Trust based multi objective honey badger algorithm to secure routing in vehicular ad-hoc networks

A vehicular ad-hoc network (VANET) is a set of intelligent vehicles that interact without any fixed infrastructure. Data transmission between each transmitter/receiver pair is accomplished using routing protocols. However, communication over the VANET is vulnerable to malicious attacks, because of the unavailability of fixed infrastructure and wireless communication. In this paper, the trust based multi objective honey badger algorithm (TMOHBA) is proposed to achieve secure routing over the VANET. The TMOHBA is optimized by incorporating different cost functions, namely, trust, end to end delay (EED), routing overhead, energy, and distance. The developed secure route discovery using the TMOHBA is used to improve the robustness against the malicious attacks, for increasing the data delivery. Moreover, the shortest path discovery is used to minimize the delay while improving the security of VANET. The TMOHBA method is evaluated using the packet delivery ratio (PDR), throughput and EED. Existing researches such as hybrid enhanced glowworm swarm optimization (HEGSO) and ad-hoc on-demand distance vector based secure protocol (AODV-SP) are used to evaluate the TMOHBA method. The PDR of the TMOHBA method for 10 malicious attacks is 90.6446% which is higher when compared to the HEGSO and AODV-SP

Routing schemes in FANETs: a survey

Flying ad hoc network (FANET) is a self-organizing wireless network that enables inexpensive, flexible, and easy-to-deploy flying nodes, such as unmanned aerial vehicles (UAVs), to communicate among themselves in the absence of fixed network infrastructure. FANET is one of the emerging networks that has an extensive range of next-generation applications. Hence, FANET plays a significant role in achieving application-based goals. Routing enables the flying nodes to collaborate and coordinate among themselves and to establish routes to radio access infrastructure, particularly FANET base station (BS). With a longer route lifetime, the effects of link disconnections and network partitions reduce. Routing must cater to two main characteristics of FANETs that reduce the route lifetime. Firstly, the collaboration nature requires the flying nodes to exchange messages and to coordinate among themselves, causing high energy consumption. Secondly, the mobility pattern of the flying nodes is highly dynamic in a three-dimensional space and they may be spaced far apart, causing link disconnection. In this paper, we present a comprehensive survey of the limited research work of routing schemes in FANETs. Different aspects, including objectives, challenges, routing metrics, characteristics, and performance measures, are covered. Furthermore, we present open issues

An energy-efficient cluster head selection in wireless sensor network using grey wolf optimization algorithm

Clustering is considered as one of the most prominent solutions to preserve theenergy in the wireless sensor networks. However, for optimal clustering, anenergy efficient cluster head selection is quite important. Improper selectionofcluster heads(CHs) consumes high energy compared to other sensor nodesdue to the transmission of data packets between the cluster members and thesink node. Thereby, it reduces the network lifetime and performance of thenetwork. In order to overcome the issues, we propose a novelcluster headselection approach usinggrey wolf optimization algorithm(GWO) namelyGWO-CH which considers the residual energy, intra-cluster and sink distance.In addition to that, we formulated an objective function and weight parametersfor anefficient cluster head selection and cluster formation. The proposedalgorithm is tested in different wireless sensor network scenarios by varyingthe number of sensor nodes and cluster heads. The observed results conveythat the proposed algorithm outperforms in terms of achieving better networkperformance compare to other algorithms

Design and Analysis of An Improved AODV Protocol Based on Clustering Approach for Internet of Vehicles (AODV-CD)

The Internet of Vehicles (IoVs) has become a vital research area in order to enhance passenger and road safety, increasing traffic efficiency and enhanced reliable connectivity. In this regard, for monitoring and controlling the communication between IoVs, routing protocols are deployed. Frequent changes that occur in the topology often leads to major challenges in IoVs, such as dynamic topology changes, shortest routing paths and also scalability. One of the best solutions for such challenges is “clustering”. This study focuses on IoVs’ stability and to create an efficient routing protocol in dynamic environment. In this context, we proposed a novel algorithm called Cluster-based enhanced AODV for IoVs (AODV-CD) to achieve stable and efficient clustering for simplifying routing and ensuring quality of service (QoS). Our proposed protocol enhances the overall network throughput and delivery ratio, with less routing load and less delay compared to AODV. Thus, extensive simulations are carried out in SUMO and NS2 for evaluating the efficiency of the AODV-CD that is superior to the classic AODV and other recent modified AODV algorithms.

F3TM: flooding factor based trust management framework for secure data transmission in MANETs

Due to the absence of infrastructure support, secure data dissemination is a challenging task in scalable mobile ad hoc networks (MANETs) environment. In most of the traditional routing techniques for MANETs, either security has not been taken into account or only one aspect of security concern has been addressed without optimizing the routing performance. This paper proposes Flooding Factor based Framework for Trust Management (F3TM) in MANETs. True flooding approach is utilized to identify attacker nodes based on the calculation of trust value. Route Discovery Algorithm is developed to discover an efficient and secure path for data forwarding using Experimental Grey Wolf algorithm for validating network nodes. Enhanced Multi-Swarm Optimization is used to optimize the identified delivery path. Simulations are carried out in ns2 to assess and compare the performance of F3TM with the state-of-the-art frameworks: CORMAN and PRIME considering the metrics including delay, packet delivery ration, overhead and throughput. The performance assessment attests the reliable security of F3TM compared to the state-of-the-art frameworks

An Intelligent Optimized Route-Discovery Model for IoT-Based VANETs

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Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs

FANET: Smart city mobility off to a flying start with self‐organized drone‐based networks

Due to recent advancements in smart city traffic and transport monitoring industry 4.0 applications. Flying Ad-Hoc Networks (FANETs) ability to cover geographically large areas, makes it a suitable technology to address the challenges faced during remote areas traffic monitoring. The implementation of drone based FANETs have several advantages in remote traffic monitoring, including free air-to-air drone assisted communication zone and smart surveillance and security. The drone-based FANETs can be deployed within minutes without requiring physical infrastructure, making it suitable for mission critical applications in several areas of interests. Here a drone-based FANETs application for smart city remote traffic monitoring is presented while addressing several challenges including coverage of larger geographical area and data communication links between FANETs nodes. A FANET-inspired enhanced ACO algorithm that easily coped with drone assisted technology of FANETs is proposed to cover the large areas. Simulation results are presented to compare the proposed technique against different network lifetime and number of received packets. The presented results show that the proposed technique perform better compared to other state-of-the-art techniques