Designing Cisco Enterprise Networks test Dumps

500-490 test Format | Course Contents | Course Outline | test Syllabus | test Objectives

Objectives
After taking this course, you should be able to:
Design Enhanced Interior Gateway Routing Protocol (EIGRP) internal routing for the enterprise network
Design Open Shortest Path First (OSPF) internal routing for the enterprise network
Design Intermediate System to Intermediate System (IS-IS) internal routing for the enterprise network
Design a network based on customer requirements
Design Border Gateway Protocol (BGP) routing for the enterprise network
Describe the different types and uses of Multiprotocol BGP (MP-BGP) address families
Describe BGP load sharing
Design a BGP network based on customer requirements
Decide where the L2/L3 boundary will be in your Campus network and make design decisions
Describe Layer 2 design considerations for Enterprise Campus networks
Design a LAN network based on customer requirements
Describe Layer 3 design considerations in an Enterprise Campus network
Examine Cisco SD-Access fundamental concepts
Describe Cisco SD-Access Fabric Design
Design an Software-Defined Access (SD-Access) Campus Fabric based on customer requirements
Design service provider-managed VPNs
Design enterprise-managed VPNs
Design a resilient WAN
Design a resilient WAN network based on customer requirements
Examine the Cisco SD-WAN architecture
Describe Cisco SD-WAN deployment options
Design Cisco SD-WAN redundancy
Explain the basic principles of QoS
Design Quality of Service (QoS) for the WAN
Design QoS for enterprise network based on customer requirements
Explain the basic principles of multicast
Designing rendezvous point distribution solutions
Describe high-level considerations when doing IP addressing design
Create an IPv6 addressing plan
Plan an IPv6 deployment in an existing enterprise IPv4 network
Describe the challenges that you might encounter when transitioning to IPv6
Design an IPv6 addressing plan based on customer requirements
Describe Network APIs and protocols
Describe Yet Another Next Generation (YANG), Network Configuration Protocol (NETCONF), and Representational State Transfer Configuration Protocol (RESTCONF)
Prerequisites
Before taking this course, you should have earned CCNA certification or be familiar with:
Basic network fundamentals and building simple LANs
Basic IP addressing and subnets
Routing and switching fundamentals
Basic wireless networking concepts and terminology
Outline
Designing EIGRP Routing
Designing OSPF Routing
Designing IS-IS Routing
Designing BGP Routing and Redundancy
Understanding BGP Address Families
Designing the Enterprise Campus LAN
Designing the Layer 2 Campus
Designing the Layer 3 Campus
Discovering the Cisco SD-Access Architecture
Exploring Cisco SD-Access Fabric Design
Designing Service Provider-Managed VPNs
Designing Enterprise-Managed VPNs
Designing WAN Resiliency
Examining Cisco SD-WAN Architectures
Cisco SD-WAN Deployment Design Considerations
Designing Cisco SD-WAN Routing and High Availability
Understanding QoS
Designing LAN and WAN QoS
Exploring Multicast with Protocol-Independent Multicast-Sparse Mode
Designing Rendezvous Point Distribution Solutions
Designing an IPv4 Address Plan
Exploring IPv6
Deploying IPv6
Introducing Network APIs and Protocols
Exploring YANG, NETCONF, RESTCONF, and Model-Driven Telemetry
Lab outline
Designing Enterprise Connectivity
Designing an Enterprise Network with BGP Internet Connectivity
Designing an Enterprise Campus LAN
Designing Resilient Enterprise WAN
Designing QoS in an Enterprise Network
Designing an Enterprise IPv6 Network

Designing Cisco Enterprise Networks (ENSLD 500-490) is a 90-minute exam associated with the CCNP Enterprise Certification. This test certifies a candidate's knowledge of enterprise design including advanced addressing and routing solutions, advanced enterprise campus networks, WAN, security services, network services, and SDA. The course, Designing Cisco Enterprise Networks, helps candidates to prepare for this exam.
The following subjects are general guidelines for the content likely to be included on the exam. However, other related subjects may also appear on any specific delivery of the exam. To better reflect the contents of the test and for clarity purposes, the guidelines below may change at any time without notice.
25% 1.0 Advanced Addressing and Routing Solutions
1.1 Create structured addressing plans for IPv4 and IPv6
1.2 Create stable, secure, and scalable routing designs for IS-IS
1.3 Create stable, secure, and scalable routing designs for EIGRP
1.4 Create stable, secure, and scalable routing designs for OSPF
1.5 Create stable, secure, and scalable routing designs for BGP
1.5.a Address families
1.5.b Basic route filtering
1.5.c Attributes for path preference
1.5.d Route reflectors
1.5.e Load sharing
1.6 Determine IPv6 migration strategies
1.6.a Overlay (tunneling)
1.6.b Native (dual-stacking)
1.6.c Boundaries (IPv4/IPv6 translations)
25% 2.0 Advanced Enterprise Campus Networks
2.1 Design campus networks for high availability
2.1.a First Hop Redundancy Protocols
2.1.b Platform abstraction techniques
2.1.c Graceful restart
2.1.d BFD
2.2 Design campus Layer 2 infrastructures
2.2.a STP scalability
2.2.b Fast convergence
2.2.c Loop-free technologies
2.2.d PoE and WoL
2.3 Design multicampus Layer 3 infrastructures
2.3.a Convergence
2.3.b Load sharing
2.3.c Route summarization
2.3.d Route filtering
2.3.e VRFs
2.3.f Optimal topologies
2.3.g Redistribution
2.4 Describe SD-Access Architecture (underlay, overlay, control and data plane, automation, wireless, and security)
2.5 Describe SD-Access fabric design considerations for wired and wireless access (overlay, fabric design, control plan design, border design, segmentation, virtual networks, scalability, over the top and fabric for wireless, multicast)
20% 3.0 WAN for Enterprise Networks
3.1 Compare WAN connectivity options
3.1.a Layer 2 VPN
3.1.b MPLS Layer 3 VPN
3.1.c Metro Ethernet
3.1.d DWDM
3.1.e 4G/5G
3.1.f SD-WAN customer edge
3.2 Design site-to-site VPN
3.2.a Dynamic Multipoint VPN (DMVPN)
3.2.b Layer 2 VPN
3.2.c MPLS Layer 3 VPN
3.2.d IPsec
3.2.e Generic Routing Encapsulation (GRE)
3.2.f Group Encrypted Transport VPN (GET VPN)
3.3 Design high availability for enterprise WAN
3.3.a Single-homed
3.3.b Multihomed
3.3.c Backup connectivity
3.3.d Failover
3.4 Describe Cisco SD-WAN Architecture (orchestration plane, management plane, control plane, data plane, on-boarding and provisioning, security)
3.5 Describe Cisco SD-WAN design considerations (control plane design, overlay design, LAN design, high availability, redundancy, scalability, security design, QoS and multicast over SD-WAN fabric)
20% 4.0 Network Services
4.1 Select appropriate QoS strategies to meet customer requirements (DiffServ, IntServ)
4.2 Design end-to-end QoS policies
4.2.a Classification and marking
4.2.b Shaping
4.2.c Policing
4.2.d Queuing
4.3 Design network management techniques
4.3.a In-band vs. out-of-band
4.3.b Segmented management networks
4.3.c Prioritizing network management traffic
4.4 Describe multicast routing concepts (source trees, shared trees, RPF, rendezvous points)
4.5 Design multicast services (SSM, PIM bidirectional, MSDP)
10% 5.0 Automation
5.1 Choose the correct YANG data model set based on requirements
5.2 Differentiate between IETF, Openconfig, and Cisco native YANG models
5.3 Differentiate between NETCONF and RESTCONF
5.4 Describe the impact of model-driven telemetry on the network
5.4.a Periodic publication
5.4.b On-change publication
5.5 Compare dial-in and dial-out approaches to model-driven telemetry

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500-490 Enterprise certification

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Huawei's Eric Xu: Innovating Nonstop for sooner Digitalization

[Shenzhen, China, September 23, 2021] nowadays, Huawei kicks off its annual flagship event, HUAWEI join, which is being held wholly on-line for the first time. Themed "Dive into Digital", this 12 months's adventure brings together business visionaries, company leaders, true tech experts, and ecosystem companions to discover how to more suitable combine digital technology with enterprise scenarios and trade expertise, and the way stakeholders can work collectively greater conveniently to foster an open business ecosystem and drive shared success. Eric Xu, Huawei's Rotating Chairman, opened the adventure with a keynote speech. the total textual content is as follows:

Eric Xu delivers a keynote speech

Huawei Rotating Chairman Eric Xu promises a keynote speech at HUAWEI join 2021

thank you for tuning in to HUAWEI connect online. Having the probability to connect with you online is a testament to the development the area has made in digital transformation. today, i would like to focus on how Huawei is innovating nonstop to velocity up that development extra.

the area is altering quick, and so is digital technology. there is a world consensus on the value of going digital nowadays. It could be the best component all and sundry can agree on. more than a hundred and seventy countries have released a national digital strategy. recent tendencies have reminded us that digital transformation is now extra true and pressing than ever.

first off, the lingering pandemic has accelerated the digitalization of products and capabilities over the remaining two years. in line with McKinsey, COVID-19 has caused digital transformation to start ahead via seven years globally and by way of a full 10 years in Asia Pacific. Their research also discovered that going digital isn't any longer considered as some tedious and impractical endeavour. On the contrary, organizations have proceeded 20 to 25 times faster than expected. And now or not it's fairly much permitted that hybrid onsite and far off work might be the way forward for the place of work.

The 2d principal catalyst is the proactive world response to carbon emissions and global warming. The european has announced its plan to obtain carbon neutrality with the aid of 2050, and China has pledged to hit height emissions by using 2030 and develop into carbon neutral by 2060. Digital expertise holds the key to decreasing emissions throughout all industries. in response to a survey by the realm economic discussion board, by way of 2030, ICT expertise will aid in the reduction of industrial emissions by 12.1 billion lots, roughly 10 instances the volume emitted by the ICT business itself.

Third, the more and more complex world ambiance has caused corporations to region greater strategic precedence on business resilience, for which digital technology is a key enabler. financial healing from the pandemic and low-carbon construction are both pushing corporations worldwide to opt for up the pace of their digital transformation.

The good news is that the underlying expertise has under no circumstances been more ready. Many countries got here to know this of their efforts to grapple with the pandemic. The construction of the underlying digital expertise and infrastructure has laid an excellent groundwork for digital transformation.

Globally, there are already 176 5G business networks and more than 10,000 initiatives exploring how 5G can force industrial digitalization. On the customer end, there are already greater than 490 million 5G clients global. in line with IDG, 81% of businesses worldwide are already the use of cloud or have purposes in the cloud. AI is developing sooner than ever. A examine with the aid of Roland Berger indicates that AI has already penetrated every sector. In definite sectors, comparable to excessive-tech, telecoms, finance, automobile, and assembly, AI adoption exceeds 60%, and in company features, healthcare, and retail, adoption rates are roughly 50%, 40%, and 38% respectively.

just as digital transformation is a shared vision, the technology itself can be shared too. So what is the most efficient manner ahead? All nations, businesses, and industries are different, and they have unique challenges. So of route their understandings, options, tempo of development, and procedures to digital transformation are inclined to fluctuate as well. So true digital transformation continues to be a protracted manner forward.

Huawei's mission and imaginative and prescient is to carry digital to each adult, home and company for a totally linked, intelligent world. I trust assisting industries go digital is a important aspect to our mission. You may even say we would not be able to accomplish our mission without the a success digital transformation of industries.

There are four pillars to our cost proposition:

  • Ubiquitous connectivity: We consider that every grownup has the correct to be related, and Huawei's function is to convey connectivity to all americans and issues, and to maintain elevating the bar for user event.
  • Pervasive intelligence: We see AI as a universal-aim know-how that can support all industries convey each step of their conclusion-to-conclusion price creation method to the subsequent degree.
  • personalized event: every grownup is entertaining. we're dedicated to presenting personalised items and functions so that the individuality of each adult is thoroughly respected and their competencies is absolutely unleashed.
  • Digital platform: We firmly believe that digitalization will deliver civilization to wholly new heights. we're dedicated to presenting open, relaxed, bendy, and straightforward-to-use digital platforms to spark innovation throughout industries, pressure industrial improve, and develop social progress.
  • Digital construction relies on digital know-how. For digital technology to dwell principal, we ought to proceed to innovate and create value. Cloud, AI, and networks are three essential digital technologies. i'd like to talk about these three these days after which touch on what we're doing to permit low-carbon building. i may share some of the development we've made and our thoughts on the place the trade is heading.

    First, let's take a glance at cloud features.

    On September 1, 2016, at the very first HUAWEI connect, I delivered a keynote referred to as "embrace and integrate with the Cloud to become a Digital business".

    On March 19, 2017, we introduced the establishment of our Cloud BU on the Huawei Eco-associate convention, held in Changsha, China. at the time we also mentioned that, from 2017 onward, Huawei would ramp up efforts to build open public cloud systems with public cloud features. We were to focus on select industries and work with companions to construct a cloud ecosystem and grow the pie collectively.

    Now, four years later, HUAWEI CLOUD has brought collectively more than 2.three million builders, 14,000 consulting partners, and 6,000 expertise partners, and additionally made more than 4,500 services purchasable within the HUAWEI CLOUD marketplace. It has turn into an important platform for internet groups, natural organisations, and governments alike to take their groups digital. HUAWEI CLOUD, together with partner public clouds, now serves 27 areas in more than a hundred and seventy countries everywhere. according to a analyze by Gartner, HUAWEI CLOUD was the fastest becoming cloud within the IaaS market in 2020, and made it into the proper 2 for cloud service suppliers in China, and appropriate 5 globally. we have now come a long method, and that's just the beginning.

    With HUAWEI CLOUD, our mission is to construct the cloud foundation for an intelligent world through ubiquitous cloud and intelligence. As industries velocity up their digital transformation, HUAWEI CLOUD is primed to strengthen even extra.

    As digital transformation starts to take root, and with the becoming diversity and sophistication of digital purposes, common cloud functions that effectively deliver the basics like elastic materials and simplified O&M aren't any longer going to reduce it. tremendous-elastic components, alongside agile application development and iteration, are the manner ahead for cloud features. here's why tech groups, typical corporations, and governments have all began embracing the idea of Cloud Native. The shift in opposition t cloud-native purposes will permit natural enterprises and governments to advantage from enhanced aid elasticity and agility. beyond that, they could be able to create stronger cost by way of harnessing the power of huge statistics and AI that include new, cloud-native services.

    As an suggest and early adopter of Cloud Native, HUAWEI CLOUD has released a very good variety of cloud-native features for the reason that 2016, helping internet companies, traditional firms, and governments develop into cloud natives themselves. constructing on this experience, we introduced up the thought of Cloud Native 2.0 in 2020, the subsequent section of development where we hope to allow all corporations to develop into new cloud natives.

    As cloud-native applications turn into more common across all kinds of diverse scenarios, the need for distributed deployment, unified administration throughout clouds and areas, and making certain a consistent event will turn into increasingly critical.

    To tackle this need, after years of tough work, today we're launching the industry's first distributed, cloud-native carrier referred to as HUAWEI CLOUD UCS. usastands for "ubiquitous cloud native provider". With HUAWEI CLOUD UCS, we wish to deliver companies with a consistent event while the usage of cloud-native purposes that don't seem to be restrained by means of geographical, move-cloud, or site visitors barriers. usaaims to carry cloud-native capabilities to every business situation and speed up the adoption of cloud-native functions in all industries.

    Now, let's flow on to artificial intelligence.

    In October 2018, Huawei launched its full-stack, all-situation AI portfolio at HUAWEI join in Shanghai. On August 23, 2019, we announced the open source plan for our AI computing framework, MindSpore, in Shenzhen. for the reason that these bulletins, we have stuck to our plans and have managed to fulfill our aims.

    First, in terms of hardware, more than 10 of our companions have launched AI hardware items that use our Ascend modules and playing cards.

    second, MindSpore went open source in March 2020, as scheduled. From that point to the conclusion of August 2021, it has been downloaded more than 600,000 times, making it the most bright AI community in China. There are additionally more than 100 universities that include MindSpore of their curriculum. it's reasonable to assert that MindSpore has develop into the mainstream AI computing framework in China.

    additionally, greater than 500 of our companions have developed over 600 AI options based on Ascend. These options are used across a wide variety of industries. frequently speaking, our full-stack, all-scenario AI portfolio is moving ahead as expected.

    At HUAWEI join 2019, we released the Atlas 900 cluster. at the time, a single cluster used 1,024 Ascend 910 AI processors, providing 256 PFLOPS of computing vigour. Now, a single Atlas 900 cluster can fritter away to four,096 Ascend 910 AI processors, providing 1 EFLOPS on non-blocking off networks.

    On properly of these clusters, HUAWEI CLOUD ModelArts can use inter-cluster dynamic adaptive routing technology to extend the computing energy of a cluster with the aid of a factor of between four and 32, counting on the vigour constraints. That adds up to computing vigor of up to 32 EFLOPS and an increase in linear speedup ratio to more than eighty five%. The Atlas 900 cluster, as well as the cloud functions in line with it, presently serve more than 300 companies throughout all forms of industries, including transportation, finance, energy, manufacturing, and healthcare. they're used by way of many firms and analysis institutes for large model training.

    These are some of the extra noteworthy pre-informed gigantic models supported with the aid of the Atlas 900 AI cluster:

  • HUAWEI CLOUD Pangu chinese language NLP significant mannequin
  • HUAWEI CLOUD Pangu CV huge mannequin
  • HUAWEI CLOUD Pangu drug molecule gigantic mannequin
  • HUAWEI CLOUD Pangu scientific computing huge model
  • LuojiaNet, a committed far off sensing framework
  • Pangu chinese NLP gigantic model for Peng Cheng Laboratory
  • Biopharmaceutical massive model for Peng Cheng Laboratory
  • In Huawei's full-stack, all-situation AI method, ModelArts is positioned as an enabler of AI applications. Its aim is to permit extremely essential AI utility development, helping tackle the becoming shortage of AI authorities and consultants. Our hope is that ModelArts will equip every and every engineer who has a primary hold close on AI to independently strengthen their personal AI fashions and functions. during the last three-plus years, ModelArts has been utilized in heaps of AI application tasks across diverse industries. throughout this time, we have persevered innovating and gathering industry be aware of-a way to superior adapt the framework to fulfill the wants of organizations at diverse ranges of digital transformation and AI adoption. This has resulted in a collection of full-pipeline, situation-based mostly services in response to ModelArts. The creation of those features marks step one in realizing our dreams for ModelArts.

    for most agencies, there are three different levels of AI utility development, and ModelArts gives focused features for every.

    in the early stage, most corporations take a more experimental approach to AI for either generalized or more selected initiatives. during this stage, they are primarily concentrated on model building and feasibility. The AI capabilities of organizations during this stage are sometimes quite constrained. To handle this, ModelArts offers features and construction tools like area suites, illustration scenarios, Pangu massive fashions, and pre-knowledgeable models, enabling engineers to right away pick up, train, and verify AI fashions without having to clutter round with too a good deal code.

    The 2d stage is the "brief win" section where, constructing on a success experimentation, firms tend to center of attention on how they could use AI to create immediate price. right through this section, AI development is not any longer about developing models, but about facilitating one or extra real-world initiatives, catering to certain deployment environments and certain trade requirements, and adopting devoted designs. So for agencies in this stage, ModelArts gives things like depended on add-ons and safety algorithms, ModelBox, AutoSearch, and Pangu significant fashions, enabling AI engineers to adapt options to distinct deployment environments and swiftly develop AI purposes that will also be used in true-world scenarios.

    The third stage is characterized through the construction of systemic AI applications or AI sub-programs. This stage often requires collaboration between numerous functions, tools, and programs. ModelArts supports simplified and effective AI device building by using providing MLOps, OptVerse AI Solver, scientific computing, Pangu giant models, heterogeneous distributed equipment schedulers, and a wide range of business-particular components and equipment from ecosystem companions. With ModelArts, we're dedicated to equipping each engineer with the tools and support they need to increase AI purposes, and we seem to be forward to attaining this intention as quickly as viable.

    Even probably the most pro AI consultants discover it challenging to combine AI into precise-world scenarios across different industries. this is because industrial scenarios are numerous and do not often have a whole lot in normal. Even with tremendously automated tools, AI mannequin building must be done on a case-by using-case basis, which is extremely labor intensive and time ingesting. A common lack of decent data to instruct models presents a good greater challenge. For AI models to be correct, we should feed them massive quantities of statistics. a scarcity of scenario-based mostly information skill that fashions frequently fail to fulfill precise-world necessities, rendering AI pointless in certain scenarios. In instances like this, giant models are a fine answer.

    With pre-educated tremendous models, builders should not have to birth from scratch when setting up AI for any state of affairs. instead, smaller, state of affairs-certain models will also be automatically extracted via focused practicing in keeping with a big mannequin. This shortens the construction cycle from months to days, marking a shift from guide AI model building to industrial-grade building.

    greater importantly, focused practising according to giant fashions drastically improves mannequin performance and AI usability. These are actual outcomes from our Southern factory. With best forty facts samples, the accuracy of AI models informed with well-known strategies can most effective reach about 80%, which actually would not meet our necessities. but if we coach them based on large models, we're capable of raise the accuracy to as high as ninety nine.5%. So now the use of AI for detecting defects is a practical truth.

    next, i'd want to focus on commercial enterprise networks.

    As corporations go digital, they tend to see exponential increase in community complexity, as a result of they must take care of:

  • extra linked branches and access places in a hybrid work environment
  • greater dynamic alterations to experience as a result of better employee mobility
  • greater connections as office networks converge with IoT
  • extra efficiency requirements and regular network alterations as a result of cloud and new apps
  • extra sorts of equipment from extra providers, leading to more suitable management scope
  • more demand on network assurance as the focal point shifts from connection-centric to event-centric
  • at the same time, these organizations may not see linear increase of their number of O&M engineers – or they won't see any increase in any respect. The hole between the complexity of network O&M and the availability of O&M engineers will handiest continue to expand. This challenge to network O&M can also be addressed by way of making use of digital know-how. Innovating, no longer expanding the O&M group, is the appropriate way to take care of the becoming complexity of network O&M.

    in keeping with this perception, we came up with the theory of self sustaining riding networks, or ADN. We consider that networks of the longer term will be like independent automobiles which are in a position to automatically operate and preserve themselves without manual interference. ADNs could have 4 qualities:

  • First, they could be self-pleasing. That skill the community can immediately installation functions in keeping with person intent. The most reliable goal is to completely automate provider deployment.
  • second, they can be self-healing, meaning that the community can predict and prevent faults, and instantly get well from incidents. totally automated O&M is the greatest goal during this respect.
  • Third, self-optimizing, with networks that can automatically regulate and optimize themselves to deliver a sophisticated event. ultimately, we wish to intention for wholly automatic network optimization.
  • Fourth, autonomy. This capacity that community capabilities will be capable of autonomously adapt, be trained, and evolve.
  • this is our vision for ADNs and what we sooner or later hope to obtain.

    over the past two years, we've been innovating options for world networks in keeping with the ADN idea. we've got also been working along side valued clientele from the finance, schooling, and healthcare sectors to innovate and installation new purposes.

    in the finance sector, Huawei and China CITIC bank have applied ADNs to Strengthen the bank's information middle community. In 2020, our ADNs enabled conclusion-to-conclusion automation of functions throughout over forty eventualities on one statistics core network with machine provided with the aid of a single vendor. This 12 months, we are able to retain pushing the envelope to aid heterogeneous scenarios that contain distinctive clouds and equipment from dissimilar vendors. Take the bank's features for sending cash transfers to foreign college students, as an example. during the past, launching a new provider like this took an ordinary of greater than 30 days to do collaborative design and contrast throughout domains and manage any adjustments. Now the complete system can be completed inside just half-hour.

    Being capable of rapidly find faults is the largest headache when managing any information core network, but it surely's now not the case with ADNs. ADNs offer end-to-conclusion visibility into network excellent. They additionally make it possible to locate seventy five types of ordinary faults within three minutes, and provide advice for fixing the fault within five minutes. This year, our ADNs all started the use of capabilities graphs for self-discovering. they are in a position to analyze reside community facts to always learn about new faults, boosting basic coverage to ninety seven%.

    in the training sector, Huawei and Xi'an Jiaotong college are the usage of ADNs to redefine campus networks. as the college deploys more and more wise educating and campus capabilities, it has to manipulate a turning out to be variety of IoT gadgets like cameras, barrier gates, sensible doors, and lecture recording instruments. throughout their 4 campuses, they've greater than 500,000 devices across 50 classes. they are utilized in all types of different places and may entry the campus network, which may doubtlessly pose a safety chance.

    Our ADN know-how helps the school's networks immediately establish devices and supply access within seconds. Powered by means of AI, the ADNs can also learn about and label unknown instruments online. Now it could identify ninety eight% of instruments on its own. instant access over campus networks has already turn into mainstream. during the past, Wi-Fi inference, roaming, and utility help had been large challenges to the tuition. They needed to manually optimize the Wi-Fi network, which changed into very inefficient. Now with Huawei's AI-based optimization performance, they have reduced the want for manual interference and expanded their Wi-Fi RSSI achievement price from 64% to 90%.

    finally, i might want to discuss how Huawei is supporting low-carbon development with digital technology.

    Like I stated previous, digital technology is key to going low-carbon. Huawei will proceed to innovate in digital technology to help low-carbon building. we've three priorities during this enviornment:

  • First, we invest and innovate in power-saving applied sciences to deliver greater energy-productive ICT items for a low-carbon ICT trade.
  • 2nd, we invest in improvements where vigor electronics and digital technologies converge to advertise clean energy and the digitalization of typical power.
  • Third, we supply digital know-how to aid all sectors go digital and low-carbon.
  • assisting the ICT trade go low-carbon is our first priority. For decades, Huawei has been setting up gadget and options across the intention of reducing power consumption and emissions. New necessities are emerging on combating local weather alternate and reaching low-carbon building in all sectors. These necessities carry the bar for ICT machine. In response, we can set better goals of realizing power conservation through innovation.

    Our second priority is to advertise clear energy and the digitalization of typical energy. As part of international efforts to obtain top CO2 emissions and carbon neutrality, we goal to make use of our digital technology to advertise clear power and the digitalization of ordinary energy. For this goal, we recently deploy a subsidiary called Huawei Digital vigour. Our vision has several layers. We want to promote clean power and the digitalization of ordinary power. We're also working to extra without problems integrate digital and energy electronics technologies, and converge advice and energy flows to pressure an power revolution for a much better, greener future.

    mainly, Huawei Digital energy converges power electronics and digital technologies, as a way to use bits to manipulate watts. That ability we use digital technology to control power electronics gadget. Our leading focal areas span from clean vigour technology, power digitalization, and transportation electrification, to green ICT infrastructure, and built-in smart energy. We provide relaxed, efficient, green, and clever solutions for these areas. We also provide the energy sector with widely-used enablement platforms, together with these for embedded vigour, intelligent power distribution, and power storage. furthermore, we can enhance a unified energy management Cloud carrier platform for all digital power eventualities. This could be an open software platform for all of our customers and partners.

    through presenting these products and solutions, Huawei Digital vigor goals to aid low-carbon construction in all areas, together with households, buildings, factories, campuses, villages, and cities. we will work to force the shift towards low carbon, and eventually zero carbon.

    Our third precedence is to cut back emissions in typical sectors, specifically these with usually heavier emissions. here's central to the transition in opposition t a low-carbon world. or not it's also a key part of our innovation method. We remain dedicated to proposing digital know-how to help all sectors go digital and low-carbon. it's fair to claim that slicing emissions is a shared aim between Huawei and basically all the sectors we work with. we have made some interesting progress to date.

    In wise transportation, our site visitors easy administration answer reduces traffic jams and emissions in cities. Our sensible highway solution supports free movement tolling and has helped reduce gasoline use by 321,seven-hundred lots thus far.

    Our sensible heating solution is already reaping merits for Harbin, a city in northeast China. in the metropolis's Daowai District, on-demand heating reduces energy use via a normal of 12.1%. If smart heating is used throughout 13 billion rectangular meters of building area in China, then CO2 emissions will decrease with the aid of 16.199 million tons per 12 months.

    Our wise agriculture answer is additionally creating real value for farmers in Switzerland. Drones that use large facts and 5G are in a position to inspect farmland 20 times sooner than before. through precision weeding, farms can reduce weedicide use by means of 90%.

    there is little question about it: Digital transformation is an extended-term technique that may not occur overnight. fortunately, the tech sector is extra dynamic and vibrant than ever. Nonstop innovation has been the driving drive behind digitalization so far. moving ahead, if we hope to reach more formidable goals for digitalization, nonstop innovation will proceed to be key. So let's innovate nonstop for a stronger future.

    thank you!


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