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

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.

Download Full-text

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

International journal of Computer Networks & Communications ◽

10.5121/ijcnc.2021.13205 ◽

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.

Download Full-text

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

Journal of Sensors ◽

10.1155/2021/5575802 ◽

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.

Download Full-text

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

Wireless Communications and Mobile Computing ◽

10.1155/2019/7080249 ◽

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.

Download Full-text

SARSA based access control with approximation by TileCoding

Computer Science and Information Systems ◽

10.2298/csis180830022z ◽

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.

Download Full-text

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

10.21203/rs.3.rs-512769/v1 ◽

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.

Download Full-text

Traffic Class Prioritization-Based Slotted-CSMA/CA for IEEE 802.15.4 MAC in Intra-WBANs

Sensors ◽

10.3390/s19030466 ◽

2019 ◽

Vol 19 (3) ◽

pp. 466 ◽

Cited By ~ 9

Author(s):

Farhan Masud ◽

Abdul Abdullah ◽

Ayman Altameem ◽

Gaddafi Abdul-Salaam ◽

Farkhana Muchtar

Keyword(s):

Energy Consumption ◽

Packet Loss ◽

Ieee 802.15.4 ◽

Sensor Nodes ◽

Delivery Ratio ◽

Channel Access ◽

Period Range ◽

Packet Delivery ◽

Delivery Delay ◽

Traffic Class

This paper proposes an improved Traffic Class Prioritization based Carrier Sense Multiple Access/Collision Avoidance (TCP-CSMA/CA) scheme for prioritized channel access to heterogenous-natured Bio-Medical Sensor Nodes (BMSNs) for IEEE 802.15.4 Medium Access Control (MAC) in intra-Wireless Body Area Networks (WBANs). The main advantage of the scheme is to provide prioritized channel access to heterogeneous-natured BMSNs of different traffic classes with reduced packet delivery delay, packet loss, and energy consumption, and improved throughput and packet delivery ratio (PDR). The prioritized channel access is achieved by assigning a distinct, minimized and prioritized backoff period range to each traffic class in every backoff during contention. In TCP-CSMA/CA, the BMSNs are distributed among four traffic classes based on the existing patient’s data classification. The Backoff Exponent (BE) starts from 1 to remove the repetition of the backoff period range in the third, fourth, and fifth backoffs. Five moderately designed backoff period ranges are proposed to assign a distinct, minimized, and prioritized backoff period range to each traffic class in every backoff during contention. A comprehensive verification using NS-2 was carried out to determine the performance of the TCP-CSMA/CA in terms of packet delivery delay, throughput, PDR, packet loss ratio (PLR) and energy consumption. The results prove that the proposed TCP-CSMA/CA scheme performs better than the IEEE 802.15.4 based PLA-MAC, eMC-MAC, and PG-MAC as it achieves a 47% decrease in the packet delivery delay and a 63% increase in the PDR.

Download Full-text

Network Coding for Efficient Video Multicast in Device-to-Device Communications

Sensors ◽

10.3390/s20082254 ◽

2020 ◽

Vol 20 (8) ◽

pp. 2254 ◽

Cited By ~ 5

Author(s):

Lei Wang ◽

Yulong Li ◽

Bo Pan ◽

Qiuwei Wu ◽

Jun Yin ◽

...

Keyword(s):

Network Coding ◽

Packet Loss ◽

Loss Rate ◽

Transmission Rate ◽

Packet Loss Rate ◽

Source Node ◽

Video Multicast ◽

Data Packets ◽

Device To Device ◽

Efficient Video

Device-to-Device (D2D) communication is one of the critical technologies for the fifth-generation network, which allows devices to communicate directly with each other while increasing transmission rate, but this communication is vulnerable to interference. When video transmission is carried out in an environment with interference, problems such as high packet loss rate, poor quality of the video, and blurred screen may exist. These problems can be effectively solved by redundant coding operations at the source node, but the extra coding operation imposes a heavy computational burden on the source node. In order to alleviate the computational overhead of the source node, reduce transmission delay, and guarantee transmission quality, this paper proposes an efficient video multicast transmission scheme based on Random Linear Network Coding (RLNC) in D2D networks. In the scheme, the receiving devices in the transmission participate in the process of generating repair packets that are used to remedy the loss of encoded packets during transmission. The source node multicasts the encoded video file. The receiving nodes re-encode the received data packets with RLNC and then send them to the network again. The nearby nodes can decode the original data through the encoded or re-encoded data packets. The performance of the proposed scheme is evaluated through both simulation and real experiments. The experimental results show that compared with the traditional RLNC scheme, this scheme could balance the computation overhead of the mobile devices and reduce the encoding and decoding delay by about 8%. When the packet loss rate is high, the proposed scheme can obtain better video quality than the traditional replication-based scheme.

Download Full-text

Data Transmission with Improving Lifetime of Cluster Network

Turkish Journal of Computer and Mathematics Education (TURCOMAT) ◽

10.17762/turcomat.v12i2.827 ◽

2021 ◽

Vol 12 (2) ◽

pp. 420-428

Author(s):

Anitha S, Et. al.

Keyword(s):

Energy Consumption ◽

Network Lifetime ◽

Data Transmission ◽

Cluster Head ◽

Packet Delivery Ratio ◽

Sensor Nodes ◽

Delivery Ratio ◽

Packet Delivery ◽

Cluster Network ◽

Cryptographic Algorithm

The efficiency of selecting the cluster head plays a major role in resolving the complexities faced in network management aiming to improve the longevity of sensors in the network. The clustering process is followed by selecting proper cluster heads with the consideration of energy conservation among participant nodes. While coming to security concept on WSN, the trust based cluster head selection is significant with the assumption of cooperation of all sensor nodes. In view of this assumption, the traditional methods could not help in defining the ideal cluster head of the network. This work proposes Voronoi Clustered Secure Contextual Cryptographic Algorithm (VC-SCCA) by combining Voronoi method for clustering process and cryptographic algorithm for secure data transmission. This is considered as two-tier architecture whereas, clustering takes place in first tier and encryption along with decryption takes place in the second tier. The proposed algorithm is compared with two state-of-art methods such as, Secured WSN (SeC‐WSN) and Taylor based Cat Salp Swarm Algorithm (Taylor C-SSA) in terms of energy consumption, Packet Delivery Ratio (PDR), network lifetime, encryption time and decryption time. As a result, the proposed VC-SCCA achieves 53.2% of energy consumption, 98.6% of packet delivery ratio, 97.5% of network lifetime, 62.8sec of encryption time and 71.2sec decryption time.

Download Full-text