K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Wireless Sensor Networks (WSN) acquired a lotof attention due to their widespread use in monitoring hostileenvironments, critical surveillance and security applications. Inthese applications, usage of wireless terminals also has grownsignificantly. Grouping of Sensor Nodes (SN) is called clusteringand these sensor nodes are burdened by the exchange of messagescaused due to successive and recurring re-clustering, whichresults in power loss. Since most of the SNs are fitted with nonrechargeablebatteries, currently researchers have been concentratingtheir efforts on enhancing the longevity of these nodes. Forbattery constrained WSN concerns, the clustering mechanism hasemerged as a desirable subject since it is predominantly good atconserving the resources especially energy for network activities.This proposed work addresses the problem of load balancingand Cluster Head (CH) selection in cluster with minimum energyexpenditure. So here, we propose hybrid method in which clusterformation is done using unsupervised machine learning based kmeansalgorithm and Fuzzy-logic approach for CH selection

K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

Wireless Sensor Networks (WSN) acquired a lotof attention due to their widespread use in monitoring hostileenvironments, critical surveillance and security applications. Inthese applications, usage of wireless terminals also has grownsignificantly. Grouping of Sensor Nodes (SN) is called clusteringand these sensor nodes are burdened by the exchange of messagescaused due to successive and recurring re-clustering, whichresults in power loss. Since most of the SNs are fitted with nonrechargeablebatteries, currently researchers have been concentratingtheir efforts on enhancing the longevity of these nodes. Forbattery constrained WSN concerns, the clustering mechanism hasemerged as a desirable subject since it is predominantly good atconserving the resources especially energy for network activities.This proposed work addresses the problem of load balancingand Cluster Head (CH) selection in cluster with minimum energyexpenditure. So here, we propose hybrid method in which clusterformation is done using unsupervised machine learning based kmeansalgorithm and Fuzzy-logic approach for CH selection

Design and Evaluation of Memory Efficient Data Structure Scheme for Energy Drainage Attacks in Wireless Sensor Networks

Wireless Sensor Networks (WSN) are deployed on a large scale and require protection from malicious energy drainage attacks, particularly those directed at the routing layer. The complexity increases during critical operations like cluster head selection where detection of such attacks is challenging. The dependency of WSN on batteries elevates the concern posed by these threats, making detection and isolation crucial, especially within the framework of energy-efficient clustering protocols such as Low Energy Adaptive Clustering Hierarchy (LEACH). Various approaches have been proposed in prior research to deal with such attacks. However, the use of memory-efficient data structures has yet to be effectively addressed. In this article, considering the limitations of WSN, we utilize memory-efficient data structures named Bloom filters, count-min (CM) sketch, and cellular automata (CA) to address abnormal energy drainage. A CA-based trust model is used to choose the legitimate node as the cluster head. CM sketch is used to control the frequency of a node selected as a cluster head, achieving fairness in the cluster head selection process, and Bloom filters maintain the record of malicious nodes blocked from participating in the communication or cluster head selection process. CA and trust functions collectively keep a record of neighbors' energy and their trust in the network. Grayhole, blackhole, and scheduling attacks are three well-known threats that lead to abnormal energy drainage in legitimate nodes. The proposed solution effectively detects and addresses abnormal energy drainage in WSN. Its impact is simulated and observed using ns2 IEEE 802.15.4 medium access control (MAC) and LEACH clustering protocols, specifically in the context of the mentioned attacks. The effectiveness of the proposed model was rigorously analysed, and it was observed that it reduces the energy consumption of WSN by approximately 16.66%, 48.33%, and 43.33% in the cases of grayhole, blackhole, and scheduling attacks, respectively. In terms of space/time complexity, its growth is linear O(n). The proposed solution also consumes 0.08-0.10 J more energy compared to the original LEACH as a cost of the solution, which is not more than 2% of the total initial energy. The tradeoff of implementing heightened security is worthwhile, as the proposed approach outperforms the original LEACH and related methods, effectively mitigating abnormal energy drainage in WSN and extending network lifetime, especially in challenging environments with persistent battery recharging challenges. INDEX TERMS WSN, LEACH, cellular automata, CM sketch, Bloom filter, energy drainage, blackhole, grayhole, and scheduling attacks, trust model

Machine Learning Based Transmission Scheduling For LoRaWANs.

PhD Theses.First and foremost, I would like to thank the government of the Kingdom of Saudi Arabia for the opportunity to pursue my research programme. It has been a great honour to work alongside such an elite team, for which I would like to express my sincerest gratitude to my research supervision panel. Firstly, to my primary supervisor Dr. Kok Keong Chai for his limitless support and continual guidance throughout my research progress. Secondly, to Prof. Yue Chen and Dr. Jesus Requena for their influential feedback and advice. I owe a deep sense of gratitude to Prof. Talib Alukaidey for his genuine support and long-standing ties before and during my research at Queen Mary University of London. Also a special thank you to Dr. Atm Alam for his generous efforts and enlightenment throughout my research. The deepest heartfelt thank you to my father Maj. Gen. Ali Alenezi who taught me the meaning of perseverance, persistence and discipline, to my mother Bahiah Alsharif who taught me the value of seeking knowledge and for always believing in me, to my wife, to my brothers and sisters for the love they have given. Their presence and moral support has made it all possible, for which I am forever indebted to you all. Lastly, thank you to my friends and colleagues for being part of this once in a lifetime experience

Autoconfiguración de redes ad hoc basadas en confianza.

[ES] En la presente tesis se aborda el problema del descubrimiento de vecinos en redes estáticas inalámbricas ad hoc, redes sin infraestructura. En estas redes los nodos deben descubrir los vecinos como un primer paso tras el despliegue. Además se aborda el problema de creación de redes espontáneas basadas en la confianza, y el de selección de vecinos. Se han presentado distintos algoritmos que solucionan el problema siguiendo unas premisas que se irán relajando a lo largo de la tesis. Se han implementado esos algoritmos en Castalia 3.2 para su validación y comparación con otros protocolos de referencia. Los protocolos determinísticos presentan mejores resultados de simulación, aunque requieren que sigan una planificación en la transmisión. En cuanto al protocolo aleatorio CDPRR (Collision Detection Probabilistic Round Robin) no sigue una planificación pero requiere el conocimiento del número de nodos de la red. El protocolo CDH (Collision Detection Hello) permite el desconocimiento del número de nodos. Ambos logran el descubrimiento de los vecinos con probabilidad 1 mediante la detección de colisiones. Ambas propuestas obtienen mejores prestaciones que los protocolos usados como referencia. Tanto para CDH como para CDPRR se ha realizado un modelo analítico de determinadas métricas. Se ha propuesto un protocolo aleatorio basado en líder que permite obtener buenas prestaciones y se puede usar de forma asíncrona aunque solo permite su uso en entornos one-hop. Finalmente, se presenta un protocolo aleatorio consciente de la energía que permite buenos resultados para altos duty cycles y redes compuestas de pocos nodos. En cuanto a la creación de redes espontáneas basadas en la confianza, se ha propuesto un modelo que usa el protocolo CDPRR como base. Este protocolo de creación de redes espontáneas basadas en la confianza permite premisas más realistas y mejora un protocolo determinístico de referencia. Finalmente, se propone un protocolo que combina el descubrimiento y la selección de vecinos con el objetivo de proporcionar nodos favoritos. Estos nodos permiten el envío de información al exterior de la red o en futuras operaciones como el encaminamiento.[CA] En la present tesi s'aborda el problema del descobriment de veïns en xarxes estàtiques sense fil ad hoc, xarxes sense infraestructura. En estes xarxes els nodes han de descobrir els veïns com un primer pas després del desplegament. A més s'aborda el problema de creació de xarxes espontànies basades en la confiança, i el de selecció de veïns. S'han presentat distints algoritmes que solucionen el problema seguint unes premisses que se n'aniran relaxant al llarg de la tesi. S'han implementat eixos algoritmes en Castalia 3.2 per a la seua validació i comparació amb altres protocols de referència. Els protocols determinístics presenten millors resultats de simulació, encara que requerixen que seguisquen una planificació en la transmissió. Quant al protocol aleatori CDPRR (Collision Detection Probabilistic Round Robin) no seguix una planificació però requerix el coneixement del nombre de nodes de la xarxa. El protocol CDH (Collision Detection Hello) permet el desconeixement del nombre de nodes. Ambdós aconseguixen el descobriment dels veïns amb probabilitat 1 per mitjà de la detecció de col·lisions. Ambdós propostes obtenen millors prestacions que els protocols usats com a referència. Tant per a CDH com per a CDPRR s'ha realitzat un model analític de determinades mètriques. S'ha proposat un protocol aleatori basat en líder que permet obtindre bones prestacions i es pot usar de forma asíncrona encara que només permet el seu ús en entorns onehop. Finalment, es presenta un protocol aleatori conscient de l'energia que permet bons resultats per a alts duty cycles i xarxes compostes de pocs nodes. Quant a la creació de xarxes espontànies basades en la confiança, s'ha proposat un model que usa el protocol CDPRR com a base. Este protocol de creació de xarxes espontànies basades en la confiança permet premisses més realistes i millora un protocol determinístic de referència. Finalment, es proposa un protocol que combina el descobriment i la selecció de veïns amb l'objectiu de proporcionar nodes favorits. Estos nodes permeten l'enviament d'informació a l'exterior de la xarxa o en futures operacions com l'encaminament.[EN] This thesis addresses the neighbor discovery problem in static wireless ad hoc networks, infrastructure-less networks. In these networks the nodes must discover the neighbors as a first step after the deployment. Furthermore, the thesis addresses the problem of creation of spontaneous networks based on trust, and the neighbor selection. Several algorithms have been presented that solve the problem following some assumptions that will be relaxed throughout the thesis. Those algorithms have been implemented in Castalia 3.2 for validation and comparison with other reference protocolos. The deterministic protocols provide better simulation results, although they require a transmission schedule. As for the randomized protocol CDPRR (Collision Detection Probabilistic Round Robin), it does not follow a schedule but it requires the knowledge of the number of nodes in the network. The CDH (Collision Detection Hello) protocol allows the ignorance of the number of nodes. They both achieve the discovery of the neighbors with probability 1 by detecting collisions. Both proposals achieve better performance than the protocols used as reference. For CDH and CDPRR an analytical model has been carried out regarding several metrics. A randomized protocol based on leader has been proposed that achieves a good performance and it can be used in an asynchronous way although it can only be used in one-hop environments. Finally, an energy-aware randomized protocol is proposed, which achieves good results for high duty cycles and networks composed of a small number of nodes. As for the creation of spontaneous networks based on trust, a model has been proposed which is based on the CDPRR protocol. This protocol for the creation of spontaneous networks based on trust allows more realistic assumptions and outperforms a determinsitic protocol used as reference. Finally, a protocol is proposed which combines the discovery and selection of neighbors aiming at providing favourite nodes. These nodes allow sending information towards outside the network or in future operations such as routing.Sorribes Díaz, JV. (2021). Autoconfiguración de redes ad hoc basadas en confianza [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/180283TESI