Wireless networks that are decentralized and communicate without using existing infrastructure are known as mobile ad-hoc networks. The most common sorts of threats and attacks can affect MANETs. Therefore, it is advised to utilize intrusion detection, which controls the system to detect additional security issues. Monitoring is essential to avoid attacks and provide extra protection against unauthorized access. Although the current solutions have been designed to defeat the attack nodes, they still require additional hardware, have considerable delivery delays, do not offer high throughput or packet delivery ratios, or do not do so without using more energy. The capability of a mobile node to forward packets, which is dependent on the platform's life quality, may be impacted by the absence of the network node power source. We developed the Safe Routing Approach (SRA), which uses behaviour analysis to track and monitor attackers who discard packets during the route discovery process. The attacking node recognition system is made for irregular routing node detection to protect the controller network's usual properties from becoming recognized as an attack node. The suggested method examines the nearby attack nodes and conceals the trusted node in the routing pathway. The path is instantly assigned after the initial discovery of trust nodes based on each node's strength value. It extends the network's life span and reduces packet loss. In terms of Packet Delivery Ratio (PDR), energy consumption, network performance, and detection of attack nodes, the suggested approach is contrasted with AIS, ZIDS, and Improved AODV. The findings demonstrate that the recommended strategy performs superior in terms of PDR, residual energy, and network throughput.

Safe Routing Approach by Identifying and Subsequently Eliminating the Attacks in MANET

Optimization of the cross-border intelligent e-commerce platform based on data flow node analysis is studied in this manuscript. In the era of the popularization of big data applications, the application of big data technology has gradually shown its own advantages, and also the penetration field has gradually expanded. In our designed model, the 2 aspects of the novelty are reflected. (1) The data flow node analysis is conducted. We apply the machine learning algorithms and the graph theory for the work of node modelling and pattern analysis. The intelligent coding theory is applied for the implementation of the model. (2) The cross-border intelligent e-commerce platform is implemented with the optimal solution. We apply the platform into the applications.

Optimization of cross-border intelligent e-commerce platform based on data flow node analysis

Over the last decade, the Internet of Things (IoT) has become ever more popular, as is evident from its role in changing the human lifestyle and conferring remarkable privileges for them. It has a significant presence in various crucial areas, including smart cities, smart factories, manufacturing, transportation, and healthcare. Massive amounts of data generated by IoT devices have the potential to endanger the lifetime of nodes in IoT‐based networks due to increased communication power consumption. It has become crucial to propose solutions for network‐based issues, such as quality of service, security, network heterogeneity, congestion avoidance, reliable routing, and energy conservation. To address the mentioned problems, routing protocols play a critical role in data transmission among heterogeneous items. In such environments, routing refers to constructing routes between mobile nodes. Since identifying optimal routes among IoT nodes and establishing an effective routing protocol in an IoT network are an NP‐hard issue, employing metaheuristic algorithms may be a viable solution to overcome this problem. Various IoT routing protocols based on metaheuristic algorithms have been presented in recent years, but there is still a lack of systematic study for reviewing the existing works. The current study emphasizes the impact of metaheuristic algorithms in the IoT routing problem, discusses the optimization models, presents a comprehensive comparison of protocols based on critical parameters, and eventually suggests some hints for future studies.

The importance of nature‐inspired metaheuristic algorithms in the data routing and path finding problem in the internet of things

WSN (Wireless Sensor Network) is gradually evolving into the most prevalent technology adopted in business and industrial sectors as a result of major developments in processing, communication, and low-power consumption of embedded computer devices. WSNs are quickly evolving into a cutting-edge technology that may be used in a variety of contexts. In wireless sensor networks, the most critical difficulty is often seen as being the use of energy. Researchers have investigated a variety of approaches in order to find a solution to this significant challenge posed by wireless sensor networks. One of these approaches, a routing strategy that is founded on clustering, has been shown to be useful in research studies and is currently regarded as one of the finest solutions to resolve the challenge of excessive energy expenditure. The intention of this study was to find a way to reduce the amount of energy that was used while maintaining acceptable levels of performance. At the beginning, the algorithm will separate the network into individual cells or clusters. The genetic algorithm was then brought into the picture, and it was utilised to determine the optimal number of nodes that should be present in a network. Following the placement of the nodes in the surroundings, the chromosomal length is adjusted to be equal to the quantity of nodes in order to facilitate the process of gradual convergence. As a consequence of this, the length of the chromosomes is reduced, and we are able to reach convergence on the optimal solution more quickly. The cluster heads found inside each chromosome, on the other extreme, are passed to the K-Means method as starting points in order to facilitate a rapid clustering process.

Enhancement of Energy Efficiency and Network Lifetime Using Modified Cluster Based Routing in Wireless Sensor Networks

The study develops the mapping-based cuttlefish optimization algorithm (MCFA) to select the cluster head (CH). A local and global search integration is occurred by using this algorithm, and chaos mapping is introduced to solve the issues of trapping in local optimum. NS-2 tools are used and test the efficiency of the MCFA algorithm with ant colony optimization (ACO) in terms of path optimality, delay time, etc. The results prove that the proposed MCFA achieves better performance than the existing ACO algorithm. 

Cluster Head Selection Based on Mapping-based Cuttlefish Optimization Algorithm for Multipath Routing in MANET

Routes discovery that can provide reliable data transmission in Mobile Ad-hoc Networks is challenging due to its wireless channel characteristics and dynamic transmission environment. Link failure frequently occurs in ad-hoc networks due to nodes' mobile nature, which is not static to their position. The dynamic characteristic of the mobile ad hoc network facilitates multi-path routing protocols as a novel research area. This paper comprises an approach based on ACO acknowledge as NDLR-MP, an ACO-based node-disjoint multi-path routing protocol using AODV protocol. The proposed protocol intends to find all node-disjoint paths from source to destination in a single route discovery process that will conclusively minimize the routing control overhead. In this approach (NDLR-MP), the data packet transportation is initialized just after the first path is determined, wherein all the other secondary routes are also concurrently discovered. Additionally, we have also suggested an efficient local route repair method that redirects the current traffic to an available route if a broken link to the next hop is positioned towards the destination. The proposed route detection and maintenance methods can be considered as performance evaluation metrics. Moreover, results obtained on the Network Simulator (EXata 2.0) have shown the performance and effectiveness of the proposed approach of NDLR-MP in contrast to the AODV protocol, which has significantly amplified the performance of the provided protocol. The parameters like route availability, control overhead, average E-2-E, and PDR are comparing with the existing protocol.

Ashutosh Sharma

Papers

Ant Colony Based Node Disjoint Local Repair in Multipath Routing in MANET Network