Welcome!

Containers Expo Blog Authors: Pat Romanski, Elizabeth White, Liz McMillan, ManageEngine IT Matters, Jyoti Bansal

Related Topics: Containers Expo Blog, Java IoT, @CloudExpo

Containers Expo Blog: Blog Feed Post

Musings on Neural Networking By @DaveGraham | @CloudExpo #Cloud

I’ve always had a fascination with the way information is acquired and process

Given my last post was in November of 2013 (trust me, I’ve been busy), I figured I’d start out with a heady topic like “Neural

Networking” in an age where Deep Machine Learning and perhaps its lesser cousin, assisted Machine Learning (I’ll define in a bit), seem to be all the rage.  However, before we begin, I want to make a few things clear:

  • I’m no expert in these fields.
  • I’m musing out loud here.  You’re my audience and what you determine to be salient and what you deem junk is, well, your problem, not mine.
  • DML/AML, Neural Networking, and a whole host of other terms, acronyms, mindf**k level events, etc. are here. Deal with it.

So with such an illustrious preface, I suppose we should let the party begin.

I’ve always had a fascination with the way information is acquired and process. Reading back through the history of this site, you can see this tendency towards more fanciful thinking, e.g., GPGPU assisted network analytics, future storage systems using Torrenza-style processing.  What has once been theory has made its way into the realm of praxis; looking no further than ICML 2015, for example, to see the forays into DML that nVidia is making with their GPUs.  And on the story goes.  Having said all this, there are elements of data, of data networking, of data processing, which, to date, have NOT gleaned all the benefits of this type of acceleration.  To that end, what I am going to attempt to posit today is an area where Neural Networking (or at least the benefits therein) can be usefully applied to an area interacted with every single nanosecond of every day: the network.

Glossary:
Before we get much further, we should probably have a definition of some terms that I will be using:

  • Deep Machine Learning (DML): burgeoning area of machine learning research focused on machine intelligence utilizing underlying principles of neural networking
  • Assisted Machine Learning (aka Hybrid; AML): a half-step towards DML where pre-pended processing is done by fixed systems within a rough grid approach  and learning takes place on these processed chunks of data.
  • Neural Networking: “a computing system made up of a number of simple, highly interconnected processing elements, which process information by their dynamic state response to external inputs.” (In “Neural Network Primer: Part I” by Maureen Caudill, AI Expert, Feb. 1989)
  • Packet Forwarding Engines (PFE): base level of hardware in a contemporary network switch

State of the Union: Networks
To talk about the future, some mention is needed of the current état de fait of systems networking.

Packet Forward Engines (PFEs) are the muscle of networking switches. Today, we’re facing routinely more powerful PFEs, both custom as well as mainline/merchant.  Companies like Cisco, Broadcom, Xpliant, Intel, Marvel, Juniper, etc. have propagated designs and delivered ever-increasingly scalable devices that can process billions of bits of information at a time.  The traceable curve here closely follows an analog of Moore’s law while not exactly staying within the same bounds (e.g. I could point out that Broadcom’s Trident/Trident+ compared to the currently shipping Trident 2 are not all that far removed from each other both in frequency, scale, latency, and processing power).  If we allow for interstitial comparisons cross-vendor, the story changes somewhat and, to my mind, the curve becomes even more pronounced.  Comparing custom silicon from Juniper or Cisco to that of Broadcom, for example, shows a higher level of capability present in these more custom designs, albeit with a slower time to market.  All this is being said by way of pointing out that compared to host-level development of processors (like Intel’s Xeon/Core and AMD‘s APU/CPU line ups), these specialized processing units have a different scale in/scale out process.  Consequently, their application has been mostly stagnant; a switch line or two released with a regular cadence of roughly 18 months or so, interspersed by the next important part of networking: the software.

Software development is as critical to the current state of networking as the hardware is.  Relying on fixed pipeline devices (as the Trident 2 is), requires a certain level of determinism to be designed into the software that controls it.  With the seminal development of software development kits (SDKs), the de-coupling has allowed for vendors to write against a known set of functions with a healthy separation from the underlying hardware.  This abstraction has both accomplished a level of increasing functionality and capability within the systems (e.g. Broadcom’s concept of a programmable unified forwarding table (UFT)),  as well as allowing for agile development of the overlaying software (e.g. quicker time to market for a network operating system (NOS) built on top of said SDK).  Having this level of functionality is important as it allows more agile decisions to be made as standards or protocols are ratified for implementation.    An NOS is only as capable as the hardware it lies upon, however, and that leads us to the third part of the current network: the control plane processing.

The control plane of a network switch is the brain of the operations. A PFE is useless as a commodity processor.  If you examine its structure closely, its functional blocks are designed for very purpose driven applications.  This type of processing, while important for the datagrams it will functionally serve, is useless for running more banal applications like an NOS.  However, generic processing hardware, like PowerPC, MIPS, ARM, or even x86 cores can be harnessed to manage this type of workload very effectively.  In recent years, there has been increasing momentum to moving these control plane processing entities from more archaic and proprietary architectures like PPC and MIPS, to more modern and commercially available standards like ARM and x86.  This move has allowed for modernizing the control plane from an embedded system to a discrete “system on a switch” running modern operating systems and either virtualizing the NOS (e.g. like Juniper’s QFX5100 switch line) or partitioning via containers or some other level of abstraction.  The benefits of such systems cannot be ignored as again, time to market and feature development becomes more agile in nature.  (Side note: the role of ARM as a valid control plane foundation cannot be overlooked and will be the subject of another post at some point in the not-so-distant future).

In summary, the current networking switch present in the data center is comprised of a PFE, a network operating system (NOS), and a control plane to run the NOS. This is not unlike a commodity server with lots of physical interfaces designed for ingress and egress of data.  These switches are increasingly complex and performance-heavy and provide a robust foundation upon which to build neural networks.

Becoming Neural, not Neurotic
When you walk into your living room, tell your Xbox One to turn itself on (“Xbox On!”) and watch as the always-listening machine powers up your TV and itself and then scans you really quick to determine identity, you’re watching machine learning in action. This process makes use of both audio and visual queuing and localization of data (a core component of neural networking) to derive identity and causality.  You had to walk through a setup process to both capture your image as well as your vocalization.  This was stored in a local database and used as a reference point.  The system is given rough control points to operate against but is functionally able to interact against this baseline; case in point, depending on my level of beard growth or not, my Xbox has various levels of success in determining who I am by sight.  The same goes for my iPhone, my Android, my Amazon Echo, etc.  Each of these machines has a minimal database connected to a backend process (the “cloud” or another hosted platform) and performs a fixed function (voice recognition, facial recognition).  All this explanation is to demonstrate that we’re in the throes of neural networks without even realizing.  If we look at the network as a necessary part of this process, it becomes the springboard for incredible capability.

So how can a transport layer become “neural”?  Looking back at our definition of “neural networks” we see that at its very foundation is the concept connectedness.  A network is a collection of interconnected devices using some sort of medium, whether copper, optical, or radio frequency that allows them to interoperate or exchange data.  Transporting data, whether electrical, radio frequency, or optical, is just that: transport.  It implies neither intelligence nor insight.  The sender and the receiver, however, can operate on data and make decisions with some level of determinism, though, and this is where we will focus.  Historically, one would look for the systems attached to the transport layer as the true members of the network.  However, as noted previously, with the advent of “system on a switch” control planes, suddenly we have the appearance of systems as joining points, not just transport pipes.

Moving further, if these transport junctions or pipes suddenly develop the intelligence, based on no other inputs but data, to route “conversations” or data in ways that logically make sense and have derived value to either the sender, receiver, or both, have we achieved a neural network? We can see some basic interworkings of this in the use of LLDP (link layer discovery protocol) as a low level exchange of “who are you?” information, but this is derived from extant specifications of what a datagram should look like.  This isn’t flaunting the concepts of neural networking but belies that data, exclusive of content and context, is known already.  So, the next logical leap is how that data is interpreted.

Let’s presuppose that LLDP has provided two neighboring switches with the identity, capability, and proximity to each other.  What then?  As hosts are connected one side to another, data will flow based on the hosts requirements for connectedness and data.  The transport layer, at that point, is nothing more than transport; simple forwarding devices.  However, let’s also assume that these two switches have a system attached to each respective control plane that is constantly watching traffic as it flows across and is “learning.”  What these switches are learning can be perceived as raw input and can be manipulated and quantified as such.  In a neural networking world, these systems are nascent; raw with no heuristic capability as yet designed.

The situation described above is precisely why networking systems function so completely today.  They’re not tasked with anything beyond fixed parameters or inspection.  Think of it:  IETF and IEEE have specified what a datagram should look like.  It should have Layer-2 source and destination media access control (mac) address along with payload, for example.  But beyond this, what is accomplished?  The PFE is looking for datagrams that conform to these standards to pass along; anything else is malformed and dropped.  You quickly reach a situation where, heuristically, you’re limiting the overall potential of these machines to be simple engines, receiving parameters and doing as told.  What, then, could be done?

Vision Casting
I can sit here and postulate any number of ideas that my peers have already done.  I’m more interested in what we can do with the data that is already present.  We can argue that daemons that run in the kernel, statistic packages that collect PFE-published data points, or other such utilities are useful.  In a way, they are, but they represent a subset of capabilities and are mostly human driven (AML at its finest).  What if, however, each time a request is made, the switch learns what data points are being requested and viewed and is able to selectively feed only the most salient points back to its consumers without flooding tons of useless information?  What if this is a priori to a receiver (in the classic SNMP use case)? What if this is machine driven (DML) and becomes part of the flow?

For a network to become “aware” and fully realized as neural in nature (and presupposing the eventual coupling of machine state to machine state thru a hyperaware network as my conclusion) it must be able to functionally process data on its own, either by simple heuristic learning (profiling, as noted above, is just one method) or through the contrived mechanisms of its NOS in a non-rigid manner (e.g. not L2 learning, etc.)  Certainly the use of standardized protocols for initial communication is encouraged, since it can engage heterogenous systems together in communication without other proprietary lower-level protocols like HiGig, but beyond this initial negotiation, the hope and desire is that learning, forwarding, reporting, and engaging become autonomous and self-forming.  As systems interact, then, decisions will be made based on what the datagram contains, the way the PFE is responding to traffic flows and utilization, and also what the next connected device is doing.  This capability is present, to some extent, today in systems that use a network management system (NMS) that wholistically can see the network for what it is, but this external intelligence, is again, driven from the outside in and not organic to the devices themselves.

Conclusion
I’ve laid out what I hope is the framework for an ongoing discussion of neural networks (without delving into AML/DML this go around) and their role within the actual network space.  I’m curious as to your thoughts (constructive, please).

Read the original blog entry...

More Stories By Dave Graham

Dave Graham is a Technical Consultant with EMC Corporation where he focused on designing/architecting private cloud solutions for commercial customers.

@ThingsExpo Stories
New competitors, disruptive technologies, and growing expectations are pushing every business to both adopt and deliver new digital services. This ‘Digital Transformation’ demands rapid delivery and continuous iteration of new competitive services via multiple channels, which in turn demands new service delivery techniques – including DevOps. In this power panel at @DevOpsSummit 20th Cloud Expo, moderated by DevOps Conference Co-Chair Andi Mann, panelists will examine how DevOps helps to meet th...
DevOps at Cloud Expo – being held October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA – announces that its Call for Papers is open. Born out of proven success in agile development, cloud computing, and process automation, DevOps is a macro trend you cannot afford to miss. From showcase success stories from early adopters and web-scale businesses, DevOps is expanding to organizations of all sizes, including the world's largest enterprises – and delivering real r...
Most technology leaders, contemporary and from the hardware era, are reshaping their businesses to do software in the hope of capturing value in IoT. Although IoT is relatively new in the market, it has already gone through many promotional terms such as IoE, IoX, SDX, Edge/Fog, Mist Compute, etc. Ultimately, irrespective of the name, it is about deriving value from independent software assets participating in an ecosystem as one comprehensive solution.
In his keynote at @ThingsExpo, Chris Matthieu, Director of IoT Engineering at Citrix and co-founder and CTO of Octoblu, focused on building an IoT platform and company. He provided a behind-the-scenes look at Octoblu’s platform, business, and pivots along the way (including the Citrix acquisition of Octoblu).
SYS-CON Events announced today that A&I Solutions has been named “Bronze Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Founded in 1999, A&I Solutions is a leading information technology (IT) software and services provider focusing on best-in-class enterprise solutions. By partnering with industry leaders in technology, A&I assures customers high performance levels across all IT environments including: mai...
SYS-CON Events announced today that Systena America will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Systena Group has been in business for various software development and verification in Japan, US, ASEAN, and China by utilizing the knowledge we gained from all types of device development for various industries including smartphones (Android/iOS), wireless communication, security technology and IoT serv...
Every successful software product evolves from an idea to an enterprise system. Notably, the same way is passed by the product owner's company. In his session at 20th Cloud Expo, Oleg Lola, CEO of MobiDev, will provide a generalized overview of the evolution of a software product, the product owner, the needs that arise at various stages of this process, and the value brought by a software development partner to the product owner as a response to these needs.
Five years ago development was seen as a dead-end career, now it’s anything but – with an explosion in mobile and IoT initiatives increasing the demand for skilled engineers. But apart from having a ready supply of great coders, what constitutes true ‘DevOps Royalty’? It’ll be the ability to craft resilient architectures, supportability, security everywhere across the software lifecycle. In his keynote at @DevOpsSummit at 20th Cloud Expo, Jeffrey Scheaffer, GM and SVP, Continuous Delivery Busine...
SYS-CON Events announced today that Outscale will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Outscale's technology makes an automated and adaptable Cloud available to businesses, supporting them in the most complex IT projects while controlling their operational aspects. You boost your IT infrastructure's reactivity, with request responses that only take a few seconds.
SYS-CON Events announced today that Progress, a global leader in application development, has been named “Bronze Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Enterprises today are rapidly adopting the cloud, while continuing to retain business-critical/sensitive data inside the firewall. This is creating two separate data silos – one inside the firewall and the other outside the firewall. Cloud ISVs ofte...
SYS-CON Events announced today that Interoute has been named “Bronze Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Interoute is the owner operator of Europe's largest network and a global cloud services platform, which encompasses over 70,000 km of lit fiber, 15 data centers, 17 virtual data centers and 33 colocation centers, with connections to 195 additional partner data centers. Our full-service Unifie...
SYS-CON Events announced today that CollabNet, a global leader in enterprise software development, release automation and DevOps solutions, will be a Bronze Sponsor of SYS-CON's 20th International Cloud Expo®, taking place from June 6-8, 2017, at the Javits Center in New York City, NY. CollabNet offers a broad range of solutions with the mission of helping modern organizations deliver quality software at speed. The company’s latest innovation, the DevOps Lifecycle Manager (DLM), supports Value S...
SYS-CON Events announced today that Enzu will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY, and the 21st International Cloud Expo®, which will take place October 31-November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA. Enzu’s mission is to be the leading provider of enterprise cloud solutions worldwide. Enzu enables online businesses to use its IT infrastructure to their competitive ad...
SYS-CON Events announced today that Peak 10, Inc., a national IT infrastructure and cloud services provider, will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Peak 10 provides reliable, tailored data center and network services, cloud and managed services. Its solutions are designed to scale and adapt to customers’ changing business needs, enabling them to lower costs, improve performance and focus intern...
Everywhere we turn in our industry we can find strong opinions about the direction, type and nature of cloud’s impact on computing and business. Another word that is used in every context in our industry is “hybrid.” In his session at 20th Cloud Expo, Alvaro Gonzalez, Director of Technical, Partner and Field Marketing at Peak 10, will use a combination of a few conceptual props and some research recently commissioned by Peak 10 to offer a real-world consideration of how the various categories of...
Detecting internal user threats in the Big Data eco-system is challenging and cumbersome. Many organizations monitor internal usage of the Big Data eco-system using a set of alerts. This is not a scalable process given the increase in the number of alerts with the accelerating growth in data volume and user base. Organizations are increasingly leveraging machine learning to monitor only those data elements that are sensitive and critical, autonomously establish monitoring policies, and to detect...
SYS-CON Events announced today that SoftLayer, an IBM Company, has been named “Gold Sponsor” of SYS-CON's 18th Cloud Expo, which will take place on June 7-9, 2016, at the Javits Center in New York, New York. SoftLayer, an IBM Company, provides cloud infrastructure as a service from a growing number of data centers and network points of presence around the world. SoftLayer’s customers range from Web startups to global enterprises.
The 21st International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Digital Transformation, Machine Learning and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding busin...
Multiple data types are pouring into IoT deployments. Data is coming in small packages as well as enormous files and data streams of many sizes. Widespread use of mobile devices adds to the total. In this power panel at @ThingsExpo, moderated by Conference Chair Roger Strukhoff, panelists will look at the tools and environments that are being put to use in IoT deployments, as well as the team skills a modern enterprise IT shop needs to keep things running, get a handle on all this data, and deli...
SYS-CON Events announced today that Loom Systems will exhibit at SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Founded in 2015, Loom Systems delivers an advanced AI solution to predict and prevent problems in the digital business. Loom stands alone in the industry as an AI analysis platform requiring no prior math knowledge from operators, leveraging the existing staff to succeed in the digital era. With offices in S...