In this video we demonstrate how to configure Juniper Switch SSH password in Mist dashboard, where would your switch get management IP address from and how to learn what IP to use to actually connect to the switch using SSH.
Welcome to the WiFi Ninjas Video where we domonstrate how to configure a Juniper Switch using Mist Dashboard. Curious about pros, cons, limitations and what’s available for us to tinker with in this recent Juniper Mist wired integration? Dig in! We tried to cover it all 😉 Enjoy!
Welcome to our latest blog!
If you’re like me and want to have most compact, cold, silent and energy efficient ESXi server at home, you probably looked at Intel NUC more than once 😉
I’m now upgrading (or rather downgrading?) my lovely 2U ESXi that built myself 2 years ago. It is still powerful, but I have no space for it. I will tell you why.
My server room is located under the stairs. It was filled with equipment – Cisco FTD 5506x firewall, Cisco 3560cx switch, Cisco WLC3504, Cisco 9120, 9130, 3x 3702 APs, 2U ESXi server and UPS battery ensuring my NFS storage is not corrupted in the event of a power cut.
All that boxes generated so much heat, that I have decided to make space for clothes airer – my washing was dry just 2-3 hours after putting it inside the server room 🙂 This space could also be used as sauna.
I then decided to simplify my home network and lab. Moved NAS to the cloud, virtualised firewall (chosen Untangle – amazingly sleek), mounted APs properly outside of the server room and switched to Mist.
Now I’m down to just an ESXi server, 1 small, passive, lovely Juniper EX2300-C-12P switch (that can be managed from Mist cloud!) and 2x Mist APs – AP41 and AP43. No more controllers, batteries, firewalls.
Do you see what my problem is?
Washing don’t dry out quickly anymore, as it’s cold in the server room!
To fix this, I will put a dehumidifier in that room. But I need more space to do it. This is why I wanted to switch to micro server (NUC) – so I can replace the rack with massive ESXi server with dehumidifier.
I ordered 10th Gen Intel NUC with 64GB of RAM and 2TB SSD – it’s more than enough to run my production and lab networks. But since I no longer have a physical firewall, I encountered a challenge – NUC has only one wired NIC card. I now needed two – one leg connected to BT fibre converter (WAN PPPoE) and one leg connected to the switch (LAN).
After putting ESXi 7.0 on my NUC (it was quite challenging – NUC Intel wired NIC is not supported by ESXi and it required adding Intel NIC drivers to the ESXi image – thank you Bernhard @WiFi_Burns for your help!), I realised that my USB NICs are not recognised when connected.
Additional drivers are required to make it work.
Since we WiFi nerds don’t use VMware excessively, I personally found instructions available from VMware quite confusing and difficult to follow, so I’ve decided to put all steps needed to make external USB network adapters work on Intel NUC running ESXi.
Steps required to use USB Network Adapter on VMware ESXi (tested on NUC 10)
1. Download .zip file from here, making sure you get the correct version for your ESXi (currently 6.5, 6.7 or 7.0 are supported)
2. Make sure Safari (assuming you’re using Safari) doesn’t automatically unzip the downloaded file (Safari > Preferences > General > untick ‘Open “safe” files after downloading’)
3. Upload .zip to ESXi datastore
4. Enable SSH (Web Client > Host > Manage > Services > SSH > Start)
5. SSH to the ESXi terminal with your favourite client or straight from the Web Client (Host > Actions > SSH Console)
6. Find a location of a .zip package on ESXi (use find / -name “*.zip” command)
7. Run esxcli software vib install -d /path/to/the offline bundle
8. Reboot your ESXi with a new USB NIC connected (Web Client > Host > Reboot)
Your external network adapters should now be natively supported in ESXi 6.5, 6.7 or 7.0 run on 10th Generation Intel NUC.
I have tried two different adapters, Belkin F2CU040btBLK USB-C and some very old USB-A 3.0 Adata one – both worked perfectly. I left Belkin plugged in as it’s much newer and 2 weeks after switching to NUC I can confirm that I’ve not had a single network performance issue. My USB-C wired NIC is happily used as a WAN interface by Untangle Firewall VM. Happy days!
Lastly, if you need Intel NUC 10th Gen ESXi image without having PhD in VMware PowerCLI and Google, give us a shout and we will share the image, hopefully saving you some time!
Tons of love,
WiFi Ninjas x
Hey! Welcome to our latest WiFi Ninjas Blog 🙂 We’ve been busy lately testing some available RTLS solutions from a few different major wireless players and fell absolutely in love with the topic to the point, where we shake from overexcitement when thinking or talking about it ????
This summarises how we feel:
Steve Jobs once said, “people don’t know what they want until you show it to them”. He was right.
20 years ago, WiFi was “a nice to have”. 18 years ago, paper maps were at peak of their popularity, until GPS receivers got small enough to be put in the handheld devices. Is anyone not using Google Maps on their mobile? 15 years ago, not many people felt they needed a wireless headset, until Bluetooth was introduced. 7 years ago, NFC was a niche. Today, most of us use contactless payments using cards, phones or watches.
Indoor wireless RTLS is at the early adoption stage. Technology is available, we just need to make it more interesting and rewarding to use.
Satellite-based location positioning services are not always practical indoors. We could offer wireless RTLS functionality based on WiFi, BLE or soon, possibly, Ultra Wide Band (UWB). Modern smartphones have both WiFi and BLE radios built in. Additionally, new iPhones support UWB. Wireless vendors leverage cell of origin, trilateration, triangulation, angle of arrival, proximity and more with WiFi, BLE, UWB, GPS, NFC, mobile networks or any combination of those methods and technologies, offering different levels of accuracy and functionality. RTLS market is growing fast – according to Bluetooth.com, 1.7 billion devices will use indoor BLE RTLS by 2023, translating to even 500% increase in BLE RTLS implementations in some verticals!
So, what do we need to see the RTLS market explosion? We’ll be speculating, but our hearts tell us that indoor RTLS needs solve real challenges like indoor wayfinding or call for help and simply be more interesting not only for the business’ IT and marketing, but for everyone. We also need more skilled wireless professionals willing to embrace broader wireless technologies and emerging use-cases, like BLE and RTLS, on top of WiFi design, security and analysis skills, while not forgetting about programmability elements.
But enough of the babbling, let’s cut straight to the juicy content! Here is what we will cover in this blog:
- RTLS Technologies
- RTLS Tracking Methods
- Cell of Origin
- WiFi Trilateration
- WiFi Angle of Arrival
- Mist vBLE Arrays and Probability Surfaces
- RTLS Functionality
- Presence & Analytics
- Engagement & Actions
- RTLS RF Design
- Design Tips
- RTLS Technologies
- Demo Time!
- Test Environment
- WiFi Trilateration
- WiFi Hyperlocation
- Mist BLE Arrays
- Location API
- Challenge 1 (Meraki Location API): Do You Need RTLS RF Design for WiFi Location & Presence Analytics?
- Challenge 2 (Cisco CMX Location API): Can You Leverage Enterprise Messaging Solutions to Benefit from Indoor RTLS?
- Most popular tracking technology, as it also provides access to the network.
- Can offer different levels of location accuracy, depending on the tracking method used (cell of origin, Trilateration, AoA, etc.).
- Multiple element antenna arrays can substantially improve location accuracy – Cisco Hyperlocation is a great example.
- Can be used to track associated and unassociated probing clients.
- Associated is proffered, since stations are chattier (with their screen on at least).
- Normally, WiFi based RTLS is based on RSSI/Location information from probe requests only, as probing client normally sends requests on multiple channels, and is therefore seen by multiple APs. This, however, results in very infrequent location calculation ranging from 10 seconds to 5 minutes (according to Cisco) but our own tests shown that modern unassociated stations don’t probe at all. Note, that happy (high RSSI/SNR) associated client probably won’t probe at all, and therefore its location could not be calculated with better accuracy than ‘cell of origin’ (see below) until its re-associating (roaming). Cisco has addressed this challenge with a feature called ‘FastLocate’. It uses a dedicated built in antenna array (4800) or a halo module (3600 / 3700) to scan multiple channels and get RSSI values from clients’ data packets across multiple channels without sacrificing performance of clients serving radio by going off-channel to do just that.
- To track unassociated station, two conditions must be met: station must not use MAC randomisation (they normally do) and it must be probing. Not all unassociated stations are probing.
- Client apps are optional and can be used to increase tracking accuracy, location calculation frequency and add engage or actions element. Note, that using mobile SDK in WiFi-based RTLS is challenging, as the application normally has no way of knowing the MAC address of the device it sits on.
- On top of location analytics, WiFi is normally used to provide presence analytics (more info below).
- BLE relies on physical beacons, often battery operated; vBLE moves beacon role from BLE beacons to APs .
- BLE is often used to offer proximity-triggered actions and vBLE can be used for location analytics on top or instead of WiFi
- Client app is required for fast (sub-second with Mist) and accurate (1-3 metres) BLE/vBLE. Station listens to the BLE transmissions coming from the BLE AP (BLE APs are transmitting). Mobiles listens to all (directional with Mist) beams from all BLE APs in the area and sends RSSI values with beams ID to the server/cloud, where location engine will calculate station XY coordinates and send them to the station. Note, that mobile station can send that information using mobile network; device doesn’t have to be associated using WiFi for BLE RTLS to work.
- Clients with no apps will be treated / located as BLE tags / assets. In this scenario, client is sending BLE transmissions to BLE APs (BLE APs are receiving). Mist uses its directional arrays to pinpoint asset tag transmission location with mind-blowing accuracy, all other vendors will typically rely on tag proximity to BLE radio built into the AP / anchor.
- More BLE beams heard = better accuracy.
- More element antenna arrays can substantially improve location accuracy – Mist BLE Arrays are a great example.
- BLE seems to be very well suited for RTLS, as it doesn’t travel as far as WiFi, therefore offering theoretically better accuracy than WiFi. Note that both BLE (2.4GHz) and WiFi (2.4 or 5GHz) are using the same frequency (actually WiFi can even sit on a higher frequency with 5GHz, and therefore theoretically not travel as far as 2.4GHz) but BLE (Bluetooth LOW Energy) uses significantly lower power levels to operate.
- XY coordinates are calculated for vBLE and are typically not calculated for BLE (proximity used instead, but there are exceptions to that rule!).
RTLS Tracking Methods
Cell of Origin
- Simplest location technique.
- Typically leveraging location of AP that clients are connected to but might be the AP that sees the probing or associated client with strongest RSSI.
- Great for simple zone-wide accuracy.
- Requires at least 1 AP per zone and careful RF design.
- XY coordinates are not calculated.
- Distance (lateration) based location technique using RSSI in 802.11, measured by either STA or AP/Sensor.
- Adds more accuracy within a zone (tested with Meraki and Cisco) – 2-3m labbed (in perfect environment), 5-7m marketed, 7-10m real.
- Real accuracy is lower than labbed and marketed, as it’s difficult to have LOS between 3x AP and STA everywhere. Also, cross floor leakage, atriums, walls and signal deterioration – all affect accuracy.
- Note, that we normally use Trilateration in WiFi RTLS and it’s often confused with Triangulation.
- Trilateration: requires 3 APs with known distance between them; uses RSSI (distance, lateration) to calculate intersection (client XY coordinates) between three circles (as shown above).
- Triangulation: requires at least 2 APs with known distance between them; uses this baseline and multiple-element antenna arrays (that we typically don’t have in WiFi APs, with Hyperlocation being exception here) to calculate arriving signal angles to find XY coordinates of the client (as shown below).
- XY coordinates are calculated.
WiFi Angle of Arrival
- AoA (angulation) location technique using angle of incidence at which STA signals arrive at the receiving sensors.
- Requires at least 2 APs / sensors / modules (at least 3 recommended for better accuracy).
- Note, that AoA with three APs is in fact a tri-angulation.
- Requires multiple element antenna arrays or antenna mechanical agility.
- Cisco Hyperlocation uses a mix of WiFi Trilateration (RSSI), WiFi AoA and BLE
- Cisco 3600/3700 Hyperlocation module has 32-element antenna array
- Cisco 4800 built-in Hyperlocation has 16-element antenna array
- According to Cisco, Hyperlocation module used with older APs and 4800 built-in array offers same levels of accuracy
- AoA is more accurate than Trilateration (tested with Cisco Hyperlocation) – 1-3m labbed, 1-3m marketed, 1-5m real
- Real accuracy is lower than labbed and marketed for similar reasons as discussed for Trilateration. Additionally, AoA requires extremely careful mounting and calibrating APs positions in maps services (height, azimuth).
- XY coordinates are calculated.
Mist vBLE Array and Probability Surfaces
- Unique to Mist.
- Every Mist AP has 16 Directional Antennae Bluetooth Array – 8 reflectors and 8 directional antennas.
- Uses BLE concept, where Mist SDK on the mobile device is listening the beacons from the beams and sends the RSSI and device sensor information back to the Mist cloud through either WiFi or cellular. Mist also supports assets tracking.
- Mist is not using standard Trilateration, but ‘Probability Surfaces’, where combination of listening to directed AP Beams and machine learning constantly evaluating Path Loss Formula (PLF) per device to calculate station location.
- Extremely good accuracy: 1-2m labbed, 1-3m marketed, 1-3m real (mind blasting).
- XY coordinates are calculated.
Presence & Analytics
- Typically relies on WiFi
- Provides network level stats, such as:
- Current visitors: devices count, dwell time, gender and age split, device types present
- Avg. visit distribution: time of day, day of week, new vs repeat, duration, gender, age
- Bounce rate (stayed vs bounced; enter and stay for longer than 3 min)
- Conversion rate (converted vs passed; clients that passed the venue but didn’t enter)
- Visitors engagement ratio (stayed connected over specified time)
- We can leverage social media, mobile apps or splashpage forms to onboard WiFi clients and grab users’ details (be careful with GDPR!)
- Typically relies on WiFi, BLE/vBLE, GPS, Mobile, UWB, Ultrasounds
- Provides zone/location level insight, such as:
- Zone analytics & zone paths
- Location on the map (dashboard or client app – blue dot)
- Some location features can be leveraged directly through specific web user interfaces (CMX, Purple, Mist or Meraki Dashboards) but it’s generally more powerful and useful to get, manipulate, filter and visualise location data using API – output can be crafted to any business needs. Typically, the following attributes can be grabbed (or subscribed to if you’re using Mist Webhooks) via location API:
- Client XY coordinates
- Zone entry and exit events
- Virtual beacon (Mist), beacon proximity (everyone else)
- Raw tracked client’s data: RSSI, time, MAC, etc.
- Zone analytics importance
- Zone analytics is extremely valuable for businesses, especially retail, to understand impact of their actions (new displays, stands, brands, promotions, etc.) on paths users are taking and stats for each zone (dwell time, count, etc.)
- CMX GUI – Zone Paths example:
- Purple GUI Zone – Paths example:
Engagement & Actions
- Uses Presence, Analytics and Location insight to create personalised user experience
- Example 1:
- Returning user that has opted in and has previously bought a pizza (tagged with ‘pizza lover’ tag) entering 1st Floor dining area after 3.15pm will get a 50% off offer delivered via App Push Notification (This would also require some CRM integration)
- Example 2:
- When user is in a proximity to a BLE beacon or a vBLE area, open wifininjas.net website in a loyalty app integrated browser
- Example 3:
- Zone A (sports cars) will use different Captive Portal than Zone B (donuts)
- Example 4:
- User uses app for indoor wayfinding – where am I and how can I find client X reception and how to get there?
- Example 5:
- User requires assistance in the shop (looking for a certain size of shoes to try); user can use the mobile app to ‘call for help’ and grab attention of staff; staff knows where to find a client calling for assistance as they also use location-aware mobile app
- User requires assistance in the shop (looking for a certain size of shoes to try); user can use the mobile app to ‘call for help’ and grab attention of staff; staff knows where to find a client calling for assistance as they also use location-aware mobile app
RTLS RF Design
- APs should be located around zone perimeters to create a convex hull
- Each client should be within convex hull of at least 3 APs with solid RSSI (-65dBm is OK)
- It’s ideal for all tracking methods, even though AoA and Mist BLE require just 2 APs to work; still, more APs give better accuracy
- Ideally, use dedicated radio or module for RTLS to maximise location scanning performance and minimise performance impact to client-serving radios
- Ensure LOS is maintained between APs and clients (AP behind ceiling tiles is a no-no)
- Don’t mount APs too high! Not more than 4.5m is OK
- Validate secondary and tertiary signal strength in your favourite survey tool
- Cisco specific:
- Enter thick walls into Prime and ‘Enable OW (Outer Walls) Location’ in CMX to use it for calculation
- Always use FastLocate functionality (leverage client data packets and probes to calculate location)
Note, that number of APs has tripled!
Generally speaking, if the design is good for RTLS, it’s also good for any
other use case (data, voice, most high-density scenarios, etc.). Sometimes some
WiFi radios need to be put into non-client-serving mode as too much WiFi can be
damaging to the performance of the network (topic for a different discussion).
- All APs were positioned quite nicely, LOS with a client maintained everywhere within a convex hull making it slightly unrealistically great (normally possible in lab environment only).
- Laser tool was used to measure height of the APs.
- Tested with traditional Cisco and Cisco Meraki
- We have deemed Meraki Dashboard unusable for RTLS (shows only point of association and overlays all clients from all floors on every floor map) so we’ve also used Purple as an RTLS Dashboard overlay with Meraki testing
- Prime (or DNAC) is needed to create maps, place APs, set their height, azimuth, specify zones, inclusion & exclusion areas, walls, rails (wayfinding paths)
- Theoretically CMX is not required if Hyperlocation is not in use and we could connect AireOS or C9800 WLC directly to the DNAS. Unfortunately, we couldn’t do it as:
- Direct connection requires DigiCert CA Root Certificate that we don’t have on the WLC
- C9800 code version 16.12.2 is required, but 16.12.1 was newest publicly available at time of testing
- Theoretical expected accuracy of 5-7m
- Better than expected accuracy when inside the convex hull (2.55m average; 2.69m 90% error distance)
- Still good accuracy when on the edge of the convex hull (2.57m average; 3.38m 90% error distance)
- Location Computation Frequency of 11-15 seconds (with screen on, associated and active device) is not enough to offer blue dot experience but it’s still good for basic RTLS functionality like simple, static wayfinding or zone analytics with zones sized accordingly to solution accuracy
- Prime or DNAC still needed for maps
- Overall complicated setup, prone to user errors and bugs
- CMX on-prem required to do all data crunching – it’s quite a lot of data to go through!
- DNAS can be used to access presence, analytics and location data in the cloud if required
- Note, that at the time of testing DNAS was lagging behind CMX and was generally slower and less accurate than CMX!
- DNAS can also be used for many more things, like integration with 3rd party tools or Open Roaming integration (amazing idea that we feel will change the way we use public WiFi – let’s leave it for a future blog ????)
- Theoretical expected accuracy of 1-3m
- Totally brain smashing accuracy inside the convex hull (0.73m average; 0.73m 90% error distance) for a non-moving client
- Good accuracy at the edge of the convex hull (1.78m average; 2.03m 90% error distance) for a non-moving client
- Note, that accuracy of mobile clients will depend on their speed of movement and since location computation frequency is 2.3-2.4 seconds at best, the distance travelled within that timeframe will be typically added to the calculated location error distance
Let’s look at the video showing CMX app, CMX Dashboard and Matt walking around my house ????
- Accuracy is generally really good!
- Blue dot location update (location calculation frequency) of 2-3 seconds is not bad and should be enough for most indoor RTLS use cases.
- We didn’t draw rails (wayfinding paths) in Prime so what we’ve seen here is raw XY calculations displayed on the map. Rails around the path Matt’s taken would snap him into it, making blue dot appear more accurate.
- CMX has great zone path visualisations built in
and it’s generally a rarity (Purple also has it built in and it’s as good; note
that not everyone will leverage GUI-based zone paths analytics since we can use
API and visualise it ourselves and integrate it with existing tools but it
requires clearly defined requirements and solid skills and effort).
Mist: vBLE Array
- Yup, that’s it ???? Class leading simplicity. We’ve had a lab running by lunchtime and never had a chance to play with Mist before!
- All maps management, wayfinding paths, beacons and zones done easily in the Dash.
- Less than 1m inside the convex hull.
- Reliable sub second Location Computation Frequency when used with an app, making it difficult for other major WiFi vendors to compete with.
The video screams million words! Let’s take a look ????
- Absolutely mind-bending accuracy with quickest location computation frequency we’ve seen to date in indoor RTLS space!
- It is expected to still use WiFi to get network-wide presence and analytics stats, despite using BLE for location.
- Mobile app is required for the proper BLE solution to work (might not be a bad thing, since mobile app is required anyway to get the most of any indoor RTLS solution, despite the technology used).
- Mist has no zone path visualisations built in (we only have basic zone analytics) – it’s expected to leverage API to access / visualise this data.
Below is a quick summary showing results of our tests for different indoor RTLS solutions!
Location API integration with existing infrastructure – two examples!
Meraki API – Cell of Origin Example
We have recently worked on project for a beautiful, listed retail store in London, where following a very successful design and implementation of Meraki data WiFi network in the store, retail RTLS topic has emerged. With RF design crafted for data, we have faced a very real challenge – would the existing placement, type and number of APs be useful for indoor Real Time Location Services with a zone-level accuracy?What would be the challenges, limitations and reasonable expectations in terms of RTLS usage and accuracy? Could Meraki API help achieve goals set by the business?
RTLS was not in the original scope and, combined with a store physical environment, we have faced some challenges:
- RF Design: the network was designed with data in mind. We didn’t have APs placed on the outside coverage zones’ perimeters, had just 1 or 2 APs per zone in most areas and proved with a detailed WiFi survey/assessment that zone accuracy leveraging WiFi trilateration should not be expected.
- Physical Environment: the building was listed, APs/antennas mounting options limited, walls and ceiling mostly wooden, with very low attenuation. All three sections (east, west, central) had big atriums contributing to cross-floor RF leakage strongly. Building had 6 levels.
- Vendor Choice: we had Cisco Meraki and Purple already in place. Purple leverages Meraki API and uses Meraki pre-calculated XY coordinates (this can’t be changed) to display users’ location on the map. With data design, we didn’t have enough APs per zone to rely on the Meraki XY coordinates. Trilateration requires min. 3 APs in a zone to work reliably. Normally, we would have just one best AP (strongest RSSI) in every zone, with additional two APs needed for trilateration being located in adjacent zones or even a floor or two away! This has contributed to wildly inaccurate location readings in Purple (approx. 22m 90% error distance, often on a wrong floor) and could not be relied on. Note, that network-wide WiFi-based Presence & Analytics stats were perfectly reliable.
Floor diagrams below show the difference in RF Design for Data (what we have) vs RF Design for RTLS (what we would need for WiFi Trilateration to work):
Based on the additional very detailed survey (more than 100 test locations across multiple floors with 3 different device types: flagship Windows 10 laptop, Android phone and iPhone), where we temporarily installed several new APs on tripods, we concluded that achieving satisfactory and reliable zone-location accuracy (10m 90% error distance) using WiFi trilateration would require to approximately double the number of APs. The business has decided not to install additional APs and knowing that a mixture of Meraki and Purple could not offer reliable location insights and that WiFi trilateration would not be practical to use at all (because of the design, regardless of a vendor), we looked for alternative solutions and new success criteria were defined:
- Location analytics with zone accuracy was the new goal; access to zone-based stats & clients’ paths deemed critical.
- Zone sizes were increased; sometimes a zone would be as big as a 30x20m open space, sometimes as small as 8x8m room.
- Still use Purple for presence & analytics, guest splash page & social media integration.
We have gathered some facts: data & voice performance over WiFi, capacity, coverage and roaming were all rock solid across all WLANs (MAB/CWA for guests and EAP-TLS machine auth for corp) and for all test devices (company issued laptops, major OSes, newer and older phones). High density areas, like ground floor entrance hall, could get very busy during holiday periods (200+ associated devices in a small 15x20m area) and were covered by three high-gain dual-band sector antennas. 5GHz was almost free of channel contention with careful APs placement around atriums and use of properly tweaked RF Profiles: 20MHz channels width, limited max and min Tx power, disabled data rates of 11Mbps and lower. 2.4GHz was tweaked even more, with several APs having their radios off and max Tx power set to the level, where RSSI was generally lower on 2.4GHz than on 5GHz throughout the store and only OFDM rates were allowed. 2.4GHz was still considered best effort. Presence & analytics with Purple was spotless.
Switching focus to location zone analytics, we have confirmed with a detailed post-deployment survey, that our test clients were reliably associating with APs installed in the zones they were in. WiFi scans from unassociated devices taken in multiple spots in each zone revealed that we could use strongest RSSI reading from one best AP to accurately pinpoint the probing or associated device to the zone it was in. We concluded that we could potentially leverage two attributes to correlate WiFi devices with their current zones:
- Associated devices only: use MAC address of the AP the device is associated with.
- Associated OR unassociated probing devices: use MAC address of the AP that reports probing or associated device with strongest RSSI.
Two things to note:
- WiFi MAC randomisation makes it impossible to track unassociated devices that use it.
- New mobile platforms battery saving modes make those devices very quiet – they often won’t probe at all.
To further simplify our zone analytics calculations, we have decided to use just one attribute moving forward – MAC address of the AP that reports the probing or associated devices with strongest RSSI.
We have discovered that it is possible to get the RSSI attribute for every client seen by all near APs with Meraki API location data. Readings are provided every minute and contain RSSI values covering last 60 seconds. While it’s not very fast and could not be used for a blue dot experience, it is enough for our use case – historical view of zone paths and analytics.
Using strongest RSSI proved to be 95% accurate across entire building and 100+ test spots when correlating user (reporting AP) location with a zone.
Raw Data from Meraki API – note ap_mac, seen_time, client_mac and RSSI
As we know exactly which zone all the APs are installed on, we could easily generate reports showing clients paths with zone accuracy, time spent in each zone, number of clients per zone, etc. without relying on wrongly pre-calculated Meraki XY coordinates.
To automate the zone paths visualisation and zone analytics, client’s software development team has created a tool to do just that. At this point, imagination was the limit.
Sometimes we are limited by a solution functionality when trying to meet
client’s requirements. In our example, Purple could only use Meraki
pre-calculated XY coordinates and it was not practical or accurate enough (even
for a zone-wide accuracy) to use with a data / voice RF design. Let’s answer
our initial question. Do You Need RTLS RF Design for WiFi Location, Presence
& Analytics? Short answer is “no” for presence & analytics
and “it depends” for location. Presence & analytics provide us with
network-wide stats, without the location awareness and therefore will not require
RTLS design. Location, however, requires very careful RF design to provide
different levels of accuracy. With a solid data RF design, where
association and roaming trends are reliably predictable, we could expect solid zone-wide
accuracy. Anything more accurate (trilateration, Hyperlocation, vBLE) would
require more APs, detailed survey, RTLS RF design, careful placement of
APs/antennas and pedantic maps services configuration with spotless APs
positions, height and azimuth set.
Cisco CMX API – Location Analytics integration with WebEx Teams Chatbot Example
At Natilik, we’re currently in the process of upgrading our showcase with Cisco DNA. The plan is to have full SDA Fabric, C9800-based Fabric Wireless, proper RF design with Cisco 4800 APs, CMX and DNAS in one part of the office and a mixture of AP43 with BT11 in the other part. We’d love to not only showcase Cisco Hyperlocation and Mist BLE Arrays in action, but also leverage the tech to offer indoor wayfinding with turn by turn navigation and onboard guests using Hotspot 2.0 (called Open Roaming by Cisco) for our visitors WiFi.
As of today, we don’t have the new showcase fully running yet, so all we have to play with is ‘standard’ corporate WiFi design for Voice and Data.
The above shows one out of the two floors we occupy. With current design, all we can use is Cell of Origin and, around reception, WiFi Trilateration. And that’s it. Location Calculation Frequency of 11-15 seconds is not enough to offer blue dot experience, but we thought it could still be good enough to solve some wayfinding challenges!
We have Cisco AireOS Wireless with CMX, Cisco WebEx Teams and everyone has a corporate phone enrolled with Meraki MDM.
We would love to use the kit we have today to locate a colleague, zone or a meeting room by asking WebEx Teams chatbot about the location of person/location we’re after without the need to install the mobile application, as we can’t have a turn-by-turn indoor navigation just yet anyway.
Let’s imagine that Mac wants to find Matt (yeah, we don’t hold our hands all the time and sometimes attend different meetings on different floors, lol). How do I do it? How would WebEx Teams chatbot know about my or Matt’s location? How could it show or tell me how to find him? Is it really that helpful with approximately 10-12m 90% error distance accuracy? Can we still draw an indoor map showing where should Mac go to find Matt?
First, we had to set realistic expectations. We shouldn’t expect the solution to pinpoint user to his or her desk knowing, that calculated user location has 10-12m accuracy. Instead, we have decided to use zones that are big enough to account for that location accuracy.
Here are the zones we’ve created, ensuring that each zone has at least one AP. We’ve also considered expected AP association ensuring it all makes sense:
Now, we need to figure out what happens when Mac is asking WebEx Teams chatbot about Matt’s location.
Wait, what is a chatbot? Good question! Most modern enterprise messaging solutions allow to create custom chatbots with custom functionality. We are fortunate enough to have a proper coding nerd in our ranks, Darren, that finds coding chatbots as easy as you probably find putting your socks on. Darren has created NatBot (I wonder where the name comes from!), that can translate natural language with certain key words to specific actions.
To make it all fly, we’ll leverage Cisco CMX Location API, Cisco Meraki MDM API and a cloud map service (i.e. Mapwize) to visualise the results.
Finally, let’s look at detailed steps that are happening in the background when Mac is looking for Matt ????
- Mac Deryng asks NatBot via WebEx Teams: “Where is Matt Starling”?
- NatBot notes who is asking and who is he/she looking for
- Mac Deryng is asking
- He’s looking for Matt Starling
- Find correlation between names and corporate iPhones MAC addresses
- NatBot leverages Meraki MDM API to find MAC address of Mac’s phone (MDM returns MAC address)
- NatBot leverages Meraki MDM API to find MAC address of Matt’s phone (MDM returns MAC address)
- Find location of MAC address on the map and correlate it with a zone overlaid on the map
- NatBot leverages Cisco CMX Location API to find location / zone that Mac is in (CMX returns zone name)
- NatBot leverages Cisco CMX Location API to find location / zone that Matt is in (CMX returns zone name)
- Show results for Mac
- NatBot displays zone name that Matt is in and displays a map of the floor, highlighting that zone
- Additionally, NatBot displays a ‘map’ button
- Mac knows which zone Matt is in, but he’s not sure how to get there; Mac clicks on the ‘map’ button in his WebEx Teams
- NatBot builds a URL using specific Mapwaze syntax that contains start zone (Mac) and target zone (Matt) and opens that URL
- Browser displays Mapwaze service, that uses pre-created zones, lifts, staircases and paths and shows exactly how to get from start zone to target zone
Sounds complicated? Watching this short video should clear things up!
Sky is the limit
This is just the tip of the iceberg and we have some more ideas about what to do next, once the new showcase is in! ???? Here is the list:
- Add integration with voice assistants – why type when can just ask a question?
- Mac: “Alexa, where is Matt Starling?”
- Alexa: “He’s in the toilet on the 1st floor. Take a lift or stairs, go right, and right again after 10 metres. You can also see the map on your screen”
- Add integration with calendar
- Mac: “Alexa, what’s my next meeting?”
- Alexa: “Your next meeting is recording podcast with Matt. It’s in Fiennes meeting room on the 3rd floor. You’re also on the third floor. Walk out of the back office and take first left and look for second door on the right. You can also see the map on your screen”
- Add full wayfinding functionality leveraging mobile SDK
- Support both Cisco Hyperlocation and Mist BLE
- Offer full turn-by-turn indoor wayfinding
- Leverage mobile sensors to enhance the blue dot experience
- Use phone accelerometer and compass to make the experience smoother
- Offload indoor location with Hyperlocation to GPS and 5G
- Why limit yourself to just inside?
Lastly, here is some stuff that we think might save you some ball ache ????
- Location Computation Frequency for your mobile device will be affected when your screen is off or when your phone goes to sleep
- Screen off (WiFi-based RTLS): typically doubles the time needed to calculate device location; normally your mobile will go to sleep after several seconds with screen off unless some apps running in the background require connectivity
- Sleep (all methods): typically your device can’t be tracked when asleep; if apps are used, they would have to be excluded from battery saving modes for tracking to happen
- Always use NTP – AoA won’t work when AP, WLC or CMX have even slight time differences
- Components Compatibility
- Always check compatibility matrix!
- Newest software across the board (CMX, Prime, WLC) does not mean it will work (we’ve learned it the hard way)
- APs Mounting
- Mount APs carefully, especially if multi-element arrays are in use; make sure they’re level!
- Maps Services Fine-Tuning
- Set APs exact locations, height and azimuth in maps services! It MUST be spotless for the solution to work
- Don’t mix Hyperlocation with non-Hyperlocation APs
- Device associated with a non-Hyperlocation AP on will always be shown as ‘RSSI’ (and not ‘AoA’) in CMX, even if there are Hyperlocation APs nearby
- Associate WiFi Clients
- Modern devices won’t probe when not associated (with WiFi on), so tracking unassociated devices, in most cases, provide very little value (and even less with WiFi MAC randomisation)
- Use Mobile Apps
- Optional for WiFi, but can increase accuracy and sampling frequency; mandatory for BLE
- Add C9800 to CMX as ‘Unified WLC’ using SSH, as opposed to ‘WLC’ using SNMP
You’ve made it! This blog has almost 6000 words. Well done! ????
With tons of love,
WiFi Ninjas x
We have recently come across few production networks, where distance between two APs or APs and a client stations was much closer than I was comfortable with.
Natural reaction was to suggest moving radios at least few metres apart. But why exactly? What happens when two or more transmitting radios are too close to one another? How would placing a laptop next to the AP affect wireless network quality?
Intrigued and eager to answer questions that, interestingly, no one was asking, I have decided to lab it up, research it more deeply and document my findings. I quickly realised that there is not one, but two issues potentially affecting wireless transmission, where distances between radios were too short. Let’s discuss Channel Leakage and Near-Field Interference.
- Channel Leakage
- Near-Field Interference
Few months after a successful design and refresh of a WiFi estate for a financial institution in London, I came back to work on a periodic wireless survey and to assess if there is anything that would be potentially stopping them from introducing more agile working heavily relying on the new WiFi deployment.
I was told that there is a separate company that is working closely with my client in the same offices and that they use their own, separate WiFi network. They have decided to put their own APs next (few inches away) to our APs convinced that since it worked perfectly for my client, it would continue working when two overlaid networks operate simultaneously. This is how the new original vs new deployment looked like:
Having completed the survey, we have concluded that city centre location inside a multi-tenant building with multiple WiFi networks leaking from the outside and adjacent floors combined with two separate, overlaid WiFi networks contributed to very high CCI averaging at 10 or sometimes more. RF tuning across both networks has helped a lot with the contention but the overall quality of the WiFi was still not great. It felt slow despite having strong underlying infrastructure, little CCI and fast Internet pipe. Quick wireless capture has revealed excessive retransmissions rates peaking at 30% in some areas even when there were not too many clients (maybe 10 per radio, often less) competing for the airtime, channel utilisation peaking at 10% and with no obvious faults with the configuration.
Next step was to reproduce the issue in the lab, where I wanted to show how channel separation and AP-to-AP distance impacts percentage of retries in the wireless transmission.
- 2x Cisco 3702i APs registered to C9800-CL WLC broadcasting separate BSSIDs on 5GHz only
- 20MHz static non-overlapping, clean channels (100 & 104 and 100 & 140) and max Tx power (1) set
- One mobile station associated to each BSSID, running external speed test in the loop
- Ekahau Sidekick used for wireless captures
4 different tests were performed, each test involved wireless capture over 30 seconds and was repeated 5 times to minimise measurement errors:
- Channels 100 & 104 (no channel spacing)
- Test 1: APs 0 metres away from one another
- Test 2: APs 3 metres away from one another
- Channels 100 & 140 (200MHz channel
- Test 3: APs 0 metres away from one another
- Test 4: APs 3 metres away from one another
We can clearly see in Test 1, that close physical distance between radios combined with no channel separation resulted in 15.4% retries.
Introducing 200MHz channel separation (Test 3) without extending distance between radios has reduced retries ratio by about half, to 8.2%.
Moving APs 3 metres away from one another has further reduced the retries to 3.9% (Test2; no channel separation) and 2.3% (Test 4; 200MHz channel separation).
Unplanned channel leakage really is an adjacent-channel interference, even though our channels theoretically don’t overlap. ACI will naturally cause increased number of retries, and therefore decrease the throughput and contribute to the slow WiFi perception.
Note: we used flagship Cisco APs with great quality of components providing great RF accuracy. Using cheaper APs that pack cheaper antennas and radios would result in less stellar performance of spectral masks (algorithms applied to the levels of radio transmissions used to reduce main channel leaking to adjacent channels) and amplify the effects of intermodulation (signal modulation on two or more different, non-harmonic, frequencies), increasing effects of ACI and percentage of retries when reasonable channel separation and physical distance between AP radios are not maintained.
Another distance issue that I have frequently seen in an enterprise environment is placing receivers too close to transmitters.
Let’s start with a quick definition of what near-field is in wireless.
Near-field is a 1 wavelength region, where electromagnetic field EM charges and electric charge effects are extensively produced, potentially negatively affecting quality of the received transmission within this region.
Near-field interference decreases drastically, in a logarithmic fashion, when the receiver is moved farther away from the transmitter. It is normally considered enough to be 1 wavelength away from the transmitter to negate the impact of near-field interference. Near-field also affects reflected signal for Rx antennas.
Based on the above, we can conclude that:
- Radios should never be positioned closer than 1 wavelength apart from one another
- Receive antennas should not be positioned closer than one wavelength to any reflecting obstacle due to reflection indicted multi-path phase cancellation
How far is 1 wavelength? It depends on the frequency. The higher the frequency the shorter the wavelength. Here are the wavelength calculations for our beloved 802.11 bands:
2.4GHz frequency wavelength = 12.5cm
5GHz frequency wavelength = 6cm
Now we know, that when we position 2.4GHz radios closer than 12.5cm away from one another (or 6cm in 5GHz) we would suffer from extensive near-field interference and that the situation would improve greatly when we start increasing this distance. Bear in mind, that unwanted channel leakage might contribute to packets corruption here too, so it typically is recommended to keep at least few metres distance between the radios!
Couple of examples, where near-field interference can affect quality of WiFi transmission:
- Enterprise-class AP placed on a small desk with few people sitting around it and their laptops virtually adjacent to the AP; note, that external antennas can increase the negative effect of a near-field interference
- Capturing wireless packets with a capturing device positioned to close to a client or an AP
We must remember that WiFi is not NFC! ????
In this test I targeted impact of near-field interference on wireless receive quality, where receiver (AP in a sniffing mode) was within 1 wavelength of a transmitter (AP serving clients).
- 2x Cisco 3702i APs registered to Cisco 3504 WLC and one test client associated to client serving AP
- AP with blue LED is serving clients
- AP with green LED is running as a sniffer and capturing packets on the same channel as the AP serving clients
- Below tests are based on 5GHz, but in my tests I could have easily reproduced them across both 5GHz and 2.4GHz bands
It was enough to perform a very simple test here – check captured packets integrity in two scenarios:
- Test 1: AP sniffer placed 60 centimetres away from a client-serving AP (more than 1 wavelength distance between radios)
- Test 2: AP sniffer placed on top of a client-serving AP (less than 1 wavelength distance between radios)
Here are the results:
Test 1 captures, where APs are fairly far away from one another, are clean. Putting transmitting and receiving radios very close together (Test 2) results in corruption of almost all packets transmitted by client-serving AP.
When receiver is placed too close to transmitter (especially
true when the distance is less than 1 wavelength apart), near field
interference will cause packets to lose integrity and result in failed Frames
Check Sequence (FCS).
As shown in the above tests, unwanted channel leakage can seriously affect the transmission quality over distances less than few metres, especially without proper channel separation on the neighbouring BSSIDs. Near-field interference can cause corruption of most of the transmitted frames, where distance between transmitting and receiving radios is less than 1 wavelength apart. Finally, after having a chat with my friend Nigel (Twitter @WiFiNigel), we have concluded that the Rx overdrive might also play a role in the frames corruption. Unfortunately, it is difficult to ascertain which phenomena impacts the frames corruption most using the home lab, so I’ll just conclude with this: don’t stack APs! 🙂 And put them away from strong reflectors. All above issues can be easily avoided by using good quality enterprise equipment, solid RF design and having a high-level understanding of how the distance induced interference can affect the quality of the wireless transmission.
In our previous blog (please start there), we were typing in all the site IDs, WLAN IDs, API authentication tokens & Mist API HTTPS URL manually. It’s no fun, right?
Since we’re likely to interact with Mist API using one Mist account, we’ll probably use one API key globally.
Additionally, we’ll probably interact with specific organisations, sites or attributes (like WLANs) that are more ‘local’. It might be separate clients in a managed service environment or separate sites under one org. Whatever it is, it makes sense to think of it as a specific, local environment, something that is not global.
Surprise! We can define our variables on both “Environment” and “Global” level in Postman.
API token will be set as a “Global” variable, and all the rest attributes we used so far will be defined inside an “Environment” called “Mist WiFi Ninjas”.
- Use Global and Environment Variables to make our lives easier
First, note that we are not using any environments right now.
Our request still has long, manually pasted streams representing site, WLAN and Mist API URL.
Let’s create our new Environment and name it “Mist WiFi Ninjas”
Define our variables on the Environment level
Go to Globals
Define your global token.
Remember to include “Token ” prefix before pasting actual token value.
Replace our manual values with variables
Enjoy Postman environment that is easier on the eyes! Easy peasy lemon squeezy!
WiFi Ninjas x
Let’s face the truth. We can’t avoid dev stuff in WiFi forever! REST API, Python, JSON, Ansible and whatever else is needed – here we come!
It’s time. This is day 1 of our studies!
The mission for today? Actually we have a few 🙂
- Prepare the environment to work with Mist REST API using Postman
- List all WLANs created in WiFi Ninjas site using Mist API using GET
- Narrow the list down to a specific WLAN – “WiFiNinjas(.)(.)”
- Rename “WiFiNinjas(.)(.)” WLAN to “WiFiNinjasTitties” using PUT
Extreeeemely complicated, we know 😉
Let’s assume everyone knows what the API is. In case it’s not the case, here is a quick read:
Mist (and most other Enterprise solutions) use REST:
Lastly, from Mist Documentation:
Steps to complete our little task below!
You can get it here:
Token is needed so the Mist Dash can authorize us to access API.
Log into Mist Dash, then go to and hit ‘POST’:
If you hit ‘POST’ again, new token will be generated!
Take note of the “key” – it’s our token.
Let’s assume we want to list created WLANs in the test ‘WiFi Ninjas’ site.
Check API URL to list Site WLANs
Mist API is nicely documented. You can go to Mist API documentation page to check the URL for everything that’s possible using RESTful API:
We now know the syntax to get our WLANs.
Get Org ID and Site ID
Next we need to know the “WiFi Ninjas” Site ID to check against.
Go to Mist Dash. You can get Org ID and Site ID from the browser URL:
We now have everything we need to list our WLANs in ‘WiFi Ninjas’ site!
Use obtained API token, WLAN GET URL and Site ID to list the WLANs
- Create new GET Request by hitting ‘+‘
- Type https://api.mist.com//api/v1/sites/<siteID>/wlans into request URL
- Ensure to include https:// prefix!
- Go to ‘Headers‘ tab and specify (type in) Authorization (use Token obtained in previous steps in VALUE fields; ensure to include key word ‘Token ‘ before pasting in the actual token!) and Content-Type (type ‘application/json’ in VALUE field)
- Hit ‘SEND‘
Note the “id” of “WiFiNinjas(.)(.)” WLAN
Copy WLAN “id” to our GET URL
We should now see the details of just “WiFiNinjas(.)(.)” WLAN.
PS. We love that (.)(.) suffix!
Change WLAN name
Let’s rename “WiFiNinjas(.)(.)” to “WiFiNinjasTitties”! 🙂
Since we’re changing WLAN config, we’ll use PUT this time.
Change request type to PUT, go to “Body” tab, ensure “JSON” type is selected and write down lines that you want changed between curly brackets.
Note, that there is no comma at the end of the line.
You can now refresh your Mist Dash or GET the WLAN info via API to check if the name was changed.
Worked like charm! 🙂
Finally, we can use Postman to translate our actions into code (we’ll stick to Python), that can be used in scripts.
We have successfully listed all Mist WLANs, then narrowed it down to one WLAN and finally we’ve changed the name of that WLAN. All with REST API GET and PUT requests – how cool!
WiFi Ninjas x
Upgrading Cisco Catalyst 9800 software is easy and sleek.
You could use all standards protocols to put a new image on the controller: FTP, TFTP, SFTP or HTTPS.
Here are the steps:
- Download new .bin image from Cisco; I went for the newest TAC recommended image.
- On the WLC, go to Administration > Software Upgrade or simply start writing ‘upgrade’ in the search bar. Select Transport Type (I used HTTPS), bootflash File System and select newly downloaded image with .bin extension. Click ‘Download & Install‘ and confirm that you really, truly and purposefully want to do it!
- Wait for the file to finish downloading to the WLC and hit ‘Save Configuration & Reload‘ once Status is all green.
- Lastly, train your Jedi skills. Be patient.
Installation and reload is extremely fast and takes just a minute or two (at least for the CL version).
It’s simple, right? Sure! Took me a while to figure that one out.
Our goal in this post is to demo Cisco Catalyst 9800 WLC FlexConnect Configuration.
It’s assumed you’re familiar with all C9800 solution building blocks (we’ve covered it before here) but if it’s your first time, here is very quick recap:
And this is the lab. Note that VLAN 20 is now removed from the ESXi Trunk on the switch port G0/7. It is no longer needed as the AP plugged to port G0/1 will be dropping users’ data locally now.
- Since we’re leveraging FlexConnect local switching (AP puts wireless users into the network, data traffic is no longer tunneled back to the C9800 WLC), AP trunk must allow vlan 20 (that is a wireless users VLAN, local to the AP)
- C9800-CL VM is freshly deployed as shown here or it is configured for central switching as shown here
- C9800 can communicate with the network; wireless management interface (VLAN 11 in this example) is up
- AP is registered to the C9800
In this example, we still have my AP registered as ‘local’ (central switching), centrally switched SSID is up, my phone is associated and has full access following the ‘central switching deployment’ blog here.
The only places where the config is different between Central and Flex are:
- Policy Profile – sets SSID set to local switching and maps to a local VLAN
- Flex Profile – defines AP Flex attributes like AP Native VLAN, Local Auth and AP Local VLANs are specified here
- Site Tag – tells the AP to join as Flex and use specific Flex Profile
I’ll put more wording around the above only, as we’ve already covered all other relevant details in the ‘centrally switched’ blog post here.
This is how we registered AP as Flex and configured locally switched Flex WLAN.
1. Clean up the config
For simplicity, I just deleted all Profiles and Tags except of RF Profile and RF Tag (and that’s it, I didn’t delete anything else; still, don’t worry if you start with a fresh blank config :))
2. Create new WLAN profile
3. Create Policy Profile
“Central Switching” must be unticked to enable Flex Connect Local Switching; it also makes sense to untick “Central DHCP” as we’re probably happier with DHCP process being handled locally and not via a WLC. I also like to include the VLAN ID that we are mapping this Policy Profile to in the Name or Description, as we might have more Policy Profiles mapping different VLANs for different WLANs and it’s good to know what policy does what just by glancing at its name or description.
“VLAN/VLAN Group” is where you map WLAN to a VLAN! There is no direct equivalent to that mapping as we know from the AireOS. Please note that if you create a VLAN & name it (either through CLI: (config)# vlan 20; (config-vlan)# name LAB-WIRELESS-USERS or GUI: Configuration > Layer2 > VLAN) and use VLAN name to refer to it in a Policy Profile, it WILL NOT WORK! You must refer to a VLAN via its ID (and not a name, since it doesn’t exist on the AP!). If you want to refer a VLAN name here, you must specify 100% matching VLAN ID and corresponding VLAN name in the Flex Profile. See “Flex Profile” section below for more details.
4. Create Policy Tag
5. Create AP Join Profile
6. Create Flex Profile
We didn’t have to create Flex Profile for Centrally Switched WLAN, but we will need it here. We can use Flex Profile for many different things, but those are quite important:
- General Tab
- Native VLAN ID – this is where we specify AP mgmt. VLAN that the AP will be sitting in.
- Efficient Image Upgrade – this means that when we upgrade the controller code, it will be pushed to just one Flex AP (called the FlexConnect Master AP in AireOS) tagged with a Site Tag containing the same Flex Profile. The code will then be distributed to the remaining APs locally without the need to transfer it over WAN or Internet multiple times. Neat.
- Local Authentication Tab
- This is where we can specify a RADIUS server local to the AP for wireless clients authentication so it doesn’t have to be central and go through a DC somewhere far far away. Radius Server Group can also be used in a very valid scenario, where the preference is to use central RADIUS for authentication and visibility and switch to local (from AP perspective) RADIUS when the central one is down. EAP based WLANs would gain a survivalability element in case the WLC or communication to the WLC goes down. Existing clients could potentially re-authenticate and new ones could connect but bear in mind that Flex AP and WLAN in not-connected mode (WLC not reachable) would lose access to RRM and roaming optimisation mechanisms.
- Policy ACL Tab
- If you ever want to use any ACLs on APs / WLANs configured as Flex Local Switching, you must create an ACL in ‘Configuration > ACL’ and, on top of that, you MUST add this ACL under ‘Flex Profile > Policy ACL’ tab! By doing so, the specific ACL is pushed down to the AP and can be refered to (statically or via RADIUS).
- VLAN Tab
- This is where you can create VLANs that will be pushed down to the AP. Remember VLAN/VLAN Group under Access Policies Tab of the Policy Profile, where we mapped the profile to wireless users’ VLAN 20 using VLAN ID? If we’d like to refer to the VLAN by its name, we would need to have a matching VLAN/name configured here!
7. Create Site Tag
We’ve come to the last place, where Flex relevant config sits! The second we untick “Enable Local Site”, “Flex Profile” dropdown appears. For the AP to join the WLC as a Flex AP, we need to untick “Enable Local Site” and select “Flex Profile” that the AP will use.
8. Create RF Profile (for 2.4 and 5GHz) and RF Tag
Since I created them in our ‘central’ switching blog and didn’t delete them, refer to our blog here to find out more about RF Profiles and Tags.
AP(s) will now reboot and should join back as a Flex AP and broadcast our SSID:
That’s it! 🙂 We massively hope it was helpful for someone!
Tons of love,
WiFi Ninjas x
Hey! And welcome to another C9800 blog 🙂 Recently, Matt has blogged about Redundancy configuration using GUI and covered HA/SSO operation here. Today, I wanted to do a deeper dive into the topic. Enjoy!
In my lab, both C9800-CL VMs will sit on a single ESXi box. In the real world, they would rather be distributed across separate VM hosts or even separate geographical locations. In any case, configuration would stay identical and same pre-reqs are still relevant. Most importantly, both vWLCs need access to the LAN on their mgmt. interface (that will also be used by APs to register to) and a separate ‘P2P’ L2 link to form & monitor HA and sync configuration.
See a full picture of my lab below:
And to make things simple, also see a simplified logical diagram of C9800-CL networking and interfaces mapping to the VMware vSwitches:
HA/SSO nitty-gritty stuff
- HA/SSO in C9800 works differently to how it works in Aironet, it’s more like a VSS now.
- Initially, both C9800-CL WLCs will require management IP address.
- Note, that management IP is optional for a secondary WLC if you have a console access to it. Mgmt IP is no longer required to form a HA Pair
- Redundancy Management as we know it from AireOS (additional IP per WLC from the same subnet as mgmt.) doesn’t exist anymore and therefore Redundancy Port IP is no longer automatically derived from the Redundancy Management IP (it used to be 169.254. + last two octets of the Redundancy Management IP) – you have to manually specify “Redundancy Port” IP and elect one of the VM interfaces to be used as a Redundancy Port (RP)
- “Redundancy Port IP” is now called “Redundancy Local IP” (GUI) or “Local HA Interface IP” (CLI) <- same thing, just called differently in different places
- Local HA Interface IP (I’ll call it just that as we’ll use CLI to form HA/SSO in this example) should be in a different subnet to a management interface. This subnet should not be routable.
- Both WLCs are using the same mgmt. IP to maintain AP CAPWAP during failover once HA/SSO is formed
- Two units are using a dedicated Redundancy Port (now called HA-Interface) to sync
- Role election happens at boot, uses priority (1-15, default is 1; higher priority is preferred) or lowest MAC if priority is the same; two controllers are supported, not more
- It’s best practice to assign higher priority to the preferred active WLC
- Standby WLC continuously monitors Active via RP keepalives
- Gratuitous ARP is sent by a Secondary WLC that is taking over the Active role
- No preempt functionality is supported – failback, if needed, is manual
- SSO Failure Detection: 50 ms
- Reconciliation Time (Standby becoming Active): max 1020ms
- Reloading Active WLC via CLI: # reload will also reload a standby immediately
- Forming HA wipes out the config!!!
- Always form a HA first, configure later
- WLC Interface used for HA will disappear from the interfaces list (sh ip int br etc. will not list it anymore)
- HA Pair can only be formed between two WLCs of the same form factor (C9800-CL VMs in this example)
- Both WLCs must be running same code version
- Max RP RTT = 80ms, min bandwidth = 60Mbps, minimum MTU = 1500
- Both WLCs are built,
accessible, VMware networking is configured, WLCs have access to the LAN and
separate L2 link for the HA is available between the WLCs
- C9800-CL HA-Interface that we intend to use as a Redundancy Port L2 HA inter-vWLC link must be put into a separate, unused VLAN! Using existing VLAN/subnet, especially if it’s management VLAN/subnet, would theoretically work (I’ve tested it) but it will cause instability, duplicate ARP entries and ARP resolution issues. See below the ‘show logging’ output from my switch, where I had HA-Interfaces IP sitting in the mgmt. subnet:
- See full deployment guide of the C9800-CL for VMware ESXi in our previous blog here
- Prepare IP addresses and subnets; in this example we will use the following:
- Active WLC
- Chassis 1, priority 2
- Mgmt. (VLAN 11): 10.10.11.35 /24
- HA Local IP (VLAN 666): 10.10.66.35 /24 (VLAN 666
- Backup WLC
- Chassis 2, priority 1
- Initial Mgmt (VLAN 11): 10.10.11.40 /24 (optional if have console access, won’t be used anymore once HA is formed)
- Mgmt: (VLAN 11) 10.10.11.35 /24 (shared between HA WLCs once HA is formed)
- HA Local IP (VLAN 666): 10.10.66.40 /24
- Active WLC
I feel CLI gives us better visibility into what is happening on both WLCs while forming HA Redundancy, therefore we will use CLI here. It is possible to use GUI too, but I am not a huge fan of “click, wait, pray and hope for the best” approach, where I can’t see what’s happening 🙂
- Active C9800-CL
- # chassis ha-interface Gig 3 local-ip 10.10.66.35 /24 remote-ip 10.10.66.40
- # chassis 1 priority 2
- # wr
- # reload
- Standby C9800-CL
- # chassis ha-interface Gig 3 local-ip 10.10.66.40 /24 remote-ip 10.10.66.35
- # chassis 1 renumber 2
- # chassis 1 priority 1
- # wr
- # reload
Refer to our previous C9800-CL Redundancy blog written by Matt here
Note: Standby WLC would need to be accessible on its management IP address to use GUI for Redundancy configuration.
Tshoot & Validation
It is good and useful to know how to monitor, tshoot and validate HA Redundancy configuration. You can do it in both CLI (see below) and GUI (Monitoring > System > Redundancy; Dashboard > Slot: Active / Standby)
# show chassis
- Validate Chassis# and Priority. Also see the HA state (“Ready” is the final and desired stage, you can also see “Initializing” etc.) and HA-Local IP of both C9800-CL VMs.
# show chassis ha-status local
- Check before the reboot while forming the HA
- Active should have higher priority, HA Local and Remote IPs and assigned interfaces are shown, together with Chassis# and Priority that will be assigned to this local WLC upon reboot (you might have changed those values and it can be slightly confusing, so it’s best to check after configuring and before rebooting_
# show redundancy
- Another useful show command, where we can validate uptime in current state, versions, modes and more!
Want to Know More?
Yeh, totally get it – me too 😉 I’ll drop some useful stuff that I came across and used at some point here that might help with configuration and troubleshooting.
- # redundancy force-switchover
- Can be very useful in scenarios like primary DC maintenance, where Backup C9800-CL takes over. Since there is no preempt mechanism in C9800 HA (former Active WLC won’t claim its original Active role back when it comes back online)
Clear HA Configuration
- # chassis clear
- # reload
This is how it looks in the CLI:
Note: it’s enough to clear chassis information on the active HA Pair WLC, despite the information that the ‘other’ (Backup) chassis will keep its HA configuration. I’ve tested it and it will not! Backup chassis will also reboot with clear redundancy config!
- Chassis clear is used to break the HA; be careful with this as you will end up with duplicate IPs! Both former Active and Passive WLCs will share identical configuration upon reboot!
Successful HA/SSO Formation
This is how successful HA formation should look like in a console of both Active and Passive WLCs:
Successful HA/SSO Formation upon reboot once ha-interface was configured; Active (left) was elected Active due to higher priority
That’s it for now! It feels great to play around with new toys and discovering differences between old and new WLCs! Don’t hesitate to comment, add to the discussion or simply let the world know that you are enjoying beta-testing Cisco gen 1 products as much as we are 😉