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2021

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Vadivel, R.

Improved Wolf Prey Inspired Protocol for Routing in Cognitive Radio Ad Hoc Networks

Abstract Views :269 | PDF Views:0

Authors

J. Ramkumar ¹, R. Vadivel ²

Affiliations
1 Department of Computer Science, VLB Janakiammal College of Arts and Science, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Bharathiar University, Coimbatore, Tamil Nadu, IN

Source

International Journal of Computer Networks and Applications, Vol 7, No 5 (2020), Pagination: 126-136

Abstract

Fifth Generation (5G) technology has started providing the brand new facilities to the mobile communication world. With its enhanced performance and scalability, it has attracted many domains. Routing overhead in 5G networks is increased rapidly because of the complexity present in the route discovery process, where optimization in routing. Poor routing becomes a sophisticated and dynamic challenge in the 5G network. Hence, there exists a need for finding the best route in an optimized manner. This paper proposes an Improved Wolf Prey Inspired Protocol (IWPIP) for finding the ideal route in the dynamic environment like 5G based cognitive radio ad-hoc network. IWPIP focuses on finding the ideal route based on the reliability of route, shorter distance, and shorter hops that minimize the consumption of energy to increase the network lifetime. Before sending the data packets, routes are evaluated using a fitness function. IWPIP's efficiency has been demonstrated through comprehensive simulation, which resulted in promising outcomes in terms of throughput, packet delivery and drop ratio, delay, and energy consumption.

Keywords

Optimization, Routing, Bio-Inspired, Energy, Delay, Cognitive Radio Ad Hoc Networks, Wolf Prey Inspired Protocol.

Full Text

References

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J.Ramkumar and R.Vadivel, "CSIP—Cuckoo Search Inspired Protocol for Routing in Cognitive Radio Ad Hoc Networks", Advances in Intelligent Systems and Computing, Vol. 556, pp. 145-153, 2017. https://doi.org/10.1007/978-981-10-3874-7_14

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Ensemble Miscellaneous Classifiers Based Misbehavior Detection Model for Vehicular Ad-Hoc Network Security

Abstract Views :317 | PDF Views:1

Authors

S. Sumithra ¹, R. Vadivel ¹

Affiliations
1 Department of Information Technology, Bharathiar University, Coimbatore, Tamil Nadu, IN

Source

International Journal of Computer Networks and Applications, Vol 8, No 2 (2021), Pagination: 90-107

Abstract

Vehicular Ad-Hoc Network is an emerging technology, mainly developed for road safety applications, entertainment applications, and effective traffic conditions. VANET applications work based on the accurate mobility information shared among the vehicles. Sometimes attackers manipulate the mobility information shared by the adjacent vehicle or neighboring vehicle, which results in terrible consequences. To deal with the illusion-based type of attacks, researchers have proposed enormous solutions. Unfortunately, those solutions could not deal with the dynamic vehicle conditions and variable cyber malfunctions, which reduces the misbehavior detection accurateness and increases the false-positive rate. In this paper, the dynamic vehicle context is taken into account to propose a two solutions such as Miscellaneous VANET Classifiers based Misbehavior Detection Model (MVC-MDM) and Ensemble Miscellaneous VANET Classifiers based Misbehavior Detection Model (EMVC-MDM). This model is constructed based on the Mobility Data Gathering phase, Mobility Context Feature Extraction phase, Mobility Context Feature Level Fixing phase, Hampel Filter based Context Reference Building phase, Constructing Miscellaneous VANET Classifiers based Misbehavior Detection model and Ensemble Miscellaneous VANET Classifiers based Misbehavior Detection phase. Vehicle context is prepared using the data-centric features and the behavior-based features of the vehicles. The Nonparametric Hampel filter and Kalman filter are used to building the context reference model. These filters discover the temporal and spatial correlation of the uniformity in the current mobility information. Vehicle features are extracted locally according to the stability, likelihood, and performance of the vehicles' mobility information. A random forest based learning algorithm is used to train and test the classifiers. The proposed MVC-MDM and EMVC-MDM has been simulated in various context scenarios and the presence of misbehaving vehicles. NGSIM dataset has been used for extensive simulation. The results prove that the effectiveness and the reliability of the proposed MVC-MDM and EMVC-MDM are higher than the existing misbehavior detection systems.

Keywords

Stability, Likelihood, Performance, Hampel Filter, Kalman Filter.

Full Text

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Whale Optimization Routing Protocol for Minimizing Energy Consumption in Cognitive Radio Wireless Sensor Network

Abstract Views :264 | PDF Views:1

Authors

J. Ramkumar ¹, R. Vadivel ²

Source

International Journal of Computer Networks and Applications, Vol 8, No 4 (2021), Pagination: 455-464

Abstract

Cognitive Radio Wireless Sensor Networks (CR-WSN) works on nodes that are dependent on batteries. A critical problem with CR-WSN is a lack of energy, especially in situations such as warfare where rapid and aggressive action is needed. The battery level of nodes degrades CR-WSN performance. Researchers face significant difficulty developing a routing protocol for CR-WSN, and that obstacle is posed by energy consumption to deliver a packet. A substantial number of nodes reside in CR-WSN. Every node in CR-WSN is constrained by battery. To minimize network cost, it should be feasible to have the routing protocol used for CR-WSN to be energy efficient. This paper proposes an optimization-based routing protocol, namely Whale Optimization Routing Protocol (WORP), for identifying the best route in CR-WSN to minimize the delay and lead to network efficiency. WORP draws inspiration from the behaviors of whales as they forage, similar to their hunting activity. By prioritizing residual energy and the total energy of the nodes in the route, WORP encourages energy-aware route selection. WORP is examined via simulation with NS2 against current routing protocols. Benchmark performance metrics are used to assess the effectiveness of WORP. Results make an indication that WORP has superior performance than current routing protocols in CR-WSN.

Keywords

WSN, CR-WSN, Routing, Optimization, Delay, Energy Consumption.

Full Text

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Constrained Cuckoo Search Optimization Based Protocol for Routing in Cloud Network

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Authors

J. Ramkumar ¹, R. Vadivel ², B. Narasimhan ³

Affiliations
1 PG and Research Department of Computer Science, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, IN
2 Department of Information Technology, Bharathiar University, Coimbatore, Tamil Nadu, IN
3 Department of Computer Technology, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, IN

Source

International Journal of Computer Networks and Applications, Vol 8, No 6 (2021), Pagination: 795-803

Abstract

Cloud Computing (CC) is the process of providing on-demand data to the user via the internet. In CC, users don't need to manage data storage and computational power actively. Finding the best route in a cloud network is entirely different from other general networks which it is due to high scalability. Protocols developed for other general networks will never suit or give better performance in cloud networks due to its scalability. This paper proposes a bio-inspired protocol for routing in a cloud network, namely Constrained Cuckoo Search Optimization-based Protocol (CCSOP). The routing strategy of CCSOP is inspired by the natural characteristics of the cuckoo bird towards finding a nest to lay its eggs. Levy Flight concept is applied with different constraints to enhance optimization performance towards finding the best route in a cloud network that minimizes energy consumption. CCSOP is evaluated in Greencloud using benchmark network performance metrics against the current routing protocols. The efficacy of CCSOP is evaluated using benchmark performance measures. CCSOP appears to outperform current cloud network routing protocols in terms of energy consumption.

Keywords

Cuckoo, Cloud, Energy, Flight, Levy, Optimization, Routing, Scalability.

Full Text

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