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Singh, Daljeet
- Studies on Genetic Diversity in Growth, Yield and Quality Traits in Tomato (Lycopersicon esculentum Mill.)
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PDF Views:120
Authors
Affiliations
1 Department of Vegetable Crops, Punjab Agricultural University, Ludhiana-141 004, IN
2 Indian Institute of Horticulture Research, Hessaraghatta, Bangalore-560089, Karnataka, IN
3 Farm Advisory Service Scheme, Amritsar-143001, Punjab, IN
1 Department of Vegetable Crops, Punjab Agricultural University, Ludhiana-141 004, IN
2 Indian Institute of Horticulture Research, Hessaraghatta, Bangalore-560089, Karnataka, IN
3 Farm Advisory Service Scheme, Amritsar-143001, Punjab, IN
Source
Journal of Horticultural Sciences, Vol 8, No 1 (2013), Pagination: 21-24Abstract
Evaluation of 35 genotypes of tomato for yield, quality and fruit characters under net-house revealed that PCV was higher than GCV for most traits. High heritability, with moderate to high GCV and genetic gain, was recorded for number of fruits per plant, yield per plant, fruit weight, number of fruit-clusters per plant, polar diameter and number of flower-clusters per plant indicating, that, these characters could be improved by simple selection. Total yield per plant had positive and highly significant correlation with number of fruit-clusters per plant, number of flowerclusters per plant and fruit weight. Number of locules per fruit showed positive and significant correlation with fruit weight and equatorial diameter but, significant negative correlation with polar diameter. Maximum direct contribution to total yield per plant was made by number of fruits per plant, followed by number of locules per fruit.Keywords
Tomato, Heritability, PCV, GCV, Growth, Yield, Quality Traits.Full Text
- An Efficient Restricted Flooding Based Route Discovery (RFBRD) Scheme for AODV Routing
Abstract Views :77 |
PDF Views:1
Authors
Poonam T. Agarkar
1,
Manish D. Chawhan
2,
Rahul N. Nawkhare
3,
Daljeet Singh
4,
Narendra P. Giradkar
5,
Prashant R. Patil
6
Affiliations
1 Department of Electronics Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, (M.S), IN
2 Department of Electronics and Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, (M.S), IN
3 School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, IN
4 Center for Space Research, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, IN
5 Department of Electronics and Telecommunication Engineering, Smt. Radhikatai Pandav College of Engineering, Nagpur, (M.S), IN
6 Department of Management Studies, Smt. Radhikatai Pandav College of Engineering, Nagpur, (M.S), IN
1 Department of Electronics Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, (M.S), IN
2 Department of Electronics and Telecommunication Engineering, Yeshwantrao Chavan College of Engineering, Nagpur, (M.S), IN
3 School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, IN
4 Center for Space Research, Division of Research and Development, Lovely Professional University, Phagwara, Punjab, IN
5 Department of Electronics and Telecommunication Engineering, Smt. Radhikatai Pandav College of Engineering, Nagpur, (M.S), IN
6 Department of Management Studies, Smt. Radhikatai Pandav College of Engineering, Nagpur, (M.S), IN
Source
International Journal of Computer Networks and Applications, Vol 10, No 5 (2023), Pagination: 792-805Abstract
AODV is one of the widely used routing schemes in WSN and MANET due to its on-demand characteristics and low overhead. The excessive flooding at the time of route discovery consumes lots of node energy. The network performance deteriorates due to the unconstrained and blind flooding of route request (RREQ) packets. The excessive flooding mechanism accounts for multiple reception of RREQ packets at nodes. It causes unwanted path loops, and packet collisions thus exhausting the node batteries. The restricted flooding-based route discovery (RFBRD) mechanism introduced in this paper adopts two different strategies for receiving first and subsequent RREQ packets before they are forwarded. On reception of the first RREQ at an intermediate node, the RREQ is forwarded/restricted based on node densities evaluated for the neighbourhood as well as the network. Four regions and five probabilities are considered based on node densities in the neighbourhood and the network. The mobile nodes lying in the low-density region are allowed to transmit the RREQ packets with higher probability as compared to other nodes present in high-density regions when the RREQ is received for the first time. For subsequent RREQ packets at an intermediate node, the RREQ is forwarded/restricted based on energy ratios and is allowed to forward the RREQ packets, if the node has sufficient residual energy concerning neighbourhood and network energies. Simulation analysis showed enhanced and improved performance in terms of end-to-end delay, and network residual energy concerning traditional AODV.Keywords
RREQ, Restricted Flooding Mechanism, RFBRD, Residual Energy, Average Energy, Energy Ratios, AODV.Full Text
References
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- Optimizing Ad-Hoc Routing Protocols in WSN to Enhance QoS Parameters Using Evolutionary Computation Algorithms
Abstract Views :4 |
PDF Views:0
Authors
Affiliations
1 School Of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, IN
2 Faculty of Medicine, Research Unit of Health Sciences and Technology, University of Oulu, FI
1 School Of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, IN
2 Faculty of Medicine, Research Unit of Health Sciences and Technology, University of Oulu, FI
Source
International Journal of Computer Networks and Applications, Vol 11, No 2 (2024), Pagination: 232-247Abstract
Wireless Sensor Networks (WSNs) have garnered considerable attention within the research community focused on fraternity due to their extensive utilization in healthcare, environmental surveillance, disaster avoidance, farming methods, wildfire detection, and other practical applications. Enormous applications have been developed in the Internet of Things (IoT) era resulting in an ever-increasing number of connected WSN devices. As a result, WSNs consistently face challenges in delivering the required quality of service (QoS) affecting the average end-to-end delay, energy utilization, and packet loss throughout the transmission process. An efficient routing protocol must be designed to address these constraints and improve the operational efficiency of WSNs regarding Quality of Service (QoS) metrics. Motivated by these challenges, this paper presents an advanced routing algorithm by integrating optimization in the AODV routing protocol for ad hoc networks employing Particle Swarm Optimization (PSO). The proposed multipath protocol is termed the EPSO-AODV algorithm. The proposed algorithm is assessed through numerous simulations carried out with varied system setups and parameters. Additionally, the efficiency of the proposed protocol is assessed in comparison to conventional routing protocols including AODV, Dynamic Source Routing (DSR), Destination-Sequenced Distance Vector (DSDV), and Optimized Link State Routing (OLSR) protocols. It is observed from the experimental findings that the proposed approach outperforms existing algorithms and offers several benefits including better energy efficiency, ensuring high packet delivery ratio, throughput, and minimal end-to-end delay delay, reduced normalization load. The proposed protocol efficiently distributes energy usage to enhance throughput and enhance the performance of wireless sensor networks. As per the simulation results, the packet delivery ratio has improved from 81.58% to 91.60% whereas the throughput is observed to be 36.32 kbps for conventional AODV and 74.21 kbps for the proposed algorithm. The routing overhead is lowered by approximately 40% and the AE2E delay was found to be 0.04 lower in comparison to AODV. The residual energy in the context of the EPSO-AODV proposal is less (4981 Joules) than AODV (6344 Joules) which proves the superior efficiency of the proposed algorithm.Keywords
Ad Hoc On-Demand Distance Vector Routing, Particle Swarm Optimization, Machine Learning, Network Lifespan, Energy Balancing, Localization, Clustering, Routing Overhead, Throughput, End-to-End Delay.Full Text
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