Evaluate the performance of K-Means and the fuzzy C-Means algorithms to formation balanced clusters in wireless sensor networks

The clustering approach is considered as a vital method for wireless sensor networks (WSNs) by organizing the sensor nodes into specific clusters. Consequently, saving the energy and prolonging network lifetime which is totally dependent on the sensors battery, that is considered as a major challenge in the WSNs. Classification algorithms such as K-means (KM) and Fuzzy C-means (FCM), which are two of the most used algorithms in literature for this purpose in WSNs. However, according to the nature of random nodes deployment manner, on certain occasions, this situation forces these algorithms to produce unbalanced clusters, which adversely affects the lifetime of the network. Based for our knowledge, there is no study has analyzed the performance of these algorithms in terms clusters construction in WSNs. In this study, we investigate in KM and FCM performance and which of them has better ability to construct balanced clusters, in order to enable the researchers to choose the appropriate algorithm for the purpose of improving network lifespan. In this study, we utilize new parameters to evaluate the performance of clusters formation in multi-scenarios. Simulation result shows that our FCM is more superior than KM by producing balanced clusters with the random distribution manner for sensor nodes

A Combined Dual Leader and Relay Node Selection for Markov Cluster Based WSN Routing Protocol

The major challenge in Wireless Sensor Networks (WSNs) is to increase the node’s lifespan and decrease energy utilization. To avoid this issue, many Clustering Routing Protocols (CRPs) have been developed, where Cluster Head (CH) in each cluster accumulates the data from each other node and transfers it to the sink through Relay Nodes (RNs). But both CHs and RNs dissipate more energy to aggregate and transfer data. As a result, it is vital to choose the appropriate CHs and RNs concurrently to reduce energy utilization. Hence, this article proposes a Weighted Markov Clustering with Dual Leader and Relay node Selection based CRP (WMCL-DLRS-CRP) in WSNs. This protocol aims to lessen energy dissipation during inter- and intra-cluster communication. Initially, a Markov Clustering (MCL) algorithm is applied by the sink to create nodes into clusters based on a threshold distance. Then, a dual leader selection scheme is proposed to elect dual CHs in each cluster according to the node weighting factor that considers the node’s remaining energy, the distance between CHs and sink, the distance among all nodes, and abundance. Also, an RN selection scheme is proposed to choose the appropriate RNs based on a new Predicted Transmission Rate (PTR) factor. Moreover, the elected RNs transfer the data from the CHs to the sink, resulting in a tradeoff between the node’s energy utilization and lifetime. At last, extensive simulations illustrate that the WMCL-DLRS-CRP achieves better network performance compared to the existing protocols

Novel reliable and dynamic energy-aware routing protocol for large scale wireless sensor networks

Wireless sensor networks (WSN) are made up of an important number of sensors, called nodes, distributed in random way in a concerned monitoring area. All sensor nodes in the network are mounted with limited energy sources, which makes energy harvesting on top of the list of issues in WSN. A poor communication architecture can result in excessive consumption, reducing the network lifetime and throughput. Centralizing data collection and the introduction of gateways (GTs), to help cluster heads (CHs), improved WSN life time significantly. However, in vast regions, misplacement and poor distribution of GTs wastes a huge amount of energy and decreases network’s performances. In this work, we describe a reliable and dynamic with energy-awareness routing (RDEAR) protocol that provides a new GT’s election approach taking into consideration CHs density, transmission distance and energy. Applied on 20 different networks, RDEAR reduced the overall energy consumption, increased stability zone and network life time as well as other compared metrics. Our proposed approach increased network’s throughput up to 75.92% , 67.7% and 9.78% compared to the low energy adaptive clustering hierarchy (LEACH), distributed energy efficient clustering (DEEC) and static multihop routing (SMR), protocols, respectively

Modifikasi Inisialisasi Cluster head menggunakan Fuzzy C-Means Clustering untuk Efisiensi Energi pada Proses Data Gathering di Lingkungan Wireless Sensor Network

Proses pengumpulan data (data gathering) akan berpengaruh terhadap masa hidup jaringan dan konsumsi energi. Salah satu permasalah yang sering terjadi adalah konsumsi energi dan masa hidup jaringan, dimana energi yang dimiliki pada suatu protokol Wireless sensor network sangat terbatas, sedangkan proses pengambilan data dilakukan secara berulang-ulang. Sehingga diperlukan suatu metode penghematan energi agar energi yang dikonsumsi menjadi rendah dan masa hidup jaringan lebih lama. Penelitian ini mengusulkan modifikasi pemilihan cluster head menggunakan Fuzzy C-Means dan Particle Swarn Optimation untuk efisiensi nnergi pada wireless sensor network. Perbandingan masa hidup jaringan menunjukan bahwa strategi usulan memiliki tingkat hidup yang lebih panjang yaitu 9549 round atau 2,06 kali lipat dari protokol Low Energy Adaptive Clustering Hierarchy (LEACH) pada sink (50,50) dengan rata-rata energi per transmisi 0.00032676 joule per transmission dan 7644 round atau 1,6 kali lipat dari protokol LEACH pada sink (50,100) dengan rata-rata energi per transmisi 0.000486052 joule per transmission. Hal ini mempertegas bahwa dengan melakukan optimasi data gathering dengan konsep multi hop pada wireless sensor network mampu meningkatkan masa hidup jaringan dan konsumsi energi yang rendah

Routing Design Issues in Heterogeneous Wireless Sensor Network

WSN has important applications such as habitat monitoring, structural health monitoring, target tracking in military and many more. This has evolved due to availability of sensors that are cheaper and intelligent but these are having battery support. So, one of the major issues in WSN is maximization of network life. Heterogeneous WSNs have the potential to improve network lifetime and also provide higher quality networking and system services than the homogeneous WSN. Routing is the main concern of energy consumption in WSN. Previous research shows that performance of the network can be improve significantly using protocol of hierarchical HWSN. However, the appropriateness of a particular routing protocol mainly depends on the capabilities of the nodes and on the application requirements. This study presents different aspects of Heterogeneous Wireless Sensor network and design issues for routing in heterogeneous environment. Different perspectives from different authors regarding energy efficiency based on resource heterogeneity for heterogeneous wireless sensor networks have been presented