scholarly journals SIMULATION OF ENERGY CONSUMPTION IN MULTI CLUSTER WIRELESS SENSOR NETWORKS

2018 ◽  
pp. 22-26
Author(s):  
S. I. Pella
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Performance ◽  
Network Connectivity ◽  
Wireless Sensor ◽  
Cluster Network ◽  
Cluster Networks ◽  
Energy Conserving ◽  
Single Cluster

Energy conserving protocols in wireless sensor networks (WSNs), such as S-MAC, introduce multi-cluster network. The border nodes in multi cluster WSNs have more active time than the other nodes in the network; hence have more energy depletion rate. Since battery replacement in most networks is considered difficult, one or more nodes running out of energy prematurely will affect the network connectivity and decrease the overall network performance severely. This paper aims to (1) analyze the energy consumption in a multi-cluster sensor network and compare it to the single cluster scenario (2) investigate the merging time in a single cluster network. The result shows that, in average the energy needed to deliver a packet in the multi cluster networks is about 150% more than the energy needed in the single cluster networks. Moreover, the merging time in the single cluster network using schedule offset as the merging criteria in average is slightly smaller than one in the network using schedule ID as the merging criteria.

An Energy-Balance Based Distributed Topology Control Algorithm for Wireless Sensor Networks

2012 ◽  
Vol 490-495 ◽  
pp. 1392-1396 ◽  
Author(s):  
Chu Hang Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Topology Control ◽  
Control Algorithm ◽  
Path Loss ◽  
Network Connectivity ◽  
Premature Death ◽  
Residual Energy ◽  
Wireless Sensor

Topology control is an efficient approach which can reduce energy consumption for wireless sensor networks, and the current algorithms mostly focus on reducing the nodes’ energy consumption by power adjusting, but pay little attention to balance energy consumption of the whole network, which results in premature death of many nodes. Thus, a distributed topology control algorithm based on path-loss and residual energy (PRTC) is designed in this paper. This algorithm not only maintains the least loss links between nodes but also balances the energy consumption of the network. The simulation results show that the topology constructed by PRTC can preserve network connectivity as well as extend the lifetime of the network and provide good performance of energy consumption.

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.

Energy-Efficient Route Protocols to Minimize Holes in Wireless Sensor Networks Using Probability Enhancement Algorithm

2021 ◽  
Vol 17 (4) ◽  
pp. 16-28
Author(s):  
Chinmaya Kumar Nayak ◽  
Satyabrata Das
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Network Performance ◽  
Cluster Head ◽  
Network Connectivity ◽  
Wireless Sensor ◽  
Energy Hole ◽  
Enhancement Method ◽  
Efficient Route

Wireless sensor networks are widely utilized. In the network of wireless sensors, the nodes of sensors normally disseminated arbitrarily are conditional on the method preferred to realize the sensor network. Primarily, the lifespan of a sensor node depends on the active node numbers along with the network connectivity. When a sensor node runs out of power, the sensor node dies too early, affecting network performance. Therefore, an energy hole will be formed with the network. To avoid the problem of energy holes, a number of rules are already proposed. This paper proposed a new method to resolve the problem of energy holes in wireless sensor networks and maximizes the useful life of the network through a different way of cluster head selection using asymmetrical clustering method. This paper proposed PE (probability enhancement) method for choosing the cluster head, which gives improved output compared to LEACH as well as PEGASIS protocol. The result of simulation is performed with MATLAB, and it appears that the projected scheme works better than the previous scheme.

scholarly journals Optimizing Energy Consumption in IoT based Scalable Wireless Sensor Networks

2021 ◽  
Vol 10 (4) ◽  
pp. 0-0
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 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.

QoS Aware Multi-hop Multi-path Routing Approach in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 43-52
Author(s):  
Omkar Singh ◽  
Vinay Rishiwal
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Life Time ◽  
Base Station ◽  
Environmental Data ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
End To End

Background & Objective: Wireless Sensor Network (WSN) consist of huge number of tiny senor nodes. WSN collects environmental data and sends to the base station through multi-hop wireless communication. QoS is the salient aspect in wireless sensor networks that satisfies end-to-end QoS requirement on different parameters such as energy, network lifetime, packets delivery ratio and delay. Among them Energy consumption is the most important and challenging factor in WSN, since the senor nodes are made by battery reserved that tends towards life time of sensor networks. Methods: In this work an Improve-Energy Aware Multi-hop Multi-path Hierarchy (I-EAMMH) QoS based routing approach has been proposed and evaluated that reduces energy consumption and delivers data packets within time by selecting optimum cost path among discovered routes which extends network life time. Results and Conclusion: Simulation has been done in MATLAB on varying number of rounds 400- 2000 to checked the performance of proposed approach. I-EAMMH is compared with existing routing protocols namely EAMMH and LEACH and performs better in terms of end-to-end-delay, packet delivery ratio, as well as reduces the energy consumption 13%-19% and prolongs network lifetime 9%- 14%.

Energy Efficient Group Based Linear Wireless Sensor Networks for Application in Pipeline Monitoring

2020 ◽  
Vol 10 ◽  
Author(s):  
Chinedu Duru ◽  
Neco Ventura ◽  
Mqhele Dlodlo
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Remote Monitoring ◽  
Linear Array ◽  
Minimum Energy ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sink Node ◽  
Pipeline Monitoring

Background: Wireless Sensor Networks (WSNs) have been researched to be one of the ground-breaking technologies for the remote monitoring of pipeline infrastructure of the Oil and Gas industry. Research have also shown that the preferred deployment approach of the sensor network on pipeline structures follows a linear array of nodes, placed a distance apart from each other across the infrastructure length. The linear array topology of the sensor nodes gives rise to the name Linear Wireless Sensor Networks (LWSNs) which over the years have seen themselves being applied to pipelines for effective remote monitoring and surveillance. This paper aims to investigate the energy consumption issue associated with LWSNs deployed in cluster-based fashion along a pipeline infrastructure. Methods: Through quantitative analysis, the study attempts to approach the investigation conceptually focusing on mathematical analysis of proposed models to bring about conjectures on energy consumption performance. Results: From the derived analysis, results have shown that energy consumption is diminished to a minimum if there is a sink for every placed sensor node in the LWSN. To be precise, the analysis conceptually demonstrate that groups containing small number of nodes with a corresponding sink node is the approach to follow when pursuing a cluster-based LWSN for pipeline monitoring applications. Conclusion: From the results, it is discovered that energy consumption of a deployed LWSN can be decreased by creating groups out of the total deployed nodes with a sink servicing each group. In essence, the smaller number of nodes each group contains with a corresponding sink, the less energy consumed in total for the entire LWSN. This therefore means that a sink for every individual node will attribute to minimum energy consumption for every non-sink node. From the study, it can be concurred that energy consumption of a LWSN is inversely proportional to the number of sinks deployed and hence the number of groups created.

Improved DV-Hop Localization Scheme for Randomly Deployed WSNs

2020 ◽  
Vol 10 (1) ◽  
pp. 94-109 ◽  
Author(s):  
Rekha Goyat ◽  
Mritunjay Kumar Rai ◽  
Gulshan Kumar ◽  
Hye-Jin Kim ◽  
Se-Jung Lim
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Research Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Error ◽  
Anchor Nodes ◽  
Least Energy ◽  
Range Free

Background: Wireless Sensor Networks (WSNs) is considered one of the key research area in the recent. Various applications of WSNs need geographic location of the sensor nodes. Objective: Localization in WSNs plays an important role because without knowledge of sensor nodes location the information is useless. Finding the accurate location is very crucial in Wireless Sensor Networks. The efficiency of any localization approach is decided on the basis of accuracy and localization error. In range-free localization approaches, the location of unknown nodes are computed by collecting the information such as minimum hop count, hop size information from neighbors nodes. Methods: Although various studied have been done for computing the location of nodes but still, it is an enduring research area. To mitigate the problems of existing algorithms, a range-free Improved Weighted Novel DV-Hop localization algorithm is proposed. Main motive of the proposed study is to reduced localization error with least energy consumption. Firstly, the location information of anchor nodes is broadcasted upto M hop to decrease the energy consumption. Further, a weight factor and correction factor are introduced which refine the hop size of anchor nodes. Results: The refined hop size is further utilized for localization to reduces localization error significantly. The simulation results of the proposed algorithm are compared with other existing algorithms for evaluating the effectiveness and the performance. The simulated results are evaluated in terms localization error and computational cost by considering different parameters such as node density, percentage of anchor nodes, transmission range, effect of sensing field and effect of M on localization error. Further statistical analysis is performed on simulated results to prove the validation of proposed algorithm. A paired T-test is applied on localization error and localization time. The results of T-test depicts that the proposed algorithm significantly improves the localization accuracy with least energy consumption as compared to other existing algorithms like DV-Hop, IWCDV-Hop, and IDV-Hop. Conclusion: From the simulated results, it is concluded that the proposed algorithm offers 36% accurate localization than traditional DV-Hop and 21 % than IDV-Hop and 13% than IWCDV-Hop.

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