scholarly journals Determination of the K-optimal number of chains-based routing protocol formed by the K-Means algorithm for the WSN

Author(s):  
Samah Alnajdi ◽  
Fuad Bajaber

<span>Wireless sensor networks comprise of a large number of lightweight and relatively low-cost computational nodes which their main task is to sense the surrounding environment and collect the information to send it wirelessly to a central point to take the appropriate actions. Although these networks had been used in various applications, achieving this task is challenging due to the many constraints of sensor nodes including their limited processing power, communication bandwidth, and power supply. Therefore, an energy efficient routing protocols had to be developed specifically for sensor networks to insure longer lifetime and reasonable performance of the network. In this work, we propose an energy efficient hierarchical routing protocol using chain-based clustering. <span>By simulation on MATLAB, the proposed protocol proved to enhance the performance as it prolongs the lifetime of the network and decreases the energy consumption, the transmission delay, and the overhead compared to other existing protocols as it depends on some advanced methods including dynamic selection of number of chains method, k-means clustering method, advanced greedy chain construction method, and multi-factor based leader selection method.</span></span>

2016 ◽  
Vol 15 (4) ◽  
pp. 6654-6658
Author(s):  
Irfan Shaqiri ◽  
Aristotel Tentov

In this paper we give an overview of some routing protocols which can improve the efficiency and scalability of wireless sensor networks. The Wireless Sensor Network (WSN) is a network consisting of ten to thousand small nodes with sensing, computing and wireless communication capabilities. WSN are generally used to monitor activities and report events, such as pollution parameters, healthcare issues, fire info etc. in a specific area or environment. It routs data back to the Base Station (BS). Data transmission is usually a multi-hop from node to node towards the BS. This type of networks is limited in power, computational and communication bandwidth. The main goal of all researchers is to find out the energy efficient routing protocol which will improve considerably networks resources in term of prolonging lifetime of sensor nodes. Also we highlight the various routing protocol with advantages and limitations as well. 


Author(s):  
A. Radhika ◽  
D. Haritha

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.


2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Faris A. Almalki ◽  
Soufiene Ben Othman ◽  
Fahad A. Almalki ◽  
Hedi Sakli

Healthcare is one of the most promising domains for the application of Internet of Things- (IoT-) based technologies, where patients can use wearable or implanted medical sensors to measure medical parameters anywhere and anytime. The information collected by IoT devices can then be sent to the health care professionals, and physicians allow having a real-time access to patients’ data. However, besides limited batteries lifetime and computational power, there is spatio-temporal correlation, where unnecessary transmission of these redundant data has a significant impact on reducing energy consumption and reducing battery lifetime. Thus, this paper aims to propose a routing protocol to enhance energy-efficiency, which in turn prolongs the sensor lifetime. The proposed work is based on Energy Efficient Routing Protocol using Dual Prediction Model (EERP-DPM) for Healthcare using IoT, where Dual-Prediction Mechanism is used to reduce data transmission between sensor nodes and medical server if predictions match the readings or if the data are considered critical if it goes beyond the upper/lower limits of defined thresholds. The proposed system was developed and tested using MATLAB software and a hardware platform called “MySignals HW V2.” Both simulation and experimental results confirm that the proposed EERP-DPM protocol has been observed to be extremely successful compared to other existing routing protocols not only in terms of energy consumption and network lifetime but also in terms of guaranteeing reliability, throughput, and end-to-end delay.


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