A Double-Timescale Reinforcement Learning Based Cloud-Edge Collaborative Framework for Decomposable Intelligent Services in Industrial Internet of Things

With the proportion of intelligent services in the industrial internet of things(IIoT)rising rapidly,its data dependency and decomposability increase the difficulty of scheduling computing resources.In this paper,we propose an intelligent service computing framework.In the framework,we take the long-term rewards of its important participants,edge service providers,as the optimization goal,which is related to service delay and computing cost.Considering the different update frequencies of data deployment and service offloading,double-timescale reinforcement learning is utilized in the framework.In the small-scale strategy,the frequent concurrency of services and the difference in service time lead to the fuzzy relationship between reward and action.To solve the fuzzy reward problem,a reward mapping-based reinforcement learning(RMRL)algorithm is proposed,which enables the agent to learn the relationship between reward and action more clearly.The large time scale strategy adopts the improved Monte Carlo tree search(MCTS)algorithm to improve the learning speed.The simulation results show that the strategy is superior to popular reinforcement learning algorithms such as double Q-learning(DDQN)and dueling Q-learning(dueling-DQN)in learning speed,and the reward is also increased by 14%.

Core competencies and perceived training needs of nurses in the background of Internet plus nursing service:a qualitative descriptive study

Background:The Internet plus nursing service program is being piloted in China,which has become a new home nursing service model led by nurses.To enable safe and effective homecare service delivery,nurses working in the program need a high level of competency.However,the content of these core competencies and the training needs of nurses for Internet plus nursing services are still unknown.Aim:To describe nurses’perceptions of core competencies and training needs to work in the Internet plus nursing service program,thereby providing a reference for the development of training programs.Methods:A qualitative descriptive study using semi-structured interviews was conducted on 15 nurses with experience of working in the Internet plus nursing service program.Interviews were audio-recorded and transcribed verbatim,and the data were analyzed using thematic analysis.Results:Core competencies involved comprehensive assessment competence,direct care practice competence,health education and consulting competence,risk estimation and response competence,and communication competence.Training needs involved complex operational items,knowledge of chronic disease management,professional communication,risk identification and response,nursing standards,norms,and procedures,and utilization of information technology.Conclusions:The training system may be developed based on nurses’core competencies and their training needs to promote professional development of the Internet plus nursing service.

Analysis of the Current Situation of“Internet Plus Nursing Service”

In the era of“Internet Plus,”technologies like big data,the Internet of Things,and cloud computing have revitalized nursing services in China,leading to the emergence of the“Internet Plus Nursing Services”model.This model facilitates on-site nursing care for discharged patients and special groups with mobility challenges,further advancing the construction of a Healthy China and enabling more people to access high-quality and continuous nursing services.Governments at all levels should actively improve the systems related to“Internet Plus Nursing Services”and simplify the appointment and operation processes.It is also essential to standardize the medical waste disposal process to ensure the quality of on-site nursing services,protect the legitimate rights and interests of both caregivers and patients and safeguard patient privacy and security.Additionally,building a robust“Internet Plus”platform to promote“online appointment of nurses”services,integrate nursing resources,and foster the healthy development of“Internet Plus Nursing Services”is crucial.

基于WebService的Internet GIS集成与应用

InternetGIS是GIS发展的重要方向,InternetGIS要想真正达到实用化,必须解决网络环境下多源异构空间数据集成、网络环境下的空间元数据服务等关键技术。WebService是分布式计算领域出现的最新成果,它是实现异构系统互操作的理想计算模型。本文研究了基于WebService的InternetGIS软件的体系结构,网络环境下多源异构空间数据的互操作实现,基于WebService的空间元数据服务,提出了一个基于WebService的InternetGIS应用系统集成方案,以期为InternetGIS应用集成提供一个新的思路,并以南京“数字房产”项目为例介绍了其应用。

Effect of Internet+continuous midwifery service model on psychological mood and pregnancy outcomes for women with highrisk pregnancies

BACKGROUND There are many drawbacks to the traditional midwifery service management model,which can no longer meet the needs of the new era.The Internet+continuous midwifery service management model extends maternal management from prenatal to postpartum,in-hospital to out-of-hospital,and offline to online,thereby improving maternal and infant outcomes.Applying the Internet+continuous midwifery service management model to manage women with highrisk pregnancies(HRP)can improve their psycho-emotional opinion and,in turn,minimize the risk of adverse maternal and/or fetal outcomes.AIM To explore the effectiveness of a midwife-led Internet+continuous midwifery service model for women with HRP.METHODS We retrospectively analyzed the clinical data of 439 women with HRP who underwent prenatal examination and delivered at Shanghai Sixth People's Hospital(affiliated to the Shanghai Jiao Tong University School of Medicine)from April to December 2022.Among them,239 pregnant women underwent routine obstetric management,and 200 pregnant women underwent Internet+continuous midwifery service mode management.We used the State-Trait Anxiety Inventory,Edinburgh Postnatal Depression Scale,and analysis of delivery outcomes to compare psychological mood and the incidence of adverse delivery outcomes between the two groups.RESULTS The data showed that in early pregnancy,the anxiety and depression levels of the two groups were similar;the levels gradually decreased as pregnancy progressed,and the decrease in the continuous group was more significant[31.00(29.00,34.00)vs 34.00(32.00,37.00),8.00(6.00,9.00)vs 12.00(10.00,13.00),P<0.05].The maternal self-efficacy level and strategy for weight gain management were better in the continuous group than in the traditional group,and the effective rate of midwifery service intervention in the continuous group was significantly higher than in the control group[267.50(242.25,284.75)vs 256.00(233.00,278.00),74.00(69.00,78.00)vs 71.00(63.00,78.00),P<0.05].The incidence of adverse delivery outcomes in pregnant women and newborns and fear of maternal childbirth were lower in the continuous group than in the traditional group,and nursing satisfaction was higher[10.50%vs 18.83%,8.50%vs 15.90%,24.00%vs 42.68%,89.50%vs 76.15%,P<0.05].CONCLUSION The Internet+continuous midwifery service model promotes innovation through integration and is of great significance for improving and promoting maternal and child health in HRP.

利用IDC在Internet上发布数据库信息

结合校园网流量费查询系统的开发 ,介绍了利用IDC技术在Internet上发布数据库信息的方法 ,对其工作原理、ODBC数据源指定、用户身份认证、IDC脚本文件和HTML模板文件的结构与设计等作了较详细的阐述 ,并分析了这种技术的适用范围。

Strategic Thinking of the Internet of Things and M2M Services

Editor＇s Desk：The Internet of Things is an important part of the emerging high-tech industry and has been recognized as one of the important technologies for addressing global financial crisis and revitalizing the economy. Therefore, at the beginning of the new year, we are honored to have invited Mr. Samuel Qi （Qi Qingzhong）, a famous Chinese communication technology expert and GM of Shanghai Symphony Telecommunications Co., Ltd., to give his views on the development strategy of the Internet of Things and Machine to Machine （M2M） Communications.

Length matters:Scalable fast encrypted internet traffic service classification based on multiple protocol data unit length sequence with composite deep learning

As an essential function of encrypted Internet traffic analysis,encrypted traffic service classification can support both coarse-grained network service traffic management and security supervision.However,the traditional plaintext-based Deep Packet Inspection(DPI)method cannot be applied to such a classification.Moreover,machine learning-based existing methods encounter two problems during feature selection:complex feature overcost processing and Transport Layer Security(TLS)version discrepancy.In this paper,we consider differences between encryption network protocol stacks and propose a composite deep learning-based method in multiprotocol environments using a sliding multiple Protocol Data Unit(multiPDU)length sequence as features by fully utilizing the Markov property in a multiPDU length sequence and maintaining suitability with a TLS-1.3 environment.Control experiments show that both Length-Sensitive(LS)composite deep learning model using a capsule neural network and LS-long short time memory achieve satisfactory effectiveness in F1-score and performance.Owing to faster feature extraction,our method is suitable for actual network environments and superior to state-of-the-art methods.

SERVICE COMMUNITY CONSTRUCTION METHOD OF INTERNET OF THINGS BASED ON SEMANTIC SIMILARITY

Internet of Things (IoT) as an important and ubiquitous service paradigm is one of the most important issues in IoT applications to provide terminal users with effective and efficient services based on service community. This paper presents a semantic-based similarity algorithm to build the IoT service community. Firstly, the algorithm reflects that the nodes of IoT contain a wealth of semantic information and makes them to build into the concept tree. Then tap the similarity of the semantic information based on the concept tree. Finally, we achieve the optimization of the service community through greedy algorithm and control the size of the service community by adjusting the threshold. Simulation results show the effectiveness and feasibility of this algorithm.

A framework for Internet service evolution based on active object

The wide use of Internet Service in distributed computing and e-business has made the evolution of Internet Service to be one of the most prevalent research fields in software development domain. Traditional methods for software development cannot adapt to the challenge of Internet Service oriented software development. In this paper, we propose a new paradigm for the evolution of Internet Service with active objects from the characteristics of Intemet Service and principles of active objects. The paradigm uses an automatic monitoring mechanism of active object to detect and process evolution requirement in system based on Internet Service.

用Web Services实现LAN和Internet数据库访问的一致性

Web Services是近年来出现的最重要的技术之一。它可以解决跨平台、分布式计算等问题,代表了下一代网络计算和企业应用的必然趋势。但是Web Services并不是只能解决“大”问题,本文中将利用其来实现通过LAN和Internet两种方式访问数据库的统一操作登录界面。

Performance Analysis of Wavelength Division Multiplexing Asynchronous Internet Router Employing Space Priority Mechanism under Self-Similar Traffic Input—Multi-Server Queueing System with Markovian Input and Erlang-k Services

In this paper, we analyze the queueing behaviour of wavelength division multiplexing (WDM) Internet router employing partial buffer sharing (PBS) mechanism with self-similar traffic input. In view of WDM technology in networking, each output port of the router is modelled as multi-server queueing system. To guarantee the quality of service (QoS) in Broadband integrated services digital network (B-ISDN), PBS mechanism is a promising one. As Markov modulated Poisson process (MMPP) emulates self-similar Internet traffic, we can use MMPP as input process of queueing system to investigate queueing behaviour of the router. In general, as network traffic is asynchronous (unslotted) and of variable packet lengths, service times (packet lengths) are assumed to follow Erlang-k distribution. Since, the said distribution is relatively general compared to deterministic and exponential. Hence, specific output port of the router is modelled as MMPP/Ek/s/C queueing system. The long-term performance measures namely high priority and low priority packet loss probabilities and the short-term performance measures namely mean lengths of critical and non-critical periods against the system parameters and traffic parameters are computed by means of matrix-geometric methods and approximate Markovian model. This kind of analysis is useful in dimensioning the router under self-similar traffic input employing PBS mechanism to provide differentiated services (DiffServ) and QoS guarantee.

Research on the influence factors of China＇s pension service industry development under the background of“Internet ＋”

With Internet as the carrier, through research and analysis on the influencing factors of the elderly life in China, online interactive providing intelligence pension services for the elderly, pension services is industry development process of prime minister Li Keqiang ＂Internet ＋＂ action plan put forward by the beneficial exploration.So, in the new situation research on the influence factors of China＇ s pension service industry development under the background of＂Internet ＋＂ it becomes very important to explore research.

Automated Service Search Model for the Social Internet of Things

The social internet of things(SIoT)is one of the emerging paradigms that was proposed to solve the problems of network service discovery,navigability,and service composition.The SIoT aims to socialize the IoT devices and shape the interconnection between them into social interaction just like human beings.In IoT,an object can offer multiple services and different objects can offer the same services with different parameters and interest factors.The proliferation of offered services led to difficulties during service customization and service filtering.This problem is known as service explosion.The selection of suitable service that fits the requirements of applications and objects is a challenging task.To address these issues,we propose an efficient automated query-based service search model based on the local network navigability concept for the SIoT.In the proposed model,objects can use information from their friends or friends of their friends while searching for the desired services,rather than exploring a global network.We employ a centrality metric that computes the degree of importance for each object in the social IoT that helps in selecting neighboring objects with high centrality scores.The distributed nature of our navigation model results in high scalability and short navigation times.We verified the efficacy of our model on a real-world SIoT-related dataset.The experimental results confirm the validity of our model in terms of scalability,navigability,and the desired objects that provide services are determined quickly via the shortest path,which in return improves the service search process in the SIoT.

基于Internet的分布式计算Web Service体系构架

由于Internet的迅速发展,有多种基于Internet的分布式计算模型提出,亦产生过诸多争论.本文论述了一个新的分布式计算体系构架———WebService.文中论述了如何基于WebService体系构架建立一个基本的分布式系统.该系统所包括的基本组成部分及各自功能,系统的运行过程,其中体现的核心思想及其优越性.同时,对与WebService相关的核心技术标准的现状和未来发展也作了讨论.

A Machine Learning-Based Distributed Denial of Service Detection Approach for Early Warning in Internet Exchange Points

The Internet service provider(ISP)is the heart of any country’s Internet infrastructure and plays an important role in connecting to theWorld WideWeb.Internet exchange point(IXP)allows the interconnection of two or more separate network infrastructures.All Internet traffic entering a country should pass through its IXP.Thus,it is an ideal location for performing malicious traffic analysis.Distributed denial of service(DDoS)attacks are becoming a more serious daily threat.Malicious actors in DDoS attacks control numerous infected machines known as botnets.Botnets are used to send numerous fake requests to overwhelm the resources of victims and make them unavailable for some periods.To date,such attacks present a major devastating security threat on the Internet.This paper proposes an effective and efficient machine learning(ML)-based DDoS detection approach for the early warning and protection of the Saudi Arabia Internet exchange point(SAIXP)platform.The effectiveness and efficiency of the proposed approach are verified by selecting an accurate ML method with a small number of input features.A chi-square method is used for feature selection because it is easier to compute than other methods,and it does not require any assumption about feature distribution values.Several ML methods are assessed using holdout and 10-fold tests on a public large-size dataset.The experiments showed that the performance of the decision tree(DT)classifier achieved a high accuracy result(99.98%)with a small number of features(10 features).The experimental results confirmthe applicability of using DT and chi-square for DDoS detection and early warning in SAIXP.

Discussion of Mobile Internet Service Development

With the enforcement of 3G network capabilities in the future, the mobile Internet will greatly change the service modes of traditional Internet, rather than simply combine the Internet with mobile networks. The development of new technologies such as Mashup and mobile widgets will enable better service for users and new business models, bringing benefits for the industrial chain members including operators, vendors, Content Providers/Service Providers (CPs/SPs) and Internet application providers. The mobile Internet and the traditional Internet not only compete for contents and services, but also cooperate with each other; and the mobile Internet services should focus on mobile applications to avoid the homogenization with traditional Internet service.

Pervasive Services in New-generation Internet:Mechanisms and Key Technologies

The original infrastructure of the Internet can no longer meet personalized and diversified demands of current increasing network subscribers. It has exposed many defects and shortcomings. For examples, the mechanism of using ports to distinguish services is inflexible and dangerous with the emergence of various services; the current Internet architecture does not make use of the close relationship between network resources and services, but simultaneously maintains two processing systems for the resources and services respectively, wasting both subscribers’ time and network resources; the Internet class of services granularity is not fine enough, failing to meet personalized and diversified user demands. In order to solve these problems, this paper discusses the mechanisms and key technologies for pervasive services in the new-generation Internet. The paper focuses on the definition, classification and identifier design of personalized and diversified user services. The service identifier design fulfills the unified identifier and processing of various network services, discovers the close relationship between services and resources, and can offer personalized and diversified services according to users’ demands.

New Blue Ocean of Wideband Wireless Mobile Internet: Modern Service

Wideband Wireless Mobile Internet (WWMI) has become one of the most important technologies for Modern Service. The Modern Service information communication multi-access network can easily realize the new operation modes formed by various Modern Service support systems. We think that under the new operation modes, the charges on calling and information will become more negligible, while the charge on services provided by the direct service support of various Modern Service platforms will turn into a major revenue source. It is suggested that the operators build an operation service support platform with common services to cooperate with thousands of information websites, help clients to transform information into profit and carry out operations and services.