Hybrid Metaheuristic Algorithm-Based Clustering with Multi-Hop Routing Protocol for Wireless Sensor Networks

2021 ◽  
pp. 843-855
Author(s):  
S. Jagadeesh ◽  
I. Muthulakshmi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Wireless Sensor ◽  
Metaheuristic Algorithm ◽  
Hybrid Metaheuristic

scholarly journals Hybridization of Metaheuristic Algorithm for Dynamic Cluster-based Routing Protocol in Wireless Sensor Networks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Shaha T. Al-Otaibi ◽  
Amal Al-Rasheed ◽  
Romany F. Mansour ◽  
Eunmok Yang ◽  
Gyanendra Prasad Joshi ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Wireless Sensor ◽  
Metaheuristic Algorithm ◽  
Dynamic Cluster ◽  
Cluster Based Routing

Independent Grid Structure-Based Routing Protocol in Wireless Sensor Networks

2013 ◽  
Vol E96.B (1) ◽  
pp. 309-312 ◽  
Author(s):  
Euisin LEE ◽  
Soochang PARK ◽  
Hosung PARK ◽  
Sang-Ha KIM
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Wireless Sensor ◽  
Grid Structure

Performance Analysis of TBC-ACO Routing Protocol with Existing Routing Protocols of Wireless Sensor Networks

2017 ◽  
Vol 7 (8) ◽  
pp. 169
Author(s):  
A. Radhika ◽  
D. Haritha
Keyword(s):  
Energy Efficiency ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Swarm Intelligence ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Energy Efficient ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Aware

Wireless Sensor Networks, have witnessed significant amount of improvement in research across various areas like Routing, Security, Localization, Deployment and above all Energy Efficiency. Congestion is a problem of  importance in resource constrained Wireless Sensor Networks, especially for large networks, where the traffic loads exceed the available capacity of the resources . Sensor nodes are prone to failure and the misbehaviour of these faulty nodes creates further congestion. The resulting effect is a degradation in network performance, additional computation and increased energy consumption, which in turn decreases network lifetime. Hence, the data packet routing algorithm should consider congestion as one of the parameters, in addition to the role of the faulty nodes and not merely energy efficient protocols .Nowadays, the main central point of attraction is the concept of Swarm Intelligence based techniques integration in WSN.  Swarm Intelligence based Computational Swarm Intelligence Techniques have improvised WSN in terms of efficiency, Performance, robustness and scalability. The main objective of this research paper is to propose congestion aware , energy efficient, routing approach that utilizes Ant Colony Optimization, in which faulty nodes are isolated by means of the concept of trust further we compare the performance of various existing routing protocols like AODV, DSDV and DSR routing protocols, ACO Based Routing Protocol  with Trust Based Congestion aware ACO Based Routing in terms of End to End Delay, Packet Delivery Rate, Routing Overhead, Throughput and Energy Efficiency. Simulation based results and data analysis shows that overall TBC-ACO is 150% more efficient in terms of overall performance as compared to other existing routing protocols for Wireless Sensor Networks.

SPREAD - A Routing Protocol to Meet End-to-end Adjusted Deadline in Real Time Wireless Sensor Networks

2020 ◽  
Vol 10 (1) ◽  
pp. 63-78
Author(s):  
Neetika Jain ◽  
Sangeeta Mittal
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Real Time ◽  
Routing Protocol ◽  
Resource Constraints ◽  
Wireless Sensor ◽  
Network Simulator ◽  
Packet Delivery ◽  
High Data ◽  
Hard Real Time

Background: Real Time Wireless Sensor Networks (RT-WSN) have hard real time packet delivery requirements. Due to resource constraints of sensors, these networks need to trade-off energy and latency. Objective: In this paper, a routing protocol for RT-WSN named “SPREAD” has been proposed. The underlying idea is to reserve laxity by assuming tighter packet deadline than actual. This reserved laxity is used when no deadline-meeting next hop is available. Objective: As a result, if due to repeated transmissions, energy of nodes on shortest path is drained out, then time is still left to route the packet dynamically through other path without missing the deadline. Results: Congestion scenarios have been addressed by dynamically assessing 1-hop delays and avoiding traffic on congested paths. Conclusion: Through extensive simulations in Network Simulator NS2, it has been observed that SPREAD algorithm not only significantly reduces miss ratio as compared to other similar protocols but also keeps energy consumption under control. It also shows more resilience towards high data rate and tight deadlines than existing popular protocols.

PERFORMANCE EVALUATION ANALYSIS OF WIRELESS SENSOR NETWORKS ROUTING PROTOCOLS IN SMART GRIDS

2016 ◽  
Vol 26 (1) ◽  
pp. 17
Author(s):  
Carlos Deyvinson Reges Bessa
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Smart Grids ◽  
Network Routing ◽  
Base Station ◽  
Wireless Sensor ◽  
Delay Jitter ◽  
La Red

ABSTRACTThis work aims to study which wireless sensor network routing protocol is more suitable for Smart Grids applications, through simulation of AODV protocols, AOMDV, DSDV and HTR in the NS2 simulation environment. Was simulated a network based on a residential area with 47 residences, with one node for each residence and one base station, located about 25m from the other nodes. Many parameters, such as packet loss, throughput, delay, jitter and energy consumption were tested.  The network was increased to 78 and 93 nodes in order to evaluate the behavior of the protocols in larger networks. The tests proved that the HTR is the routing protocol that has the best results in performance and second best in energy consumption. The DSDV had the worst performance according to the tests.Key words.- Smart grid, QoS analysis, Wireless sensor networks, Routing protocols.RESUMENEste trabajo tiene como objetivo estudiar el protocolo de enrutamiento de la red de sensores inalámbricos es más adecuado para aplicaciones de redes inteligentes, a través de la simulación de protocolos AODV, AOMDV, DSDV y HTR en el entorno de simulación NS2. Se simuló una red basada en una zona residencial con 47 residencias, con un nodo para cada residencia y una estación base, situada a unos 25 metros de los otros nodos. Muchos parámetros, tales como la pérdida de paquetes, rendimiento, retardo, jitter y el consumo de energía se probaron. La red se incrementó a 78 y 93 nodos con el fin de evaluar el comportamiento de los protocolos de redes más grandes. Las pruebas demostraron que el HTR es el protocolo de enrutamiento que tiene los mejores resultados en el rendimiento y el segundo mejor en el consumo de energía. El DSDV tuvo el peor desempeño de acuerdo a las pruebas.Palabras clave.- redes inteligentes, análisis de calidad de servicio, redes de sensores inalámbricas, protocolos de enrutamiento.

scholarly journals Fuzzy Logic-Based Geographic Routing Protocol for Dynamic Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (1) ◽  
pp. 196 ◽  
Author(s):  
Xing Hu ◽  
Linhua Ma ◽  
Yongqiang Ding ◽  
Jin Xu ◽  
Yan Li ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Fuzzy Logic ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Geographic Routing ◽  
Wireless Sensor ◽  
Location Information ◽  
Destination Node ◽  
Routing Overhead ◽  
Geographic Routing Protocol

The geographic routing protocol only requires the location information of local nodes for routing decisions, and is considered very efficient in multi-hop wireless sensor networks. However, in dynamic wireless sensor networks, it increases the routing overhead while obtaining the location information of destination nodes by using a location server algorithm. In addition, the routing void problem and location inaccuracy problem also occur in geographic routing. To solve these problems, a novel fuzzy logic-based geographic routing protocol (FLGR) is proposed. The selection criteria and parameters for the assessment of the next forwarding node are also proposed. In FLGR protocol, the next forward node can be selected based on the fuzzy location region of the destination node. Finally, the feasibility of the FLGR forwarding mode is verified and the performance of FLGR protocol is analyzed via simulation. Simulation results show that the proposed FLGR forwarding mode can effectively avoid the routing void problem. Compared with existing protocols, the FLGR protocol has lower routing overhead, and a higher packet delivery rate in a sparse network.

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