scholarly journals Traffic and Energy Aware Optimization for Congestion Control in Next Generation Wireless Sensor Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Saneh Lata Yadav ◽  
R. L. Ujjwal ◽  
Sushil Kumar ◽  
Omprakash Kaiwartya ◽  
Manoj Kumar ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Packet Loss ◽  
Loss Rate ◽  
Packet Loss Rate ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Huffman Coding ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Packet Delivery

Congestion in wireless sensor networks (WSNs) is an unavoidable issue in today’s scenario, where data traffic increased to its aggregated capacity of the channel. The consequence of this turns in to overflowing of the buffer at each receiving sensor nodes which ultimately drops the packets, reduces the packet delivery ratio, and degrades throughput of the network, since retransmission of every unacknowledged packet is not an optimized solution in terms of energy for resource-restricted sensor nodes. Routing is one of the most preferred approaches for minimizing the energy consumption of nodes and enhancing the throughput in WSNs, since the routing problem has been proved to be an NP-hard and it has been realized that a heuristic-based approach provides better performance than their traditional counterparts. To tackle all the mentioned issues, this paper proposes an efficient congestion avoidance approach using Huffman coding algorithm and ant colony optimization (ECA-HA) to improve the network performance. This approach is a combination of traffic-oriented and resource-oriented optimization. Specially, ant colony optimization has been employed to find multiple congestion-free alternate paths. The forward ant constructs multiple congestion-free paths from source to sink node, and backward ant ensures about the successful creation of paths moving from sink to source node, considering energy of the link, packet loss rate, and congestion level. Huffman coding considers the packet loss rate on different alternate paths discovered by ant colony optimization for selection of an optimal path. Finally, the simulation result presents that the proposed approach outperforms the state of the art approaches in terms of average energy consumption, delay, and throughput and packet delivery ratio.

scholarly journals Multivariate Weighted Isotonic Regressive Modest Adaptive Boosting Based Resource-Aware Routing In WSN

2021 ◽  
Author(s):  
N. Muruganandam ◽  
V. Venkatraman ◽  
R. Venkatesan
Keyword(s):  
Packet Loss ◽  
Data Transmission ◽  
Loss Rate ◽  
Packet Loss Rate ◽  
Sensor Nodes ◽  
Delivery Ratio ◽  
Adaptive Boosting ◽  
Data Packets ◽  
Packet Delivery ◽  
Resource Aware

Abstract WSN includes a scenario where huge amount of sensor nodes are distributed to monitor environmental conditions with route collected data towards sinks via the internet. WSNs efficiently manage the wider network with available resources, such as residual energy and wireless channel bandwidth. Therefore, routing algorithm is important to enhance battery-constrained networks. Many existing techniques are developed for balancing consumption of energy but efficient routing was not achieved. Multivariate Weighted Isotonic Regressive Modest Adaptive Boosting based Resource Aware Routing (MWIRMAB-RAR) technique is introduced for enhancing routing. The MWIRMAB-RAR technique includes a different process namely resource-aware node selection, route path discovery, and data transmission. Initially, the MWIRMAB-RAR technique uses the Modest Adaptive Boosting technique uses the Multivariate Weighted Isotonic Regression function for detecting resource-efficient sensor nodes for effective data transmission. After that, multiple route paths are established based on the time of flight method. After establishes route path, source node sends data packets to sink node via resource-efficient nodes. The data delivery was enhanced and minimizes packet loss as well as delay. The simulation analysis is carried out on certain performance factors such as energy consumption, packet delivery ratio, packet loss rate, and delay with number of data packets and sensor nodes. The obtained evaluation indicates MWIRMAB-RAR outperforms well in terms of increasing data packet delivery and reduces consumption of energy, packet loss rate, and delay.

scholarly journals Event Based Clustering Localized Energy Efficient Ant Colony Optimization (EBC_LEE-ACO) for Performance Enhancement of Wireless Sensor Network

2018 ◽  
Vol 8 (4) ◽  
pp. 3177-3183 ◽  
Author(s):  
S. D. Chavan ◽  
A. V. Kulkarni
Keyword(s):  
Energy Consumption ◽  
Ant Colony Optimization ◽  
Energy Efficient ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Packet Delivery ◽  
Event Based ◽  
Packet Drop

The main challenge of a wireless sensor network (WSN) in disaster situations is to discover efficient routing, to improve quality of service (QoS) and to reduce energy consumption. Location awareness of nodes is also useful or even necessary. Without knowing the position of sensor nodes, collected data is insignificant. Ant colony optimization (ACO) is a unique form of optimization method, which is highly suitable for adaptive routing and guaranteed packet delivery. The primary drawbacks of ACO are data flooding, huge overhead of control messages and long convergence time. These drawbacks are overcome by considering location information of sensor nodes. An event-based clustering localized energy efficient ant colony optimization (EBC_LEE-ACO) algorithm is proposed to enhance the performance of WSN. The main focus of the proposed algorithm is to improve QoS and minimize the network energy consumption by cluster formation and selecting the optimal path based on the biological inspired routing-ACO and location information of nodes. In clustering, data is aggregated and sent to the sink (base station) through cluster head (CH) which reduces overheads. EBC_LEE-ACO is a scalable and energy efficient reactive routing algorithm which improves QoS, lifetime and minimizes energy consummation of WSN as compared to other routing algorithms like AODV, ACO, ACO using RSSI. The proposed algorithm reduces energy consumption by approximately 7%, in addition to improvement in throughput, packet delivery ratio and increase in packet drop which has been observed in comparison with other algorithms, i.e. autonomous localization based eligible energetic Path_with_Ant Colony optimization (ALEEP with ACO) of the network. Use of IEEE 802.11 standard in proposed work increased packet drop.

scholarly journals Quantile Regressive Fish Swarm Optimized Deep Convolutional Neural Learning for Reliable Data Transmission in IoV

2021 ◽  
Vol 13 (2) ◽  
pp. 81-97
Author(s):  
S. Suguna Devi ◽  
A. Bhuvaneswari
Keyword(s):  
Packet Loss ◽  
Data Transmission ◽  
Loss Rate ◽  
Reliable Data ◽  
Packet Loss Rate ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
End To End Delay ◽  
Neural Learning

Route path identification on the Internet of Vehicles (IoV) is complicated due to the nature of high dynamic mobility, bandwidth constraints, and traffic load. A vehicle present on the IoV communicates with each other to find the status of the road and location of other vehicles for reliable data transmission. However, the existing routing algorithm does not effectively improve the packet delivery ratio and reduce the delay. To resolve these issues, A Quantile Regressive Fish Swarm Optimized Deep Convolutional Neural Learning (QRFSODCNL) technique is introduced reliable data transmission with minimum end to end delay in IoV. The Do Convolutional Neural Learning uses multiple layers such as one input layer, three hidden layers, and one output layer for vehicle location identification and optimal route path discovery. The different node characteristics of vehicle nodes are analyzed in the hidden layers using the quantile regression function. Depends on the regression analysis, the neighbouring node is identified with minimal time. To improve the throughput and reduce the packet loss rate, the artificial fish swarm optimization technique is applied to choose the best route among the population based on the fitness function. Simulation is carried out to analyze the performance of QRFSODCNL technique and existing methods with different metrics such as packet delivery ratio, packet loss rate, average end to end delay, and throughput. The discussed outcome proves that the QRFSODCNL technique outperforms well as compared to the stateof-the-art methods.

scholarly journals Link Failure Detection and Classification in Wireless Sensor Networks using Classification Method

2019 ◽  
Vol 8 (12) ◽  
pp. 1132-1135
Keyword(s):  
System Performance ◽  
Detection Rate ◽  
Sensor Node ◽  
Weak Link ◽  
Failure Detection ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Link Failure ◽  
Packet Delivery

This paper develops a method to detect the failures of wireless links between one sensor nodes to another sensor node in WSN environment. Every node in WSN has certain properties which may vary time to time based on its ability to transfer or receive the packets on it. This property or features are obtained from every node and they are classified using Neural Networks (NN) classifier with predetermined feature set which are belonging to both weak link and good link between nodes in wireless networks. The proposed system performance is analyzed by computing Packet Delivery Ratio (PDR), Link Failure Detection Rate (LFDR) and latency report.

scholarly journals An Enhanced Underwater Linear Wireless Sensor Network Deployment Strategy for Data Collection

2018 ◽  
Vol 8 (3) ◽  
Author(s):  
Zahoor Ahmed ◽  
Kamalrulnizam Abu Bakar
Keyword(s):  
Wireless Sensor Network ◽  
Data Collection ◽  
Sensor Network ◽  
Research Work ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Deployment Strategy ◽  
Underwater Pipeline

The deployment of Linear Wireless Sensor Network (LWSN) in underwater environment has attracted several research studies in the underwater data collection research domain. One of the major issues in underwater data collection is the lack of robust structure in the deployment of sensor nodes. The challenge is more obvious when considering a linear pipeline that covers hundreds of kilometers. In most of the previous work, nodes are deployed not considering heterogeneity and capacity of the various sensor nodes. This lead to the problem of inefficient data delivery from the sensor nodes on the underwater pipeline to the sink node at the water surface. Therefore, in this study, an Enhanced Underwater Linear Wireless Sensor Network Deployment (EULWSND) has been proposed in order to improve the robustness in linear sensor underwater data collection. To this end, this paper presents a review of related literature in an underwater linear wireless sensor network. Further, a deployment strategy is discussed considering linearity of the underwater pipeline and heterogeneity of sensor nodes. Some research challenges and directions are identified for future research work. Furthermore, the proposed deployment strategy is implemented using AQUASIM and compared with an existing data collection scheme. The result demonstrates that the proposed EULWSND outperforms the existing Dynamic Address Routing Protocol for Pipeline Monitoring (DARP-PM) in terms of overhead and packet delivery ratio metrics. The scheme performs better in terms of lower overhead with 17.4% and higher packet delivery with 20.5%.

scholarly journals Sensing Coverage Algorithm of Sparse Mobile Sensor Node with Trade-Off between Packet Loss Rate and Transmission Delay

2019 ◽  
Vol 2019 ◽  
pp. 1-11
Author(s):  
Kehua Zhao ◽  
Yourong Chen ◽  
Siyi Lu ◽  
Banteng Liu ◽  
Tiaojuan Ren ◽  
...  
Keyword(s):  
Packet Loss ◽  
Data Transmission ◽  
Loss Rate ◽  
Packet Loss Rate ◽  
Transmission Delay ◽  
Sensor Nodes ◽  
Mobile Sensor ◽  
Sensing Coverage ◽  
Mobile Sensor Node ◽  
Monitoring Area

To solve the problem of sensing coverage of sparse wireless sensor networks, the movement of sensor nodes is considered and a sensing coverage algorithm of sparse mobile sensor node with trade-off between packet loss rate and transmission delay (SCA_SM) is proposed. Firstly, SCA_SM divides the monitoring area into several grids of same size and establishes a path planning model of multisensor nodes’ movement. Secondly, the social foraging behavior of Escherichia coli in bacterial foraging is used. A fitness function formula of sensor nodes’ moving paths is proposed. The optimal moving paths of all mobile sensor nodes which can cover the entire monitoring area are obtained through the operations of chemotaxis, replication, and migration. The simulation results show that SCA_SM can fully cover the monitoring area and reduce the packet loss rate and data transmission delay in the process of data transmission. Under certain conditions, SCA_SM is better than RAND_D, HILBERT, and TCM.

Designing and Implementing a Lightweight WSN MAC Protocol for Smart Home Networking Applications

2016 ◽  
Vol 26 (03) ◽  
pp. 1750043 ◽  
Author(s):  
Ching-Han Chen ◽  
Ming-Yi Lin ◽  
Wen-Hung Lin
Keyword(s):  
Smart Home ◽  
Ieee 802.15.4 ◽  
Mac Protocol ◽  
Discrete Event ◽  
Packet Delivery Ratio ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Medium Access ◽  
Packet Delivery

Wireless sensor networks (WSNs) represent a promising solution in the fields of the Internet of Things (IoT) and machine-to-machine networks for smart home applications. However, to feasibly deploy wireless sensor devices in a smart home environment, four key requirements must be satisfied: stability, compatibility, reliability routing, and performance and power balance. In this study, we focus on the unreliability problem of the IEEE 802.15.4 WSN medium access control (MAC), which is caused by the contention-based MAC protocol used for channel access. This problem results in a low packet delivery ratio, particularly in a smart home network with only a few sensor nodes. In this paper, we first propose a lightweight WSN protocol for a smart home or an intelligent building, thus replacing the IEEE 802.15.4 protocol, which is highly complex and has a low packet delivery ratio. Subsequently, we describe the development of a discrete event system model for the WSN by using a GRAFCET and propose a development platform based on a reconfigurable FPGA for reducing fabrication cost and time. Finally, a prototype WSN controller ASIC chip without an extra CPU and with our proposed lightweight MAC was developed and tested. It enhanced the packet delivery ratio by up to 100%.

scholarly journals Low-Energy Secure Routing Protocol for WSNs Based on Multiobjective Ant Colony Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xueli Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Ant Colony Optimization Algorithm

As one of the three pillars of information technology, wireless sensor networks (WSNs) have been widely used in environmental detection, healthcare, military surveillance, industrial data sampling, and many other fields due to their unparalleled advantages in deployment cost, network power consumption, and versatility. The advent of the 5G standard and the era of Industry 4.0 have brought new opportunities for the development of wireless sensor networks. However, due to the limited power capacity of the sensor nodes themselves, the harsh deployment environment will bring a great difficulty to the energy replenishment of the sensor nodes, so the energy limitation problem has become a major factor limiting its further development; how to improve the energy utilization efficiency of WSNs has become an urgent problem in the scientific and industrial communities. Based on this, this paper researches the routing technology of wireless sensor networks, from the perspective of improving network security, and reducing network energy consumption, based on the study of ant colony optimization algorithm, further studies the node trust evaluation mechanism, and carries out the following research work: (1) study the energy consumption model of wireless sensor networks; (2) basic ant colony algorithm improvement; (3) multiobjective ant colony algorithm based on wireless sensor routing algorithm optimization. In this study, the NS2 network simulator is used as a simulation tool to verify the performance of the research algorithm. Compared with existing routing algorithms, the simulation results show that the multiobjective ant colony optimization algorithm has better performance in evaluation indexes such as life cycle, node energy consumption, node survival time, and stability compared with the traditional algorithm and the dual cluster head ant colony optimization algorithm.

scholarly journals SARSA based access control with approximation by TileCoding

2019 ◽  
Vol 16 (3) ◽  
pp. 689-704
Author(s):  
Fei Zhu ◽  
Pai Peng ◽  
Quan Liu ◽  
Yuchen Fu ◽  
Shan Zhong
Keyword(s):  
Access Control ◽  
Error Rate ◽  
Packet Loss ◽  
Loss Rate ◽  
Control Method ◽  
Packet Loss Rate ◽  
Sensor Nodes ◽  
Utilization Rate ◽  
Security Problem ◽  
Server Utilization

Traditional sensor nodes ignore the packet loss rate during information transmission and the access control security problem caused by server utilization when uploading data. To solve the problem, we propose a SARSA based access control method with approximation by TileCoding (SACT), which takes the sensor packet loss rate and the server error rate into account. The network state is estimated by the packet loss rate and variable bit error rate to get a server access control strategy to improve security performance. The eventual strategy complies with the minimum information loss and the maximum server utilization. Results of experiments show that the algorithm is capable of achieving good results in the total amount of information received by the server system. The SACT improves the server utilization rate and the overall security performance of the network.

scholarly journals Delta Ruled First Order Iterative Deep Neural Learning for Sybil and Wormhole Attacks Detection in Healthcare Wireless Sensor Network

2021 ◽  
Author(s):  
John Clement Sunder A ◽  
K.P. Sampoornam KP ◽  
R.Vinodkumar R
Keyword(s):  
Packet Loss ◽  
Detection Rate ◽  
Loss Rate ◽  
Attack Detection ◽  
Packet Loss Rate ◽  
Sensor Nodes ◽  
Wormhole Attack ◽  
First Order ◽  
Wormhole Attacks ◽  
Routing Performance

Abstract Detection and isolation of Sybil and wormhole attack nodes in healthcare WSN is a significant problem to be resolved. Few research works have been designed to identify Sybil and wormhole attack nodes in the network. However, the detection performance of Sybil and wormhole attack nodes was not effectual as the false alarm rate was higher. In order to overcome such limitations, Delta Ruled First Order Iterative Deep Learning based Intrusion Detection (DRFOIDL-ID) Technique is proposed. The DRFOIDL-ID Technique includes two main phase namely attack detection and isolation. The DRFOIDL-ID Technique constructs Delta Ruled First Order Iterative Deep Learning in attack detection phase with aim of detecting the occurrence of Sybil and wormhole attacks in healthcare WSN. After detecting the attack nodes, DRFOIDL-ID Technique carried outs isolation process with the objective of increasing the routing performance. During the isolation phase, DRFOIDL-ID Technique keep always the identified Sybil and wormhole attack nodes through transmitting the isolation messages to all sensor nodes in healthcare WSN. Hence, DRFOIDL-ID Technique improves the routing performance with lower packet loss rate. The DRFOIDL-ID Technique conducts the simulation process using factors such as attack detection rate, attack detection time, false alarm rate and packet loss rate with respect to a diverse number of sensor nodes and data packets. The simulation result proves that the DRFOIDL-ID Technique is able to improve the attack detection rate and also reduces the attack detection time as compared to state-of-the-art works.

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