scholarly journals An Energy Model Using Sleeping Algorithms for Wireless Sensor Networks under Proactive and Reactive Protocols: A Performance Evaluation

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 3024 ◽  
Author(s):  
Carolina Del-Valle-Soto ◽  
Ramiro Velázquez ◽  
Leonardo J. Valdivia ◽  
Nicola Ivan Giannoccaro ◽  
Paolo Visconti

The continuous evolution of the Internet of Things (IoT) makes it possible to connect everyday objects to networks in order to monitor physical and environmental conditions, which is made possible due to wireless sensor networks (WSN) that enable the transfer of data. However, it has also brought about many challenges that need to be addressed, such as excess energy consumption. Accordingly, this paper presents and analyzes wireless network energy models using five different communication protocols: Ad Hoc On-Demand Distance Vector (AODV), Multi-Parent Hierarchical (MPH), Dynamic Source Routing (DSR), Low Energy Adaptive Clustering Hierarchy (LEACH) and Zigbee Tree Routing (ZTR). First, a series of metrics are defined to establish a comparison and determine which protocol exhibits the best energy consumption performance. Then, simulations are performed and the results are compared with real scenarios. The energy analysis is conducted with three proposed sleeping algorithms: Modified Sleeping Crown (MSC), Timer Sleeping Algorithm (TSA), and Local Energy Information (LEI). Thereafter, the proposed algorithms are compared by virtue of two widely used wireless technologies, namely Zigbee and WiFi. Indeed, the results suggest that Zigbee has a better energy performance than WiFi, but less redundancy in the topology links, and this study favors the analysis with the simulation of protocols with different nature. The tested scenario is implemented into a university campus to show a real network running.

2021 ◽  
Vol 27 (3) ◽  
pp. 225-235
Author(s):  
Xiaotao Ju

This research was conducted to enhance the energy performance of wireless sensor networks (WSN) and improve the performance of end-to-end delay and packet receiving rate of network operation. In this study, the low-energy data collection routing algorithm and adaptive environment sensing method in WSN were mainly examined. The node centrality, energy surplus, and node temperature were calculated for cluster head selection to reduce the energy consumption of nodes and improve the reliability of network data. The research results have shown that the parameter setting guided by the theoretical analysis makes each node selfishly achieve the maximum expected benefit while the whole network runs reliably, and the energy consumption is reduced by the selfishness of the node. As a result, the proposed algorithm can effectively reduce the network energy consumption and increase the network life cycle of wireless sensor networks. It can be seen that the machine learning methods such as support vector machine are used to model and analyze the state of the sensing node, and to obtain more accurate wireless channel availability judgment based on the historical state data, thereby adaptively adjusting the working duty ratio and reducing the invalidity data sent.


2012 ◽  
Vol 463-464 ◽  
pp. 261-265
Author(s):  
Fei Hui ◽  
Xiao Le Wang ◽  
Xin Shi

In this paper, hazardous materials transportation monitoring system is designed, implemented, and tested using Wireless Sensor Networks (WSNs). According to energy consumption and response time during clustering of Wireless Sensor Networks LEACH (Low Energy Adaptive Clustering Hierarchy) routing protocol, we proposed STATIC-LEACH routing protocol based on static clustering, it can effectively reduce energy consumption of the wireless sensor nodes and reduce network latency of cluster. With WSN and GSM/GPRS, low cost and easy deployment remote monitoring is possible without interfering with the operation of the transportation.


2014 ◽  
Vol 11 (3) ◽  
pp. 1017-1035 ◽  
Author(s):  
Young-Long Chen ◽  
Mu-Yen Chen ◽  
Fu-Kai Cheung ◽  
Yung-Chi Chang

Energy is limited in wireless sensor networks (WSNs) so that energy consumption is very important. In this paper, we propose a hybrid architecture based on power-efficient gathering in sensor information system (PEGASIS) and low-energy adaptive clustering hierarchy (LEACH). This architecture can achieve an average distribution of energy loads, and reduced energy consumption in transmission. To further extend the system lifetime, we combine the intersection-based coverage algorithm (IBCA) with LEACH architecture and the hybrid architecture to prolong the system lifetime that introducing sensor nodes to enter sleep mode when inactive. This step can save more energy consumption. Simulation results show that the performance of our proposed LEACH architecture with IBCA and the hybrid architecture with IBCA perform better than LEACH architecture with PBCA in terms of energy efficiency, surviving nodes and sensing areas.


Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 135 ◽  
Author(s):  
Vicente Casares-Giner ◽  
Tatiana Inés Navas ◽  
Dolly Smith Flórez ◽  
Tito R. Vargas H.

In this work it is considered a circular Wireless Sensor Networks (WSN) in a planar structure with uniform distribution of the sensors and with a two-level hierarchical topology. At the lower level, a cluster configuration is adopted in which the sensed information is transferred from sensor nodes to a cluster head (CH) using a random access protocol (RAP). At CH level, CHs transfer information, hop-by-hop, ring-by-ring, towards to the sink located at the center of the sensed area using TDMA as MAC protocol. A Markovian model to evaluate the end-to-end (E2E) transfer delay is formulated. In addition to other results such as the well know energy hole problem, the model reveals that for a given radial distance between the CH and the sink, the transfer delay depends on the angular orientation between them. For instance, when two rings of CHs are deployed in the WSN area, the E2E delay of data packets generated at ring 2 and at the “west” side of the sink, is 20% higher than the corresponding E2E delay of data packets generated at ring 2 and at the “east” side of the sink. This asymmetry can be alleviated by rotating from time to time the allocation of temporary slots to CHs in the TDMA communication. Also, the energy consumption is evaluated and the numerical results show that for a WSN with a small coverage area, say a radio of 100 m, the energy saving is more significant when a small number of rings are deployed, perhaps none (a single cluster in which the sink acts as a CH). Conversely, topologies with a large number of rings, say 4 or 5, offer a better energy performance when the service WSN covers a large area, say radial distances greater than 400 m.


2014 ◽  
Vol 9 (11) ◽  
pp. 1904 ◽  
Author(s):  
Mohammed Joda Usman ◽  
Zhang Xing ◽  
Haruna Chiroma ◽  
Abdulsalam Ya’u Gital ◽  
Adamu I. Abubakar ◽  
...  

2018 ◽  
Vol 7 (2.31) ◽  
pp. 1
Author(s):  
C Cynthia, Prudhvi Krishna Saguturu ◽  
Komali Bandi ◽  
Srikanth Magulluri ◽  
T Anusha

In Wireless sensor networks and ad hoc networks nodes have a freedom to move from one place to another, they are self-configuring this type of the structure fulfil the requirements of several application. A survey on the different MANET protocols will be done in this paper. Mainly this paper will focus on the Quality of Service on the different parameters like Throughput and Delay between different protocols like AODV (Ad Hoc on Demand Distance Vector), DSDV (Destination-Sequenced Distance-Vector Routing), DSR (Dynamic Source Routing), and TORA (Temporary Ordered Routing Algorithm). DSDV is called as proactive protocol because they know everything about the nodes in the network before the communication start. DSR, AODV, TORA protocols are called reactive protocol because nodes in this network do not know anything about network. They are also called ON-DEMAND routing protocols. After this analysis you will come to know which MANET protocol is best for different application. 


Author(s):  
Frantisek Zboril ◽  
Jan Horacek ◽  
Martin Drahansky ◽  
Petr Hanacek

Security of wireless sensor networks (WSN) relates in many aspects to security of distributed systems. On the first sight WSNs form a large distributed ad-hoc system with lot of tiny devices that sense some phenomena and communicate wirelessly. Due to some limitations, among which the energy consumption problem is the most important one, security issues could demand different solutions than those used in the area of ordinary distributed systems. In this chapter, the authors briefly introduce the hardware and software approach to WSN design first, and then they define the main security aspects in such systems. Then some security mechanisms are presented, and their connection to possible countermeasures of the identified risks is described.


2018 ◽  
Vol 14 (3) ◽  
pp. 155014771876464 ◽  
Author(s):  
Adem Fanos Jemal ◽  
Redwan Hassen Hussen ◽  
Do-Yun Kim ◽  
Zhetao Li ◽  
Tingrui Pei ◽  
...  

Clustering is vital for lengthening the lives of resource-constrained wireless sensor nodes. In this work, we propose a cluster-based energy-efficient router placement scheme for wireless sensor networks, where the K-means algorithm is used to select the initial cluster headers and then a cluster header with sufficient battery energy is selected within each cluster. The performance of the proposed scheme was evaluated in terms of the energy consumption, end-to-end delay, and packet loss. Our simulation results using the OPNET simulator revealed that the energy consumption of our proposed scheme was better than that of the low-energy adaptive clustering hierarchy, which is known to be an energy-efficient clustering mechanism. Furthermore, our scheme outperformed low-energy adaptive clustering hierarchy in terms of the end-to-end delay, throughput, and packet loss rate.


2014 ◽  
Vol 665 ◽  
pp. 745-750
Author(s):  
Qi Gong Chen ◽  
Yong Zhi Wang ◽  
Li Sheng Wei ◽  
Wen Gen Gao

Energy consumption is a hot issue in WSNs (Wireless Sensor Networks). In this paper, we present an improved clustering algorithm. By changing the order of traditional WSNs clustering algorithm, this algorithm uses k-means clustering firstly base on optimal number of cluster head is determined; Then selects cluster head by an improved LEACH (Low Energy Adaptive Clustering Hierarchy) algorithm; Finally, Our experimental results demonstrate that this approach can reduces energy consumption and increases the lifetime of the WSNs.


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