Update to WLAN Vendor Tiers

Two years ago I posted a list of what I thought were the current state of Wireless LAN Vendors into three tiers. It received quite a few comments, and I thought it high time to revisit this list. (plus a little nudge from Zaib over at http://www.wlanbook.com.

This is not some ‘Gartner Magic Quadrant’ type thing. No hard data, like from a Dell’Oro Group report. This is just my personal opinion of where these fall. Not a ranking by quality, or by technology… just a ‘gut feel’ from what I see out in the marketplace. They are just random inside the Tiers. I was not about to try and rank these within tiers… that would take more research and numbers… then this wouldn’t be a ‘gut feel’ but measured.

I would love to hear what you think. Did I miss any major vendor? Any of these placed in the wrong Tier?

Tier One

• Cisco
• Aruba
• Motorola

Tier Two

• Ruckus
• Aerohive
• Meraki
• Ubiquiti
• Hewlett Packard
• Xirrus
• D-Link
• Meru
• Enterasys/Siemens
• Trapeze

Tier Three

• Senao/Engenius
• Mikrotik
• Bluesocket
• 3Com
• LANCOM
• Extricom
• Proxim Wireless
• Belkin
• Linksys
• Netgear
• Fon
• SMC
• RealTek
• TrendNet
• ZyXEL

There are other Vendors who work in more Niche space like FireTide and Belair that I haven’t added to any of these tiers. Or those like Extreme that just OEM someone else’s product lines.

This is purely one man’s opinion… what are your opinions? Who should be moved between tiers, who should be added or removed? What WLAN vendors do you see in your space?

The “Magic” of Wireless Mesh

This document is also available for download via a PDF White Paper.

The Wireless Mesh Cost vs Throughput Spreadsheet.

 

The “Magic” in magic is really just a combination of illusion and mis-direction.  And yet we are entertained by being convinced we’ve seen something that breaks known physical laws.

We know the woman really isn’t being sawn in half, yet we don’t mind suspending reality for a couple of minutes while we try and figure out how the magician is doing his magic.

In the world of Wireless Mesh, sometimes WLAN professionals get too caught up in the mis-direction and illusion of getting something for nothing that we forget all about the laws of physics that determine connections and throughput and watch as our customers suspend reality hoping to get something for nothing, and not paying any penalties.

In reality, there is nothing “magic” about Wireless Mesh. It follows known laws concerning RF propagation, packet transfers, and network packet protocols.

I believe that Wireless Mesh does have it’s place in WLAN Design… but many people, in their quest to save a bit of money end up ruining their Wi-Fi network by employing mesh incorrectly.

To emphasize this point, I’ve developed an Excel Spreadsheet and made it available to download. (Link to Mesh Analysis Spreadsheet) – this spreadsheet, like all good spreadsheets, pulls the variables out where you can see them. All the fields colored in Green are the input points for the algorithms. You, as a WLAN designer can choose your own amounts for these.

Here are the variables you can enter to drive the equations in the Spreadsheet:

• Expected net TCP data rate on the 2.4GHz Access Frequency
  • I started using a value of 25Mbs to reflect a network where the bulk of the client devices are still 802.11g
• Expected net TCP data rate on the 5GHz Mesh Frequency
• This is estimated at a value consistent with an 802.11n connection
• Remember – the Mesh AP’s must be within range to have great SNR to maintain this data throughput!
• Number of Clients per 2.4GHz Access Point
• Cost of a wired Ethernet Backhaul connection
• Including Cat 5e cabling, installation, and cost for a switch port
• Sample Size of the Mesh Network
• number of Access Points to provide coverage for clients, as well as enough Mesh AP’s to maintain high throughput speeds between 5GHz Mesh RF connections.
• Average Loss in Percentage per additional Hop.
  • I’ve started with the minimum loss of 50%, in actuality there could be 10% to 15% more loss because of overhead and other issues.

802.11g	2.4GHz dedicated to Access	25	Mbs
802.11an	5GHz dedicated to Mesh	75	Mbs
Number of Clients per Access Point		25	Clients/AP
Cost Per Access Point – Installed		$600	/AP
Cost per wired Backhaul Connection		$400	/Cable Drop & Switch Port
Sample Size of Wireless Mesh Network		50	Access points
Average Loss per each additional hop		60%	% loss

 

Remember, you are the one to make these assumptions. This is not something that I’m making up – you put in your actual costs, size of system, assumptions on data throughput and number of clients per access point.

You can use this spreadsheet to work with your customers/clients to help them better understand the value and costs of providing Wireless Mesh versus other alternatives like Ethernet cable or a dedicated Wireless Bridge.

As an aside, I like to keep these in order both in my mind, as well as in the mind of my customers. Order of AP backhaul desired:

• Fiber
• Copper
• Dedicated Wireless Bridge
• One-Hop Wireless Mesh
• and way down here in the very last position
• a Multi-Hop Wireless Mesh

 

Also remember the first hop is ‘free’ – only kind of – since there isn’t the requisite 50% loss on this first hop. The receiving Mesh AP doesn’t need to re-transmit the packet on the 5GHz channel. The client packet comes into AP #1 on 2.4GHz, AP #1 then re-transmits the packet on 5GHz, then AP #2 receives the packet and places it directly on it’s Ethernet port.

But for subsequent Mesh Hops, AP #2 would have to re-transmit the packet on the same 5GHz channel it came in on… thus the 50% drop (Plus additional loses due to overhead issues) Each subsequent hop also results in this drastic degradation of data throughput.

Here are some graphical examples of this process of going to multiple hops. The horizontal access is number of Mesh AP’s – one more than the Mesh Hop (two meshed AP’s equals one Mesh Hop).

Note the gradual reduction in total cost as you add more Mesh Hops. It is true that adding Mesh rather than Ethernet will save you money, but only on the installation costs, not the actual cost of the Access Point.  But also note the drastic drop in throughput as you add more hops.

In this graph we can see as the average cost per installed AP drops (savings from the Ethernet cabling costs as you go with more and more Mesh Hops) the actual cost per kilobyte for each end user skyrockets. This is a function of more and more client devices sharing less and less actual Ethernet backhaul.

In this final graph we’ll focus on comparing the savings in percentage of lowered backhaul costs, compared with the loss of throughput. The “Sweet Spot” is at two Mesh AP’s or one Mesh Hop. Each additional Mesh Hop barely adds much in the way of cost savings, but instead has a huge drop in throughput.

Learn from the experience of others, and don’t get caught with a Wireless Mesh system that doesn’t provide for the requirements of your client devices.

Wireless Mesh isn’t “Magic” – it’s merely an illusion of cost savings – you still can’t break the laws of physics.

 

(a note that I’m not talking about Strix or Firetide Wireless mesh so hold your comments on those vendor’s proprietary solutions)

 

Seeing Patterns in Random Data

What we are after is very consistent data connections for our customers and clients. Below is one way to help quantify that your Wireless LAN is giving your clients consistent results. I know not everyone enjoys statistics… but sometimes with just a little massaging of data, in this case sorting the data first, will help allow you to see patterns–information–in your data. Rather than just take a single sample of data throughput, take a bunch. In this case I took 25 samples – the more the better. Now you can see more than a single snapshot in time – but a set of datapoints that we can learn much more from than a single point.

When looking at collected data, sometimes it seems to be quite random in nature. Looking at this random data, folks can make mistakes in analysis. One method we use to help ‘clean up’ this random data is to first sort the collected data from high to low, and graph according to percentage. This allows us to see graphically the differences between data sets.

As an example, I’ve put together the following sample data sets. Each has the exact same Maximum, Minimum and Average… but obviously, much different results. This is the value of this sorting method, it allows one to quickly see differences in data.

Maximum	20
Minimum	5
Average	11.36
Datapoints	25

The first is a graph showing the two sets of data, fairly random looking. Both look like they are quite similar in nature, both inconsistent, and with a fairly same average.

But when you take this same information and sort it first, you can see distinct differences in the resulting graphs. One set of data is much more consistent than the other. Even though they both have the same averages.

We’d like to see very flat lines, showing customer experiences to be fairly consistent across the board. The higher the lines the higher the client’s throughput results.

A line with it’s curve toward the bottom left represents a fairly low consistent result. A diagonal line represents high variability – more inconsistency. A line with the curve in the upper right represents consistently higher results.

Another way to use these ‘sorted’ graphs is to look at the 50% line – this represents the ‘average’ someone would achieve. The 80% line on the bottom represents that 80% of all collected data meets or exceeds this number.

This is a good telltale sign for following the 80/20 rule. Don’t waste too much time and money trying to fix the last 20% – put the bulk of your resources towards getting the 80% to be as consistent (flat) as possible.

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