scholarly journals Collision-Aware Routing Using Multi-Objective Seagull Optimization Algorithm for WSN-Based IoT

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8496
Author(s):  
Preetha Jagannathan ◽  
Sasikumar Gurumoorthy ◽  
Andrzej Stateczny ◽  
Parameshachari Bidare Divakarachar ◽  
Jewel Sengupta
Keyword(s):  
Optimization Algorithm ◽  
Network Performance ◽  
The Internet ◽  
Delivery Ratio ◽  
Energy Aware ◽  
Transmission Delays ◽  
Multi Objective ◽  
Everyday Objects ◽  
Structure Reliability ◽  
Scalable Network

In recent trends, wireless sensor networks (WSNs) have become popular because of their cost, simple structure, reliability, and developments in the communication field. The Internet of Things (IoT) refers to the interconnection of everyday objects and sharing of information through the Internet. Congestion in networks leads to transmission delays and packet loss and causes wastage of time and energy on recovery. The routing protocols are adaptive to the congestion status of the network, which can greatly improve the network performance. In this research, collision-aware routing using the multi-objective seagull optimization algorithm (CAR-MOSOA) is designed to meet the efficiency of a scalable WSN. The proposed protocol exploits the clustering process to choose cluster heads to transfer the data from source to endpoint, thus forming a scalable network, and improves the performance of the CAR-MOSOA protocol. The proposed CAR-MOSOA is simulated and examined using the NS-2.34 simulator due to its modularity and inexpensiveness. The results of the CAR-MOSOA are comprehensively investigated with existing algorithms such as fully distributed energy-aware multi-level (FDEAM) routing, energy-efficient optimal multi-path routing protocol (EOMR), tunicate swarm grey wolf optimization (TSGWO), and CoAP simple congestion control/advanced (CoCoA). The simulation results of the proposed CAR-MOSOA for 400 nodes are as follows: energy consumption, 33 J; end-to-end delay, 29 s; packet delivery ratio, 95%; and network lifetime, 973 s, which are improved compared to the FDEAM, EOMR, TSGWO, and CoCoA.

scholarly journals Drop-Burst Length Evaluation of Urban VANETs

2017 ◽  
Vol 6 (2) ◽  
pp. 67
Author(s):  
Awos Kh. Ali ◽  
Iain Phillips ◽  
Huanjia Yang
Keyword(s):  
High Speed ◽  
Network Performance ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
Transportation Systems ◽  
Delivery Ratio ◽  
Burst Length ◽  
Network Load ◽  
Hoc Networks ◽  
Scalable Network

Networks performance is traditionally evaluated using packet delivery ratio (PDR) and latency (delay). We propose an addition mechanism the drop-burst length (DBL). Many traffic classes display varying application-level performance according to the pattern of drops, even if the PDR is similar. In this paper we study a number of VANET scenarios and evaluate them with these three metrics.Vehicular Ad-hoc Networks (VANETs) are an emerging class of Mobile Ad-hoc Network (MANETs) where nodes include both moving vehicles and fixed infrastructure. VANETs aim to make transportation systems more intelligent by sharing information to improve safety and comfort. Efficient and adaptive routing protocols are essential for achieving reliable and scalable network performance. However, routing in VANETs is challenging due to the frequent, high-speed movement of vehicles, which results in frequent network topology changes.Our simulations are carried out using NS2 (for network traffic) and SUMO (for vehicular movement) simulators, with scenarios configured to reflect real-world conditions. The results show that OLSR is able to achieve a best DBL performance and demonstrates higher PDR performance comparing to AODV and GPSR under low network load. However, with GPSR, the network shows more stable PDR under medium and high network load. In term of delay OLSR is outperformed by GPSR.

Hybrid Multi-Objective-Optimization Algorithm for Energy Efficient Priority-based QoS Routing in IoT networks

2021 ◽  
Author(s):  
THEN MOZHI
Keyword(s):  
Optimization Algorithm ◽  
Energy Efficient ◽  
Fitness Function ◽  
Optimization Technique ◽  
Qos Routing ◽  
Traffic Load ◽  
Delivery Ratio ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
End To End

The growing requirement for real-time Internet of Things (IoT) applications has ended with Quality of Service (QoS) communication protocols. where heterogeneous IoT data collection and communication processing contains specific requirements in terms of energy, reliability, latency, and priority. Due to energy constraints, a proper estimation model for monitoring and control is accomplished by the objective of sensing and end-to-end communication respectively. moreover, the connectivity requires a QoS routing protocol to finding the route selection for sensor networks. Hence, data routing and prioritization and Satisfying the QoS requirements are the significant challenges in such networks. So for the Multi-objective Optimization for QoS Routing method is used for differentiating the traffics while data communication and gives the requirements to be caring about the network resource. In this paper, the Energy-Efficient Priority-based Multi-Objective QoS routing (PMQoSR) mechanism ensures the energy and Qos in IoT networks. the proposed system regulates the routing performance based on the QoS parameters, using optimization technique for three hybrid algorithms, named as WLFA- Whale Lion Fireworks optimization algorithm with Fitness Function Routing(FFR) mechanisms .the WLFA to prevent congestion and minimizes the localization error using and select the shortest routing path through the network period uses Priority label and time delay patterns when sending data to the destination. We evaluate its performance and existing competing schemes in terms of Energy-Efficient. The results demonstrate that PMQoSR holds out considering network traffic, packets forwarding, error rate, energy, and distance between the nodes and also considers priority-aware routing to improve the traffic load, throughput, end-to-end delay, and packet delivery ratio when compared with the existing systems.

scholarly journals Fitness Function Based Particle Swarm Optimization Algorithm for Mobile Adhoc Networks

2018 ◽  
Vol 7 (3.1) ◽  
pp. 31
Author(s):  
Rohan Gupta ◽  
Gurpreet Singh ◽  
Amanpreet Kaur ◽  
Aashdeep Singh
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Network Performance ◽  
Particle Swarm Optimization Algorithm ◽  
Fitness Function ◽  
Particle Swarm ◽  
Delivery Ratio ◽  
Average Delay ◽  
Swarm Optimization ◽  
Mobile Adhoc Network

Mobile adhoc network is a network which carries out discussion between nodes in the absence of infrastructure. The fitness function based Particle Swarm Optimization Algorithm has been projected for improving the network performance. The effect of changing the number of nodes, communication range and transmission range is investigated on various qualities of service metrics namely packet delivery ratio, throughput and average delay. The investigation has been carried out using NS-2 simulator.  

Multi-objective energy-aware batch scheduling using ant colony optimization algorithm

2019 ◽  
Vol 131 ◽  
pp. 41-56 ◽  
Author(s):  
Zhao-hong Jia ◽  
Yan Wang ◽  
Chao Wu ◽  
Yun Yang ◽  
Xing-yi Zhang ◽  
...  
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Ant Colony ◽  
Batch Scheduling ◽  
Ant Colony Optimization Algorithm ◽  
Energy Aware ◽  
Multi Objective

scholarly journals Comparative Study of AODV andDSR Routing Protocols forGateway Placement Optimization

2016 ◽  
Vol 15 (4) ◽  
pp. 6659-6665
Author(s):  
Jamal Muafaq Hameed Al-Bayati
Keyword(s):  
Routing Protocols ◽  
Network Performance ◽  
Ad Hoc ◽  
Mobile Ad Hoc Network ◽  
The Internet ◽  
Delivery Ratio ◽  
Mobile Nodes ◽  
Gateway Node ◽  
Placement Optimization ◽  
Mobile Ad Hoc

This paper considers mobile ad-hoc network (MANET) in which mobile nodes can reach the Internet via stationary gateway node. The gateway works as bridge between MANET and the Internet. Several studies show that location of the gateway inside network topology has a significant effect on overall network performance. Two different scenarios, with varying number of nodes and two gateway locations, have been considered under the assumption that all mobile nodes are connected to Internet through the same gateway. Simulation has been done using NS-2 software, producing a computer model of AODV and DSR routing protocols. Comparison of these routing protocols is performed in terms of Average (end-to-end) delay, Throughput, Normalized routing load and Packet delivery ratio metrics. Simulation results suggest that AODV routing protocol has better performance in both scenarios. In addition, the results suggest that location of gateway at the center gives better results compared to gateway positioned at the edge.

A Bandwidth and Energy Aware QoS Routing Protocol for Enhanced Performance in Ad-hoc Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 203-213
Author(s):  
Priyanka Bharadwaj ◽  
Surjeet Balhara
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocol ◽  
Ad Hoc ◽  
Qos Routing ◽  
Delivery Ratio ◽  
Energy Aware ◽  
Multimedia Services ◽  
Average Delay ◽  
Hoc Networks

Background & Objective: There are some challenging issues such as providing Quality of Service (QoS), restricted usage of channels and shared bandwidth pertaining to ad-hoc networks in a dynamic topology. Hence, there is a requirement to support QoS for the application environment and multimedia services in ad-hoc networks with the fast growing and emerging development of information technology. Eventually, bandwidth is one of the key elements to be considered. Methods: Energy aware QoS routing protocol in an ad-hoc network is presented in this article. Results and Conclusion: The simulation results indicate that the improved protocol outperforms Adhoc On-Demand Distance Vector (AODV) routing protocol in terms of QoS metric such as throughput, packet delivery ratio, loss rate and average delay.

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