Energy Efficient Congestion Aware Resource Allocation and Routing Protocol for IoT Network using Hybrid Optimization Techniques

2021 ◽  
Author(s):  
K. V. Praveen ◽  
P. M. Joe Prathap
Keyword(s):  
Resource Allocation ◽  
Routing Protocol ◽  
Energy Efficient ◽  
Optimization Techniques ◽  
Hybrid Optimization ◽  
Hybrid Optimization Techniques ◽  
Congestion Aware

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.

scholarly journals A Novel Energy Efficient Resource Management System in Cloud Computing Environment.

2018 ◽  
Vol 7 (4.19) ◽  
pp. 1030
Author(s):  
S. K. Sonkar ◽  
M. U.Kharat
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Resource Management ◽  
Virtual Machine ◽  
Energy Efficient ◽  
Service Providers ◽  
Optimization Techniques ◽  
Cloud Provider ◽  
Efficient Resource ◽  
Machine Allocation

Primary target of cloud provider is to provide the maximum resource utilization and increase the revenue by reducing energy consumption and operative cost. In the service providers point of view, resource allocation, resource sharing, migration of resources on demand, memory management, storage management, load balancing, energy efficient resource usage, computational complexity handling in virtualization are some of the major tasks that has to be dealt with. The major issue focused in this paper is to reduce the energy consumption problem and management of computation capacity utilization.  For the same, an energy efficient resource management method is proposed to grip the resource scheduling and to minimize the energy utilized by the cloud datacenters for the computational work. Here a novel resource allocation mechanism is proposed, based on the optimization techniques. Also a novel dynamic virtual machine (VM) allocation method is suggested to help dynamic virtual machine allocation and job rescheduling to improve the consolidation of resources to execute the jobs. Experimental results indicated that proposed strategy outperforms as compared to the existing systems.  

Hybrid Tabu Search Hopfield Recurrent ANN Fuzzy Technique to the Production Planning Problems

2012 ◽  
Vol 2 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Pandian M. Vasant ◽  
Timothy Ganesan ◽  
Irraivan Elamvazuthi
Keyword(s):  
Tabu Search ◽  
Optimization Technique ◽  
Optimization Techniques ◽  
Oil Refinery ◽  
Hybrid Optimization ◽  
Real World Problem ◽  
Prime Objective ◽  
The Moment ◽  
Hybrid Optimization Techniques ◽  
Planning Problems

The fuzzy technology reveals that everything is a matter of degree. At the moment, many industrial production problems are solved by operational research optimization techniques, under the considerations of some real assumptions. In this paper, the authors have several applications of fuzzy linear, non-linear, non-continues and other mathematical programming applications. The prime objective of this paper is to investigate a new application to the literature and to solve the crude oil refinery production problem by using the hybrid optimization techniques of Tabu Search (TS), Hopfield Recurrent Artificial Neural Network (HRANN) and fuzzy approaches. In application, the real world problem of refinery model has been developed and thorough comparative studies have been carried on varies optimization techniques. The final results and findings reveal that, the hybrid optimization technique provides better, robust, efficient, flexible and stable solutions.

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