Clustering objectives in wireless sensor networks: A survey and research direction analysis

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect data, and transfer it to remote servers for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been a fundamental challenge in these types of net- works given the deployment size and the associated quality concerns such as resource management, scalability, and reliability. Topology management is considered a viable technique to address these concerns. Clustering is the most well-known topology management method in WSNs, grouping nodes to manage them and/or executing various tasks in a distributed manner, such as resource management. Although clustering techniques are mainly known to improve energy consumption, there are various quality-driven objectives that can be realized through clustering. In this paper, we review comprehensively existing WSN clustering techniques, their objectives and the network properties supported by those techniques. After refining more than 500 clustering techniques, we extract about 215 of them as the most important ones, which we further review, catergorize and classify based on clustering objectives and also the network properties such as mobility and heterogeneity. In addition, statistics are provided based on the chosen metrics, providing highly useful insights into the design of clustering techniques in WSNs.publishedVersio

Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks

This book presents collective works published in the recent Special Issue (SI) entitled "Recent Developments on Mobile Ad-Hoc Networks and Vehicular Ad-Hoc Networks”. These works expose the readership to the latest solutions and techniques for MANETs and VANETs. They cover interesting topics such as power-aware optimization solutions for MANETs, data dissemination in VANETs, adaptive multi-hop broadcast schemes for VANETs, multi-metric routing protocols for VANETs, and incentive mechanisms to encourage the distribution of information in VANETs. The book demonstrates pioneering work in these fields, investigates novel solutions and methods, and discusses future trends in these field

An Intelligent Management System for Hybrid Network between Visible Light Communication and Radio Frequency

This thesis investigates the challenges and potential solutions associated with hybrid Visible Light Communication (VLC) and Radio Frequency (RF) systems for indoor network environments. The rapid development of VLC technology, characterized by its high data rates, energy efficiency, and inherent security features, offers promising opportunities to complement RF networks in providing seamless connectivity and improved performance. However, integrating VLC and RF technologies effectively requires addressing a range of research and engineering challenges, including network coexistence, handover mechanisms, resource allocation, localization, and standardization.We begin by conducting a comprehensive literature review encompassing existing research, technologies, and solutions related to hybrid VLC/RF architectures, handover management, indoor localization techniques, and the challenges faced by these systems. This background provides a solid foundation for understanding the current state-of-the-art and identifying research gaps in the field of hybrid VLC/RF networks.Next, we propose a novel hybrid network architecture that integrates VLC and RF communication systems to enhance their strengths while mitigating their weaknesses. We discuss various types of hybrid VLC/RF architectures found in the literature and present our proposed design, which addresses the identified challenges through innovative strategies and mechanisms.To improve system performance in our hybrid system, we develop an enhanced priority feedback channel that optimizes the traffic priority based on user preferences and network conditions. This approach minimizes service disruptions, reduces latency, and maintains user Quality of Experience (QoE)\nomenclature{QoE}{Quality of Experience}.Furthermore, we introduce a novel intelligent management system architecture tailored for hybrid VLC/RF networks. This system employs advanced algorithms and techniques to optimize resource allocation, load balancing, localization, and handover management, ensuring efficient operation and seamless connectivity.We evaluate the performance of our proposed solutions through extensive simulations and testbed experiments, considering different network scenarios and metrics. The results demonstrate significant improvements in terms of data rate, latency, handover success rate, and localization accuracy, validating the effectiveness of our proposed architecture and management system.Lastly, we explore several real-world applications and case studies of our intelligent management system in various indoor environments, such as retail stores, offices, and hospitals. These examples illustrate the practical benefits of our solution in enhancing customer experiences, optimizing operational efficiency, facilitating targeted marketing, and improving energy management.In conclusion, this thesis contributes to the advancement of hybrid VLC/RF networks by proposing an innovative architecture and intelligent management system that address the key challenges faced by these systems in indoor environments. The findings and solutions presented in this work provided the backbone for the future research and development efforts aimed at fully harnessing the potential of VLC technology in combination with RF networks

SRP-HEE: A Modified Stateless Routing Protocol based on Homomorphic Energy based Encryption for Wireless Sensor Network

Due to the wireless nature, the sensors node data are prone to location privacy of source and classification of the packet by unauthorized parties. Data encryption is one of the most effective ways to thwart unauthorized access to the data and trace information. Traditional wireless network security solutions are not viable for WSNs In this paper, a novel distributed forward aware factor based heuristics towards generating greedy routing using stateless routing is SRP-HEE for wireless sensor network. The model employs the homomorphic Energy based encryption technique. Energy based Encryption model is devoted as homomorphic mechanism due to their less computational complexity. Additionally, privacy constraint becoming a critical issue in the wireless sensor networks (WSNs) because sensor nodes are generally prone to attacks which deplete energy quickly as it is exposed to mobile sink frequently for data transmission. Through inclusion of the Forward aware factor on the Greedy routing strategies, it is possible to eliminate the attacking node which is depleting the energy of the source node. Heuristic conditions are used for optimizing the sampling rate and battery level for tackling the battery capacity constraints of the wireless sensor nodes. The Node characteristics of the propagating node have been analysed utilizing kalman filter and linear regression. The cooperative caching of the network information will enable to handle the fault condition by changing the privacy level of the network. The Simulation results demonstrate that SRP-HEE model outperforms existing technique on basis of Latency, Packet Delivery Ratio, Network Overhead, and Energy Utilization of nodes

Energy Efficient Multicast Routing in Mobile Ad Hoc Networks: Contemporary Affirmation of Benchmarking Models in Recent Literature

The Mobile Ad hoc Networks playing critical role in network aided communication requirements The features such as ad hoc and open architecture based connectivity and node mobility are elevating the mobile ad hoc networks as much as feasible to deploy and use The direct communication between any of two nodes in this network is possible if target node is in the range of source node If not the indirect communication took place which is usually referred as multi hop routing The multi hop routing occurs as either a unicast model one source node to one destination node multicast model one source node to multiple destination nodes or multiple casting manifold unicast routing In these routing strategies provision of service quality in multi hop routing is a challenging task The optimal quality of service in routing magnifies the delivery ratio transmission rate network life span and other expected characteristics of the ad hoc routing Among the quality service provision factors minimal energy conservation is prime factor which is since the nodes involved in routing are self-energized and if discharged early then the route will be destructed that causes discontinued routing The energy consumption is more specific in multicast routing hence it is grabbing the more attention of the current research contribution

Learning algorithms for the control of routing in integrated service communication networks

There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

Design Models for Trusted Communications in Vehicle-to-Everything (V2X) Networks

Intelligent transportation system is one of the main systems which has been developed to achieve safe traffic and efficient transportation. It enables the road entities to establish connections with other road entities and infrastructure units using Vehicle-to-Everything (V2X) communications. To improve the driving experience, various applications are implemented to allow for road entities to share the information among each other. Then, based on the received information, the road entity can make its own decision regarding road safety and guide the driver. However, when these packets are dropped for any reason, it could lead to inaccurate decisions due to lack of enough information. Therefore, the packets should be sent through a trusted communication. The trusted communication includes a trusted link and trusted road entity. Before sending packets, the road entity should assess the link quality and choose the trusted link to ensure the packet delivery. Also, evaluating the neighboring node behavior is essential to obtain trusted communications because some misbehavior nodes may drop the received packets. As a consequence, two main models are designed to achieve trusted V2X communications. First, a multi-metric Quality of Service (QoS)-balancing relay selection algorithm is proposed to elect the trusted link. Analytic Hierarchy Process (AHP) is applied to evaluate the link based on three metrics, which are channel capacity, link stability and end-to-end delay. Second, a recommendation-based trust model is designed for V2X communication to exclude misbehavior nodes. Based on a comparison between trust-based methods, weighted-sum is chosen in the proposed model. The proposed methods ensure trusted communications by reducing the Packet Dropping Rate (PDR) and increasing the end-to-end delivery packet ratio. In addition, the proposed trust model achieves a very low False Negative Rate (FNR) in comparison with an existing model

Measurements, Models, Systems and Design

531 s.