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

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.

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Energy-Efficient Clustering Routing Protocol for Wireless Sensor Networks Based on Yellow Saddle Goatfish Algorithm

Mathematics ◽

10.3390/math8091515 ◽

2020 ◽

Vol 8 (9) ◽

pp. 1515 ◽

Cited By ~ 1

Author(s):

Alma Rodríguez ◽

Carolina Del-Valle-Soto ◽

Ramiro Velázquez

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Routing Protocol ◽

Energy Efficient ◽

Cluster Structure ◽

Sensor Nodes ◽

Wireless Sensor ◽

Cluster Heads ◽

Energy Efficient Clustering

The usage of wireless sensor devices in many applications, such as in the Internet of Things and monitoring in dangerous geographical spaces, has increased in recent years. However, sensor nodes have limited power, and battery replacement is not viable in most cases. Thus, energy savings in Wireless Sensor Networks (WSNs) is the primary concern in the design of efficient communication protocols. Therefore, a novel energy-efficient clustering routing protocol for WSNs based on Yellow Saddle Goatfish Algorithm (YSGA) is proposed. The protocol is intended to intensify the network lifetime by reducing energy consumption. The network considers a base station and a set of cluster heads in its cluster structure. The number of cluster heads and the selection of optimal cluster heads is determined by the YSGA algorithm, while sensor nodes are assigned to its nearest cluster head. The cluster structure of the network is reconfigured by YSGA to ensure an optimal distribution of cluster heads and reduce the transmission distance. Experiments show competitive results and demonstrate that the proposed routing protocol minimizes the energy consumption, improves the lifetime, and prolongs the stability period of the network in comparison with the stated of the art clustering routing protocols.

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Hesitant Fuzzy Entropy-Based Opportunistic Clustering and Data Fusion Algorithm for Heterogeneous Wireless Sensor Networks

Sensors ◽

10.3390/s20030913 ◽

2020 ◽

Vol 20 (3) ◽

pp. 913

Author(s):

Junaid Anees ◽

Hao-Chun Zhang ◽

Sobia Baig ◽

Bachirou Guene Lougou ◽

Thomas Gasim Robert Bona

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Data Fusion ◽

Network Lifetime ◽

Cluster Formation ◽

Fuzzy Entropy ◽

Sensor Nodes ◽

Wireless Sensor ◽

Heterogeneous Clustering

Limited energy resources of sensor nodes in Wireless Sensor Networks (WSNs) make energy consumption the most significant problem in practice. This paper proposes a novel, dynamic, self-organizing Hesitant Fuzzy Entropy-based Opportunistic Clustering and data fusion Scheme (HFECS) in order to overcome the energy consumption and network lifetime bottlenecks. The asynchronous working-sleeping cycle of sensor nodes could be exploited to make an opportunistic connection between sensor nodes in heterogeneous clustering. HFECS incorporates two levels of hierarchy in the network and energy heterogeneity is characterized using three levels of energy in sensor nodes. HFECS gathers local sensory data from sensor nodes and utilizes multi-attribute decision modeling and the entropy weight coefficient method for cluster formation and the cluster head election procedure. After cluster formation, HFECS uses the same techniques for performing data fusion at the first hierarchical level to reduce the redundant information flow from the first-second hierarchical levels, which can lead to an improvement in energy consumption, better utilization of bandwidth and extension of network lifetime. Our simulation results reveal that HFECS outperforms the existing benchmark schemes of heterogeneous clustering for larger network sizes in terms of half-life period, stability period, average residual energy, network lifetime, and packet delivery ratio.

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A New Data Fusion Algorithm for Wireless Sensor Networks Inspired by Hesitant Fuzzy Entropy

Sensors ◽

10.3390/s19040784 ◽

2019 ◽

Vol 19 (4) ◽

pp. 784 ◽

Cited By ~ 3

Author(s):

Jiayao Wang ◽

Olamide Tawose ◽

Linhua Jiang ◽

Dongfang Zhao

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Data Fusion ◽

Base Station ◽

Fuzzy Entropy ◽

Sensor Nodes ◽

Wireless Sensor ◽

Fusion Algorithm ◽

Time Performance

The wireless sensor network (WSN) is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. Therefore, energy consumption in wireless sensor networks is one of the most challenging problems in practice. On the other hand, data fusion can effectively decrease data redundancy, reduce the amount of data transmission and energy consumption in the network, extend the network life cycle, improve the utilization of bandwidth, and thus overcome the bottleneck on energy and bandwidth consumption. This paper proposes a new data fusion algorithm based on Hesitant Fuzzy Entropy (DFHFE). The new algorithm aims to reduce the collection of repeated data on sensor nodes from the source, and strives to utilize the information provided by redundant data to improve the data reliability. Hesitant fuzzy entropy is exploited to fuse the original data from sensor nodes in the cluster at the sink node to obtain higher quality data and make local decisions on the events of interest. The sink nodes periodically send local decisions to the base station that aggregates the local decisions and makes the final judgment, in which process the burden for the base station to process all the data is significantly released. According to our experiments, the proposed data fusion algorithm greatly improves the robustness, accuracy, and real-time performance of the entire network. The simulation results demonstrate that the new algorithm is more efficient than the state-of-the-art in terms of both energy consumption and real-time performance.

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An Improvement Routing Protocol Based LEACH for Wireless Sensor Networks

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.614.472 ◽

2014 ◽

Vol 614 ◽

pp. 472-475 ◽

Cited By ~ 2

Author(s):

Jin Gang Cao

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Routing Protocol ◽

Base Station ◽

Optimal Number ◽

Sensor Nodes ◽

Wireless Sensor ◽

Number Of Clusters ◽

Cluster Heads

Due to limited energy, computing ability, and memory of Wireless sensor Networks(WSN), routing issue is one of the key factors for WSN. LEACH is the first clustering routing protocol, which can efficiently reduce the energy consumption and prolong the lifetime of WSN, but it also has some disadvantage. This paper proposed an improvement based LEACH, called LEACH-T. According to different number of clusters, LEACH-T uses variable time slot for different clusters in steady-state phase, and single-hop or multi-hop to transmit data between cluster heads and Base Station. Also it considered residual energy of sensor nodes and the optimal number of clusters during selection of the cluster heads. The simulation results show that LEACH-T has better performance than LEACH for prolonging the lifetime and reducing the energy consumption.

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Short-Hops vs. Long-Hops

Network Security Technologies - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-4666-4789-3.ch005 ◽

2014 ◽

pp. 74-83

Author(s):

Mekkaoui Kheireddine ◽

Rahmoun Abdellatif

Keyword(s):

Energy Source ◽

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Base Station ◽

Sensor Nodes ◽

Wireless Sensor ◽

Large Area ◽

Wireless Sensor Nodes ◽

Energy Consuming

Sensor networks are composed of miniaturized wireless sensor nodes with limited capacity and energy source. Generally, these sensor networks are used, in many applications, to monitor inaccessible environments (battlefields, volcano monitoring, animal tracking…), hence the impossibility to replace or to recharge the batteries. As sensors may be deployed in a large area, radio transceivers are the most energy consuming of sensor nodes, which means that their usage needs to be very efficient in order to maximize node life, which leads us to maximize the network's life. In wireless sensor networks and in order to transmit its data, a node can route its messages towards destination, generally the base station, either by using small or large hops, so optimizing the hop length can extend significantly the lifetime of the network. This chapter provides a simple way to verify, which makes the energy consumption minimal by choosing proper hop length.

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Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327910999200614002236 ◽

2020 ◽

Vol 10 ◽

Author(s):

Chinedu Duru ◽

Neco Ventura ◽

Mqhele Dlodlo

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Remote Monitoring ◽

Linear Array ◽

Minimum Energy ◽

Sensor Nodes ◽

Wireless Sensor ◽

Sink Node ◽

Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

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Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

International Journal of Sensors Wireless Communications and Control ◽

10.2174/2210327909666190208161350 ◽

2020 ◽

Vol 10 (1) ◽

pp. 94-109 ◽

Cited By ~ 1

Author(s):

Rekha Goyat ◽

Mritunjay Kumar Rai ◽

Gulshan Kumar ◽

Hye-Jin Kim ◽

Se-Jung Lim

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Research Area ◽

Sensor Nodes ◽

Wireless Sensor ◽

Localization Error ◽

Anchor Nodes ◽

Least Energy ◽

Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

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Study of Data Fusion Mechanism Based on the WSN

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.321-324.600 ◽

2013 ◽

Vol 321-324 ◽

pp. 600-603

Author(s):

Wei Liu ◽

Qin Sheng Du ◽

Le Le Wang

Keyword(s):

Wireless Sensor Networks ◽

Energy Consumption ◽

Sensor Networks ◽

Data Fusion ◽

Wireless Sensor ◽

Network Technology ◽

Fusion Method ◽

Simulation Test ◽

Embedded Computing ◽

New Type

Wireless sensor networks integrated four technologies including sensor, embedded computing, network technology and wireless communication. It is a new type of non-infrastructure wireless network. In this paper, a data fusion method has been brought forward based on wireless sensor networks, and through an algorithm simulation test, It is proved that the algorithm is effective to reduce the energy consumption of the network, and extend the lifetime of the network.

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Time-selective data fusion for in-network processing in ad hoc wireless sensor networks

International Journal of Distributed Sensor Networks ◽

10.1177/1550147718811302 ◽

2018 ◽

Vol 14 (11) ◽

pp. 155014771881130 ◽

Cited By ~ 1

Author(s):

Jaanus Kaugerand ◽

Johannes Ehala ◽

Leo Mõtus ◽

Jürgo-Sören Preden

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Data Fusion ◽

Data Streams ◽

Ad Hoc ◽

Sensor Nodes ◽

Sensor Data ◽

Wireless Sensor ◽

Temporal Consistency ◽

Variable Delays

This article introduces a time-selective strategy for enhancing temporal consistency of input data for multi-sensor data fusion for in-network data processing in ad hoc wireless sensor networks. Detecting and handling complex time-variable (real-time) situations require methodical consideration of temporal aspects, especially in ad hoc wireless sensor network with distributed asynchronous and autonomous nodes. For example, assigning processing intervals of network nodes, defining validity and simultaneity requirements for data items, determining the size of memory required for buffering the data streams produced by ad hoc nodes and other relevant aspects. The data streams produced periodically and sometimes intermittently by sensor nodes arrive to the fusion nodes with variable delays, which results in sporadic temporal order of inputs. Using data from individual nodes in the order of arrival (i.e. freshest data first) does not, in all cases, yield the optimal results in terms of data temporal consistency and fusion accuracy. We propose time-selective data fusion strategy, which combines temporal alignment, temporal constraints and a method for computing delay of sensor readings, to allow fusion node to select the temporally compatible data from received streams. A real-world experiment (moving vehicles in urban environment) for validation of the strategy demonstrates significant improvement of the accuracy of fusion results.

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

10.21203/rs.3.rs-434634/v1 ◽

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.

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