Teaching Reform Conception of Software Engineering Core Courses for Cloud Application

In the 10 years after the concept of cloud computing was put forward,compared with traditional technologies and methods,great changes have taken place in the development methods,technical architecture,deployment methods and operation and maintenance modes of software systems.At present,software projects for cloud applications occupy the mainstream in the market.However,the undergraduate training programs for software engineering or computer science majors in many universities in China are still relatively traditional,lagging behind the development of cloud computing technology for freshmen.In view of this situation,this paper tries to select 3 core courses of“Requirements Analysis and System Design,Web Development Technology,Cloud Native Technology”in the undergraduate training program of software engineering major of Harbin Institute of Technology 2020 as the baseline,and puts forward the idea of breaking the barriers between courses and carrying out penetrating teaching reform.It aims to train students to have the ability to analysis,design and implementation of cloud-based application systems to meet the new needs of the market.

Adaptive Application Offloading Decision and Transmission Scheduling for Mobile Cloud Computing

Offloading application to cloud can augment mobile devices' computation capabilities for the emerging resource-hungry mobile application, however it can also consume both much time and energy for mobile device offloading application remotely to cloud. In this paper, we develop a newly adaptive application offloading decision-transmission scheduling scheme which can solve above problem efficiently. Specifically, we first propose an adaptive application offloading model which allows multiple target clouds coexisting. Second, based on Lyapunov optimization theory, a low complexity adaptive offloading decision-transmission scheduling scheme has been proposed. And the performance analysis is also given. Finally, simulation results show that,compared with that all applications are executed locally, mobile device can save 68.557% average execution time and 67.095% average energy consumption under situations.

Improving Performance of Cloud Computing and Big Data Technologies and Applications

Cloud computing technology is changing the development and usage patterns of IT infrastructure and applications. Virtualized and distributed systems as well as unified management and scheduling has greatly im proved computing and storage. Management has become easier, andOAM costs have been significantly reduced. Cloud desktop technology is develop ing rapidly. With this technology, users can flexibly and dynamically use virtual ma chine resources, companies＇ efficiency of using and allocating resources is greatly improved, and information security is ensured. In most existing virtual cloud desk top solutions, computing and storage are bound together, and data is stored as im age files. This limits the flexibility and expandability of systems and is insufficient for meetinz customers＇ requirements in different scenarios.

Mobile Cloud Computing and Applications

In 2010, cloud computing gained momentum. Cloud computing is a model for real-time, on-demand, pay-for-use network access to a shared pool of configurable computing and storage resources. It has matured from a promising business concept to a working reality in both the private and public IT sectors. The U.S. government, for example, has requested all its agencies to evaluate cloud computing alternatives as part of their budget submissions for new IT investment.

Impact of Coronavirus Pandemic Crisis on Technologies and Cloud Computing Applications

In light of the coronavirus disease 2019(COVID-19)outbreak caused by the novel coronavirus,companies and institutions have instructed their employees to work from home as a precautionary measure to reduce the risk of contagion.Employees,however,have been exposed to different security risks because of working from home.Moreover,the rapid global spread of COVID-19 has increased the volume of data generated from various sources.Working from home depends mainly on cloud computing(CC)applications that help employees to efficiently accomplish their tasks.The cloud computing environment(CCE)is an unsung hero in the COVID-19 pandemic crisis.It consists of the fast-paced practices for services that reflect the trend of rapidly deployable applications for maintaining data.Despite the increase in the use of CC applications,there is an ongoing research challenge in the domains of CCE concerning data,guaranteeing security,and the availability of CC applications.This paper,to the best of our knowledge,is the first paper that thoroughly explains the impact of the COVID-19 pandemic on CCE.Additionally,this paper also highlights the security risks of working from home during the COVID-19 pandemic.

AgamottoEye:Recovering Request Flow for Cloud Systems via Log Analysis

Cloud applications are implemented on top of different distributed systems to provide online service.A service request is decomposed into multiple sub-tasks,which are dispatched to different distributed systems components.For cloud providers,monitoring the execution of a service request is crucial to promptly find problems that may compromise cloud availability.In this paper,we present AgamottoEye,to automatically construct request flow from existing logs.AgamottoEye addresses the challenges of analyzing interleaved log instances,and can successfully extract request flow spread across multiple distributed systems.Our experiments with Hadoop2/YARN show that AgamottoEye can analyze 25,050 log instances in 57.4s,and the extracted request flow information is helpful with error detection and diagnosis.

An Interactive Online Platform for Algorithms Teaching

Learning programming has become an important part of education.However,most students have extreme difficulty learning programming and complex algorithms.This is because programming has a hierarchical logic.Solving complex problems requires students to develop skills in decomposing problems.To this end,this paper describes an effective method to develop an online platform for teaching complex algorithms.

URL Phishing Detection Using Particle Swarm Optimization and Data Mining

The continuous destruction and frauds prevailing due to phishing URLs make it an indispensable area for research.Various techniques are adopted in the detection process,including neural networks,machine learning,or hybrid techniques.A novel detection model is proposed that uses data mining with the Particle Swarm Optimization technique(PSO)to increase and empower the method of detecting phishing URLs.Feature selection based on various techniques to identify the phishing candidates from the URL is conducted.In this approach,the features mined from the URL are extracted using data mining rules.The features are selected on the basis of URL structure.The classification of these features identified by the data mining rules is done using PSO techniques.The selection of features with PSO optimization makes it possible to identify phishing URLs.Using a large number of rule identifiers,the true positive rate for the identification of phishing URLs is maximized in this approach.The experiments show that feature selection using data mining and particle swarm optimization helps tremendously identify the phishing URLs based on the structure of the URL itself.Moreover,it can minimize processing time for identifying the phishing website instead.So,the approach can be beneficial to identify suchURLs over the existing contemporary detecting models proposed before.

SOME STATISTICAL CHARACTERISTICS AND THE APPLICATION OF JAPANESE GMS LOW CLOUD WINDS

A statistical study of GMS low cloud winds in January,April,July and October,1983 shows that on an average,there exist 223.5 low cloud winds over western North Pacific each synoptic time.The low cloud winds have a diurnal change with more low cloud winds at 12 Z than at 00 Z. The wind fields at 850 hPa over western North Pacific,with and without application of low cloud winds, have been analyzed by a successive correction scheme.The results indicate that the flow patterns without low cloud winds are considerably distorted from short of wind data over the oceanic region.On the con- trary,with application of low cloud winds,the flow patterns get much more improved over the oceanic region.

Call for Papers Special Issue on Cloud Computing and Big Data Applications

The publication of Tsinghua Science and Technology was started in 1996. Since then, it has been an international academic journal sponsored by Tsinghua University and published bimonthly. This journal aims at presenting the state-of-art scientific achievements in computer science and other IT fields.

Fog computing for vehicular Ad-hoc networks: paradigms, scenarios, and issues

Vehicular Ad-hoc networks（VANETs） are kinds of mobile Ad-hoc networks（MANETs）, which consist of mobile vehicles with on-board units（OBUs） and roadside units（RSUs）. With the rapid development of computation and communication technologies, peripheral or incremental changes in VANETs evolve into a revolution in process. Cloud computing as a solution has been deployed to satisfy vehicles in VANETs which are expected to require resources（such as computing, storage and networking）. Recently, with special requirements of mobility, location awareness, and low latency, there has been growing interest in research into the role of fog computing in VANETs. The merging of fog computing with VANETs opens an area of possibilities for applications and services on the edge of the cloud computing. Fog computing deploys highly virtualized computing and communication facilities at the proximity of mobile vehicles in VANET. Mobile vehicles in VANET can also demand services of low-latency and short-distance local connections via fog computing. This paper presents the current state of the research and future perspectives of fog computing in VANETs. Moreover, we discuss the characteristics of fog computing and services based on fog computing platform provided for VANETs. In this paper, some opportunities for challenges and issues are mentioned, related techniques that need to be considered have been discussed in the context of fog computing in VANETs. Finally, we discuss about research directions of potential future work for fog computing in VANETs. Within this article, readers can have a more thorough understanding of fog computing for VANETs and the trends in this domain.