Optimizing the reliability of communication network using specially designed genetic algorithm

2009 ◽  
Author(s):  
Anoj Kumar ◽  
K. K. Mishra ◽  
A.K. Misra
Keyword(s):  
Genetic Algorithm ◽  
Communication Network

scholarly journals Security in Smart Meter using Iot

2020 ◽  
Vol 9 (4) ◽  
pp. 2293-2295
Keyword(s):  
Genetic Algorithm ◽  
Communication Network ◽  
Smart Grid ◽  
Rural Areas ◽  
Secure Communication ◽  
Power Flow ◽  
Communication Channel ◽  
Smart Meter ◽  
Utility Company ◽  
Fundamental Part

Today digitalization is key of our lifestyle not only in cities but also in rural areas. Nowadays, Internet of Things (IoT) is adding feathers to this globalization. In this research paper we will discuss about the safety and security of one of the most popular applications in IoT, i.e, Smart Meter in Smart Grid. Especially about Smart Meter in Smart Grid, which is fundamental part of it. Smart Meter unlike traditional metering system bidirectional in nature. Thus they have two streams one for power flow and second is data collection, analysis and processing i.e, communication, this is done by communication channel. Assured, strong, high-end security must be designed to the communication network so that data cannot be tampered, manipulated or interrupted by outer world. Here we will apply a unique technique of cryptography by which a secure communication channel method using Genetic Algorithm can be designed. By implementing this technique we can ensure a safe communication between customer and utility company. Thus, provide security to the data flow.

An energy-efficient VM placement method for cloud data centers using a hybrid genetic algorithm

2018 ◽  
Vol 20 (4) ◽  
pp. 430-445 ◽  
Author(s):  
Mohamed Amine Kaaouache ◽  
Sadok Bouamama
Keyword(s):  
Genetic Algorithm ◽  
Communication Network ◽  
Energy Consumption ◽  
Data Centers ◽  
Hybrid Genetic Algorithm ◽  
Vm Placement ◽  
Content Type ◽  
Cloud Data ◽  
Placement Method ◽  
Cloud Data Centers

Purpose This purpose of this paper is to propose a novel hybrid genetic algorithm based on a virtual machine (VM) placement method to improve energy efficiency in cloud data centers. How to place VMs on physical machines (PMs) to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers. Over the past few years, many approaches for VM placement (VMP) have been proposed; however, existing VM placement approaches only consider energy consumption by PMs, and do not consider the energy consumption of the communication network of a data center. Design/methodology/approach This paper attempts to solve the energy consumption problem using a VM placement method in cloud data centers. Our approach uses a repairing procedure based on a best-fit decreasing heuristic to resolve violations caused by infeasible solutions that exceed the capacity of the resources during the evolution process. Findings In addition, by reducing the energy consumption time with the proposed technique, the number of VM migrations was reduced compared with existing techniques. Moreover, the communication network caused less service level agreement violations (SLAV). Originality/value The proposed algorithm aims to minimize energy consumption in both PMs and communication networks of data centers. Our hybrid genetic algorithm is scalable because the computation time increases nearly linearly when the number of VMs increases.

A Genetic Algorithm-Based Energy-Efficient QoS Classification Method in Next Generation Electric Power Communication Networks

2013 ◽  
Vol 422 ◽  
pp. 266-272
Author(s):  
Yong Xia ◽  
Wei Zhe Ma ◽  
Man Rui Song ◽  
Fan Bo Meng
Keyword(s):  
Genetic Algorithm ◽  
Communication Network ◽  
Energy Efficiency ◽  
Energy Consumption ◽  
Electric Power ◽  
Packet Loss ◽  
Rapid Development ◽  
Loss Ratio ◽  
Next Generation ◽  
Packet Loss Ratio

With the rapid development of the information and communication technology (ICT) and the considerable increasing of the network business, the energy consumption of the network equipments improves continually. Thus building the technology of the next generation electric power communication network based on energy efficiency has become the research focus of the current electric power communication field. This paper researches the problem of the QoS graded optimization in the next generation electric power communication network. First of all, we discuss the network model of the networks QoS graded optimization, and analyze the delay and the packet loss ratio in time-variant networks. Secondly, we introduce the mathematical description of the throughput capacity and the energy consumption in time-variant networks and build the optimizing model of the energy efficiency which describes the networks QoS classification through considering the QoS constraints such as the networks delay and packet loss ratio etc. Thirdly, we propose using Genetic Algorithm to solve the model and find the QoS classes which make the networks reach the maximum energy efficiency through iterative optimization. Finally, the simulation results indicate the method proposed in this paper is available.

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