Energy Efficient Multi-hop routing scheme using Taylor based Gravitational Search Algorithm in Wireless Sensor Networks

A group of small sensors can participate in the wireless network infrastructure and make appropriate transmission and communication sensor networks. There are numerous uses for drones, including military, medical, agricultural, and atmospheric monitoring. The power sources available to nodes in WSNs are restricted. Furthermore, because of this, a diverse method of energy availability is required, primarily for communication over a vast distance, for which Multi-Hop (MH) systems are used. Obtaining the optimum routing path between nodes is still a significant problem, even when multi-hop systems reduce the cost of energy needed by every node along the way. As a result, the number of transmissions must be kept to a minimum to provide effective routing and extend the system\u27s lifetime. To solve the energy problem in WSN, Taylor based Gravitational Search Algorithm (TBGSA) is proposed, which combines the Taylor series with a Gravitational search algorithm to discover the best hops for multi-hop routing. Initially, the sensor nodes are categorised as groups or clusters and the maximum capable node can access the cluster head the next action is switching between multiple nodes via a multi-hop manner. Initially, the best (CH) Cluster Head is chosen using the Artificial Bee Colony (ABC) algorithm, and then the data is transmitted utilizing multi-hop routing. The comparison result shows out the extension of networks longevity of the proposed method with the existing EBMRS, MOGA, and DMEERP methods. The network lifetime of the proposed method increased by 13.2%, 21.9% and 29.2% better than DMEERP, MOGA, and EBMRS respectively

Survey on Various Aspects of Clustering in Wireless Sensor Networks Employing Classical, Optimization, and Machine Learning Techniques

A wide range of academic scholars, engineers, scientific and technology communities are interested in energy utilization of Wireless Sensor Networks (WSNs). Their extensive research is going on in areas like scalability, coverage, energy efficiency, data communication, connection, load balancing, security, reliability and network lifespan. Individual researchers are searching for affordable methods to enhance the solutions to existing problems that show unique techniques, protocols, concepts, and algorithms in the wanted domain. Review studies typically offer complete, simple access or a solution to these problems. Taking into account this motivating factor and the effect of clustering on the decline of energy, this article focuses on clustering techniques using various wireless sensor networks aspects. The important contribution of this paper is to give a succinct overview of clustering

Secure and Energy Aware Cluster based Routing using Trust Centric – Multiobjective Black Widow Optimization for large scale WSN

Wireless Sensor Network (WSN) is a promising approach that is developed for a wide range of applications due to its low installation cost. However, the nodes in the WSN are susceptible to different security threats, because these nodes are located in hostile or harsh environments. Moreover, an inappropriate selection of routing path affects the data delivery of the WSN. The important goal of this paper is to obtain secure data transmission while minimizing energy consumption. In this paper, Trust Centric - Multiobjective Black Widow Optimization (TC-MBWO) is proposed for selection of Secure Cluster Head (SCH) from the large-scale WSN. Moreover, the secure routing path is generated by using the TC-MBWO, in which the factors considered for the cost function are: residual energy, distance, trust and node degree. Therefore, the secured clustering and routing achieved by using TC-MBWO, provides the resistance against malicious nodes and simultaneously the energy consumption is also minimized by identifying the shortest path. The proposed TC-MBWO method is analyzed in terms of alive nodes, dead nodes, energy consumption, throughput, and network lifetime. Here, the TC-MBWO method is compared with different existing methods such as Low Energy Adaptive Clustering Hierarchy (LEACH), Particle Swarm Optimization - Grey Wolf Optimizer (PSO-GWO), Particle-Water Wave Optimization (P-WWO) and Particle-based Spider Monkey Optimization (P-SMO). The alive nodes of the TC-MBWO are 70 for 2800 rounds which are higher in number when compared to the PSO-GWO, P-WWO and P-SMO

Distribuirani obrambeni mehanizmi za clone napade temeljeni na algoritmu za istraživanje gravitacije (GSA) u WSN

Wireless Sensor Networks (WSN) are often deployed in hostile environment and are vulnerable to attacks because of the resource constrained nature of the sensors. Clone attack in WSN is one of the major issues where the messages are eavesdropped, the captured node is cloned, and multiple nodes with same identity are produced by attacker. In order to overcome these issues, in this paper, a Distributed Defense Mechanism for Clone Attacks based on Gravitational Search Algorithm (GSA) in WSN is proposed. For efficiently detecting the suspect nodes, the nodes in the channel can be divided into witness node and the claimer node. The witness nodes are responsible for the suspect nodes detection, whereas the claimer nodes should provide their identities for the detection process. For the witness nodes selection, we utilize the GSA to pick out the best witness nodes set. After selecting the witness nodes, clone attack detection is performed by observing the behavior of the neighbor nodes. On detecting the clone attack, revocation procedure is triggered to revoke the clone attack in the witness nodes. By simulation results, it can be concluded that the proposed algorithm provides better protection to clone attacks by reducing the packet drop and increasing the packet delivery ratio.Bežične senzorske mreže (WSN) često su raspoređene u neprijateljskom okruženju i ranjive su na napade zbog prirode senzora koji su tehnološki ograničeni. Clone napad u WSN jedan je od glavnih problema gdje se poruke prisluškuju, zarobljeni čvor se klonira te napadač proizvede višestruke čvorove istog identiteta. Kako bi nadvladali te probleme, ovaj rad predlaže distribuirani obrambeni mehanizam za clone napade temeljen na algoritmu za istraživanje gravitacije (GSA) u WSN. Kako bi se sumnjivi čvorovi efikasno detektirali, čvorovi u kanalu mogu se podijeliti u čvorove svjedoke i tražene čvorove. Čvorovi svjedoci odgovorni su za otkrivanje sumnjivih čvorova, dok traženi čvorovi trebaju za potrebe procesa detekcije navesti svoj identitet. Za izbor čvorova svjedoka, koristi se GSA kako bi se izabrala grupa čvorova koji su najprikladniji. Nakon izbora čvorova svjedoka, otkivanje clone napada vrši se promatranjem ponašanja susjednih čvorova. Otkrivanjem clone napada aktivira se proces opoziva kako bi se opozvao clone napad u čvorovima svjedocima. Prema rezultatima dobivenim iz simulacije može se zaključiti kako predloženi algoritam pruža bolju zaštitu od clone napada smanjivanjem odbacivanja paketa i povećavanjem omjera isporuke paketa

Review on Swarm Intelligence Optimization Techniques for Obstacle-Avoidance Localization in Wireless Sensor Networks

Wireless sensor network (WSN) is an evolving research topic with potential applications. In WSN, the nodes are spatially distributed and determining the path of transmission high challenging. Localization eases the path determining process between source and destination. The article, describes the localization techniques based on wireless sensor networks. Sensor network has been made viable by the convergence of Micro Electro- Mechanical Systems technology. The mobile anchor is used for optimizing the path planning location-aware mobile node. Two optimization algorithms have been used for reviewing the performacne. They are Grey Wolf Optimizer(GWO) and Whale Optimization Algorithm(WOA). The results show that WOA outperforms in maximizing the localization accuracy

Compound Metric Assisted Trust Aware Routing for Internet of Things through Firefly Algorithm

Security and privacy are the major concerns in the internet of things (IoT) which are uncertain and unpredictable. Trust aware routing is one of the recent and effective strategies which ensure better resilience for IoT nodes from different security threats. Towards such concern, this paper proposes a new strategy called independent onlooker withstanding trust aware routing (IOWTAR) for IoT. IOWTAR introduced a new compound trust metric by combining three individual metrics namely independent trust, onlooker trust, and withstanding trust (a combination of resilient trust and immovability trust). Independent trust and onlooker trust are assessed based on direct and indirect experiences of nodes about their neighbor nodes. Withstanding trust is assessed based on the stability and resilience of nodes towards dynamic topological changes and network failures respectively. Further, this work adapted the Firefly algorithm (FFA) to optimize the weights of individual trusts and establishes a secure path. Simulation experiments carried out over the proposed method had shown its superiority in terms of packet delivery ratio, delay, and throughput. The proposed method has gained an average improvement in the throughput is of 23.71%, 20.18%, 17.27%, and 2.88% from PSO, GSA, WOA, and CBBMOR-TSM-IOT methods respectively

Review on Swarm Intelligence Optimization Techniques for Obstacle-Avoidance Localization in Wireless Sensor Networks

Wireless sensor network (WSN) is an evolving research topic with potential applications. In WSN, the nodes are spatially distributed and determining the path of transmission high challenging. Localization eases the path determining process between source and destination. The article, describes the localization techniques based on wireless sensor networks. Sensor network has been made viable by the convergence of Micro Electro- Mechanical Systems technology. The mobile anchor is used for optimizing the path planning location-aware mobile node. Two optimization algorithms have been used for reviewing the performacne. They are Grey Wolf Optimizer(GWO) and Whale Optimization Algorithm(WOA). The results show that WOA outperforms in maximizing the localization accuracy

The Internet of Everything

In the era before IoT, the world wide web, internet, web 2.0 and social media made people’s lives comfortable by providing web services and enabling access personal data irrespective of their location. Further, to save time and improve efficiency, there is a need for machine to machine communication, automation, smart computing and ubiquitous access to personal devices. This need gave birth to the phenomenon of Internet of Things (IoT) and further to the concept of Internet of Everything (IoE)