Home » Webinar » Device-to-Cloud Data Collection, Analytics, and Smart Wi-Fi

Device-to-Cloud Management

Data Collection, Analytics, and Smart Wi-Fi

In this webinar, we cover the following topics:

  • Service-based ecosystem, including the service provider and:
    • IoT
    • Wi-Fi
    • Home Security
    • Cyber Security
    • Smart Home
    • Parental Control
    • User Experience
    • and others
  • Customer & Service Experience (QoE)
    • Reliable connectivity
    • High-quality Wi-Fi
    • Monitored service
    • Proactive response
    • Customer experience
    • Service level
  • USP Mult-Controller & Device to-Cloud
  • Smarter Wi-Fi: Fewer Truck Rolls
  • Wi-Fi User Experience
  • Wi-Fi Resolution & Optimization

Webinar Transcript

Craig Thomas (Broadband Forum): So I’d now like to pass over to Tzvi Skapinker from Friendly Technologies. I know he doesn’t look like it, but he’s another gentleman who has over 20 years of experience within the telecom enterprise and the public sector, specializing in IT, Comms, and cybersecurity. Within Friendly, he leads all of the technologies and line of products for IoT, Smart Home, Device Management, and Embedded clients and today’s presentation is entitled Device-to-Cloud Data Collection, Analytics, and Smart Wi-Fi. Tzvi I’m not going to hold you up, please take the mic.

Tzvi Skapinker (Friendly Technologies): Thank you Craig. Thank you very much. Thank you, Michael, that was also fascinating to hear and see as well. Just hope that you see my slides and you’re hearing me very well.

Craig: Yes we do.

Tzvi Skapinker: Okay. So thank you for the introduction. And today I will be discussing the emerging role that we have with the CPE ecosystem, or the device ecosystem, as we call it today. And the new challenges, it actually brings for service providers, including how to monitor and collect various applications and service data, as we’ve been hearing before. We’ll focus on, as I mentioned, the challenges in collecting, analyzing, and presenting the data which is deriving from various devices. We’ll discuss a bit about the real-life device-to-cloud integration and how this can be easily done with the current tools that the present forum is offering to service providers and a quick walk through some cloud applications for smart Wi-Fi. So without any further adieu — So just a quick note, for those of you who are not familiar with Friendly Technologies. We are a software company. We were founded back in 1997, so it’s quite a while. But we became more heavily focused on Device Management somewhere around 2006. We’ve been a member of the Broadband Forum for quite a while and recently, we actually decided to step up and get much more involved with the forum activities. And this is actually considering the upcoming challenges that we all see today.

So let’s talk just about the service-based ecosystem. So the assumption is, service providers actually want to open more things. And they want to improve the outgoing reduce churn, right, this is the main assumption that we know. And we have seen the constant role of the service provider being transitioning and transitioning from the traditional responsibility that they had with providing just the edge of the connectivity. And now they’re actually penetrating the home with Wi-Fi, Smart Home, Security, and a variety of different and connected devices as well. And so all of this actually brings us quite a challenge of how to present all of this data. And it goes back to preliminary of what are the needs of the service providers. So we want to provide a stable, secured, and efficient network. This is one of the main items that every service provider is looking for. The need to reduce the churn and every service provider wants to provide more services and higher customer satisfaction as well. But with the increase of the services and the application that we see today, there is also an increase in the need for data collection and analytics. We need to provide efficient performance and monitoring tools. Not just for managing the device as we traditionally did with the device management platforms that we’re offering, but also we need to manage the data that the device is actually capable of monitoring and sharing with us.

Another item that is very much interested that service providers are looking into is getting customer experience and overall satisfaction. And they want to get more insight on the service usage – the stability of the service, the reliability, the performance. This will actually require a lot of data streaming solutions that will be supported by both the device and the controller, or the ACS as we know them today.

So the question here is not how a service provider can leverage their existing infrastructure, because we know that they’re doing this already today. But how to maintain high operational efficiency, while still collecting data from devices and keeping the high customer and service experience expectations. So I will try to explain this a bit more in the following slides.

So a service provider today needs better tools to manage and control while still proactively understand and ensure that the quality of experience, including the different services that he is providing, are kept. So the most important criteria a service provider needs to maintain is a reliable network infrastructure. They want to have a high-quality and very stable WiFi solution because most of the services today are being offered over Wi-Fi. They want to have the ability to monitor and collect performance KPIs across various services. So we know that today we have a lot of different services being offered to the customer. And they want to have also a proactive response based on the artificial intelligence and machine learning capabilities that we can provide on top of the collected data. So we need to identify service degradation, actually, before it happens. And we want to provide a proactive resolution before the customer experiences an outage.

So what is the challenge here? We’ve been discussing a bit, but the challenge is how we can collect all the service-related data. We have this device, the device collects a lot of information and we want to send it somewhere. But we need to remember that the most important thing for a service provider is operational efficiency. A service provider wants to maintain a high level of service while managing the device. So he cannot tolerate any outage with provisioning or management while collecting data from a device. So this is considered a critical event. So provisioning and the device management is actually a crucial part to maintain the customer satisfaction. And eventually, this will reduce churn, as happy customers and satisfied with the service level that they’re getting will keep the customers for that specific service provider. So the balance here is very important, how to still collect information, how to analyze it, where to store this information, and still have high operational efficiency. And also, we need to provide better tools for this data visualization as well. So with this challenge, the Broadband Forum participants introduced TR69 and the USP offers a solution that will allow us to collect data from monitor devices without actually affecting the daily operational tasks. And this could be done by tuning, by event-driven network distribution, or by bulk data collection mechanisms. So let’s take a closer look at both of these architectures and we’ll try to see the slight differences that we have and what will be more important for every service provider.

If we’re looking at this architecture, we’ll see that this is actually an event-driven method collection architecture. And it goes through the main restriction that we had with Tr69 until today because USP is actually emerging and giving us a solution for this. So the client device actually supports a single URL for the ACS. And this means that you can send information only to one certain location for management and also an event-driven notification. So, in order to efficiently separate between the management and the provisioning task while still collecting a high volume of data, the service provider can rely on our network service load balancer that will be used to distribute the traffic and distinguish between management tasks or monitored events. The network load balancer will support this traffic series based on the Tr69 XML that we are familiar with. So this will give us the ability to differentiate and distinguish between the management and also between monitoring events. But however, this has a cost. Because it means that on the network side, the service provider needs to maintain robust L7 browsing capabilities, and also he needs to maintain that environment as well. The device management platform should support also the distributed architecture between management and events because not all information will be sent to that same specific ACS. So you need also to have a sync mechanism between all of them in order to know the status of each device all the time. This will require additional infrastructure. We all know that in order to run this, the service provider will need to provide additional infrastructure for networking, for storage, additional servers for collecting data, and so on.

The device on the device side, also it still has the same, actually constraint that it could use just one single APS. The device doesn’t know that the network is actually steering this information and you’re getting from one ecosystem, the management, and from another one you’re sending to another ecosystem, the actual monitor data. So to overcome these challenges, actually, the Broadband Forum has introduced in Tr69 and also in USP, the bulk data transfer mechanism. So let’s take a closer look at that mechanism and how it could actually assist us with using a multi-control environment and also have a device-to-cloud integration.

So a USP and also as part of Tr69 has introduced a new approach for collecting data from the CPE. And the theory of operation here is actually relying on transferring bulk data from the CPE to a collector. 

So let’s discuss a bit about device-to-cloud integration and what can we achieve with this architecture. So the data collector can actually be placed in any environment, especially various cloud service providers, as we know them today, AWS, Microsoft, Google, and others as well. So the amount of data that could be collected is actually unlimited. It can expand rapidly, it actually goes according to every service provider’s needs. The monitoring interval is actually very important because, with this approach, we can set it to new real-time. We can have information being sent from the device to the cloud, in a very short period of time from seconds to minutes, and have a new real-time data collection mechanism. This would be very efficient for various applications that we will discuss shortly. Cloud storage and data processing can be also integrated with the cloud offering for AI or AML solutions for data analytics, which can provide even more business intelligence than the service provider has today. So Tr69 or 369, you see that we provide a framework for Device Management and performance monitoring. The standard provides us the ability to do both monitoring and management and performance management using a distributed architecture with a multi-controller environment. So with this support about data competence, that will be added to the CPE as this ability to steer the monitoring events and send them to a separate collector URL, which acts as bulk data collector. 

So actually, we’ve addressed the most important thing that the service provider is looking for. On one hand, is able and capable of managing and performing various performance tasks, and on the other hand, it brings him the capability of collecting, storing, and analyzing a lot of information.

So what can he do with all of this data? Okay, so we are collecting this data, but what would we can do with that? So, for example, let’s take the Smart Wi-Fi solution that could be executed on a data collector. So every service provider or an ISP knows that one of the basic complaints that they have today, I’d say, well, my internet is not working. So we need to collect some information from the device, analyze that and see why the customer is complaining about the internet connection. So this can be done actually by combining the CPE-derived data with some external information. Like information coming from a mobile device, using some mobile application, and also from third-party connectors. And this information, we can use in order to distinguish what is the root cause of the problem. If it is a problem related to the internet connection if it is a problem related to the Wi-Fi settings if there’s a problem related to some Wi-Fi neighboring disturbance. And by collecting this information, joining them together, and offering a resolution, we will have a smarter, wiser solution. So the information is there. The information is being stored on the device, the device knows how to collect all this information and all we need is actually a better way, a more efficient way to retrieve this information and present this to our code engineers.

So let’s take a closer look at some of the device capabilities of doing this. The current device data model … provides a variety of diagnostic and performance indicators. We can collect all of this data. Like we see here in this example for ICMP diagnostic, this could be collected easily by a default data collector and provide our device connectivity matrix showing what is the status of this device. And if we get degradation we can also be alerted and we can have also a proactive approach. So this could be used to identify the degradation of service. while collecting all the relevant information from the deployed CPE. The service provider can identify the actual service degradation even before receiving the customer complaint and we can proactively act to resolve that.

Just a few more examples on the data model that could be used in order to have some more metrics that we can build a Wi-Fi user experience core by collecting Wi-Fi data elements. This actually brings us around approximately 130 Wi-Fi specific key network performance indicators, such as data speed across the wireless network, airtime, retries, and also information about the access point and the neighboring environment as well. So this consistent approach to data collection streaming into the bulk data collector within the service provider diagnostic tool will help us better understand customer Wi-Fi, network, and condition.

So this information that we’re collecting with the Wi-Fi data can be used for Wi-Fi troubleshooting, for resolving Wi-Fi coverage issues, also, for proactive problem resolution. We can identify degradation of service if we see some interference that has been caused by a neighboring Wi-Fi access point, so we can steer this access point and switch to a different channel, and so on. So, we have an example here for some of the key indicators that the service provider can retrieve. As I mentioned before, these indicators can be used to assess the service level of the radio interference, we can assess associated device statistics, identify some potential service degradation as well. So all this information is actually there. We need a better way and an easier way to retrieve this, and we were discussing and I was showing before how this information can be collected, monitored, analyzed, and have a better service resolution. and identifying the actual root cause of a problem for the service provider.

So just before ending, and handing this back, what to expect in the future. I wanted to give some very plain and simple directions of what we see in the future coming. So we all know that there will be more data sources that we will need to integrate and take information from as more connected home applications and devices, will be integrated with the device ecosystem. So the amount of data will grow exponentially. This will require advanced analytics for service usage and performance. So many more cities applying open standards with the ability to stream collected data, or device-to-cloud integration, and utilizing cloud services for storage for data analytics and application. So I think my time is up. So I want to thank you all and I’ll hand it over back to you Craig.

Craig: Tzvi thank you so much. Greatly appreciate it. Great presentation, as always. And it’s really interesting to see exactly with all of that data collection, you know what we can enable from a service provider management perspective.