Dr. Dipali Kedar Shende

@pccoer.in

Assistant Professor,E & TC
PCCOER,Ravet



              

https://researchid.co/dkshende

RESEARCH, TEACHING, or OTHER INTERESTS

Electrical and Electronic Engineering, Engineering

6

Scopus Publications

Scopus Publications


  • Use of Improved Generative Adversarial Network (GAN) Under Insufficient Data
    Pallavi Adke, Ajay Kumar Kushwaha, Supriya M. Khatavkar, and Dipali Shende
    Springer Nature Switzerland

  • Performance evaluation and comparative analysis of CrowWhale-energy and trust aware multicast routing algorithm
    Dipali K. Shende and Yogesh S. Angal
    IOS Press
    Multipath routing helps to establish various quality of service parameters, which is significant in helping multimedia broadcasting in the Internet of Things (IoT). Traditional multicast routing in IoT mainly concentrates on ad hoc sensor networking environments, which are not approachable and vigorous enough for assisting multimedia applications in an IoT environment. For resolving the challenging issues of multicast routing in IoT, CrowWhale-energy and trust-aware multicast routing (CrowWhale-ETR) have been devised. In this research, the routing performance of CrowWhale-ETR is analyzed by comparing it with optimization-based routing, routing protocols, and objective functions. Here, the optimization-based algorithm, namely the Spider Monkey Optimization algorithm (SMO), Whale Optimization Algorithm (WOA), Dolphin Echolocation Optimization (DEO) algorithm, Water Wave Optimization (WWO) algorithm, Crow Search Algorithm (CSA), and, routing protocols, like Ad hoc On-Demand Distance Vector (AODV), CTrust-RPL, Energy-Harvesting-Aware Routing Algorithm (EHARA), light-weight trust-based Quality of Service (QoS) routing, and Energy-awareness Load Balancing-Faster Local Repair (ELB-FLR) and the objective functions, such as energy, distance, delay, trust, link lifetime (LLT) and EDDTL (all objectives) are utilized for comparing the performance of CrowWhale-ETR. In addition, the performance of CrowWhale-ETR is analyzed in terms of delay, detection rate, energy, Packet Delivery Ratio (PDR), and throughput, and it achieved better values of 0.539 s, 0.628, 78.42%, 0.871, and 0.759 using EDDTL as fitness.

  • An Iterative CrowWhale-Based Optimization Model for Energy-Aware Multicast Routing in IoT
    Dipali K. Shende, Yogesh S. Angal, and S.C. Patil.
    IGI Global
    This paper proposes an energy-aware multicast routing protocol (MRP) based on the optimization algorithm named iterative Crow Whale-Energy Trust routing (iterative CrowWhale-ETR). The CrowWhale-ETR is developed by including the historical terms from Taylor series in the CrowWhale optimization algorithm. Initially, the effective nodes for the multicast routing process are considered by measuring the trust and energy level of nodes. Based on the fitness factor, the protected nodes are selected relies on the trust and energy level of individual nodes. Once the secure nodes are selected, route detection and route selection is performed based on iterative CrowWhale-ETR. Finally, the route maintenance is done as per the remaining energy and trust factors of the nodes in the network. The comparative analysis of developed iterative CrowWhale-ETR is performed with the evaluation metrics, like energy, delay, throughput and detection rate using 50 and 100 nodes in the presence as well as absence of attacks.



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