and Electrical Engineering
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Journal Article
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DMDnyanesh Mantri
Dnyanesh Mantri
NPNeeli Rashmi Prasad
Neeli Rashmi Prasad
RPRamjee Prasad
Ramjee Prasad

26 July 2015 in Wireless Personal Communications
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DMDnyanesh Mantri
Dnyanesh Mantri
NPNeeli Rashmi Prasad
Neeli Rashmi Prasad
RPRamjee Prasad
Ramjee Prasad

1 February 2013
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Conference Paper
Closed access
DMDnyanesh Mantri
Dnyanesh Mantri
NPNeeli R Prasad
Neeli R Prasad
RPRamjee Prasad
Ramjee Prasad
In the application based WSN environment, energy and bandwidth of the sensor are valuable resources and need to utilize efficiently. Data aggregation at the sink by individual node causes flooding of the data which results in maximum energy consumption. To minimize this problem we propose and evaluate the group based data aggregation method, where grouping of nodes based on available data and correlation in the intra-cluster and grouping of cluster heads at the network level help to reduce the energy consumption. In addition, proposed method uses additive and divisible data aggregation function at cluster head (CH) as in-network processing to reduce energy consumption. Cluster head transmits aggregated information to remote sink and cluster head nodes transmit data to CH. Simulation result shows, proposed algorithm provides an improvement of 14.94% in energy consumption as compared with primary cluster based protocol LEACH which uses only one CH, it also improves the network stability.

1 December 2012
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Conference Paper
Closed access
DMDnyanesh Mantri
Dnyanesh Mantri
NPNeeli Rashmi Prasad
Neeli Rashmi Prasad
RPRamjee Prasad
Ramjee Prasad
SOShingo Ohmori
Shingo Ohmori
Wireless Sensor Network (WSN) is used for the monitoring and control applications where sensor nodes gather data and send it to the sink. Most of the energy of these nodes is consumed in transmission of data packets without aggregation to sink, which may be located at single or multi hop distance. The direct transmission of data packets to the sink from nodes in the network causes increased communication costs in terms of energy, average delay and network life time. In this context the data aggregation techniques minimize the communication cost with efficient bandwidth utilization by decreasing the packet count reached at the sink. Here we propose Two Tier Cluster based Data Aggregation (TTCDA) algorithm for the randomly distributed nodes to minimize computation and communication cost. The TTCDA is energy and bandwidth efficient, since it reduces the transmission of number of packets to the sink. It is based on the additive and divisible aggregation functions at Cluster head. The functions are applied according to data packets generated by each node by considering spatial and temporal correlation. The aggregation function used in TTCDA effectively reduces the packet count reported to the sink and prevent transmission of redundant data packets by improving energy consumption. The performance of algorithm is validated using examples and simulations.

1 August 2013
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Conference Paper
Closed access
DMDnyanesh Mantri
Dnyanesh Mantri
NPNeeli Rashmi Prasad
Neeli Rashmi Prasad
RPRamjee Prasad
Ramjee Prasad
The fundamental challenge in design of Wireless Sensor Network (WSNs) is proper utilization of resources which are scare. One of the critical challenges is to maximize the bandwidth utilization in data gathering from sensor nodes and forward to sink. The main design objective of this paper is to utilize the available bandwidth efficiently in terms of reduced packet delivery ratio and throughput. Bandwidth Efficient Heterogeneity aware Cluster based Data Aggregation (BHCDA) algorithm presents the solution for the effective data gathering with in-network aggregation. It considers the network with heterogeneous nodes in terms of energy and mobile sink to aggregate the data packets. It embodies the optimal approach by Intra and inter-cluster aggregation on the randomly distributed nodes with variable data generation rate while routing data to sink. It uses the correlation of data within the packet for applying the aggregation function on data generated by nodes. BHCDA shows significant improvement in packet delivery ratio (67.66 % & 19.62 %) and throughput (37.01 % & 17.16 %) as compared with the state-of-the-art solutions, Two Tier Cluster based Data Aggregation (TTCDA) and Energy Efficient Cluster based Data Aggregation (EECDA).

1 November 2013 in Wireless Personal Communications
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Journal Article
Closed access
PDF file
DMDnyanesh Mantri
Dnyanesh Mantri
NPNeeli Rashmi Prasad
Neeli Rashmi Prasad
RPRamjee Prasad
Ramjee Prasad