scholarly journals Achievable Single-Valued Neutrosophic Graphs in Wireless Sensor Networks

2018 ◽  
Vol 14 (02) ◽  
pp. 157-185 ◽  
Author(s):  
Mohammad Hamidi ◽  
Arsham Borumand Saeid
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Equivalence Relation ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Neutrosophic Graph

This paper considers wireless sensor (hyper) networks by single-valued neutrosophic (hyper)graphs. It tries to extend the notion of single-valued neutrosophic graphs to single-valued neutrosophic hypergraphs and it is derived single-valued neutrosophic graphs from single-valued neutrosophic hypergraphs via positive equivalence relation. We use single-valued neutrosophic hypergraphs and positive equivalence relation to create the sensor clusters and access to cluster heads. Finally, the concept of (extended) derivable single-valued neutrosophic graph is considered as the energy clustering of wireless sensor networks and is applied this concept as a tool in wireless sensor (hyper) networks.

scholarly journals Calculating the Number of Cluster Heads Based on the Rate-Distortion Function in Wireless Sensor Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Mingxin Yang ◽  
Jingsha He ◽  
Yuqiang Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Fusion ◽  
Rate Distortion ◽  
Distortion Function ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Cluster Heads

Due to limited resources in wireless sensor nodes, energy efficiency is considered as one of the primary constraints in the design of the topology of wireless sensor networks (WSNs). Since data that are collected by wireless sensor nodes exhibit the characteristics of temporal association, data fusion has also become a very important means of reducing network traffic as well as eliminating data redundancy as far as data transmission is concerned. Another reason for data fusion is that, in many applications, only some of the data that are collected can meet the requirements of the sink node. In this paper, we propose a method to calculate the number of cluster heads or data aggregators during data fusion based on the rate-distortion function. In our discussion, we will first establish an energy consumption model and then describe a method for calculating the number of cluster heads from the point of view of reducing energy consumption. We will also show through theoretical analysis and experimentation that the network topology design based on the rate-distortion function is indeed more energy-efficient.

scholarly journals An Integrated Routing Mechanism on Homogenous Wireless Sensor Networks using Genetic Algorithm

2021 ◽  
Author(s):  
Ramin Danehchin
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Collection ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing ◽  
Hop Count ◽  
Routing Problem ◽  
Cluster Heads

Abstract Data collection on Wireless Sensor Networks (WSNs) is a significant challenge to satisfy the requirements of various applications. Providing an energy-efficient routing technique is the primary step in data collection over WSNs. The existing data collection techniques in the WSNs field struggle with the imbalance load distribution and the short lifetime of the network. This paper proposes a novel mechanism to select cluster-heads, cluster the wireless sensor nodes, and determine the optimal route from source nodes to the sink. We employ the genetic algorithm to solve the routing problem considering the hop-count of the cluster-heads to the sink, the number of each cluster member, residual energy of cluster-heads, and the number of cluster-heads connected to the sink as the fitness criteria. Our proposed mechanism uses a greedy approach to calculate the hop-count of each cluster-head to the sink for integrating the clustering and routing process on WSNs. The simulation results demonstrate that our proposed mechanism improves the energy consumption, the number of live nodes, and the lifetime of the network compared to other data collection approaches on WSNs.

scholarly journals A Novel Framework to Secure CBWSNS Against the Selfishness Problem

2019 ◽  
Vol 7 (2) ◽  
pp. 7-16
Author(s):  
Poonam Mittal ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Defense Mechanism ◽  
Cluster Head ◽  
Base Station ◽  
Wireless Sensor ◽  
Security Level ◽  
Stochastic Algorithm ◽  
Worst Case ◽  
Cluster Heads

Dynamic and cooperative nature of sensor nodes in Wireless Sensor Networks raises question on security. Various researchers work in this direction to spot malicious, selfish and compromised nodes. Various mechanisms followed are uniqueness of clustering, reputation system and an operation at specific nodes. LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and compress the data and forward it to the base station (sink). Each node uses a stochastic algorithm at each round to determine whether it will become a cluster head in this round. Clustering process carried out in two stages takes the role of the reputation scheme and reveals specific operation at CH, IN and MNs beside their usual activities in cluster based wireless sensor networks. This paper mentioned the final structure of the security framework, corresponding attacks and defense mechanism of the model. It also discusses various security level processes of wireless sensor networks. Results implies that in a cluster-based protocol such as LEACH in which optimally 5% of the nodes are cluster heads it is likely that a significant portion of the network can be paralyzed or the entire network disabled, in the worst-case scenario, if these cluster heads are compromised. Our main contribution in this paper is our novel approach in maintaining trusted clusters through a trust-based decision-making cluster head election algorithm.

scholarly journals A New Centralized Clustering Algorithm for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4391 ◽  
Author(s):  
Juan-Carlos Cuevas-Martinez ◽  
Antonio-Jesus Yuste-Delgado ◽  
Antonio-Jose Leon-Sanchez ◽  
Antonio-Jose Saez-Castillo ◽  
Alicia Triviño-Cabrera
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fuzzy System ◽  
Clustering Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Clustering Methods ◽  
Cluster Heads ◽  
Control Message ◽  
Message Exchange

Clustering is presently one of the main routing techniques employed in randomly deployed wireless sensor networks. This paper describes a novel centralized unequal clustering method for wireless sensor networks. The goals of the algorithm are to prolong the network lifetime and increase the reliability of the network while not compromising the data transmission. In the proposed method, the Base Station decides on the cluster heads according to the best scores obtained from a Type-2 Fuzzy system. The input parameters of the fuzzy system are estimated by the base station or gathered from the network with a careful design that reduces the control message exchange. The whole network is controlled by the base station in a rounds-based schedule that alternates rounds when the base station elects cluster heads, with other rounds in which the cluster heads previously elected, gather data from their contributing nodes and forward them to the base station. The setting of the number of rounds in which the Base Station keeps the same set of cluster heads is another contribution of the present paper. The results show significant improvements achieved by the proposal when compared to other current clustering methods.

Energy Efficient Sensor Configuration by Fishing Spider Inspired Mechanism

2013 ◽  
Vol 284-287 ◽  
pp. 2049-2055
Author(s):  
Kyu Hong Lee ◽  
Hee Sang Lee
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Efficient ◽  
Sensor Node ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Self Organized ◽  
Clustering Model ◽  
Dolomedes Triton ◽  
Fishing Spider

Wireless sensor networks have inherent characteristics that differ from other wireless networks. Therefore, topology configuration and routing methods in WSNs must address these characteristics. In this paper, we propose an energy efficient clustering model. This model was inspired by the behaviors and capabilities of the six-spotted fishing spider, Dolomedes triton. The suggested model performs cluster-heads selection and clustering in self-organized ways. In order to determine the cluster-heads and the cluster-members, each sensor node uses the local information and simple rules that have been inspired by the Dolomedes triton. We compared our model with a well-known cluster-based routing protocol that uses random fairness for the selection of sensor node cluster-heads. In our computational experiments, we have showed that the energy efficiency and lifetimes of our bio-inspired model exceeds those of the comparison protocol by only using simple bio-inspired mechanism. We also demonstrate our model’s good performance in terms of scalability, which is one of the important indicators of performance for self-organized wireless sensor networks.

An Improved Clustering Algorithm Based on Coverage Area for Wireless Sensor Networks

2012 ◽  
Vol 542-543 ◽  
pp. 643-646
Author(s):  
Li Jun Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Topology Control ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Wireless Sensor ◽  
Coverage Area ◽  
Control Approach ◽  
Cluster Heads ◽  
Network Scalability

Clustering is an effective topology control approach in wireless sensor networks, which can increase network scalability and lifetime. A clustering algorithm based on the total number of neighbor nodes is proposed to maximize the lifetime of the network. The larger amount of neighbor nodes, the more chance a node has to be selected as a cluster head. Therefore, it can ensure the minimum cluster heads in the whole network. By closing the communication parts of cluster head to avoid selecting as cluster head in next epoch, the energy of the whole system is consumed symmetrically. The simulations demonstrate the effectiveness of the algorithm.

Sign in / Sign up

Export Citation Format

Share Document