A Multi-Objective Optimization Framework for Cluster-Based Wireless Sensor Networks

Reputation and Trust‐based Monitoring Systems (RTMSs) have provided a ubiquitous framework for secure Wireless Sensor Network (WSN) computing. However, neighborhood monitoring, though useful, consumes substantial amounts of sensor resources. Therefore, employing sensors for neighborhood monitoring, which is secondary to their intended duties, depletes valuable and scarce resources. This eventually leads to shortened network lifetime, which is counter‐productive in WSNs. In this paper, we propose a novel, Connected Dominating Set (CDS)‐based reputation monitoring system. Our model is the first attempt to employ a CDS‐based monitoring backbone to securely aggregate the reputation of sensors without subjecting them to energy depletion or reputation pollution attacks encountered in existing reputation monitoring systems. Secure and certificateless node mobility and robustness to node replication and ID spoofing attacks are two vital by‐products of our model. We confirm the performance of our model via simulation studies. Copyright © 2010 John Wiley & Sons, Ltd.

Building modern Internet of Things (IoT) systems is associated with a number of challenges. One of the most significant among them is the need for wireless technology, which will serve to build connectivity between the individual components of this technology. In the larger cities of Bulgaria, measures to ensure low levels of harmful emissions, reduce noise levels, and ensure comfort in urban environments have been taken. LoRa technology shows more advantages in transmission distance and low energy consumption compared to other technologies. That is why this technology was chosen for the design of wireless sensor networks (WSN) for six cities in Bulgaria. These networks have the potential to be used in IoT configurations. Appropriate modules and devices for building WSN for cities in Bulgaria have been selected. It has been found that the greater number of nodes in the WSN leads to an increase in the average power consumed in the network. On the other hand, depending on the location of these nodes, the energy consumed may decrease. The performance of wireless sensor networks can be optimized by applying appropriate routing protocols, which are proposed in the available literature. The methodology for energy efficiency analysis of WSN can be used in the design of wireless sensor networks to determine the parameters of the environment, with the possibility of application in IoT.

Data aggregation is an important process for wireless sensor networks (WSNs). The important aspects with WSNs are to increase the lifetime and to reserve the battery power of sensor nodes. The energy of nodes is mainly utilized in the process of sensing and transmitting the data. Clustering is one of the processes in which the total WSNs are divided into the form of groups and each group has a cluster head (CH) and advantage of doing this is decrease of energy consumption and reduce the data collision. The blockchain technology is utilized in WSN by so many ways for example security, data storing, node recovery etc. because the role of blocks in blockchain is same as the role of node in WSN. In this paper, we propose a cluster-based data aggregation framework for wireless sensor networks based on the blockchain technique. The proposed scheme is based on cluster head (CH) selection based on energy, and nodes communicate with each other via the shortest path. Further, the proposed scheme is also using the concept of blockchain technology for the purpose of maximum data storage. KeywordsWireless sensor networksLow energy adaptive clustering hierarchy (LEACH)Data aggregationCluster headBlockchainAnd Energy consumption

The main constraint that affects the practical design of Wireless Sensor Networks (WSNs) is the network energy as network nodes has limited resources capabilities. Low Energy Adaptive Clustering Hierarchy (LEACH) routing protocol is one of the popular clustering based algorithms that optimize energy consumption of WSN. The selection of Cluster Heads (CHs) in each round is determined depending on a random number generated by each node, which compared to a threshold value. The generated random number is the main factor in CH selection process. Normally, the random number is varied each time when calling the random number generator. The effect of the generated random numbers is neutralized during this work to get real effect of the suggested enhancements.

Opportunistic routing in wireless sensor networks powered by ambient energy harvesting

This paper describes a multi-objective evolutionary approach for solving multi-objective 3D deployment problems in differentiated wireless sensor networks (WSNs). WSN is a wireless network consisting of spatially distributed autonomous sensors to monitor physical or environmental conditions. Deciding the location of sensor to be deployed on a terrain with the consideration different criteria is an important issue for the design of wireless sensor network. A multi-objective genetic algorithm is proposed to solve 3D differentiated WSN deployment problems with the objectives of the coverage of sensors, satisfaction of detection thresholds, and energy conservation. The preliminary experimental results demonstrated that the proposed approach is suitable for solving 3D deployment problems of WSNs with different requirements.

Safe path-finding is extremely necessary for multihop wireless systems such as Wireless Sensor Networks. Multihop wireless systems are more unprotected to safety outbreaks as associated to single-stage wireless networks. Cross-layer design production is a precise significant character for wireless sensor Advanced security network is significant submissions. for the achievement of announcement among sensor nodes in wireless sensor network because the numbers composed is regularly less and the network is most vulnerable. Numerous Security methods have been suggested to deliver safety resolutions besides numerous threats to the Cross layer modification techniques in Wireless sensor networks. In this paper we overview the existing schemes for the security of cross-layer design in wireless sensor networks. The proposed Security model will provide more security between sensor nodes and the base station in wireless sensor network. Security is important for the success of the wireless sensor network because the data collected are often sensitive and the network is particularly vulnerable. In the cross-layer design, constraints are substituted between changed layers to protect the well-organized use of energy. In this paper, we propose a secure security model that is based on cross-layer design. It uses a cross layer optimization Machine Reproduction consequences confirm that our proposed safety model better in many situations and in unpromising violence-disposed to the situation.

This paper presents the design of wireless sensor network (WSN) based on low-power wide area network technology for high-tech agriculture. This WSN allows the farmer to collect data such as air temperature, air humidity, soil moisture. The WSN system consists of components: 02 wireless sensor nodes, 01 gateway, 01 cloud server and smartphone app. This WSN tested for data transmission in two zones: zone 1 (dense urban environments) at a distance of 500m and zone 2 (urban environments - less obstacles) at a distance of 1,500m and 1,700m. The data collected at different times of the day and updated every 15 minutes. The results show that the wireless sensor network system operates stably, data constantly updated to LoRa Server and there was not data packet loss. The power consumption of sensor node and gateway determined in three operating modes: transmitting, receiving, turn-off. This shows the advantages of LoRa technology in the development of wireless sensor network which is the distance of data transmission distance and low power consumption. Besides this WSN also tested in the net house of aquaponics of the Research Center for High-tech Application in Agriculture (RCHAA), University of Science, Vietnam National University-HCM. The results show that the WSN system is working reliably and promising which brings significantly benefits to smart agriculture as aquaponics, clean vegetable farms, aquaculture farms…

This paper designs the mathematical model of fiber line power, optimization of wireless sensor network node and multi distributed IP, and uses C language to program the model, finally get a new energy-saving mechanism model of wireless sensor network.Combined with the distributed IPv6 technology and IEEE802.15.4 protocol, this paper designs a new 6LoWPAN wireless sensor network energy-saving mechanism, which realizes the seamless splicing energy-saving effect between wireless sensor network and the internet, and based on this develops Contiki integrated environment of wireless sensor network energy-saving test.Finally this paper uses Firefox browser with B/S architecture to test energysaving mechanism.Through the test we found that between two nodes of wireless sensor network, they can effectively realize sending and receiving of UDP data, and through IPv6 gateway it can connect with internet, and complete collection and transmission of data.Through the simulation calculation of power consumption, in accepting, transmission and idle periods, the wireless sensor network can save energy effectively, which reduces the splicing cost of internet and wireless sensor network.It provides the technical reference for the design of wireless sensor network.

In a wireless sensor network, the size of radio nodes has direct relation to the cost of total wireless sensor networks, and at the same time, the problem is closely connected to wireless sensor networks' performance, such as robust, fault-tolerance, and further more, it is considered at first as wireless sensor networks are designed. Therefore, the research on the size of radio nodes has significant meanings of theory and practice to design of wireless sensor networks. The paper simplifies complex coverage problem step by step. By means of math modeling, theoretical analysis and formula deducting, classical geometric theories and the method of mathematics induction are adopted, at last, the analysis formula of minimum number of nodes is theoretically educed under circumstances of entire and seamless coverage in WSN. In addition, it is worth mentioning that the conclusion is the full same with computing the number of communication nodes of wireless sensor networks.

Wireless sensor networks (WSNs) consist of many sensor nodes that are densely deployed throughout a randomized geographical area to monitor, detect, and analyze various physical phenomena. The primary obstacle encountered in WSNs pertains to the significant reliance of sensor nodes on finite battery power for wireless data transfer. Sensors as a crucial element inside Cyber-Physical Systems (CPS) renders them vulnerable to failures arising from intricate surroundings, substandard manufacturing, and the passage of time. Various anomalies can appear within WSNs, mostly attributed to defects such as hardware and software malfunctions and anomalies and assaults initiated by unauthorized individuals. These anomalies significantly impact the overall integrity and completeness of the data gathered by the networks. Therefore, it is imperative to provide a critical mechanism for the early detection of faults, even in the presence of constraints imposed by the sensor nodes. Machine Learning (ML) techniques encompass a range of approaches that may be employed to identify and diagnose sensor node faults inside a network. This paper presents a novel Energy-aware and Context-aware fault detection framework (ECFDF) that utilizes the Extra-Trees algorithm (ETA) for fault detection in WSNs. To assess the effectiveness of the suggested methodology for identifying context-aware faults (CAF), a simulated WSN scenario is created. This scenario consists of data from humidity and temperature sensors and is designed to emulate severe low-intensity problems. This study examines six often-seen categories of sensor fault, including drift, hard-over/bias, spike, erratic/precision, stuck, and data loss. The ECFDF approach utilizes an Energy-Efficient Fuzzy Logic Adaptive Clustering Hierarchy (EE-FLACH) algorithm to select a Super Cluster Head (SCH) within WSNs. The SCH is responsible for achieving optimal energy consumption within the network, and this selection process facilitates the early detection of faults. The results of the simulation indicate that the ECFDF technique has superior performance in terms of Fault Detection Accuracy (FDA), False-Positive Rate (FPR), and Mean Residual Energy (MRE) when compared to other detection and classification methods.

Wireless sensor networks (WSNs) is a class of wireless ad hoc networks in which sensor nodes sense, process, and communicate data acquired from the physical environment to an external-base-station (BS). But the fundamental challenge in the design of wireless sensor networks (WSNs) is to maximise their lifetimes especially when they have a limited and non-replenish able energy supply. Energy-efficient communication is necessary to increase the lifetime of the sensor network. In this work solutions are for the data gathering and routing problem with in network aggregation in WSNs. The aim of our work is to focus on data gathering and redundancy elimination with in-network aggregation in WSNs. The objective is to maximise the network lifetime by utilising data aggregation with redundancy removal by increasing accuracy thereby improving packet delivery ratio and reducing energy consumption. This work focuses on the maximum lifetime data gathering and routing to avoid packet loss in wireless sensor networks.

Energy consumption and energy modeling are important issues in designing and implementing of Wireless Sensor Networks (WSNs), which help the designers to optimize the energy consumption in WSN nodes. Good knowledge of the sources of energy consumption in WSNs is the first step to reduce energy consumption. Therefore, an accurate energy model is required for the evaluation of communication protocols. In this paper, an energy model for WSNs is provided considering the physical layer and MAC layer parameters by determining the energy consumed per payload bit transferred without error over AWGN channel. This model has been tested with real data and and NS-2 simulator. Results show good agreement between proposed model, experimental measurements and NS-2 simulator with mean absolute percentage error less than 5.18%. Furthermore, the proposed model is exploited to optimize transmitted power to achieve minimum energy consumption. Finally, a closed-form expression for optimum transmitted power is derived for M-QAM modulation scheme.

Today the wireless sensor networks (WSN) play a crucial role in wireless technology in various domains like military, medicine, communications etc. The energy conservation is the crucial factor in the WSN. The WSN is a system which has more number of nodes in which various sensors are fabricated on the nodes to monitor various factors of the given task. These nodes will form a network by connecting the one to other for the effective communication between the nodes, and sends the whole information to the base station (BS). As the nodes which we use for the WSN are of low cost and are battery operated. The main drawback is replacement of the battery in the WSN. The main goal is to conserve the energy consumption in WSN and also to balance the load on WSN. For this many protocols are designed like LEACH, PEGASIS, PEDAP, etc. in those balancing the load and time delayed. some drawbacks are there. So we proposed a protocol so called “Tree Based Energy Balancing routing Protocol by Self Organizing” (TEBRSO), in which instead of routing tables a routing tree will be used for routing from nodes to base station (BS), which chooses one root/control node for the broadcasting messages to the selected sensor nodes. By this protocol we can save the energy consumption in WSN and can extend the life time of it. The performance of this protocol is better when we compare with other energy saving protocols.

Wireless Sensor Networks (WSNs) are gaining immense popularity as a result of their wide potential applications in industry, military, and academia such as military surveillance, agricultural monitoring, industrial automation, and smart homes. Currently, WSN has garnered tremendous significance as it is has become the core component of the Internet of Things (IOT) area. Modern-day applications need a high level of security and quick response mechanism to deal with the emerging data trends where the response is measured in terms of latency, throughput, and scalability. Further, critical security issues need to be considered due to various types of threats and attacks WSNs are exposed to as they are deployed in harsh and hostile environments unattended in most of the mission critical applications. The fact that a complex sensor network consisting of simple computing units has similarities with specific animal communities, whose members are often very simple but produce together more sophisticated and capable entities. Thus, from an algorithmic viewpoint, bio-inspired framework such as swarm intelligence technology may provide valuable alternative to solve the large scale optimization problems that occur in wireless sensor networks. Self-organization, on the other hand, can be useful for distributed control and management tasks. In this chapter, swarm intelligence and social insects-based approaches developed to deal with a bio-inspired networking framework are presented. The proposed approaches are designed to tackle the challenges and issues in the WSN field such as large scale networking, dynamic nature, resource constraints, and the need for infrastructure-less and autonomous operation having the capabilities of self-organization and survivability. This chapter covers three phases of the research work carried out toward building a framework. First phase involves development of SIBER-XLP model, Swarm Intelligence Based Efficient Routing protocol for WSN with Improved Pheromone Update Model, and Optimal Forwarder Selection Function which chooses an optimal path from source to the sink to forward the packets with the sole objective to improve the network lifetime by balancing the energy among the nodes in the network and at the same time selecting good quality links along the path to guarantee that node energy is not wasted due to frequent retransmissions. The second phase of the work develops a SIBER-DELTA model, which represents Swarm Intelligence Based Efficient Routing protocol for WSN taking into account Distance, Energy, Link Quality, and Trust Awareness. WSNs are prone to behavior related attacks due to the misbehavior of nodes in forwarding the packets. Hence, trust aware routing is important not only to protect the information but also to protect network performance from degradation and protect network resources from undue consumption. Finally, third phase of the work involves the development of SIBER-DELTAKE hybrid model, an improved ACO-KM-ECC trust aware routing protocol based on ant colony optimization technique using K-Medoids (KM) algorithm for the formation of clusters with Elliptical Curve Cryptography (ECC). KM yields efficiency in setting up a cluster head and ECC mechanism enables secure routing with key generation and management. This model takes into account various critical parameters like distance, energy, link quality, and trust awareness to discover efficient routing.