SHIVANAND C HIREMATH
Verified @gmail.com
Electronics and Communication
RESEARCH INTERESTS
Wireless Networks and Cloud Computing
7
Scopus Publications
Scopus Publications
- QoS based scheduling mechanism for electrical vehicles in cloud-assisted VANET using deep RNN
Shivanand C. Hiremath and Jayashree D. Mallapur
Springer Science and Business Media LLC - Optimization of Secured Cluster Based Charging Dynamics and Scheduling of EV Using Deep RNN
Shivanand C. Hiremath and Jayashree D. Mallapur
Springer Nature Singapore - SOCIAL SKI DRIVER BASED EFFICIENT PARKING DYNAMICS AND COMPUTATION USING DEEP REINFORCEMENT LEARNING IN VEHICULAR CLOUD
- Fractional-social ski driver optimization-driven routing protocol for routing electric vehicle under server hosted VANET
Shivanand C. Hiremath and Jayashree D. Mallapur
Springer Science and Business Media LLC - A Cloud-Interfaced Social Ski Driver Optimized routing and Charge scheduling for EV using deep RNN
Shivan C. Hiremath and Jayashree D. Mallapur
IEEE
The rejuvenation in the field of Electric Vehicles (EVs) has earned enormous interest among various researchers as the EVs are entitled to a remarkable mode of transportation in coming days. EVs are vital to conserve the conventional fuel, but EVs poses restrictions due to inadequate batteries leading to short distance travel and when battery charge nears at critical it becomes imperative to be aware of nearby charging stations (CS) and also there exist lesser charging strategies. Hence, drawing out two challenges, 1) Optimised routing to CS and 2) Charge scheduling mechanism at CS. Hence, A cloud-interfaced Vehicular Adhoc Network (VANET) model which enables communication between the vehicle traffic server, Road Side Units (RSUs) and various EVs on roads is used along with a meta-heuristic Social Ski Driver (SSD) algorithm as a new optimal routing for EVs to CS and further, charge scheduling is employed using dissimilar power configurations at CS for emergency and normal EVs. Hence, an optimal routing decision for EVs are made based on developed fitness function considering battery power, distance and traffic density computation using deep Recurrent Neural Network (RNN). First, cloud-interfaced routing decision is computed using SSD routing algorithm, Secondly charge scheduling mechanism is employed for EVs at CS using multi-objectives such as priority, delay and response time. The performance of the proposed Optimized Social Ski driver (O-SSD) is evaluated and compared with Particle Swarm Optimization (PSO). The devised scheme outperforms in all measures like traffic density, delay, success rate of allocation during (On-peak and Off-peak hours), total trip time and minimum battery power consumption with the values of 8.3 per lane, 7.80ms, (78% and 96%), 24.85min and 12486 joules respectively. - A Cloud Interfaced Social Ski Driver Optimized Routing for Future Electric Motor Vehicles
Shivanand C. Hiremath and Jayashree D. Mallapur
Springer Nature Singapore - Optimization of Parking Dynamics in Smart City using Cloud Networks
Shivanand C. Hiremath and Jayashree D. Mallapur
IEEE
The modern India is proposing and developing smart cities, so that Indian standard of living to grow and reach on par with other countries. The smart cities should be embedded with all new technologies such as sensors, environmental, cloud access, IoT interface, data acquisition, etc. In our proposed work, we are planning to interface cloud with a smart city traffic management. In metro cities people go to cluster area such as Temples, Shopping malls, Cine theatres, etc and waste time in searching parking lots and withdrawing themselves with no solutions. We have come up with the concept that uses smart dynamic parking provision mechanism that can be accessed before the hand at target place or nearby sub parking possibilities. This solution reduces traffic turbulence and pleasure of utilizing possible parking lots as alternate solution rather than withdrawal.