An optimized whale based replication node prediction in wireless sensor network

Wireless sensor networks (WSNs) refer to a group of battery-operated tiny sensor nodes having vast application areas in daily use. These are spatially dispersed and dedicated wireless sensor nodes for observing and recording the different parameter and physical conditions of the surroundings. There is a recent advancement in the field of network connectivity and computations in WSNs. The key functions of WSNs are a data extraction and to transmit the extracted data to the server placed at an isolated location. Various types of WSNs like underground underwater, terrestrial, and multimedia networks get applications domains such as in industrial automation, traffic monitoring and control medical device monitoring, and many other areas. Despite the thriving market, there are several challenges like energy efficiency, limited storage and computation, low bandwidth, high error rates, scalability, and survivability in harsh environment; hence, network lifespan expanding is a critical demanding issues. So many researchers have earlier focused towards finding the optimal path in between member node and sink node, so that energy depletion can be reduced to improve the network lifespan. There are different challenges in WSNs but one of the most challenging issues is how to minimize the energy consumption; numerous bio-inspired techniques have been proposed previously to obtain an optimal path between the member node and the sink node. In this manuscript, we are presenting a comprehensive survey on optimization technique-based routing and clustering. The study of this comprehensive survey offers in-depth summary of the past researches in the area of WSNs.

A comprehensive survey on meta-heuristic-based energy minimization routing techniques for wireless sensor network: classification and challenges

An improved secure file deduplication avoidance using CKHO based deep learning model in a cloud environment

The use of Mobile Ad hoc Networks (MANET) apps has been deployed in numerous regions that are inaccessible to humans. In sensor networks, however, routing remains a major issue since timely delivery of data to the base station is critical. Data transmission has been more dependable and scalable in recent years thanks to Multipath Routing. The concept of Quality of Service (QoS)-based routing is relatively new, with just a few protocols addressing it. The QoS is addressed in this paper using the clustering approach. Each cluster has a cluster head which is picked using the Random Selected Leader (RSL) based optimizer algorithm in this article. Using the Cluster Heads, the suggested method selects reliable pathways for data transmission based on factors such as energy consumption, latency, and congestion index costs. In contrast to current QoS Centric protocols, the suggested protocol leverages the optimal amount of pathways for data transmission and improves the network lifetime by deploying energy-optimized Cluster Heads. Simulated environments are used to test the proposed protocol's performance. According to simulation results, the suggested protocol surpasses current protocols in terms of throughput and network life. 

Improvement of QoS and Selection of Cluster Head using RSL Algorithm with Multipath Routing Protocol in MANET

Wireless sensor networks (WSNs) plays an indispensable role in the human life by supporting a diversified number of applications that includes military, environment monitoring, manufacturing, education, agriculture, etc. However, the sensor node batteries cannot be replaced under its deployment in an unattended or remote area due to their wireless existence. Cluster‐based routing is significant in handling the issue of energy stability and network lifetime. The meta‐heuristic algorithms‐based cluster head (CH) selection is determined to be highly promising for attaining the objective of CH selection that results in acquiring an optimal network performance. In this paper, a Hybrid Grasshopper and Improved Cat Swarm Optimization Algorithm (HGICSOA)‐based clustering scheme is proposed for attaining potential CH selection and guarantee significant sink mobility‐based data transmission. The capability of GHOA that controls the rate of exploitation and exploration degree is utilized for CH selection. It specifically adopted OBL‐based GHOA for optimal CH selection based on the objective function, which is formulated using node density, residual energy, and distance between sensor node and sink. It incorporated new CSOA for mobility‐based data transmission for increasing population diversity. It also utilized the benefits of ICSOA with a predominant local search strategy for achieving better sink mobility‐based data transmission. Simulation and statistical results confirmed that the proposed HGICSOA is better in attaining maximum energy stability by 17.21% and improved network lifetime by 23.82%, compared to the benchmarked schemes used for investigation. Moreover, the prevention rate of worst sensor nodes selected as CH is improved by 21.38%, better than baseline approaches.

Hybrid Grasshopper and Improved Cat Swarm Optimization Algorithm‐based clustering for guaranteeing energy stability and network lifetime in WSN

Wireless sensor networks applications have been used in many areas that are difficult to access by humans. However, Routing remains the key challenges in sensor networks as it is important for the timely delivery of sensed datato the base station. In recent years, Multipath Routing has been used to ensure reliable and scalable data transmission in WSN. Although many multipath routing algorithms have been proposed, very few protocols have been focused on the Quality of Service (QoS) based routing. This paper proposes a QoS-aware, multipath routing protocol in which sensor nodes are clustered using the hybrid Particle Swarm Optimization-Cuckoo Search Optimization algorithm. The proposed protocol then chooses multiple stable paths (optimized network routing) using the Cluster Heads to transmit data based on multi-hop communication. Unlike the existing protocols, it relies on paths that do not affect QoS for rapid data transmission. It also extends the network lifetime by changing the Cluster Heads periodically based on the residual energy and uses the optimal number of paths to data transmission unlike the existing QoS Centric protocols. The performance of the proposed protocol is evaluated using NS-2 Simulator in different scenarios. The proposed protocol outperforms current protocols in terms of QoS parameters such as throughput, packet delivery ratio, end-to-end delay, and network lifetime, according to simulation results.

A Qos-Aware, Hybrid Particle Swarm Optimization-Cuckoo Search Clustering Based Multipath Routing in Wireless Sensor Networks

Nowadays mobile/cellular phones are considered as the most common and the key medium for establishing communication amid the sensor nodes in Wireless Sensor Network (WSN). Though Mobile Wireless Sensor networks (MWSN) is highly reliable, often they are susceptible to various Denial-of-Service (DoS) attacks, jamming attack, attacks caused by anomalies, etc. due to its shared and open-access nature, which in turn causes packet loss, delayed packet delivery, routing distractions, etc. Though some kinds of passive attacks, as well as the jamming/malicious nodes, are detected with prior methodologies, they fail to localize the jammer/attacker. In order to arrest all those difficulties we propose, a novel location Pinpointed Anti-jammer with Knowledged Estimated Localizer (KNOWEL). Initially, an energy detector is used here to set the decision threshold. In addition, an adaptive filter is utilized to discriminate the differences amid normal and reactive jammer traffic. Finally, KNOWLE detects the jammer and their exact location by learning the profile of the external attacker. Thus the proposed pinpointed anti-jammer aids secured and reliable data transmission with the detection and localization of jammer/attacker. It thereby enhances the Quality of Services (QoS) with low energy consumption. The proposed work is implemented in MATLAB, whereas the performance is evaluated and is compared with the prior work to ensure its strength over prior works.

A Novel Location Pinpointed Anti-Jammer with Knowledged Estimated Localizer for secured Data Transmission in Mobile Wireless Sensor Network

Data security is critical, and security measures vary depending on the services and applications. The collection, analysis, and auditing of digital evidence, especially in forensic investigations, necessitates a high level of security and data analytics. The ultimate purpose is to preserve multimedia data in an inspection paradigm relying on auto classify and effective deduplication techniques. Information is more useful in legal, human rights, and crime investigation comparisons than in other data consumption applications. In the present situation, where there are a large number of witnesses at crime scenes, digital data or virtual proofs play an important role in the justice system. Virtual evidence security is in high demand in the forensic and criminal justice sectors. When the public wants to share virtual proof and facts, a reliable and efficient channel between the user and the server is needed. A digital forensic administrator must oversee the evidence transaction in the digital realm. Traditional third-party administrator auditing is needed when using the virtual proof collection system. When the proof is gathered, our proposed modal, which is incorporated, then based on data analytics, if many users exchanged, then the data becomes familiar unless unfamiliar. Check familiarity status has been set as the threshold value. This template fusion modal aids in the investigation and virtual proofing of data protection, as well as data analytics for successful deduplication.

S. Selvakumar

Papers

A Qos-Aware, Hybrid Particle Swarm Optimization-Cuckoo Search Clustering Based Multipath Routing in Wireless Sensor Networks

A Novel Location Pinpointed Anti-Jammer with Knowledged Estimated Localizer for secured Data Transmission in Mobile Wireless Sensor Network

Digital Proof Collective Model Using Integrated Fusion Data Modelling