基于非线性多项式回归模型的ADOMC-NPR移动计算自动决策卸载框架

IF 0.8 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
Abdulrahman Elhosuieny, Mofreh Salem, Amr Thabet, Abdelhameed Ibrahim
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引用次数: 3

摘要

目前,移动计算应用引起了研究人员的极大兴趣。有限的处理能力和较短的电池寿命是执行计算密集型应用的障碍。提出了一种移动计算自动决策卸载框架。该框架包括自适应学习、建模和运行时计算卸载两个阶段。在自适应阶段,采用基于非线性多项式回归(NPR)方法的曲线拟合(CF)技术建立了近似的时间预测模型,该模型可以估计检测密集型应用程序的执行时间。运行时计算阶段使用时间预测模型来计算预测的执行时间,以决定是远程运行应用程序并执行卸载过程,还是在本地运行应用程序。最后,在确定卸载决策的情况下,应用RESTful web服务来执行卸载任务。在实验上,所提出的框架在时间因素方面优于具有竞争力的最先进技术73%。所提出的时间预测模型分别对矩阵行列式、图像锐化、矩阵乘法和n-queens问题的均方误差度量应用0.4997、8.9636、0.0020和0.6797,记录了原始获得值的最小偏差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ADOMC-NPR Automatic Decision-Making Offloading Framework for Mobile Computation Using Nonlinear Polynomial Regression Model
Nowadays, mobile computation applications attract major interest of researchers. Limited processing power and short battery lifetime is an obstacle in executing computationally-intensive applications. This article presents a mobile computation automatic decision-making offloading framework. The proposed framework consists of two phases: adaptive learning, and modeling and runtime computation offloading. In the adaptive phase, curve-fitting (CF) technique based on non-linear polynomial regression (NPR) methodology is used to build an approximate time-predicting model that can estimate the execution time for spending the processing of the detected-intensive applications. The runtime computation phase uses the time predicting model for computing the predicted execution time to decide whether to run the application remotely and perform the offloading process or to run the application locally. Eventually, the RESTful web service is applied to carry out the offloading task in the case of a positive offloading decision. The proposed framework experimentally outperforms a competitive state-of-the-art technique by 73% concerning the time factor. The proposed time-predicting model records minimal deviation of the originally obtained values as it is applied 0.4997, 8.9636, 0.0020, and 0.6797 on the mean squared error metric for matrix-determinant, image-sharpening, matrix-multiplication, and n-queens problems, respectively.
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来源期刊
International Journal of Web Services Research
International Journal of Web Services Research 工程技术-计算机:软件工程
CiteScore
2.40
自引率
0.00%
发文量
19
审稿时长
>12 weeks
期刊介绍: The International Journal of Web Services Research (IJWSR) is the first refereed, international publication featuring the latest research findings and industry solutions involving all aspects of Web services technology. This journal covers advancements, standards, and practices of Web services, as well as identifies emerging research topics and defines the future of Web services on grid computing, multimedia, and communication. IJWSR provides an open, formal publication for high quality articles developed by theoreticians, educators, developers, researchers, and practitioners for those desiring to stay abreast of challenges in Web services technology.
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