Swarm intelligence application for optimization of CO2 diffusivity in polystyrene-b-polybutadiene-b-polystyrene (SEBS) foaming

2017 ◽  
Author(s):  
Rahida Wati Sharudin ◽  
Norshawalina Muhamad Ajib ◽  
Marina Yusoff ◽  
Mohd Aizad Ahmad
Keyword(s):  
Swarm Intelligence ◽  
Intelligence Application

scholarly journals Swarm Intelligence Application to UAV Aided IoT Data Acquisition Deployment Optimization

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 175660-175668
Author(s):  
Elin Chen ◽  
Junfu Chen ◽  
Ali Wagdy Mohamed ◽  
Bi Wang ◽  
Zhendong Wang ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Swarm Intelligence ◽  
Deployment Optimization ◽  
Intelligence Application

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.

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