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Batth, Ranbir Singh

A Comparative Study on Efficient Path Finding Algorithms for Route Planning in Smart Vehicular Networks

Abstract Views :358 | PDF Views:0

Authors

Gurpreet Singh Shahi ¹, Ranbir Singh Batth ¹, Simon Egerton ²

Affiliations
1 School of Computer Science and Engineering, Lovely Professional University, Punjab, IN
2 Department of Computer Science and Information Technology, La Trobe University, Victoria, AU

Source

International Journal of Computer Networks and Applications, Vol 7, No 5 (2020), Pagination: 157-166

Abstract

With the rise in the economy and population of various developing and developed nations leads to an increase in the number of vehicles on the road to manifolds recently. In the smart vehicular networks, there are numerous vehicle transportation problems (VTP) exists. The main or the most common problem is the congestion occurrence due to traffic jams and road accidents, especially in urban areas. So route planning to find the optimal route for a vehicle that is moving from source to destination is an important and challenging task as the route conditions change with the traffic conditions, hence the shortest and optimal route needs to be re-evaluated. This manuscript presents a study and comparison of various pathfinding algorithms which include Dijkstra, A Star, CH, and Floyd Warshall algorithms which are available as optimal route finding algorithms. The simulation of working algorithms with comparison has been performed using SUMO with TRACI and using python coding. The simulation is performed on real maps of urban areas. The parameters used for the comparative study are travel time, distance travelled, and speeds of vehicles.

Keywords

Smart Vehicular Networks, Guidance Systems, Vehicle Transportation Problem, Routing Algorithms.

Full Text

References

Rafsanjani, Marjan Kuchaki, Hamideh Fatemidokht, Valentina Emilia Balas, and Ranbir Singh Batth. "An Anomaly Detection System Based on Clustering and Fuzzy Set Theory in VANETs." In International Workshop Soft Computing Applications, pp. 399-407. Springer, Cham, 2018.

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S. G. Manyam, S. Rathinam, S. Darbha, D. Casbeer, and P. Chandler, “Routing of two Unmanned Aerial Vehicles with communication constraints,” 2014 International Conference on Unmanned Aircraft Systems (ICUAS), 2014.

N. Akhtar, S. C. Ergen, and O. Ozkasap, “Vehicle Mobility and Communication Channel Models for Realistic and Efficient Highway VANET Simulation,” IEEE Transactions on Vehicular Technology, vol. 64, no. 1, pp. 248–262, 2015.

Shahi, G. S., Batth, R. S., & Egerton, S. (2020). MRGM: An Adaptive Mechanism for Congestion Control in Smart Vehicular Network. International Journal of Communication Networks and Information Security, 12(2), 273-280.

A. Nayar, R. S. Batth, D. B. Ha, and G. Sussendran, G. “Opportunistic networks: Present scenario-A mirror review”InternationalJournal of Communication Networks and Information Security,” 10 (1), pp. 223-241, 2018.

R. S. Batth, M. Gupta, K. S. Mann, S. Verma, and A. Malhotra, “Comparative Study of TDMA-Based MAC Protocols in VANET: A Mirror Review,” Advances in Intelligent Systems and Computing International Conference on Innovative Computing and Communications, pp. 107–123, 2019.

Chabini, Ismail, and Shan Lan. ”Adaptations of the A* algorithm for the computation of fastest paths in deterministic discrete-time dynamic networks.” Intelligent Transportation Systems, IEEE Transactions on 3.1 (2002): 60-74

Bell, M. G., Trozzi, V., Hosseinloo, S. H., Gentile, G., & Fonzone, A. (2012). Time-dependent Hyperstar algorithm for robust vehicle navigation. Transportation Research Part A: Policy and Practice, 46(5), 790-800.

P.Khan, G.Konar, &N.Chakraborty (2014). Modification of Floyd-Warshall's algorithm for Shortest Path routing in wireless sensor networks.2014 Annual IEEE India Conference (INDICON). doi:10.1109/indicon.2014.7030504

Hamrioui, Sofiane, Camil Adam Mohamed Hamrioui, Jaime Lioret, and Pascal Lorenz. "Smart and self-organised routing algorithm for efficient IoT communications in smart cities." IET Wireless Sensor Systems 8, no. 6 (2018): 305-312.

Zahedi, Khalid, Yasser Zahedi, and Abdul Samad Ismail. "CJBR: connected junction-based routing protocol for city scenarios of VANETs." Telecommunication Systems 72, no. 4 (2019): 567-578.

Haider, Shahab, Ghulam Abbas, ZiaulHaq Abbas, and Thar Baker. "DABFS: A robust routing protocol for warning messages dissemination in VANETs." Computer Communications 147 (2019): 21-34.

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J. Zhang, J. Yin, T. Xu, Z. Gao, , H. Qi, & H. Yin, “The optimal game model of energy consumption for nodes cooperation in WSN. Journal of Ambient Intelligence and Humanized Computing, pp. 1-11, 2018.

Sunita, &D.Garg, (2018). DynamizingDijkstra: “A solution to dynamic shortest path problem through retroactive priority queue”. Journal of King Saud University - Computer and Information Sciences. doi:10.1016/j.jksuci.2018.03.003.

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Koenig, Sven, Maxim Likhachev, and David Furcy. ”Lifelong planningA*.”Artificial Intelligence 155.1 (2004): 93-146.

Ramadiani, D.Bukhori, Azainil, &N.Dengen, (2018). Floyd-warshall algorithm to determine the shortest path based on android. IOP Conference Series: Earth and Environmental Science,144, 012019. doi:10.1088/1755-1315/144/1/012019.

R. Singh and K. S. Mann, “Improved TDMA Protocol for Channel Sensing in Vehicular Ad Hoc Network Using Time Lay,” Proceedings of 2nd International Conference on Communication, Computing and Networking Lecture Notes in Networks and Systems, pp. 303–311, 2018.

Fu, Liping, D. Sun, and Laurence R. Rilett. ”Heuristic shortest path algorithms for transportation applications: state of the art.” Computers & Operations Research 33.11 (2006): 3324-3343.

A Novel Fragmentation Scheme for Textual Data Using Similarity-Based Threshold Segmentation Method in Distributed Network Environment

Abstract Views :258 | PDF Views:0

Authors

Sashi Tarun ¹, Ranbir Singh Batth ¹, Sukhpreet Kaur ²

Affiliations
1 School of Computer Science and Engineering, Lovely Professional University, Phagwara, IN
2 Department of Computer Science and Engineering, Chandigarh Engineering College, Mohali, IN

Source

International Journal of Computer Networks and Applications, Vol 7, No 6 (2020), Pagination: 231-242

Abstract

Data distribution is one of the most essential architectures of any serving network. Data storage and its retrieval depend a lot on how the data is organized in the distributed environment. With the fast development of technology, the requirements of users have also changed. A user who was stationary earlier has become mobile now and requires access to the data from anywhere in the world. An unorganized data structure will result in output delay in the network and may further result in user migration from one service provider to another service provider. Data fragmentation is one of the most essential parts when it comes to data storage. Organized data always gives convenience to others to use it conveniently. Due to the vast collection of data extraction of information in a fast manner is very complicated. So, to achieve performance in a distributed system an optimal strategy is required to overcome previous lapses and serves the maximum number of users in a wide geographical network. This research paper proposes a novel relative based fragmentation method that analyses the attributes of the data in relative architecture and is helpful to achieve query performance with better speed and accuracy. To assess the current proposed work a comparison has been drawn between k-means dependent cosine similarity measurement and hybridization of cosine and soft-cosine partition methods for data partitioning. Mentioned results in the article shows that the proposed similarity-based threshold segmentation method outperforms the existing in terms of partitioning strategy, precision, and recall parameters to achieve performance.

Keywords

Fragmentation, K-Means, Similarity, Data Partitioning, Threshold, Segmentation, Precision, Recall.

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References

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A. Nayar, R. S. Batth, D. B. Ha, and G. Sussendran, G. “Opportunistic networks: Present scenario-A mirror review” International Journal of Communication Networks and Information Security,” 10 (1), pp. 223-241, 2018.

G.S Shahi, R.S Batth, S. Egerton, 2020 “MRGM: An Adaptive Mechanism for Congestion Control in Smart Vehicular Network”, International Journal of Communication Networks and Information Security 12 (2).

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A Survey of Medium Access Control Protocols for Unmanned Aerial Vehicle (UAV) Networks

Abstract Views :221 | PDF Views:2

Authors

Jyoti ¹, Ranbir Singh Batth ², Sahil Vashisht ³

Affiliations
1 School of Computer Applications, Lovely Professional University, Phagwara, Punjab, IN
2 School of Computer Science and Engineering, Lovely Professional University, Phagwara, Punjab, IN
3 Department of Computer Science and Engineering, Faculty of Engineering & Technology, SGT University, Haryana, IN

Source

International Journal of Computer Networks and Applications, Vol 8, No 3 (2021), Pagination: 238-257

Abstract

The use of Unmanned Aerial Vehicles is growing increasingly across many civil benefits, including real-time monitoring, medical emergencies, surveillance, and defence. Many different types of UAVs are being developed to meet the demands of diverse users. Therefore, the research areas in the UAV domain are evolving as the types and number of UAVs increase. UAV’s faces numerous problems in channel accessing, radio allotment, latency and most of these issues are because of the ineffective MAC protocols, moreover MAC is also important because it affects not only the system performance but also the energy efficiency in battery-powered sensor nodes. In this research article various Medium access control (MAC) protocols discussed and qualitatively compared on the basis of various Quality-of-Service (QoS) parameters.

Keywords

Unmanned Aerial Vehicles (UAV), Medium Access Control (MAC) Protocols, Antennas, QoS, Architecture.

Full Text

References

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QMRNB: Design of an Efficient Q-Learning Model to Improve Routing Efficiency of UAV Networks via Bioinspired Optimizations

Abstract Views :143 | PDF Views:1

Authors

Anshu Vashisth ¹, Balraj Singh ¹, Ranbir Singh Batth ²

Affiliations
1 School of Computer Science and Engineering, Lovely Professional University, Punjab, IN
2 Menzies Institute of Technology, Melbourne, AU

Source

International Journal of Computer Networks and Applications, Vol 10, No 2 (2023), Pagination: 256-264

Abstract

The design of efficient routing strategies for Unmanned Aerial Vehicle (UAV) Networks is a multidomain task that involves analysis of node-level & network-level parameters, and mapping them with communication & contextual conditions. Existing path planning optimization models either showcase higher complexity or cannot be scaled for larger network scenarios. Moreover, the efficiency of these models also reduces w.r.t. the number of communication requests, which limits their scalability levels. To get a better result over these challenges, this article provides an idea to design an efficient Q-Learning model to improve the routing efficiency of UAV networks via bioinspired optimizations. The model initially collects temporal routing performance data samples for individual nodes and uses them to form coarse routes via Q-Learning optimizations. These routes are further processed via a Mayfly Optimization (MO) Model, which assists in the selection of optimal routing paths for high Quality of Service (QoS) even under large-scale routing requests. The MO Model can identify alternate paths via the evaluation of a high-density routing fitness function that assists the router in case the selected paths are occupied during current routing requests. This assists in improving temporal routing performance even under dense network conditions. Due to these optimizations, the model is capable of reducing the routing delay by 8.5%, improving energy efficiency by 4.9%, and reducing the routing jitter by 3.5% when compared with existing routing techniques by taking similar routing conditions.

Keywords

UAV, Routing, Delay, Energy, Mayfly, Optimization, Jitter, efficiency, Complexity.

Full Text

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A. Vashisth and R. S. Batth, "An Overview, Survey, and Challenges in UAVs Communication Network," 2020 International Conference on Intelligent Engineering and Management (ICIEM), London, UK, 2020, pp. 342-347, doi: 10.1109/ICIEM48762.2020.9160197.

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Design of an Efficient QoS-Aware Adaptive Data Dissemination Engine with DTFC for Mobile Edge Computing Deployments

Abstract Views :75 | PDF Views:1

Authors

Gagandeep Kaur ¹, Balraj Singh ¹, Ranbir Singh Batth ²

Affiliations
1 School of Computer Science and Engineering, Lovely Professional University, Punjab, IN
2 Menzies Institute of Technology, Melbourne, AU

Source

International Journal of Computer Networks and Applications, Vol 10, No 5 (2023), Pagination: 728-744

Abstract

In the transformative landscape of mobile edge computing (MEC), where the convergence of computation and communication fuels the era of ubiquitous connectivity, formidable challenges loom large. The burgeoning demand for real-time, data-intensive applications places unprecedented pressure on existing infrastructure, demanding innovative solutions to address the intricate web of challenges. This paper embarks on a compelling journey through the realm of MEC, uncovering the multifaceted challenges that have hitherto impeded its seamless integration into our digital lives. As the proliferation of mobile devices and their insatiable appetite for data strain the network's capacity, latency becomes a formidable adversary, threatening the integrity of applications requiring split-second responsiveness. Furthermore, the capricious nature of mobile devices and their mobility introduces an unpredictable dynamism into the network topology, rendering traditional traffic control approaches ineffective. The consequence is a tangled web of congestion, resource underutilization, and compromised Quality of Service (QoS), all of which hinder the realization of MEC's full potential. In response to these challenges, we unveil a pioneering solution—a QoS-aware Adaptive Data Dissemination Engine (QADE) paired with Dynamic Traffic Flow Control (DTFC). This synergistic model augments the capabilities of MEC deployments by harnessing the power of content-based routing and advanced optimization techniques. QADE, with its innovative utilization of Elephant Herding Particle Swarm Optimizer (EHPSO), refines data dissemination processes with an unprecedented focus on QoS metrics. Temporal delay, energy consumption, throughput, and Packet Delivery Ratio (PDR) become our guiding stars in the quest for routing efficiency. By harnessing this wealth of information, QADE emerges as a beacon of efficiency, driving latency to its lowest ebb, magnifying bandwidth, mitigating packet loss, elevating throughput, and rationalizing operational costs. DTFC complements this endeavor by dynamically steering traffic flows by edge processing capacity, thereby circumventing congestion pitfalls and achieving resource utilization efficiency hitherto considered unattainable. In a series of exhaustive evaluations, our proposed QADE with DTFC emerges as a beacon of hope, surpassing traditional methodologies. With an 8.5% reduction in latency compared to RL, a 16.4% reduction compared to MTO SA, and an impressive 18.0% reduction compared to HFL, it ushers in a new era of real-time data dissemination. By championing QoS awareness, adaptability, and efficiency, this study catapults mobile edge computing into a future defined by resource optimization and stellar network performance, ushering in an era where challenges bow before innovation processes.

Keywords

Data, Dissemination, Trust, Routing, Data Flow, Control, Scenarios.

Full Text

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