Localization is widely employed in wireless sensor networks (WSN) to detect the present position of the nodes. Generally, WSN comprises numerous sensors, which makes the deployment of GPS in all nodes cost and fails to provide precise localization outcomes in several cases. The manual configuration of the position reference of the sensors is not feasible under dense networks. Therefore, the NL process can be treated as an NP-hard problem and solved by metaheuristic algorithms. In this aspect, this paper presents an improved group teaching optimization algorithm-based NL technique called IGTOA-NL for WSN. The IGTOA technique is derived by integrating the basic concepts of GTOA with the β-hill-climbing technique to improve the overall node localization process. The IGTOA-NL technique can effectually localize the nodes in WSN under varying anchor node count. To showcase the productive outcome of the IGTOA technique, a series of simulations take place under a diverse number of anchors. The resultant values highlighted the proficient NL outcome of the IGTOA technique over the current state of art NL techniques in terms of different measures.
Read MoreDoi: https://doi.org/10.54216/IJWAC.030101
Vol. Volume 3 Issue. Issue 1 PP. 08-16, (2021)
Recently, unmanned aerial vehicles (UAV) have gained maximum interest in diverse applications ranging from military to civilian areas. The presence of numerous energy-constrained UAVs in an adhoc manner poses several design issues. At the same time, the limited battery, high mobility, and adaptive characteristics of the UAVs need effective design of clustering techniques for UAVs. In this manner, this paper presents a levy flight with a krill herd optimization algorithm (LF-KHOA) for energy-efficient clustering in UAVs. The proposed LF-KHOA technique integrates the concepts of LF to the KHOA to enhance efficiency and search space exploration. In addition, the LF-KHOA technique derives a fitness function involving three input parameters to elect cluster heads (CHs) and organize clusters. The energy consumed by the UAVs depends on the distance from UAVs to nearby nodes. Therefore, the fitness function aims to decrease communication distance, which mitigates energy utilization when transmitting the information. To ensure the better performance of the LF-KHOA technique, an extensive set of simulations takes place, and the results are inspected in terms of different measures. The experimental results highlighted the betterment of the LF-KHOA technique over the current state of art techniques.
Read MoreDoi: https://doi.org/10.54216/IJWAC.030102
Vol. Volume 3 Issue. Issue 1 PP. 17-25, (2021)
In today’s World sensor networks offer various opportunities for data management applications because of their low cost, reliability, scalability, high-speed data processing, and other versatile advantageous purposes. It is a great challenge to organize data effectively and to retrieve the appropriate data from the large volume of various data sets in ad-hoc network databases, mobile databases, etc. The sensor network is necessary for routing of data, performance analysis of data management activities, and data incorporation for the right application. Data management involves intranet and extranet query handling, data access mechanism, modeling of data, different data movement algorithm, data warehousing, and data mining of network database. Additionally, connectivity, design, and lifetime are important issues for sensor networks to perform all data management activities smoothly. In this paper, we are trying to give a cognitive research tendency of Sensor network data management in the last two decades considering all the challenges and issues of both sensor network database and data management functions using Scopus and Web of Science database. To analyze data, different assessments are done considering various parameters like author, time, publication and citation number, place, source, document separately for Web of Science and Scopus database in global perspective. It is noticed that there is a significant growth of research in data management for sensor networks because of the popularity of this topic.
Read MoreDoi: https://doi.org/10.54216/IJWAC.030103
Vol. Volume 3 Issue. Issue 1 PP. 26-36, (2021)
A group of vehicles either mobile or stationery that is interconnected through a wireless network generate a vehicular ad hoc network (VANET). Providing comfort as well as safety to the drivers in vehicular scenarios is the main importance of VANETs. Since there is an increase in the number of autonomous vehicles, these networks are now being considered as an infrastructure for an intelligent transportation system. Fog computing can be provided low latent information sharing and more background knowledge by localizing one of the features. This research work is related to data aggregation in vehicular ad hoc networks. In this research work, the technique of multicasting will be proposed for the data aggregation in VANETs. The Network Simulator 2 is used to perform experiments and few performance measures are used for analysing the outcomes..
Read MoreDoi: https://doi.org/10.54216/IJWAC.030104
Vol. Volume 3 Issue. Issue 1 PP. 37-48, (2021)
As a result of the inherent weaknesses of the wireless medium, ad hoc networks are susceptible to a broad variety of threats and assaults. As a direct consequence of this, intrusion detection, as well as security, privacy, and authentication in ad-hoc networks, have developed into a primary focus of the current study. This body of research aims to identify the dangers posed by a variety of assaults that are often seen in wireless ad-hoc networks and provide strategies to counteract those dangers. The Black hole assault, Wormhole attack, Selective Forwarding attack, Sybil attack, and Denial-of-Service attack are the specific topics covered in this proposed work. In this paper, we describe a trust-based safe routing protocol with the goal of mitigating the interference of black hole nodes while routing in mobile ad-hoc networks. The overall performance of the network is negatively impacted when there are black hole nodes in the route that routing takes. As a result, we have developed a routing protocol that reduces the likelihood that packets would be lost because of black hole nodes. This routing system has been subjected to experimental testing to guarantee that the most secure path will be selected for the delivery of packets between a source and a destination. The invasion of wormholes into wireless networks results in the segmentation of the network as well as a disorder in the routing. As a result, we provide an effective approach for locating wormholes by using ordinal multi-dimensional scaling and round-trip duration in wireless ad hoc networks with either sparse or dense topologies. Wormholes that are linked by both short-route and long-path wormhole linkages may be found using the approach that was given. To guarantee that this ad hoc network does not include any wormholes that go unnoticed, this method is subjected to experimental testing. To fight against selective forwarding attacks in wireless ad-hoc networks, we have developed three different techniques. The first method is an incentive-based algorithm that makes use of a reward-punishment system to drive cooperation among three nodes for forwarding messages in crowded ad-hoc networks. A unique adversarial model has been developed by our team, and inside it, three distinct types of nodes and the activities they participate in are specified. We have demonstrated that the proposed method that is based on incentives prevents nodes from adopting individualistic behaviour, which ensures cooperation in the process of packet forwarding. In the second algorithm, a game theoretic model is proposed that uses non-cooperative game theory to ensure that intermediate nodes in resource-constrained ad-hoc networks faithfully forward packets.
Read MoreDoi: https://doi.org/10.54216/IJWAC.030105
Vol. Volume 3 Issue. Issue 1 PP. 49-58, (2021)