scholarly journals SPARCO: Stochastic Performance Analysis with Reliability and Cooperation for Underwater Wireless Sensor Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-17 ◽  
Author(s):  
Sheeraz Ahmed ◽  
Nadeem Javaid ◽  
Ashfaq Ahmad ◽  
Imran Ahmed ◽  
Mehr Yahya Durrani ◽  
...  

Reliability is a key factor for application-oriented Underwater Sensor Networks (UWSNs) which are utilized for gaining certain objectives and a demand always exists for efficient data routing mechanisms. Cooperative routing is a promising technique which utilizes the broadcast feature of wireless medium and forwards data with cooperation using sensor nodes as relays. Here, we present a cooperation-based routing protocol for underwater networks to enhance their performance called Stochastic Performance Analysis with Reliability and Cooperation (SPARCO). Cooperative communication is explored in order to design an energy-efficient routing scheme for UWSNs. Each node of the network is assumed to be consisting of a single omnidirectional antenna and multiple nodes cooperatively forward their transmissions taking advantage of spatial diversity to reduce energy consumption. Both multihop and single-hop schemes are exploited which contribute to lowering of path-losses present in the channels connecting nodes and forwarding of data. Simulations demonstrate that SPARCO protocol functions better regarding end-to-end delay, network lifetime, and energy consumption comparative to noncooperative routing protocol—improved Adaptive Mobility of Courier nodes in Threshold-optimized Depth-based routing (iAMCTD). The performance is also compared with three cooperation-based routing protocols for UWSN: Cognitive Cooperation (Cog-Coop), Cooperative Depth-Based Routing (CoDBR), and Cooperative Partner Node Selection Criteria for Cooperative Routing (Coop Re and dth).

2018 ◽  
Vol 7 (4.15) ◽  
pp. 178
Author(s):  
Komal Memon ◽  
Nafeesa Bohra ◽  
Faisal K Shaikh

There is a great demand of an Underwater Sensor Networks (UWSNs) in applications of water monitoring and offshore exploration. In such applications, network comprises of multiple sensor nodes which are deployed at different locations and depths of water. Sensor nodes perform collective tasks such as data collection and data transmission to other nodes or Base Station (BS). The bottom nodes are located at depth of water, and are not able to communicate directly with the surface level nodes, these nodes require multi-hop communication with appropriate routing protocol. Therefore, an energy efficient routing protocols are used for such scenarios, which is necessary as well as challenging task. As sensors are battery operated devices, which are really problematic to recharge or replace. The error and propagation path delays are high in acoustic channels therefore underwater communication is much effected. Realizing the circumstances, more attention has been given to compare energy efficient routing protocols which comparatively consume low energy and achieve high throughput. This paper, comprises of analysis and comparison of existing UWSN based efficient energy routing protocols. Based upon the analysis and comparison, VBF and DBR have been proposed that fulfill the requirements. The analysis is done on NS-2 and for comparison, the performance metrics which are evaluated are: Packet delivery Ratio (PDR), energy consumption, throughput and average End to End (E2E) delay. The results show that VBF protocol consume very large amount of energy as compared to DBR protocol. Whereas DBR protocol have characteristics like low energy consumption, minimum delay high PDR and high throughput than VBF protocol.  


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.


2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso

Abstract Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime


Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1835 ◽  
Author(s):  
Ruan ◽  
Huang

Since wireless sensor networks (WSNs) are powered by energy-constrained batteries, many energy-efficient routing protocols have been proposed to extend the network lifetime. However, most of the protocols do not well balance the energy consumption of the WSNs. The hotspot problem caused by unbalanced energy consumption in the WSNs reduces the network lifetime. To solve the problem, this paper proposes a PSO (Particle Swarm Optimization)-based uneven dynamic clustering multi-hop routing protocol (PUDCRP). In the PUDCRP protocol, the distribution of the clusters will change dynamically when some nodes fail. The PSO algorithm is used to determine the area where the candidate CH (cluster head) nodes are located. The adaptive clustering method based on node distribution makes the cluster distribution more reasonable, which balances the energy consumption of the network more effectively. In order to improve the energy efficiency of multi-hop transmission between the BS (Base Station) and CH nodes, we also propose a connecting line aided route construction method to determine the most appropriate next hop. Compared with UCCGRA, multi-hop EEBCDA, EEMRP, CAMP, PSO-ECHS and PSO-SD, PUDCRP prolongs the network lifetime by between 7.36% and 74.21%. The protocol significantly balances the energy consumption of the network and has better scalability for various sizes of network.


Author(s):  
Saloni Dhiman ◽  
Deepti Kakkar ◽  
Gurjot Kaur

Wireless sensor networks (WSNs) consist of several sensor nodes (SNs) that are powered by battery, so their lifetime is limited, which ultimately affects the lifespan and hence performance of the overall networks. Till now many techniques have been developed to solve this problem of WSN. Clustering is among the effective technique used for increasing the network lifespan. In this chapter, analysis of multi-hop routing protocol based on grid clustering with different selection criteria is presented. For analysis, the network is divided into equal-sized grids where each grid corresponds to a cluster and is assigned with a grid head (GH) responsible for collecting data from each SN belonging to respective grid and transferring it to the base station (BS) using multi-hop routing. The performance of the network has been analyzed for different position of BS, different number of grids, and different number of SNs.


2013 ◽  
Vol 706-708 ◽  
pp. 635-638
Author(s):  
Yong Lv

Wireless Sensor Networks consisting of nodes with limited power are deployed to collect and distribute useful information from the field to the other sensor nodes. Energy consumption is a key issue in the sensor’s communications since many use battery power, which is limited. In this paper, we describe a novel energy efficient routing approach which combines swarm intelligence, especially the ant colony based meta-heuristic, with a novel variation of reinforcement learning for sensor networks (ARNet). The main goal of our study was to maintain network lifetime at a maximum, while discovering the shortest paths from the source nodes to the sink node using an improved swarm intelligence. ARNet balances the energy consumption of nodes in the network and extends the network lifetime. Simulation results show that compared with the traditional EEABR algorithm can obviously improve adaptability and reduce the average energy consumption effectively.


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.


2021 ◽  
Vol 10 (4) ◽  
pp. 1-16
Author(s):  
Vinay Rishiwal ◽  
Preeti Yadav ◽  
Omkar Singh ◽  
B. G. Prasad

In recent era of IoT, energy ingesting by sensor nodes in Wireless Sensor Networks (WSN) is one of the key challenges. It is decisive to diminish energy ingesting due to restricted battery lifespan of sensor nodes, Objective of this research is to develop efficient routing protocol/algorithm in IoT based scenario to enhance network performance with QoS parameters. Therefore, keeping this objective in mind, a QoS based Optimized Energy Clustering Routing (QOECR) protocol for IoT based WSN is proposed and evaluated. QOECR discovers optimal path for sink node and provides better selection for sub-sink nodes. Simulation has been done in MATLAB to assess the performance of QOECR with pre-existing routing protocols. Simulation outcomes represent that QOECR reduces E2E delay 30%-35%, enhances throughput 25%-30%, minimizes energy consumption 35%-40%, minimizes packet loss 28%-32%, improves PDR and prolongs network lifetime 32%-38% than CBCCP, HCSM and ZEAL routing protocols.


Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1515 ◽  
Author(s):  
Alma Rodríguez ◽  
Carolina Del-Valle-Soto ◽  
Ramiro Velázquez

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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