RAID 60 Storage Reliability and Cost Optimization Using Weibull Distribution and Cuckoo Search Algorithm with Lévy Flights

2018 ◽  
Vol 9 (3) ◽  
pp. 13-39
Author(s):  
Mhamed Zineddine ◽  
Adel Akaaboune
Keyword(s):  
Weibull Distribution ◽  
Search Algorithm ◽  
Storage System ◽  
Cost Optimization ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Maintenance Cost ◽  
Time To Failure ◽  
Storage Devices ◽  
Complex Architectures

This article describes how in this digital age, storage devices have been permitting the design of systems with the capacity to handle massive amount of diverse types of data. Real-time storage devices have been using complex architectures to accommodate the exponential increase of generated content. Hard drives have been at the core of most of storage systems. Estimating the reliability and the time to failure of such devices will be of great value. Weibull distribution has been widely used to assess the reliability of many systems. In this article, the three parameter Weibull distribution and Cuckoo search algorithm are combined to optimize the reliability and the maintenance cost of a RIAD 60 storage system. The numerical results show that using the proposed approach in this article, a RAID 60 system could reach its optimal reliable state by swapping less reliable drives by others more (used or new) reliable, whichever, is optimal according to the sought-after reliability threshold.

scholarly journals NÂNG CAO CÔNG SUẤT CỦA HỆ THỐNG PIN LƯU TRỮ TRÊN LƯỚI ĐIỆN PHÂN PHỐI CÓ KẾT NỐI NĂNG LƯỢNG MẶT TRỜI NHẰM GIẢM CHI PHÍ

2021 ◽  
Vol 226 (16) ◽  
pp. 11-19
Author(s):  
Tôn Ngọc Triều ◽  
Nguyễn Tùng Linh ◽  
Trương Việt Anh ◽  
Phạm Văn Lới
Keyword(s):  
Energy Storage ◽  
Search Algorithm ◽  
Storage System ◽  
Cuckoo Search ◽  
Energy Storage System ◽  
Cuckoo Search Algorithm ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy

Bài báo này trình bày vấn đề mở rộng công suất hoạt động của hệ thống lưu trữ năng lượng pin (Battery Energy Storage System - BESS) trên lưới điện phân phối có kết nối nguồn năng lượng mặt trời trong khoảng 24 giờ. Trong khoảng thời gian 24 giờ khảo sát được chia thành các khoảng thời gian nhỏ là giờ cao điểm, giờ tiêu chuẩn và giờ thấp điểm. Mục tiêu là tìm ra nút và công suất tối ưu để lắp đặt BESS của nó trong mỗi khoảng thời gian để giảm thiểu chi phí mua điện và chi phí tổn thất năng lượng. Thuật toán cuckoo search (Cuckoo Search Algorithm) được áp dụng để tối ưu vị trí và mở rộng công suất vận hành của BESS. Hiệu quả của bài toán đề xuất đã được kiểm tra trên lưới điện phân phối 33 nút. Kết quả kiểm nghiệm cho thấy, phương pháp đề xuất có khả năng giảm chi phí năng lượng cũng như góp phần giảm phụ tải cao điểm trong thời gian 24 giờ.

scholarly journals Performance Analysis of Wind Turbine Monitoring Mechanism Using Integrated Classification and Optimization Techniques

2020 ◽  
Vol 2 (1) ◽  
pp. 31-41 ◽  
Author(s):  
Dr. Subarna Shakya
Keyword(s):  
Wind Turbines ◽  
Search Algorithm ◽  
Cost Effective ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Gain Factor ◽  
Optimization Techniques ◽  
The Other ◽  
Maintenance Cost ◽  
Support Vector

The advanced improvements in the techniques utilized in the field of energy generation using the wind mills has led to the remarkable minimization in its capital investments and the cost incurred in its operation. This has even enhanced the prominence of the winds farms worldwide and has raised the market share of the energy produced using the wind mills. Thus leading to the increase in the necessity for capable monitoring mechanisms that is cost effective to report the conditions of the wind turbines regularly. So that it would be helpful in early diagnosis of any fault that has occurred in the wind turbines. To have an accurate monitoring and minimized maintenance cost the paper integrates the Support Vector machine based Cuckoo Search Algorithm. The incorporation of the SVM with the CSO is validated in MATLAB under the gain-factor and the fixed value types of faults that are liable to occur in the wind turbines and the results acquired are compared with the other existing methods such as the SVM-PSO and K-NN. The results observed shows that the SVM based CSO is more accurate in predicting the fault models than the other existing models.

Optimal broadcast scheduling method for VANETs: An adaptive discrete firefly approach

2020 ◽  
Vol 39 (6) ◽  
pp. 8125-8137
Author(s):  
Jackson J Christy ◽  
D Rekha ◽  
V Vijayakumar ◽  
Glaucio H.S. Carvalho
Keyword(s):  
Intelligent Transportation System ◽  
Search Algorithm ◽  
Mac Protocol ◽  
High Mobility ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Traffic Density ◽  
Scheduling Problem ◽  
Broadcast Scheduling

Vehicular Adhoc Networks (VANET) are thought-about as a mainstay in Intelligent Transportation System (ITS). For an efficient vehicular Adhoc network, broadcasting i.e. sharing a safety related message across all vehicles and infrastructure throughout the network is pivotal. Hence an efficient TDMA based MAC protocol for VANETs would serve the purpose of broadcast scheduling. At the same time, high mobility, influential traffic density, and an altering network topology makes it strenuous to form an efficient broadcast schedule. In this paper an evolutionary approach has been chosen to solve the broadcast scheduling problem in VANETs. The paper focusses on identifying an optimal solution with minimal TDMA frames and increased transmissions. These two parameters are the converging factor for the evolutionary algorithms employed. The proposed approach uses an Adaptive Discrete Firefly Algorithm (ADFA) for solving the Broadcast Scheduling Problem (BSP). The results are compared with traditional evolutionary approaches such as Genetic Algorithm and Cuckoo search algorithm. A mathematical analysis to find the probability of achieving a time slot is done using Markov Chain analysis.

scholarly journals Optimization strategy of wireless charger node deployment based on improved cuckoo search algorithm

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yang Wang ◽  
Feifan Wang ◽  
Yujun Zhu ◽  
Yiyang Liu ◽  
Chuanxin Zhao
Keyword(s):  
Sensor Network ◽  
Sensor Node ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Sensor Nodes ◽  
Optimization Strategy ◽  
Multi Objective ◽  
Received Power

AbstractIn wireless rechargeable sensor network, the deployment of charger node directly affects the overall charging utility of sensor network. Aiming at this problem, this paper abstracts the charger deployment problem as a multi-objective optimization problem that maximizes the received power of sensor nodes and minimizes the number of charger nodes. First, a network model that maximizes the sensor node received power and minimizes the number of charger nodes is constructed. Second, an improved cuckoo search (ICS) algorithm is proposed. This algorithm is based on the traditional cuckoo search algorithm (CS) to redefine its step factor, and then use the mutation factor to change the nesting position of the host bird to update the bird’s nest position, and then use ICS to find the ones that maximize the received power of the sensor node and minimize the number of charger nodes optimal solution. Compared with the traditional cuckoo search algorithm and multi-objective particle swarm optimization algorithm, the simulation results show that the algorithm can effectively increase the receiving power of sensor nodes, reduce the number of charger nodes and find the optimal solution to meet the conditions, so as to maximize the network charging utility.

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