Fuzzy-TOPSIS based Cluster Head selection in mobile sensor networks

One of the critical parameters of Wireless Sensor Networks (WSNs) is node lifetime. There are various methods to increase WSN node lifetime, the clustering technique is being one of them. In clustering, selection of a desired percentage of Cluster Heads (CHs) is performed among the sensor nodes (SNs). Selected CHs are responsible for collecting data from their member nodes, aggregating the data and finally sending it to the sink. In this paper, we propose a Fuzzy-TOPSIS technique, based on multi criteria decision making, to choose CH efficiently and effectively to maximize the WSN lifetime. We will consider several criteria including: residual energy; node energy consumption rate; number of neighbor nodes; average distance between neighboring nodes; and distance from the sink. A threshold based intra-cluster and inter-cluster multi-hop communication mechanism is used to decrease energy consumption. We have also analyzed the impact of node density and different types of mobility strategies in order to investigate impact over WSN lifetime. In order to maximize the load distribution in the WSN, a predictable mobility with octagonal trajectory is proposed. This results in improvement of overall network lifetime and latency. Results shows that the proposed scheme improves the network lifetime by 60%, conserve energy by 80%, a significant reduction of frequent Cluster Head (CH) per round selection by 25% is achieved as compared to the conventional Fuzzy and LEACH protocols

Fuzzy TOPSIS-based Secure Neighbor Discovery Mechanism for Improving Reliable Data Dissemination in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) being an indispensable entity of the Internet of Things (IoT) are found to be more and more widely utilized for the rapid advent of IoT environment. The reliability of data dissemination in the IoT environment completely depends on the secure neighbor discovery mechanism that are utilized for effective and efficient communication among the sensor nodes. Secure neighbor discovery mechanisms that significantly determine trustworthy sensor nodes are essential for maintaining potential connectivity and sustaining reliable data delivery in the energy-constrained self organizing WSN. In this paper, Fuzzy Technique of Order Preference Similarity to the Ideal Solution (TOPSIS)-based Secure Neighbor Discovery Mechanism (FTOPSIS-SNDM) is proposed for estimating the trust of each sensor node in the established routing path for the objective of enhancing reliable data delivery in WSNs. This proposed FTOPSIS-SNDM is proposed as an attempt to integrate the merits of Fuzzy Set Theory (FST) and TOPSIS-based Multi-criteria Decision Making (MCDM) approach, since the discovery of secure neighbors involves the exchange of imprecise data and uncertain behavior of sensor nodes. This secure neighbor is also influenced by the factors of packet forwarding potential, delay, distance from the Base Station (BS) and residual energy, which in turn depends on multiple constraints that could be possibly included into the process of secure neighbor discovery. The simulation investigations of the proposed FTOPSIS-SNDM confirmed its predominance over the benchmarked approaches in terms of throughput, energy consumption, network latency, communication overhead for varying number of genuine and malicious neighboring sensor nodes in network

CH Selection via Adaptive Threshold Design Aligned on Network Energy

Energy consumption in Wireless Sensor Networks (WSN) involving multiple sensor nodes is a crucial parameter in many applications like smart healthcare systems, home automation, environmental monitoring, and industrial use. Hence, an energy-efficient cluster-head (CH) selection strategy is imperative in a WSN to improve network performance. So to balance the harsh conditions in the network with fast changes in the energy dynamics, a novel energy-efficient adaptive fuzzy-based CH selection approach is projected. Extensive simulations exploited various real-time scenarios, such as varying the optimal position of the location of the base station and network energy. Additionally, the results showed an improved performance in the throughput (46%) and energy consumption (66%), which demonstrated the robustness and efficacy of the proposed model for the future designs of WSN applications

Metaheuristics Techniques for Cluster Head Selection in WSN: A Survey

In recent years, Wireless sensor communication is growing expeditiously on the capability to gather information, communicate and transmit data effectively. Clustering is the main objective of improving the network lifespan in Wireless sensor network. It includes selecting the cluster head for each cluster in addition to grouping the nodes into clusters. The cluster head gathers data from the normal nodes in the cluster, and the gathered information is then transmitted to the base station. However, there are many reasons in effect opposing unsteady cluster head selection and dead nodes. The technique for selecting a cluster head takes into factors to consider including residual energy, neighbors’ nodes, and the distance between the base station to the regular nodes. In this study, we thoroughly investigated by number of methods of selecting a cluster head and constructing a cluster. Additionally, a quick performance assessment of the techniques' performance is given together with the methods' criteria, advantages, and future directions

Trust-based energy efficient routing protocol for wireless sensor networks

Wireless Sensor Networks (WSNs) consist of a number of distributed sensor nodes that are connected within a specified area. Generally, WSN is used for monitoring purposes and can be applied in many fields including health, environmental and habitat monitoring, weather forecasting, home automation, and in the military. Similar, to traditional wired networks, WSNs require security measures to ensure a trustworthy environment for communication. However, due to deployment scenarios nodes are exposed to physical capture and inclusion of malicious node led to internal network attacks hence providing the reliable delivery of data and trustworthy communication environment is a real challenge. Also, malicious nodes intentionally dropping data packets, spreading false reporting, and degrading the network performance. Trust based security solutions are regarded as a significant measure to improve the sensor network security, integrity, and identification of malicious nodes. Another extremely important issue for WSNs is energy conversation and efficiency, as energy sources and battery capacity are often limited, meaning that the implementation of efficient, reliable data delivery is an equally important consideration that is made more challenging due to the unpredictable behaviour of sensor nodes. Thus, this research aims to develop a trust and energy efficient routing protocol that ensures a trustworthy environment for communication and reliable delivery of data. Firstly, a Belief based Trust Evaluation Scheme (BTES) is proposed that identifies malicious nodes and maintains a trustworthy environment among sensor nodes while reducing the impact of false reporting. Secondly, a State based Energy Calculation Scheme (SECS) is proposed which periodically evaluates node energy levels, leading to increased network lifetime. Finally, as an integrated outcome of these two schemes, a Trust and Energy Efficient Path Selection (TEEPS) protocol has been proposed. The proposed protocol is benchmarked with A Trust-based Neighbour selection system using activation function (AF-TNS), and with A Novel Trust of dynamic optimization (Trust-Doe). The experimental results show that the proposed protocol performs better as compared to existing schemes in terms of throughput (by 40.14%), packet delivery ratio (by 28.91%), and end-to-end delay (by 41.86%). In conclusion, the proposed routing protocol able to identify malicious nodes provides a trustworthy environment and improves network energy efficiency and lifetime

Lifetime improved WSN using enhanced-LEACH and angle sector-based energy-aware TDMA scheduling

This research article published by Cogent Engineering, 2020Network lifetime remains as a significant requirement in Wireless Sensor Network (WSN) exploited to prolong network processing. Deployment of low power sensor nodes in WSN is essential to utilize the energy efficiently. Clustering and sleep scheduling are the two major processes involved in improving network lifetime. However, abrupt and energy unaware selection of cluster head (CH) is nonoptimal in WSN which reflects in the drop of energy among sensor nodes. This paper addresses the twofold as utilization of sensor nodes to prolong the node’s energy and network lifetime by LEACH-based cluster formation and Time Division Multiple Access scheduling (TDMA). Clusters are constructed by the design of an EnhancedLow-Energy adaptive Clustering Hierarchy protocol (E-LEACH) that uses parallel operating optimization (Grey Wolf Optimization (GWO) and Discrete Particle Swarm Optimization (D-PSO)) for selecting an optimal CH and helper CH. The fitness values estimation from GWO and D-PSO is concatenated to prefer the best optimal CH. E-LEACH also manages the cluster size which is one of the conventional disadvantages in LEACH. CHs are responsible to perform energy-aware TDMA scheduling which segregates the coverage area into 24 sectors. Alternate sectors are assigne

Energy-Efficient Routing Protocol for Selecting Relay Nodes in Underwater Sensor Networks Based on Fuzzy Analytical Hierarchy Process

The use of underwater sensor networks (UWSNs) offers great advantages in many automatic observation services such as water monitoring (ocean, sea, etc.) and registering of geological events (landslides, earthquakes). However, UWSNs have many more limitations than terrestrial sensor networks (smaller bandwidth, higher delays, etc.) with new requirements such as low power consumption by nodes or being able to select appropriate routes in a dynamic topology due to water currents and movements. To cope with these problems, the use of a routing protocol is very important. In this paper we propose a routing technique that adapts to changes in the network topology, avoiding multiple retransmissions that would affect its overall performance. This protocol is energy-efficient and is implemented using a fuzzy analytical hierarchical process (FAHP) under multi-criteria decision making (MCDM) to make an intelligent routing decision based on objectives, criteria and alternatives. To select the next node on the route, several comparison matrices are used: number of hops, distances to the sink node, and number of neighbors. The results show that the proposed setup behaves similarly to other existing underwater sensor network routing schemes using fuzzy schemes such as SPRINT.This research was funded in part by the Spanish Ministry of Science and Innovation through the project “NAUTILUS: Swarms of underwater autonomous vehicles guided by artificial intelligence: its time has come” (Grant: PID2020-112502RB/AEI/10.13039/501100011033). Partial funding for open access charge: Universidad de Málag

A Taxonomy and Review of Lightweight Blockchain Solutions for Internet of Things Networks

Internet of things networks have spread to most digital applications in the past years. Examples of these networks include smart home networks, wireless sensor networks, Internet of Flying Things, and many others. One of the main difficulties that confront these networks is the security of their information and communications. A large number of solutions have been proposed to safeguard these networks from various types of cyberattacks. Among these solutions is the blockchain, which gained popularity in the last few years due to its strong security characteristics, such as immutability, cryptography, and distributed consensus. However, implementing the blockchain framework within the devices of these networks is very challenging, due to the limited resources of these devices and the resource-demanding requirements of the blockchain. For this reason, a large number of researchers proposed various types of lightweight blockchain solutions for resource-constrained networks. The "lightweight" aspect can be related to the blockchain architecture, device authentication, cryptography model, consensus algorithm, or storage method. In this paper, we present a taxonomy of the lightweight blockchain solutions that have been proposed in the literature and discuss the different methods that have been applied so far in each "lightweight" category. Our review highlights the missing points in existing systems and paves the way to building a complete lightweight blockchain solution for resource-constrained networks.Comment: 64 pages, 11 figures

TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decision-making

The internet of things (IoT) based on a network layer perspective includes low-power and lossy networks (LLN) that are limited in terms of power consumption, memory, and energy usage. The routing protocol used in these networks is called routing over low-power and lossy networks (RPL). Therefore, the IoT networks include smart objects that need multiple routing for their interconnections which makes traffic load balancing techniques indispensable to RPL routing protocol. In this paper, we propose a method based on fuzzy logic and the technique for the order of prioritization by similarity to the ideal solution (TOPSIS) as a well-known multi-criteria decision-making method to solve the load balancing problem by routing metrics composition. For this purpose, a combination of both link and node routing metrics namely hop count, expected transmission count, and received signal strength indicator is used. The results of simulations show that this method can increase the quality of services in terms of packet delivery ratio and average end-to-end delay

A lightweight blockchain based framework for underwater ioT

The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including underwater monitoring, where sensors are located at various depths, and data must be transmitted to surface base stations for storage and processing. Ensuring that data transmitted across hierarchical sensor networks are kept secure and private without high computational cost remains a challenge. In this paper, we propose a multilevel sensor monitoring architecture. Our proposal includes a layer-based architecture consisting of Fog and Cloud elements to process and store and process the Internet of Underwater Things (IoUT) data securely with customized Blockchain technology. The secure routing of IoUT data through the hierarchical topology ensures the legitimacy of data sources. A security and performance analysis was performed to show that the architecture can collect data from IoUT devices in the monitoring region efficiently and securely. © 2020 by the authors. Licensee MDPI, Basel, Switzerland