Integrating Artificial Bee Colony Algorithm and BP Neural Network for Software Aging Prediction in IoT Environment

IEEE Access

Lingze Meng¹  Jing Liu¹ 

[1] College of Computer Science, Inner Mongolia University, Hohhot, China;

关键词: Artificial bee colony algorithm;    BP neural network;    software aging;    prediction accuracy;   

DOI  :  10.1109/ACCESS.2019.2903081

来源: DOAJ

【 摘 要 】

Software aging is a common phenomenon that exists in systems that require long periods of operation, especially in Internet-of-Things environments. The back propagation (BP) neural network has been adopted widely to predict the trend of software aging. However, the weight and threshold of the BP neural network are randomly initialized, so it is easy to get the unsatisfactory local optimal solutions and the convergence speed of computing is slow. In this paper, we propose a novel software aging prediction method using the artificial bee colony algorithm to optimize the BP neural network model for achieving better software aging prediction accuracy. The experiment results show that our method fits the prediction trend of software aging more accurately than the traditional BP neural network, and our method also has faster convergence speed and more stable prediction results.

【 授权许可】

Unknown