A Tutorial on Federated Learning from Theory to Practice:Foundations,Software Frameworks,Exemplary Use Cases,and Selected Trends

When data privacy is imposed as a necessity,Federated learning(FL)emerges as a relevant artificial intelligence field for developing machine learning(ML)models in a distributed and decentralized environment.FL allows ML models to be trained on local devices without any need for centralized data transfer,thereby reducing both the exposure of sensitive data and the possibility of data interception by malicious third parties.This paradigm has gained momentum in the last few years,spurred by the plethora of real-world applications that have leveraged its ability to improve the efficiency of distributed learning and to accommodate numerous participants with their data sources.By virtue of FL,models can be learned from all such distributed data sources while preserving data privacy.The aim of this paper is to provide a practical tutorial on FL,including a short methodology and a systematic analysis of existing software frameworks.Furthermore,our tutorial provides exemplary cases of study from three complementary perspectives:i)Foundations of FL,describing the main components of FL,from key elements to FL categories;ii)Implementation guidelines and exemplary cases of study,by systematically examining the functionalities provided by existing software frameworks for FL deployment,devising a methodology to design a FL scenario,and providing exemplary cases of study with source code for different ML approaches;and iii)Trends,shortly reviewing a non-exhaustive list of research directions that are under active investigation in the current FL landscape.The ultimate purpose of this work is to establish itself as a referential work for researchers,developers,and data scientists willing to explore the capabilities of FL in practical applications.

Deployment Strategy for Multiple Controllers Based on the Aviation On-Board Software-Defined Data Link Network

In light of the escalating demand and intricacy of services in contemporary terrestrial,maritime,and aerial combat operations,there is a compelling need for enhanced service quality and efficiency in airborne cluster communication networks.Software-Defined Networking(SDN)proffers a viable solution for the multifaceted task of cooperative communication transmission and management across different operational domains within complex combat contexts,due to its intrinsic ability to flexibly allocate and centrally administer network resources.This study pivots around the optimization of SDN controller deployment within airborne data link clusters.A collaborative multi-controller architecture predicated on airborne data link clusters is thus proposed.Within this architectural framework,the controller deployment issue is reframed as a two-fold problem:subdomain partition-ing and central interaction node selection.We advocate a subdomain segmentation approach grounded in node value ranking(NDVR)and a central interaction node selection methodology predicated on an enhanced Artificial Fish Swarm Algorithm(AFSA).The advanced NDVR-AFSA(Node value ranking-Improved artificial fish swarm algorithm)algorithm makes use of a chaos algorithm for population initialization,boosting population diversity and circumventing premature algorithm convergence.By the integration of adaptive strategies and incorporation of the genetic algorithm’s crossover and mutation operations,the algorithm’s search range adaptability is enhanced,thereby increasing the possibility of obtaining globally optimal solutions,while concurrently augmenting cluster reliability.The simulation results verify the advantages of the NDVR-IAFSA algorithm,achieve a better load balancing effect,improve the reliability of aviation data link cluster,and significantly reduce the average propagation delay and disconnection rate,respectively,by 12.8%and 11.7%.This shows that the optimization scheme has important significance in practical application,and can meet the high requirements of modern sea,land,and air operations to aviation airborne communication networks.

On Software Application Database Constraint-driven Design and Development

This paper presents a methodology driven by database constraints for designing and developing(database)software applications.Much needed and with excellent results,this paradigm guarantees the highest possible quality of the managed data.The proposed methodology is illustrated with an easy to understand,yet complex medium-sized genealogy software application driven by more than 200 database constraints,which fully meets such expectations.

On the Use of E-Learning Software Data--with Speexx Foreign Lan guage Learning System Being the Case

E-learning produces the data on the learners’utilization of the software,which helps the teacher to perceive the learners’mental status and learning efficiency,so it is of great value to make full use of the data.With Speexx foreign language learning system being the case,this thesis introduces the function of such data and the modes of how to use them to facilitate the blendedteaching and learning.

Analysis software for upper atmospheric data developed by the IUGONET project and its application to polar science

To comprehensively understand the Arctic and Antarctic upper atmosphere, it is often crucial to analyze various data that are obtained from many regions. Infrastructure that promotes such interdisciplinary studies on the upper atmosphere has been developed by a Japanese inter-university project called the Inter-university Upper atmosphere Global Observation Network （1UGONET）. The objective of this paper is to describe the infrastructure and tools developed by IUGONET. We focus on the data analysis software. It is written in Interactive Data Language （IDL） and is a plug-in for the THEMIS Data Analysis Software suite （TDAS）, which is a set of IDL libraries used to visualize and analyze satellite- and ground-based data. We present plots of upper atmospheric data provided by IUGONET as examples of applications, and verify the usefulness of the software in the study of polar science. We discuss IUGONET＇s new and unique developments, i.e., an executable file of TDAS that can run on the IDL Virtual Machine, IDL routines to retrieve metadata from the IUGONET database, and an archive of 3-D simulation data that uses the Common Data Format so that it can easily be used with TDAS.

A study on fast post-processing massive data of casting numerical simulation on personal computers

When castings become complicated and the demands for precision of numerical simulation become higher,the numerical data of casting numerical simulation become more massive.On a general personal computer,these massive numerical data may probably exceed the capacity of available memory,resulting in failure of rendering.Based on the out-of-core technique,this paper proposes a method to effectively utilize external storage and reduce memory usage dramatically,so as to solve the problem of insufficient memory for massive data rendering on general personal computers.Based on this method,a new postprocessor is developed.It is capable to illustrate filling and solidification processes of casting,as well as thermal stess.The new post-processor also provides fast interaction to simulation results.Theoretical analysis as well as several practical examples prove that the memory usage and loading time of the post-processor are independent of the size of the relevant files,but the proportion of the number of cells on surface.Meanwhile,the speed of rendering and fetching of value from the mouse is appreciable,and the demands of real-time and interaction are satisfied.

Reliability Estimation for Component-Based Software Using General Masking Grouped Data

Masked data are the system failure data when exact component causing system failure might be unknown.In this paper,the mathematical description of general masked data was presented in software reliability engineering.Furthermore,a general maskedbased additive non-homogeneous Poisson process(NHPP) model was considered to analyze component reliability.However,the problem of masked-based additive model lies in the difficulty of estimating parameters.The maximum likelihood estimation procedure was derived to estimate parameters.Finally,a numerical example was given to illustrate the applicability of proposed model,and the immune particle swarm optimization(IPSO) algorithm was used in maximize log-likelihood function.

Software Metric Analysis of Open-Source Business Software

Over the past decade, open-source software use has grown. Today, many companies including Google, Microsoft, Meta, RedHat, MongoDB, and Apache are major participants of open-source contributions. With the increased use of open-source software or integration of open-source software into custom-developed software, the quality of this software component increases in importance. This study examined a sample of open-source applications from GitHub. Static software analytics were conducted, and each application was classified for its risk level. In the analyzed applications, it was found that 90% of the applications were classified as low risk or moderate low risk indicating a high level of quality for open-source applications.

Various Software Packages for Analysis of Nuclear Magnetic Resonance Spectroscopic Data

The magnetic resonance spectroscopy(MRS)results are greatly influenced by reconstruction of the spectrum and quantitative analysis.Because of this requirement a number of programs dedicated to MRS data analysis were developed.The selection and use of appropriate software is crucial not only in clinical procedures,but also while carrying out scientific research.The choice of the software to suit the user's needs should be based on the analysis of the functionality of the program.It is particularly important from the user's viewpoint to identify what data can be loaded and processed in the program.The specific programs allow the user different degree of control over analysis parameters.Moreover,the programs for MRS data analysis differ in terms of the applied signal processing algorithms.The aim of this work,therefore,is to review available packages designed for MRS data analysis,taking into account their capabilities and limitations.

Software-Defined Optical Data Centre Networks

Based on the analysis of data centre(DC) traffic pattern, we introduced a holistic software-defined optical DC solution. Architecture-on-Demand based hybrid optical switched(OPS/OCS) data centre network(DCN) fabric is introduced, which is able to realise different inter-and intra-cluster configurations and dynamically support diverse traffic in the DC. The optical DCN is controlled and managed by a software-defined networking(SDN) enabled control plane to achieve high programmability. Moreover, virtual data centre(VDC) composition is developed as an application of such softwaredefined optical DC to create VDC slices for different tenants.

Review of Load Balancing Mechanisms in SDN-Based Data Centers

With the continuous expansion of the data center network scale, changing network requirements, and increasing pressure on network bandwidth, the traditional network architecture can no longer meet people’s needs. The development of software defined networks has brought new opportunities and challenges to future networks. The data and control separation characteristics of SDN improve the performance of the entire network. Researchers have integrated SDN architecture into data centers to improve network resource utilization and performance. This paper first introduces the basic concepts of SDN and data center networks. Then it discusses SDN-based load balancing mechanisms for data centers from different perspectives. Finally, it summarizes and looks forward to the study on SDN-based load balancing mechanisms and its development trend.

Distributed Data Acquisition and Control by Software Bus

Increasing global competition forces manufacturers of products from alltechnical fields to guarantee a high product quality for a long period of time. At thesame time it is necessary to minimize production costs. In order to meet all theserequirements, on-line data acquisition and processing are of increasing importancein distributed automation systems. A software bus operating on industrial Ethernethas an ability to minimize operating costs by offering easy installation, scalability,high degree of reliability and remote monitoring and control.

A Software Reliability Model for OSS Including Various Fault Data Based on Proportional Hazard-Rate Model

The software reliability model is the stochastic model to measure the software reliability quantitatively. A Hazard-Rate Model is the well-known one as the typical software reliability model. We propose Hazard-Rate Models Considering Fault Severity Levels (CFSL) for Open Source Software (OSS). The purpose of this research is to make the Hazard-Rate Model considering CFSL adapt to baseline hazard function and 2 kinds of faults data in Bug Tracking System (BTS), i.e., we use the covariate vectors in Cox proportional Hazard-Rate Model. Also, we show the numerical examples by evaluating the performance of our proposed model. As the result, we compare the performance of our model with the Hazard-Rate Model CFSL.

Workload-aware request routing in cloud data center using software-defined networking

Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.

Fuzzy Logic Based Group Maturity Rating for Software Performance Prediction

Driven by market requirements, software services organizations have adopted various software engineering process models （such as capability maturity model （CMM）, capability maturity model integration （CMMI）, ISO 9001：2000, etc.） and practice of the project management concepts defined in the project management body of knowledge. While this has definitely helped organizations to bring some methods into the software development madness, there always exists a demand for comparing various groups within the organization in terms of the practice of these defined process models. Even though there exist many metrics for comparison, considering the variety of projects in terms of technology, life cycle, etc., finding a single metric that caters to this is a difficult task. This paper proposes a model for arriving at a rating on group maturity within the organization. Considering the linguistic or imprecise and uncertain nature of software measurements, fuzzy logic approach is used for the proposed model. Without the barriers like technology or life cycle difference, the proposed model helps the organization to compare different groups within it with reasonable precision.

HOTCAP:a new software package for high-speed oscilloscopebased three-dimensional bunch charge and position measurement

A software package to be used in high-speed oscilloscope-basedthree-dimensionalbunch-by-bunch charge and position measurement is presented.The software package takes the pick-up electrode signal waveform recorded by the high-speed oscilloscope as input,and it calculates and outputs the bunch-by-bunch charge and position.In addition to enabling a three-dimensional observation of the motion of each passing bunch on all beam position monitor pick-up electrodes,it offers many additional features such as injection analysis,bunch response function reconstruction,and turn-by-turn beam analysis.The software package has an easy-to-understand graphical user interface and convenient interactive operation,which has been verified on the Windows 10 system.

MEIM:A Multi-Source Software Knowledge Entity Extraction Integration Model

Entity recognition and extraction are the foundations of knowledge graph construction.Entity data in the field of software engineering come from different platforms and communities,and have different formats.This paper divides multi-source software knowledge entities into unstructured data,semi-structured data and code data.For these different types of data,Bi-directional Long Short-Term Memory(Bi-LSTM)with Conditional Random Field(CRF),template matching,and abstract syntax tree are used and integrated into a multi-source software knowledge entity extraction integration model(MEIM)to extract software entities.The model can be updated continuously based on user’s feedbacks to improve the accuracy.To deal with the shortage of entity annotation datasets,keyword extraction methods based on Term Frequency–Inverse Document Frequency(TF-IDF),TextRank,and K-Means are applied to annotate tasks.The proposed MEIM model is applied to the Spring Boot framework,which demonstrates good adaptability.The extracted entities are used to construct a knowledge graph,which is applied to association retrieval and association visualization.

Simulation of a Flexible Manufacturing System with AutoMod Software

A flexible manufacturing system (FMS) is a highly automated, complex system. Simulation is a well-proven method to design or analyze an FMS. Deployment of a radio frequency identification (RFID) system in FMS produces large volumes of RFID data streams, which provide valuable information to improve the operation of FMS. Different frameworks are presented in this paper regarding the use of RFID data streams in an FMS simulation. Simulations are performed with AutoMod software. Related technical details are also presented. The paper’s structure is complied as the following steps: step 1, the introduction of AMHS, FMS and AutoMod;step 2, FMS simulation using AutoMod software;step 3, simulation frameworks driven by RFID data streams;step 4, conclusion.

A Censored Nonparametric Software Reliability Model

This paper analyses the effect of censoring on the estimation of failure rate, and presents a framework of a censored nonparametric software reliability model. The model is based on nonparametric testing of failure rate monotonically decreasing and weighted kernel failure rate estimation under the constraint of failure rate monotonically decreasing. Not only does the model have the advantages of little assumptions and weak constraints, but also the residual defects number of the software system can be estimated. The numerical experiment and real data analysis show that the model performs wdl with censored data.