Fuzzy optimization approach to component selection of fault-tolerant software system

2013 ◽  
Vol 6 (1) ◽  
pp. 49-59 ◽  
Author(s):  
P. C. Jha ◽  
Shivani Bali ◽  
U. Dinesh Kumar ◽  
Hoang Pham
Author(s):  
P. C. JHA ◽  
RAMANDEEP KAUR ◽  
SHIVANI BALI ◽  
SUSHILA MADAN

Application Package Software (APS) has emerged as a ready-to-use solution for the software industry. The software system comprises of a number of components which can be either purchased from the vendor in the form of COTS (Commercial Off-the-Shelf) or can be built in-house. Such a decision is known as Build-or-Buy decision. Under the situations wherein the software has the responsibility of supervising life-critical systems, the inception of errors in software due to inadequate or incomplete testing, is not acceptable. Such life-critical systems enforces upon meeting the quality standards of the software as unforbiddenable. This can be achieved by incorporating a fault-tolerant design that enables a system to continue its intended operation rather than failing completely when some part of the system fails. Moreover, while designing a fault-tolerant system, it must be apprehended that 100% fault tolerance can never be achieved and the closer we try to get to 100%, the more costly the system will be. The proposed model shall incorporate consensus recovery block scheme of fault tolerant techniques. Through this paper, we shall focus on build-or-buy decision for an APS in order to facilitate optimal component selection thereby, maximizing the reliability and minimizing the overall cost and source lines of code of the entire system. Further, since the proposed problem has incompleteness and unreliability of input information such as execution time and cost, hence, the environment in the proposed model is taken as fuzzy.


2012 ◽  
Vol 3 (4) ◽  
pp. 1-18 ◽  
Author(s):  
Pankaj Gupta ◽  
Shilpi Verma ◽  
Mukesh Kumar Mehlawat

Due to the rapid growth of development of component based software systems, the selection of optimal commercial-off-the-shelf (COTS) components has become the key of optimization techniques used for the purpose. In this paper, the authors use fuzzy mathematical programming (FMP) for developing bi-objective fuzzy optimization models that aims to select the best-fit COTS components for a modular software system under multiple applications development task. The proposed models maximize the functional performance and minimize the total cost of the software system satisfying the constraints of minimum threshold on intra-modular coupling density and reusability of COTS components. The efficiency of the models is illustrated using a real-world scenario of developing two financial applications for two small-scale industries.


2015 ◽  
Vol 723 ◽  
pp. 341-344
Author(s):  
Li Juan Zhang ◽  
Jiang Han ◽  
Zhang Ming Li

Research was conducted on the optimal selection of foundation improvement methods in the paper. Based on fuzzy optimization theory, four evaluation criteria such as construction time are used to evaluate the five improvement methods. The relative optimal degree 0.798 of dynamic-static consolidation method is the maximum which shows that the dynamic-static method is the optimal one; relative optimal degree and multi-evaluating criteria are used to evaluate multi-goals in the fuzzy optimization theory which will lead to the high optimal reliability result.


2021 ◽  
Author(s):  
Nitin D. Pagar ◽  
Amit R. Patil

Abstract Exhaust expansion joints, also known as compensators, are found in a variety of applications such as gas turbine exhaust pipes, generators, marine propulsion systems, OEM engines, power units, and auxiliary equipment. The motion compensators employed must have accomplished the maximum expansion-contraction cycle life while imposing the least amount of stress. Discrepancies in the selecting of bellows expansion joint design parameters are corrected by evaluating stress-based fatigue life, which is challenging owing to the complicated form of convolutions. Meridional and circumferential convolution stress equations that influencing fatigue cycles are evaluated and verified with FEA. Fractional factorial Taguchi L25 matrix is used for finding the optimal configurations. The discrete design parameters for the selection of the suitable configuration of the compensators are analysed with the help of the MADM decision making techniques. The multi-response optimization methods GRA, AHP, and TOPSIS are used to determine the parametric selection on a priority basis. It is seen that weighing distribution among the responses plays an important role in these methods and GRA method integrated with principal components shows best optimal configurations. Multiple regression technique applied to these methods also shows that PCA-GRA gives better alternate solutions for the designer unlike the AHP and TOPSIS method. However, higher ranked Taguchi run obtained in these methods may enhance the suitable selection of different design configurations. Obtained PCA-GRG values by Taguchi, Regression and DOE are well matched and verified for the all alternate solutions. Further, it also shows that stress based fatigue cycles obtained in this analysis for the L25 run indicates the range varying from 1.13 × 104 cycles to 9.08 × 105 cycles, which is within 106 cycles. This work will assist the design engineer for selecting the discrete parameters of stiff compensators utilized in power plant thermal appliances.


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