scholarly journals Network Performance Metrics for Energy Efficient Scheduling in Wireless Sensor Networks (WSNs)

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Felicia Engmann ◽  
Kofi Sarpong Adu-Manu ◽  
Jamal-Deen Abdulai ◽  
Ferdinand Apietu Katsriku
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Transmission ◽  
Network Performance ◽  
High Energy ◽  
Wireless Sensor ◽  
Ieee 802.11B ◽  
End To End Delay ◽  
Iot Devices

In Wireless Sensor Networks, sensor nodes are deployed to ensure continuous monitoring of the environment which requires high energy utilization during the data transmission. To address the challenge of high energy consumption through frequent independent data transmission, the IEEE 802.11b provides a backoff window that reduces collisions and energy losses. In the case of Internet of Things (IoTs), billions of devices communicate with each other simultaneously. Therefore, adapting the contention/backoff window size to data traffic to reduce congestion has been one such approach in WSN. In recent years, the IEEE 802.11b MAC protocol is used in most ubiquitous technology adopted for devices communicating in the IoT environment. In this paper, we perform a thorough evaluation of the IEEE 802.11b standard taking into consideration the channel characteristics for IoT devices. Our evaluation is aimed at determining the optimum parameters suitable for network optimization in IoT systems utilizing the IEEE 802.11b protocol. Performance analysis is made on the sensitivity of the IEEE 802.11b protocol with respect to the packet size, packet delivery ratio (PDR), end-to-end delay, and energy consumption. Our studies have shown that for optimal performance, IoT devices using IEEE 802.11b channel require data packet of size 64 bytes, a data rate of 11Mbps, and an interpacket generation interval of 4 seconds. The sensitivity analysis of the optimal parameters was simulated using NS3. We observed PDR values ranging between 27% and 31%, an average end-to-end delay ranging within 10-15 ms while the energy remaining was between 5.59 and 5.63Joules. The results clearly indicate that scheduling the rate of packet generation and transmission will improve the network performance for IoT devices while maintaining data reliability.

scholarly journals An Enhanced Heterogeneous Gateway-Based Energy-Aware Multi-hop Routing Protocol for Wireless Sensor Networks

2022 ◽  
Author(s):  
Fuseini Jibreel ◽  
Emmanuel Tuyishimire ◽  
I M Daabo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Base Station ◽  
Communication Strategy ◽  
Wireless Sensor ◽  
Energy Aware ◽  
Routing Scheme

Wireless Sensor Networks (WSNs) continue to provide essential services for various applications such as surveillance, data gathering, and data transmission from the hazardous environments to safer destinations. This has been enhanced by the energy-efficient routing protocols that are mostly designed for such purposes. Gateway-based Energy-Aware Multi-hop Routing protocol (MGEAR) is one of the homogenous routing schemes that was recently designed to more efficiently reduce the energy consumption of distant nodes. However, it has been found that the protocol has a high energy consumption rate, lower stability period, less data transmission to the Base station (BS). In this paper, an enhanced Heterogeneous Gateway-based Energy-Aware multi-hop routing protocol ( HMGEAR) is proposed. The proposed routing scheme is based on the introduction of heterogeneous nodes in the existing scheme, selection of the head based on the residual energy, introduction of multi-hop communication strategy in all the regions of the network, and implementation of energy hole elimination technique. Results show that the proposed routing scheme outperforms two existing ones.

scholarly journals Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

2020 ◽  
Author(s):  
Ademola Abidoye ◽  
Boniface Kabaso
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Energy Efficient ◽  
Fog Computing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Hierarchical Routing

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

scholarly journals Oppo-Flood: An Energy-Efficient Data Dissemination Protocol for Asynchronous Duty-Cycled Wireless Sensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Hyeonsang Cho ◽  
Jungmin So
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Dissemination ◽  
High Energy ◽  
Wireless Sensor ◽  
Neighboring Node ◽  
Duty Cycling ◽  
Opportunistic Forwarding ◽  
Efficient Data

In this paper, we propose a data dissemination protocol for asynchronous duty-cycling wireless sensor networks. In an asynchronous duty-cycling network, each node independently selects its wake-up time. In this environment, data dissemination becomes energy consuming, because broadcasting a packet does reach all neighbors but only the neighbors that are awake at the time. A node can forward its packet to all neighbors by continuously transmitting the packet for a whole wake-up interval, but it leads to high energy consumption and high dissemination delay. The idea proposed in this paper is to use opportunistic forwarding, where each node forwards the packet to a neighbor that wakes up early and receives the packet. Each node forwards the packet, as long as there is a neighboring node that has not received the packet yet. The main benefit of this opportunistic forwarding-based dissemination is that every time a packet is disseminated, it may take a different path to reach the nodes. At the beginning of dissemination, a sender needs to transmit for a very short duration of time because there are plenty of neighboring nodes to receive the packet. As more nodes receive the packet, the transmit duration of the sender becomes longer, thus consuming more energy. Since the order of dissemination is different every time, energy consumption is naturally balanced among the nodes, without explicit measures. Through extensive simulations, we show that the proposed protocol achieves longer network lifetime and shorter dissemination delay compared to other dissemination protocols in various network environments.

scholarly journals A Method for Energy Balance and Data Transmission Optimal Routing in Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3017 ◽  
Author(s):  
Xuesong Liu ◽  
Jie Wu
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Energy Balance ◽  
Energy Distribution ◽  
Data Transmission ◽  
Line Length ◽  
Wireless Sensor ◽  
Hop Count ◽  
Transmission Distance

Wireless sensor networks are widely used in many fields. Nodes in the network are typically powered by batteries. Because the energy consumption of wireless communication is related to the transmission distance, the energy consumption of nodes in different locations is different, resulting in uneven energy distribution of nodes. In some special applications, all nodes are required to work at the same time, and the uneven energy distribution makes the effective working time of the system subject to the node with the largest energy consumption. The commonly used clustering protocol can play a role in balancing energy consumption, but it does not achieve optimal energy consumption. This paper proposes to use the power supply line to connect the nodes to fully balance the energy. The connection scheme with the shortest power line length is also proposed. On the basis of energy balance, the method of transmitting data with the best hop count is proposed, which fully reduces the power consumption of the data transmission. The simulation results show that the proposed method can effectively reduce the energy consumption and prolong the lifetime of wireless sensor networks.

scholarly journals Centralized Energy Prediction in Wireless Sensor Networks Leveraged by Software-Defined Networking

Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5379
Author(s):  
Gustavo A. Nunez Segura ◽  
Cintia Borges Margi
Keyword(s):  
Wireless Sensor Networks ◽  
Markov Chain ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Performance ◽  
Resource Constraints ◽  
Software Defined Networking ◽  
Wireless Sensor ◽  
Prediction Algorithm ◽  
Energy Prediction

Resource Constraints in Wireless Sensor Networks are a key factor in protocols and application design. Furthermore, energy consumption plays an important role in protocols decisions, such as routing metrics. In Software-Defined Networking (SDN)-based networks, the controller is in charge of all control and routing decisions. Using energy as a metric requires such information from the nodes, which would increase packets traffic, impacting the network performance. Previous works have used energy prediction techniques to reduce the number of packets exchanged in traditional distributed routing protocols. We applied this technique in Software-Defined Wireless Sensor Networks (SDWSN). For this, we implemented an energy prediction algorithm for SDWSN using Markov chain. We evaluated its performance executing the prediction on every node and on the SDN controller. Then, we compared their results with the case without prediction. Our results showed that by running the Markov chain on the controller we obtain better prediction and network performance than when running the predictions on every node. Furthermore, we reduced the energy consumption for topologies up to 49 nodes for the case without prediction.

scholarly journals Optimizing Energy Consumption in IoT-Based Scalable Wireless Sensor Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 1-16
Author(s):  
Vinay Rishiwal ◽  
Preeti Yadav ◽  
Omkar Singh ◽  
B. G. Prasad
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Network Performance ◽  
Optimal Path ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Selection For

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.

scholarly journals Implementation of Enhanced AODV based Self-Organized Tree for Energy Balanced Routing in Wireless Sensor Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 1926-1933
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Data Transmission ◽  
Cluster Head ◽  
Residual Energy ◽  
Wireless Sensor ◽  
Self Organized ◽  
Energy Balanced Routing

Wireless sensor networks (WSN) are gaining attention in numerous fields with the advent of embedded systems and IoT. Wireless sensors are deployed in environmental conditions where human intervention is less or eliminated. Since these are not human monitored, powering and maintaining the energy of the node is a challenging issue. The main research hotspot in WSN is energy consumption. As energy drains faster, the network lifetime also decreases. Self-Organizing Networks (SON) are just the solution for the above-discussed problem. Self-organizing networks can automatically configure themselves, find an optimalsolution, diagnose and self-heal to some extent. In this work, “Implementation of Enhanced AODV based Self-Organized Tree for Energy Balanced Routing in Wireless Sensor Networks” is introduced which uses self-organization to balance energy and thus reduce energy consumption. This protocol uses combination of number of neighboring nodes and residual energy as the criteria for efficient cluster head election to form a tree-based cluster structure. Threshold for residual energy and distance are defined to decide the path of the data transmission which is energy efficient. The improvement made in choosing robust parameters for cluster head election and efficient data transmission results in lesser energy consumption. The implementation of the proposed protocol is carried out in NS2 environment. The experiment is conducted by varying the node density as 20, 40 and 60 nodes and with two pause times 5ms, 10ms. The analysis of the result indicates that the new system consumes 17.6% less energy than the existing system. The routing load, network lifetime metrics show better values than the existing system.

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