Showing papers on "Shared resource published in 2022"

A DRL-Based Service Offloading Approach Using DAG for Edge Computational Orchestration

Abstract: Edge infrastructure and Industry 4.0 required services are offered by edge-servers (ESs) with different computation capabilities to run social application's workload based on a leased-price method. The usage of Social Internet of Things (SIoT) applications increases day-to-day, which makes social platforms very popular and simultaneously requires an effective computation system to achieve high service reliability. In this regard, offloading high required computational social service requests (SRs) in a time slot based on directed acyclic graph (DAG) is an NP-complete problem. Most state-of-art methods concentrate on the energy preservation of networks but neglect the resource sharing cost and dynamic subservice execution time (SET) during the computation and resource sharing. This article proposes a two-step deep reinforcement learning (DRL)-based service offloading (DSO) approach to diminish edge server costs through a DRL influenced resource and SET analysis (RSA) model. In the first level, the service and edge server cost is considered during service offloading. In the second level, the R-retaliation method evaluates resource factors to optimize resource sharing and SET fluctuations. The simulation results show that the proposed DSO approach achieves low execution costs by streamlining dynamic service completion and transmission time, server cost, and deadline violation rate attributes. Compared to the state-of-art approaches, our proposed method has achieved high resource usage with low energy consumption.

Sharing data to better understand one of the world’s most significant shared experiences: data resource profile of the longitudinal COVID-19 psychological research consortium (C19PRC) study

Abstract: Abstract This paper serves to alert IJPDS readers to the availability of a major new longitudinal survey data resource, the COVID-19 Psychological Research Consortium (C19PRC) Study, which is being released for secondary use via the Open Science Framework. The C19PRC Study is a rich and detailed dataset that provides a convenient and valuable foundation from which to study the social, political, and health status of European adults during an unprecedented time of change as a direct result of the COVID-19 pandemic and Brexit. Here, we provide an overview of the C19PRC Study design, with the purpose of stimulating interest about the study among social scientists and maximising use of this resource.

BEAT: Blockchain-Enabled Accountable and Transparent Network Sharing in 6G

Abstract: Infrastructure sharing is a widely discussed and implemented approach and is successfully adopted in telecommunications networks today. In practice, it is implemented through prior negotiated service level agreements (SLAs) between the parties involved. However, it is recognized that these agreements are difficult to negotiate, monitor, and enforce. For future 6G networks, resource and infrastructure sharing is expected to play an even greater role. It will be a crucial technique for reducing over-all infrastructure costs and increasing operational efficiencies for operators. More efficient SLA mechanisms are thus crucial to the success of future networks. In this work, we present BEAT, an automated, transparent, and accountable end-to-end architecture for network sharing based on blockchain and smart contracts. This work focuses on a particular type of blockchain, permissioned distributed ledger, due to its permissioned nature allowing for industry-compliant SLAs with stringent governance. Our architecture can be implemented with minimal hardware changes and with minimal overheads.

Efficient, Dynamic Multi-Task Execution on FPGA-Based Computing Systems

Abstract: With growing Field Programmable Gate Array (FPGA) device sizes and their integration in environments enabling sharing of computing resources such as cloud and edge computing, there is a requirement to share the FPGA area between multiple tasks. The resource sharing typically involves partitioning the FPGA space into fix-sized slots. This results in suboptimal resource utilisation and relatively poor performance, particularly as the number of tasks increase. Using OpenCL’s exploration capabilities, we employ clever clustering and custom, task-specific partitioning and mapping to create a novel, area sharing methodology where task resource requirements are more effectively managed. Using models with varying resource/throughput profiles, we select the most appropriate distribution based on the runtime, workload needs to enhance temporal compute density. The approach is enabled in the system stack by a corresponding task-based virtualisation model. Using 11 high performance tasks from graph analysis, linear algebra and media streaming, we demonstrate an average $2.8\times$ 2 . 8 × higher system throughput at $2.3\times$ 2 . 3 × better energy efficiency over existing approaches.

A Method of Digital English Teaching Resource Sharing Based on Artificial Intelligence

Abstract: In order to better improve the quality of English teaching, this paper studies the sharing method of English digital teaching resources combined with modern digital technology. Through the collection and management of English digital teaching resources, it constructs the evaluation index system of teaching resources, so as to comprehensively and objectively evaluate the digital teaching resources and promote the construction and development of digital teaching resource and to effectively promote and improve the teaching effect, and realise the research requirements of effective sharing of massive teaching resources in complex environment.

Research on Online Education Curriculum Resources Sharing Based on 5G and Internet of Things

Abstract: Information technology has brought great changes to China’s education. 5G technology provides a better guarantee for the sharing of curriculum resources, facing the extreme shortage of educational resources in China. The contradiction between limited educational resources and unlimited development needs of higher education has become increasingly prominent. How to effectively realize resource sharing among universities has become a problem that must be considered in the talent development of universities. In order to solve this problem, universities must improve the utilization rate of resources, maximize resource sharing, and establish a more perfect resource sharing mechanism under the background of 5G and Internet of Things. This paper analyzes the current situation of research at home and abroad, the current situation of resources development, and the application of online courses under the background of Internet of Things, thus constructing an overall framework of curriculum resource sharing mode. According to effective experiments, the offline curriculum education resource sharing and traditional resource sharing schemes in the background of 5G and Internet are compared, and the necessity and importance of applying 5G Internet of Things are verified.

A Potential Game Approach for Decentralized Resource Coordination in Coexisting IWNs

Abstract: To meet the requirements of various emerging manufacturing applications, multiple Industrial Wireless Networks (IWNs) are employed to operate in the same region. However, the limited communication resources inevitably incur interference in the time and frequency domains, which is known as the coexistence problem. Existing centralized mechanisms suffer from a low computational efficiency in a large-scale network scenario, and the globally shared information cannot be fully obtained in practice. To this end, we first design an incomplete information sharing protocol to clarify the decentralized coordination among coexisting IWNs. We then formulate the coexistence problem as a non-cooperative game, which is proven to be a potential game. In addition, considering the deterministic deadlines of data transmissions in industrial applications, we propose a Deadline-aware Incomplete-Information-based Decentralized Resource Coordination (DIIDRC) algorithm. We also mathematically analyze that the DIIDRC algorithm converges to a collision-free optimal schedule in a resource-sufficient scenario or a nearly-optimal schedule in a resource-insufficient scenario. We conduct extensive simulations to verify the effectiveness of the DIIDRC algorithm. Evaluation results show that the DIIDRC algorithm has obvious superiorities over existing works in terms of the convergence rate and schedulable ratio.

Fairness-Aware VNF Sharing and Rate Coordination for High Efficient Service Scheduling

Abstract: Network service provisioning becomes flexible and programmable with the help of Network Function Virfitualization (NFV), since NFV abstracts various service functions into software components called Virtual Network Function (VNF) and VNFs can be flexibly and quickly composed to form new services. It is commonly known that sharing the same VNF among different services can improve the resource utilization. However, we should be aware that such sharing also leads to serious resource preemption. In addition, VNF sharing aggravates the generation of the performance bottleneck, which then causes the rate mismatch problem between the upstream and downstream VNFs belonging to the same service chain. In this article, we propose a dynamic and flexible algorithm to jointly address the VNF sharing resource allocation and the rate coordination between the upstream and downstream VNFs. Specifically, 1) the VNFs are shared among different service chains with a fairness factor considered for the purpose of reducing the resource preemption probability and improving the resource utilization; 2) the backpressure indicator of each VNF is defined to judge its pressure condition, based on which we can dynamically adjust the processing rates between it and its downstream or upstream VNFs by maximizing the idle resource utilization. The experimental results indicate that the proposed algorithm outperforms the other methods in terms of the average delay, the flow completion time, the throughput and the backlog, etc. Meanwhile, the proposed algorithm achieves more stable performance than the other methods.

Resource-Efficient DAG Blockchain with Sharding for 6G Networks

Abstract: The sixth-generation (6G) system is widely envisioned as a global network consisting of pervasive devices that interact with each other. Besides exchanging information, these peer entities also share heterogeneous and distributed edge resources. Blockchain is a promising technology to secure resource sharing in a peer-to-peer way. However, constrained by limited transaction throughput, existing blockchain systems (e.g., Bitcoin) cannot process numerous resource transactions concurrently produced in large-scale 6G networks. To cope with this issue, we propose a blockchain scaling scheme that combines Directed Acyclic Graph (DAG) with sharding. Our sharding method divides blockchain transactions into multiple mutually disjoint subsets maintained by different committees, which enables high-volume resource transactions to be processed and recorded concurrently. Additionally, all committees maintain a global DAG of blocks to resolve the security degradation raised by the sharding method. Moreover, we put forth a computation efficient consensus algorithm by leveraging miners' computing power to improve resource utilization efficiency. Numerical results show that the proposed scheme achieves good performance in resource utilization efficiency.

Exploring Resource-Sharing Behaviors for Finding Relevant Health Resources: Analysis of an Online Ovarian Cancer Community

Abstract: Background Online health communities (OHCs) provide patients and survivors of ovarian cancer (OvCa) and their caregivers with help beyond traditional support channels, such as health care providers and clinicians. OvCa OHCs promote connections and exchanges of information among users with similar experiences. Users often exchange information, which leads to the sharing of resources in the form of web links. Although OHCs are important platforms for health management, concerns exist regarding the quality and relevance of shared resources. Previous studies have examined different aspects of resource-sharing behaviors, such as the purpose of sharing, the type of shared resources, and peer user reactions to shared resources in OHCs to evaluate resource exchange scenarios. However, there is a paucity of research examining whether resource-sharing behaviors can ultimately determine the relevance of shared resources. Objective This study aimed to examine the association between OHC resource-sharing behaviors and the relevance of shared resources. We analyzed three aspects of resource-sharing behaviors: types of shared resources, purposes of sharing resources, and OHC users’ reactions to shared resources. Methods Using a retrospective design, data were extracted from the National Ovarian Cancer Coalition discussion forum. The relevance of a resource was classified into three levels: relevant, partially relevant, and not relevant. Resource-sharing behaviors were identified through manual content analysis. A significance test was performed to determine the association between resource relevance and resource-sharing behaviors. Results Approximately 48.3% (85/176) of the shared resources were identified as relevant, 29.5% (52/176) as partially relevant, and 22.2% (39/176) as irrelevant. The study established a significant association between the types of shared resources (χ218=33.2; P<.001) and resource relevance (through chi-square tests of independence). Among the types of shared resources, health consumer materials such as health news (P<.001) and health organizations (P=.02) exhibited significantly more relevant resources. Patient educational materials (P<.001) and patient-generated resources (P=.01) were more significantly associated with partially relevant and irrelevant resources, respectively. Expert health materials, including academic literature, were only shared a few times but had significantly (P<.001) more relevant resources. A significant association (χ210=22.9; P<.001) was also established between the purpose of resource sharing and overall resource relevance. Resources shared with the purpose of providing additional readings (P=.01) and pointing to resources (P=.03) had significantly more relevant resources, whereas subjects for discussion and staying connected did not include any relevant shared resources. Conclusions The associations found between resource-sharing behaviors and the relevance of these resources can help in collecting relevant resources, along with the corresponding information needs from OvCa OHCs, on a large scale through automation. The results from this study can be leveraged to prioritize the resources required by survivors of OvCa and their caregivers, as well as to automate the search for relevant shared resources in OvCa OHCs.

Efficient, Dynamic Multi-Task Execution on FPGA-Based Computing Systems

Abstract: With growing Field Programmable Gate Array (FPGA) device sizes and their integration in environments enabling sharing of computing resources such as cloud and edge computing, there is a requirement to share the FPGA area between multiple tasks. The resource sharing typically involves partitioning the FPGA space into fix-sized slots. This results in suboptimal resource utilisation and relatively poor performance, particularly as the number of tasks increase. Using OpenCL's exploration capabilities, we employ clever clustering and custom, task-specific partitioning and mapping to create a novel, area sharing methodology where task resource requirements are more effectively managed. Using models with varying resource/throughput profiles, we select the most appropriate distribution based on the runtime, workload needs to enhance temporal compute density. The approach is enabled in the system stack by a corresponding task-based virtualisation model. Using 11 high performance tasks from graph analysis, linear algebra and media streaming, we demonstrate an average 2.8× higher system throughput at 2.3× better energy efficiency over existing approaches.

Research on the Intelligent Cloud Animal Husbandry Platform

Abstract: Aiming at the problem that the traditional talent training mode is difficult to cultivate the intelligent animal husbandry compound talents needed by the implementation of the rural revitalization strategy, a cloud animal husbandry platform is designed to cultivate “Understand Agriculture, devote to Rural Community and Be Sincere to Farmers” compound talents. The platform adopts the two-wing multilevel architecture design of the concept of the cloud side, which is composed of three parts: the data center platform, resource sharing platform, and business cloud service platform. The data center platform is responsible for the collection, processing, integration, and asset management of the four-dimensional real data and provides computing, storage, and data asset services for the cloud livestock platform. The resource sharing platform provides sharing services from resources and development kits to carriers. Livestock cloud service platform is to carry out the integration of industry, education, and science and education, the design and implementation of cloud teaching, cloud scientific research, and cloud breeding business cloud services. Through its practical application in many universities and enterprises, the platform is verified to be safe, effective, and reliable in teaching, scientific research, and social services and has both operational and promotional value.

Interagency collaboration within the city emergency management network: a case study of Super Ministry Reform in China

Abstract: Emergencies continue to become ever more complex; responding to them, therefore, often is beyond the capabilities and capacities of any single public agency. Hence, collaboration among these actors is necessary to prepare for, respond to, and recover from such events. This seldom occurs in an effective or efficient manner, however. Drawing on resource dependence theory and the concept of social capital, this paper reveals that different types of collaborative relationships exist within the collaborative network. Super Ministry Reform of Emergency Management in China serves as a case in point. By evaluating network efficiency and classifying the collaborative relationships of involved government agencies, four types are identified: resource-redundant; resource-complementary; resource-dependent; and resource-isolated. The different influences of collaborative relationships explain why the reform is not that effective, although it has led to the merger of several core departments in the emergency management network. The findings are a reminder to consider network structure and collaboration types when engaging in institutional design.وما زال تعقيد حالات الطوارئ في ازدياد وبالتالي فإن الاستجابة لها غالبًا ما تتجاوز قدرات وإمكانيات أي وكالة عامة واحدة. ومن ثم، فإن التعاون بين الوكالات العامة هو الإعداد لحالات الطوارئ والاستجابة لها والتعافي منها. غير أن التعاون بين الوكالات العامة نادرًا ما يتم بطريقة فعالة أثناء حالات الطوارئ. مع مناقشة نظرية الاعتماد على الموارد وراس المال الاجتماعي. نعتقد أن هناك أنواع مختلفة من العلاقات التعاونية في الشبكة التعاونية، بالاعتماد على هيكل الشبكة. تأخذ هذه الورقة إصلاح الوزارة العليا لإدارة الطوارئ في الصين كدراسة حالة. نجد أربعة أنواع مختلفة: الموارد الزائدة وتكامل الموارد والاعتماد على الموارد وعزل الموارد وذلك من خلال تقييم كفاءة الشبكة وتصنيف العلاقات التعاونية للوكالات الحكومية ذات الصلة. وتفسر التأثيرات المختلفة للعلاقات التعاونية بدقة سبب عدم فعالية الإصلاح وذلك بالرغم من دمج عدة إدارات أساسية في شبكة إدارة الطوارئ. وتذكرنا هذه النتائج بالنظر في هيكل الشبكة وأنواع التعاون عند تصميم المؤسسات. كلمات مفتاحية :ادارة الطوارئ , التعاون بين الوكالات , تحليل الشبكات الاجتماعية.紧急情况变得越来越复杂，因此仅凭单一公共机构的能力和实力，往往不足以应对紧急状况。公共机构之间合作，是为了随时准备应对紧急情况，并在状况出现后即时恢复。然而，在紧急情况出现时，公共机构之间的合作很少奏效或者有效率。通过对资源依赖理论和社会资本的讨论，我们认为由于网络结构的不同，协作网络中存在不同类型的协作关系。本文以中国应急管理部改革为例。在对网络效率进行评估，对政府机构的协作关系进行分类后，我们得到了四种不同的协作类型：资源冗余型、资源互补型、资源依赖型和资源孤立型。不同协作关系的影响不同，因此即使合并了应急管理网络中的几个核心部门，改革却不够有效。因此，在建立制度时，要考虑到网络结构和协作类型。 关键词：应急治理、机构间协作、社会网络分析.

Ideological and Political Teaching Resource Sharing Method Based on Edge Computing

Abstract: In the process of ideological and political teaching resource sharing, the sharing time is long due to the interference of redundant data. Therefore, an ideological and political teaching resource sharing method based on edge computing is proposed. Based on the sharing model of ideological and political teaching resources of edge computing, the information entropy suppression method is used to eliminate the redundant data in the ideological and political teaching resources, calculate the sinking of the edge node of the resource after removing the redundancy, assign the task to the edge node, and finally build a location index for the ideological and political teaching resources to realize the sharing of ideological and political teaching resources. The results show that when using the research method to share ideological and political teaching resources, the completion time, average waiting delay, and resource download time of resource sharing are shorter.

The Influence of System Dynamics Resource Sharing on Collaborative Manufacturing Efficiency—Based on the Multiagent System and System Dynamics Method

Abstract: To improve the problems of inconvenient communication in the manufacturing industry, the ineffective use of resources, and the inability to efficiently complete manufacturing tasks, resource sharing has become an important model to promote the transformation and upgrading of the manufacturing industry. We used multiagent modeling to construct a resource-sharing model and take Baosteel as the micro background and the manufacturing industry as the macro background. Under this model, we discovered the effect of resource sharing on the efficiency of intelligent manufacturing under network collaboration through system dynamics research. We built and simulated a dynamic model of system dynamics that couples the two backgrounds and have given policy suggestions according to the simulation result.

Trust Me, I'm Lying: Enhancing Machine-to-Machine Trust

Abstract: Incorporating smart technology into critical infrastructure (CI) promises substantial efficiency improvements as networks of machines communicate and make rapid decisions autonomously. Yet the promise of greater efficiency that such cyber-physical systems (CPS) bring is tempered by increased fragility unless machine-to-machine (M2M) trust is enhanced, particularly in Internet-of-Things (IoT) networks. This work makes two contributions toward improving M2M trust. First, it proposes a multifaceted trust framework comprised of identity verification, experience, context, and recommendation scores to enable high-integrity M2M interactions. Second, this trust framework is implemented via an IoT-friendly distributed ledger on a physical testbed, where it is shown to identify and mitigate errors due to a compromised system component. This implementation mirrors real-world IoT systems in which resource- constrained endpoint devices pose trust score computation chal-lenges and the number of devices raises scalability obstacles for information sharing among nodes.

Network Education Resource Information Sharing System Based on Data Mining

Abstract: To enter a new stage of development of education informatization, network education has become a global trend of education training, the development of lifelong education, and resource sharing platform for higher vocational colleges to some extent, with network technology and multimedia technology as the core of the rapid development of modern information technology. The sharing of network education resource sharing system and the application in the whole advancement provide the conditions, it promotes the construction and development of higher vocational education resource system. This study examines the problems that exist in the construction of higher vocational college education resources, such as unreasonable management of education resources, unclear goals of higher vocational colleges, and unclear school-enterprise cooperation, based on the research status and achievements of higher vocational college education resources at home and abroad. On the basis of combing and analyzing the related concepts, theoretical basis, and construction principles of higher vocational education resources, the paper designs the network sharing system of higher vocational education resources in detail from its design objectives, design ideas, user needs, overall framework system, hierarchical structure, and functional modules. The core part is the realization of system function modules, including the resource management function module, system management function module, and user management function module. At present, domestic scholars have carried out a lot of research on the construction of basic education network resources. Although the research focuses on resource allocation, coconstruction and sharing mechanisms, and the current state of building and development methods, it also serves as a guide for the development of basic education network resources. However, most of these research results analyze problems from the qualitative perspective, and most of the research results are speculative research at the macro level, lacking practicality. With the rapid development of network education, the construction of network resource libraries is developing in the direction of intelligence and individuation to meet the different learning needs of learners. Based on the analysis of the problems encountered by learners in using the resource library for learning, this paper puts forward the application of data mining technology (DM) to guide the construction of the resource library and discusses how to improve the organizational structure of the resource library, improve the utilization rate of the resource library, and adapt to personalized learning. At present, the system is still in the system testing and experience stage, through the continuous testing of relevant functional modules, further improves the function of the sharing system, and constantly increases the scalability of the system function, in order to establish a perfect, comprehensive, and nationwide higher vocational education resource network sharing system.

The Construction and Analysis of the LTE Network Model with Joint Service of Traffic of LTE and NB-IoT Devices

Abstract: The active implementation of the Internet of Things (IoT) concept has led to an impressive increase in both the number of connected devices and data traffic during past decade. The ever-increasing data traffic, mass connectivity, and network densification introduced by the IoT concept is driving the need for a new resource sharing strategy between traditional cellular mobile devices and IoT devices. The need for resource allocation between traditional cellular subscribers and IoT devices was recently recognized by 3GPP with the ratification of the special “In-band” deployment mode in LTE Rel. 13, which allows to share radio resources between LTE and NB-IoT devices. However, 3GPP does not provide clear or specific guidance on resource allocation. The purpose of this work is to develop and analyze a model for evaluating the efficiency of resource sharing for an LTE network serving jointly traffic generating by LTE and NB-IoT devices. In the article the general principles of the Internet of Things concepts are analyzed. The mobile communication technologies recommended by 3GPP for the implementation of the concepts of the Internet of things are studied. The mathematical model of the LTE network with NB-IoT functions enabled is constructed. The algorithm for calculating quality indicators of the model is evolved.

A Global Sharing Mechanism of Resources: Modeling a Crucial Step in the Fight against Pandemics

Abstract: To face crises like the COVID-19 pandemic, resources such as personal protection equipment (PPE) are needed to reduce the infection rate and protect those in close contact with patients. The increasing demand for those products can, together with pandemic-related disruptions in the global supply chain, induce major local resource scarcities. During the first phase of the COVID-19 pandemic, we witnessed a reflex of ‘our people first’ in many regions. In this paper, however, we show that a cooperative sharing mechanism can substantially improve the ability to face epidemics. We present a stylized model in which communities share their resources such that each can receive them whenever a local epidemic flares up. Our main finding is that cooperative sharing can prevent local resource exhaustion and reduce the total number of infected cases. Crucially, beneficial effects of sharing are found for a large range of possible community sizes and cooperation combinations, not only for small communities being helped by large communities. Furthermore, we show that the success of sharing resources heavily depends on having a sufficiently long delay between the onsets of epidemics in different communities. These results thus urge for the pairing of a global sharing mechanism with measures to slow down the spread of infections from one community to the other. Our work uses a stylized model to convey an important and clear message to a broad public, advocating that cooperative sharing strategies in international resource crises are the most beneficial strategy for all. It stresses essential underlying principles of and contributes to designing a resilient global supply chain mechanism able to deal with future pandemics by design, rather than being subjected to the coincidental and unequal distribution of opportunities per community that we see at present.

Blockchain-enabled cooperative computing strategy for resource sharing in fog networks

Abstract: Several heterogeneous network designs have been developed to fulfill user experience needs, driven by widely growing applications needing large data processing, such as Industry 4.0. Fog computing is one of them since it allows for the efficient integration and exploitation of ubiquitous computing resources. Willingness and service billing concerns become important in fog computing situations for computing resource sharing. The present fog systems, on the other hand, are vulnerable to malicious attacks. The integration of blockchain technology into the fog computing environment is characterized by successfully allowing consensus in an untrustworthy environment. However, creating public blockchains requires a lot of processing power, which can quickly deplete the computational resources of IoT-enabled Smart Machines (SM) in Industry 4.0. This study suggests partitioning the fog system into fog clusters (FC), with fog nodes (FN) in each cluster sharing the same access control list (ACL) that is protected by a public blockchain. Therefore, Blockchain-enabled Resource Sharing inside SM in Fog networks (B-RSSF), a novel architecture for computing resource sharing in fog networks is proposed. B-RSSF has specified physical architecture, design principles, and inner workings. To make full and effective use of ubiquitous computing resources, fog computing’s wireless features and blockchain technology are tightly integrated. In addition, an enhanced PoW consensus mechanism for reaching consensus in an untrustworthy fog environment has been discussed. Finally, the experimental results have been conducted to evaluate the performance of the proposed scheme over other existing schemes in a fog-based environment.

Cloud Application in the Construction of English Virtual Teaching Resources Based on Digital Three-Dimensional Technology

Abstract: In order to improve the sharing effect of English teaching resources, based on digital three-dimensional technology, this paper constructs a cloud application in English virtual teaching resource database system based on digital three-dimensional technology. Moreover, this paper uses signal recognition technology to digitally process English teaching resources and establish a dynamic and changeable three-tier indicator system. In addition, this paper collects and summarizes the state data generated in the teaching operation of various departments of teaching management in real time and conducts scientific analysis and processing on it according to the management objectives to obtain valuable data information. Finally, this paper digitally processes English teaching resources into system-recognizable text to realize platform resource sharing.