SCIRD: Revealing Infection of Malicious Software in Edge Computing-Enabled IoT Networks

The Internet of Things(IoT)has characteristics such as node mobility,node heterogeneity,link heterogeneity,and topology heterogeneity.In the face of the IoT characteristics and the explosive growth of IoT nodes,which brings about large-scale data processing requirements,edge computing architecture has become an emerging network architecture to support IoT applications due to its ability to provide powerful computing capabilities and good service functions.However,the defense mechanism of Edge Computing-enabled IoT Nodes(ECIoTNs)is still weak due to their limited resources,so that they are susceptible to malicious software spread,which can compromise data confidentiality and network service availability.Facing this situation,we put forward an epidemiology-based susceptible-curb-infectious-removed-dead(SCIRD)model.Then,we analyze the dynamics of ECIoTNs with different infection levels under different initial conditions to obtain the dynamic differential equations.Additionally,we establish the presence of equilibrium states in the SCIRD model.Furthermore,we conduct an analysis of the model’s stability and examine the conditions under which malicious software will either spread or disappear within Edge Computing-enabled IoT(ECIoT)networks.Lastly,we validate the efficacy and superiority of the SCIRD model through MATLAB simulations.These research findings offer a theoretical foundation for suppressing the propagation of malicious software in ECIoT networks.The experimental results indicate that the theoretical SCIRD model has instructive significance,deeply revealing the principles of malicious software propagation in ECIoT networks.This study solves a challenging security problem of ECIoT networks by determining the malicious software propagation threshold,which lays the foundation for buildingmore secure and reliable ECIoT networks.

Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed memorysystems.However, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

Domain-Oriented Software Defined Computing Architecture

With the introduction of software defined hardware by DARPA Electronics Resurgence Initiative,software definition will be the basic attribute of information system.Benefiting from boundary certainty and algorithm aggregation of domain applications,domain-oriented computing architecture has become the technical direction that considers the high flexibility and efficiency of information system.Aiming at the characteristics of data-intensive computing in different scenarios such as Internet of Things(IoT),big data,artificial intelligence(AI),this paper presents a domain-oriented software defined computing architecture,discusses the hierarchical interconnection structure,hybrid granularity computing element and its computational kernel extraction method,finally proves the flexibility and high efficiency of this architecture by experimental comparison.

Autonomic Software Component QoS Matchmaking Algorithm Based on Fidelity Factor in Agent-Based Autonomic Computing System

Autonomic software component (ASC) QoS matchmaking problem for autonomic element has been taken as one of the most important issue in field of autonomic computing based on agent. Aimed at overcoming drawbacks such as subjec-tiveness and unfairness, and improving the self-configuration capability for autonomic element, we introduce evalua-tion mechanism of confidence of individual QoS attributes during ASC QoS matchmaking, i.e., fidelity factor for each attribute, and propose an ASC QoS matchmaking algorithm based on fidelity factor. Simulation experiments demon-strate that our proposed algorithm performs best performance in terms of QoS than other existing algorithms, and has better compromise between attribute quality and users’ evaluation when selecting ASC.

Social Computing in Open Source Community:A Study of Software Reuse

Software projects are not developed in isolation but often build upon other open source resources. These projects form a kind of reference ecosystem regarded as a software world. Most of social computing works focus on social networks such as Facebook and weibo to mine information. However, few previous works analyze Open Source Community which could help developers conduct collaborative development. In this paper, we model the Java reference ecosystem as a network based on the reuse relationships of GitHub-hosted Java projects and analyze the characteristics and the patterns of this reference ecosystem by using community detection and pattern discovery algorithms. Our study indicates that (1) Developers prefer to reuse software limited in only a small part of projects with cross cutting functionality or advanced applications. (2) Developers usually select software reused with similar function widely depending on different requirements, resulting to different patterns. Based on these collective intelligence, our study opens up several possible future directions of reuse recommendation,which are considered as guidance of collaborative development.

Artificial Intelligence Model for Software Reusability Prediction System

The most significant invention made in recent years to serve various applications is software.Developing a faultless software system requires the soft-ware system design to be resilient.To make the software design more efficient,it is essential to assess the reusability of the components used.This paper proposes a software reusability prediction model named Flexible Random Fit(FRF)based on aging resilience for a Service Net(SN)software system.The reusability predic-tion model is developed based on a multilevel optimization technique based on software characteristics such as cohesion,coupling,and complexity.Metrics are obtained from the SN software system,which is then subjected to min-max nor-malization to avoid any saturation during the learning process.The feature extrac-tion process is made more feasible by enriching the data quality via outlier detection.The reusability of the classes is estimated based on a tool called Soft Audit.Software reusability can be predicted more effectively based on the pro-posed FRF-ANN(Flexible Random Fit-Artificial Neural Network)algorithm.Performance evaluation shows that the proposed algorithm outperforms all the other techniques,thus ensuring the optimization of software reusability based on aging resilient.The model is then tested using constraint-based testing techni-ques to make sure that it is perfect at optimizing and making predictions.

A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

Recently,researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems(HPCs)to achieve exascale by applying parallelism at multiple levels.Combining different programming paradigms,such as Message Passing Interface(MPI),Open Multiple Processing(OpenMP),and Open Accelerators(OpenACC),can increase computation speed and improve performance.During the integration of multiple models,the probability of runtime errors increases,making their detection difficult,especially in the absence of testing techniques that can detect these errors.Numerous studies have been conducted to identify these errors,but no technique exists for detecting errors in three-level programming models.Despite the increasing research that integrates the three programming models,MPI,OpenMP,and OpenACC,a testing technology to detect runtime errors,such as deadlocks and race conditions,which can arise from this integration has not been developed.Therefore,this paper begins with a definition and explanation of runtime errors that result fromintegrating the three programming models that compilers cannot detect.For the first time,this paper presents a classification of operational errors that can result from the integration of the three models.This paper also proposes a parallel hybrid testing technique for detecting runtime errors in systems built in the C++programming language that uses the triple programming models MPI,OpenMP,and OpenACC.This hybrid technology combines static technology and dynamic technology,given that some errors can be detected using static techniques,whereas others can be detected using dynamic technology.The hybrid technique can detect more errors because it combines two distinct technologies.The proposed static technology detects a wide range of error types in less time,whereas a portion of the potential errors that may or may not occur depending on the 4502 CMC,2023,vol.74,no.2 operating environment are left to the dynamic technology,which completes the validation.

Teaching Reform Based on the Competency Model for Software Engineering-related Courses

This paper explores the reform and practice of software engineering-related courses based on the competency model of the Computing Curricula,and proposes some measures of teaching reform and talent cultivation in software engineering.The teaching reform emphasizes student-centered education,and focuses on the cultivation and enhancement of students’knowledge,skills,and dispositions.Based on the three elements of the competency model,specific measures of teaching reform are proposed for some professional courses in software engineering,to strengthen course relevance,improve knowledge systems,reform practical modes with a focus on skill development,and cultivate good dispositions through student-centered education.The teaching reform’s attempts and practice are conducted in some courses such as Advanced Web Technologies,Software Engineering,and Intelligent Terminal Systems and Application Development.Through the analysis and comparison of the implementation effects,significant improvements are observed in teaching effectiveness,students’mastery of knowledge and skills are noticeably improved,and the expected goals of the teaching reform are achieved.

大跨度公铁双层斜拉桥主梁涡激共振机理与控制

以拟建的某主跨808 m公铁双层斜拉桥为工程依托,采用节段模型风洞试验研究不同攻角下双层桁架梁断面的涡振性能及5种气动控制措施的抑振效果,结合计算流体动力学(CFD)静态绕流模拟,对比分析双层桁架梁断面的涡振机理及控制方法.研究表明:主梁断面原设计方案在+3°和0°风攻角下存在明显的竖向和扭转涡振现象,且振幅超过规范允许值;间隔封闭上层桥面栏杆或增设抑流板可有效抑制主梁扭转涡振,但竖向涡振振幅仍不满足规范要求;上弦杆外侧增设风嘴可有效抑制主梁竖向和扭转涡振,而下弦杆外侧增设风嘴对主梁涡振抑振效果有限.气流经主梁原设计断面上层桥面分离后,在其上下表面形成周期性脱落的大尺度旋涡,并在上层桥面后部再附,这是主梁发生竖向涡振的主要诱因;上弦杆外侧增设风嘴可引导气流平稳通过上层桥面,消除了周期性的旋涡脱落,并在其上表面形成一段狭长“回流区”,从而有效抑制了涡振的发生.

基于CT扫描数据的黄鳍金枪鱼鱼体三维重构

为研究鱼类分类与其内部结构,实验利用X射线计算机断层(CT)扫描技术对黄鳍金枪鱼鱼体进行扫描,通过医学影像软件Mimics (MIS_Research_21.0)对CT扫描数据进行处理,对黄鳍金枪鱼的骨骼、鳔和肌肉进行三维重构并测定了相应部分的体积和表面积。结果显示:(1) CT扫描可获得清晰的黄鳍金枪鱼骨骼、肌肉和鳔的影像;(2)医学影像软件Mimics可计算出黄鳍金枪鱼的骨骼、鳔和肌肉的体积和表面积,其体积分别占鱼体体积的7.76%、0.88%和91.36%,表面积分别占鱼体表面积的29.52%、0.74%和69.74%。研究表明:(1)使用X射线CT扫描技术是目前对鱼类损伤较小、鱼体骨骼、鳔和肌肉成像最便捷、最直观的方法;(2)医学影像软件Mimics可用于鱼体三维重构、计算鱼类骨骼、鳔和肌肉的体积和表面积;(3) CT扫描可用于鱼类学、鱼病学和鱼类声学回波强度的深入研究。实验可为鱼类学、鱼病学和鱼类声学回波强度等的深入研究提供参考。

蒽与马来酸酐Diels-Alder反应的量化计算研究——介绍一个计算化学实验

蒽与马来酸酐的Diels-Alder反应是基础有机化学实验课程中普遍开展的一个经典实验。本文推荐蒽与马来酸酐Diels-Alder反应的计算化学实验,该实验采用Gaussian 16程序中的密度泛函方法对蒽和马来酸酐Diels-Alder反应的反应机理进行了研究。旨在通过本实验激发学生对有机化学和计算化学的兴趣,加深学生对化学学科的理解,提升学生在科研工作中学以致用的能力。

智能算力核心基础系统软件的现状与展望

智能算力对中国人工智能技术的进步具有重要意义。发展智能算力平台,做好核心基础系统软件尤其重要。梳理了智能算力平台中的10个核心基础系统软件,对这些软件的全球现状进行了详细介绍,并探讨了当前中国算力平台上系统软件栈建设的机遇和挑战。

基于边缘计算的可重构波束控制技术研究

随着社会和技术的发展,相控阵软件无线电技术得到了快速推广和普及,其应用领域从传统的军事预警探测逐步拓展到气象探测、航空安全、无人驾驶、空间探测、天地通信中继等等。同时,新方法新体制应用对天线波束形成算法复杂度、数据传输量和波束切换的低延时等提出了更高的要求,商业应用要求高效低成本部署,并能够基于软件定义具备良好的可扩展性,传统集中式波束控制方法已无法有效应对需求。波束控制节点部署利用边缘计算理念可实现相控阵天线射频前端的就近波束形成运算与数据处理,有效减小数据传输带宽和降低延时,波束控制平台采用软件可重构体制可适应新兴领域和用户需求的不断发展变化。介绍了相控阵射频前端波束控制原理,提出了一种基于边缘计算的可重构波束控制技术,采用嵌入式分布化运算处理技术,通过建模仿真与计算,证明该技术可有效改善相控阵天线多通道数据传输压力,提升波束敏捷性,实现功能、孔径可重构,具有广泛的工程应用前景。

基于云计算的软件工程方法在通信网络中的应用与效益

文章探讨了云计算与软件工程方法的结合,以及这种结合在通信网络中的应用和效益。首先,概述了云计算的基本概念和软件工程方法,分析了两者的结合点。其次,深入探讨了基于云计算的软件工程方法如何满足通信网络的软件需求并解决存在的问题,并评估了这种方法带来的效益,包括提高工作效率、降低运营成本,以及提高网络的可靠性和安全性等。最后,总结了软件工程方法的未来发展趋势,并对未来通信网络的发展趋势和预期效益进行了预测。

基于VR一体机的古生物三维虚拟复原软件系统设计

古生物化石复原对于古生物、古地理、古气候等研究具有重大意义,但存在模型复原制作难度大、工艺成本高等问题。本文基于VR一体机硬件平台,利用虚拟现实技术开发了古生物三维虚拟复原软件系统。通过建模软件3DMax联合ZBrush精雕复原实物模型,基于三维引擎Unity3D与SteamVR协同开发了还原度高的三维空间程序,打造了交互物体展示和场景漫游控制相结合的“沉浸式”拟真三维操作环境。经HTCVIVE VR一体机对软件系统测试结果显示,软件运行流畅,具有很强的通用性,模型导入方便,交互功能便于二次开发扩展。

电脑绘图软件创作技术研究

当前,社会经济的快速发展,群众的文化水平得到大幅度提高,在文化追求及艺术鉴赏方面,体现出较为强烈的个性化、抽象化以及专属化需求,采用电脑绘图软件进行作品的创作,不仅使其具有非常强烈的个性化元素,还具备较强针对性和专属性,满足少部分群众的艺术及审美需求。在此社会文化及艺术的需求下,传统电脑绘图软件创作技术,想要创作出具备符合现代用户艺术需求的作品,不仅对设计人员提出较高的技术要求,还要打破绘图软件应用的限制。因此,电脑绘图软件创作技术研究具有一定的价值,通过研究工程类绘图软件创作技术,介绍该技术的构架设计,同时对软件模块进行拆解,按照各模块功能实现内容对其进行设计,最后对参数工程类绘图软件的创作数据库表进行设计,提高绘图软件创作技术应用效率。

紫金桥监控组态软件在丙酮氰醇装车系统中的应用

本文介绍了一种基于紫金桥监控组态软件和罗斯蒙特质量流量计的计量装车系统,该系统应用于丙酮氰醇的销售过程,提高了装车的速度、精度和安全性,同时降低了系统的复杂性和成本,增加了工作效率。首先介绍计量装车系统的组成,包括质量流量计、操作站、加密锁和监控软件等部分;然后介绍系统的组态和运行,包括设备、点、窗口的创建,以及装车流程的操作和管理;最后,总结了计量装车系统的优点和实际运行效果,证明了该系统的可行性和有效性。本文的研究对于其他类似的计量装车系统也有一定的借鉴意义。

计算机软件技术在气象信息服务中的应用

现阶段,随着科技的不断发展,计算机软件技术在各个领域得到了广泛应用。对于气象领域,各类计算机软件技术被应用到气象信息服务中,为开展气象服务工作提供了诸多便利。结合我国气象信息服务需求的特点,分析计算机软件技术在气象信息服务中应用的必要性,并且对计算机软件技术气象信息服务中的应用进行重点介绍,以期为气象服务工作的高效开展提供技术支撑。

量子计算系统软件研究综述

量子计算理论上有望解决诸多经典难解问题,近年来量子计算机的快速发展正推动这一理论进入实践.然而,当前硬件中繁多的错误会造成计算结果出错,严重限制了量子计算机解决实际问题的能力.量子计算系统软件位于应用与硬件之间,充分挖掘系统软件在硬件错误减缓方面的潜力,对于近期实现有实用价值的量子计算而言至关重要.由此,近期涌现了一批量子计算系统软件研究工作.将这些工作归纳入编译器、运行时系统和调试器3个范畴,通过对它们的分析总结,梳理量子计算系统软件的研究现状,揭示其在硬件错误减缓方面的重要作用.并对未来的研究方向进行展望.

基于机器视觉的呼出气体酒精含量检测仪自动检定装置

当前呼出气体酒精含量检测仪检定工作耗时耗力,检定过程需要人工进行判读和记录,针对该问题研制一套呼出气体酒精含量检测仪自动检定装置。依据检定规程的要求,设计配气装置实现对气体的气路设计及温度和流量等的控制。基于机器视觉系统使用Halcon联合C#开发识别算法,利用Canny边缘算法提取感兴趣区域,定位提取示值字符后训练多层感知器来识别示值结果,并实现检定过程的自动选择和报告的自动生成。实验结果表明:对五种型号的呼出气体酒精含量检测仪示值的识别准确率达到了99.5%以上,平均识别时间小于200 ms,对后续检定的平均全过程时间从3.5天缩短至1.5天。该装置满足检定规程的要求,可以应用于各地计量机构的检定工作中,具有实用价值。