Category: Strategic planning

The Mac 30 years on

Posted on by Ray in Executive leadership, Strategic Inflection Points, Strategic planning, Visionary leadershp

I have to admit it. I have been a Mac and Apple bigot since 1984. I saw the commercial for the Mac and just had to have one. I saw the Lisa, a Mac precursor at a conference in town and was very impressed.

At the time, we were using these green or orange screens at work connected to IBM mainframes running TSO or VM/CMS and we thought we were leading edge.

And then the Mac comes out with proportional fonts, graphics terminal screen, dot matrix printing that could print anything you could possibly draw, a mouse and a 3.5″ floppy.

Somehow my wife became convinced and bought our family’s first Mac for her accounting office. You could buy spreadsheet and a WYSIWIG Word processor software and run them all in 128KB. She ended up buying Mac accounting software and that’s what she used to run her office.

She upgraded over the years and got the 512K Mac but eventually when  she partnered with two other accountants she changed to a windows machines. And that’s when the Mac came home.

I used the Mac, spreadsheets and word processing for most of my home stuff and did some programming on it for odd jobs but mostly it just was used for home office stuff. We upgraded this over the years, eventually getting a PowerMac which had a base station with a separate CRT above it, but somehow this never felt like a Mac.

Then in 2002 we got the 15″ new iMac. This came as a half basketball base with a metal arm emerging out of the top of it, with a color LCD screen attached. I loved this Mac. We still have it but nobody’s using it anymore. I used it to edit my first family films using an early version of iMovie. It took hours to upload the video and hours more to edit it. But in the end, you had a movie on the iMac or on CD which you could watch with your family. You can’t imagine how empowered I felt.

Sometime later I left corporate America for the life of a industry analyst/consultant. I still used the 15″ iMac for the first year after I was out but ended up purchasing an alluminum Powerbook Mac laptop with my first check. This was faster than the 15″ iMac and had about the same size screen. At the time, I thought I would spend a lot out of time on the road.

But as it turns out, I didn’t spend that much time out of the office so when I generated enough revenue to start feeling more successful, I bought a iMac G5. The kids were using this until last year when I broke it. This had a bigger screen and was definitely a step up in power, storage and had a  Superdrive which allowed me to burn DVD-Rs for our family movies. When I wasn’t working I was editing family movies in half an hour or less (after import) and converting them to DVDs. Somewhere during this time, Garageband came out and I tried to record and edit a podcast, this took hours to complete and to export as a podcast.

I moved from the PowerBook laptop to a MacBook laptop. I don’t spend a lot of time out of the office but when I do I need a laptop to work on. A couple of years back I bought a MacBook Air and have been in love with it ever since. I just love the way it feels, light to the touch and doesn’t take up a lot of space. I bought a special laptop backpack for the old MacBook but it’s way overkill for the Air. Yes, it’s not that powerful, has less storage and  has the smaller screen (11″) but in a way it’s more than enough to live with on long vacations or out of the office

Sometime along the way I updated to my desktop to the aluminum iMac. It had a bigger screen, more storage and was much faster. Now movie editing was a snap. I used this workhorse for four years before finally getting my latest generation iMac with the biggest screen available and faster than I could ever need (he says now). Today, I edit GarageBand podcasts in a little over 30 minutes and it’s not that hard to do anymore.

Although, these days Windows has as much graphic ability as the Mac, what really made a difference for me and my family is the ease of use, multimedia support and the iLife software (iMovie, iDVD, iPhoto, iWeb, & GarageBand) over the years and yes, even iTunes. Apple’s Mac OS software has evolved over the years but still seems to be the easiest desktop to use, bar none.

Let’s hope the Mac keeps going for another 30 years.

Photo Credits:  Original 128k Mac Manual by ColeCamp, 

my original Macintosh by Blake Patterson, 

Brand new iMac, February 16, 2002 by Dennis Brekke

MacBook Air by nuzine.eu

iMac Late 2012 by Cellura Technology

HDS Influencer Summit wrap up

Posted on by Ray in Block Storage, Cloud services, Cloud storage, Decision making, Disk storage, Executive leadership, File Storage, Information economy, Object storage, Server virtualization, Storage, Storage architecture, Storage availability, storage economics, Strategic planning, System effectiveness

[Sorry for the length, it was a long day] There was an awful lot of information suppied today. The morning sessions were all open but most of the afternoon was under NDA.

Jack Domme,  HDS CEO started the morning off talking about the growth in HDS market share.  Another 20% y/y growth in revenue for HDS.  They seem to be hitting the right markets with the right products.  They have found a lot of success in emerging markets in Latin America, Africa and Asia.  As part of this thrust into emerging markets HDS is opening up a manufacturing facility in Brazil and a Sales/Solution center in Columbia.

Jack spent time outlining the infrastructure cloud to content cloud to information cloud transition that they believe is coming in the IT environment of the future.   In addition, there has been even greater alignment within Hitachi Ltd and consolidation of engineering teams to tackle new converged infrastructure needs.

Randy DeMont, EVP and GM Global Sales, Services and Support got up next and talked about their success with the channel. About 50% of their revenue now comes from indirect sources. They are focusing some of their efforts to try to attract global system integrators that are key purveyors to Global 500 companies and their business transformation efforts.

Randy talked at length about some of their recent service offerings including managed storage services. As customers begin to trust HDS with their storage they are start considering moving their whole data center to HDS. Randy said this was a $1B opportunity for HDS and the only thing holding them back is finding the right people with the skills necessary to provide this service.

Randy also mentioned that over the last 3-4 years HDS has gained 200-300 new clients a quarter, which is introducing a lot of new customers to HDS technology.

Brian Householder, EVP, WW Marketing, Business Development and Partners got up next and talked about how HDS has been delivering on their strategic vision for the last decade or so.    With HUS VM, HDS has moved storage virtualization down market, into a rack mounted 5U storage subsystem.

Brian mentioned that 70% of their customers are now storage virtualized (meaning that they have external storage managed by VSP, HUS VM or prior versions).  This is phenomenal seeing as how only a couple of years back this number was closer to 25%.  Later at lunch I probed as to what HDS thought was the reason for this rapid adoption, but the only explanation was the standard S-curve adoption rate for new technologies.

Brian talked about some big data applications where HDS and Hitachi Ltd, business units collaborate to provide business solutions. He mentioned the London Summer Olympics sensor analytics, medical imaging analytics, and heavy construction equipment analytics. Another example he mentioned was financial analysis firms usingsatellite images of retail parking lots to predict retail revenue growth or loss.  HDS’s big data strategy seems to be vertically focused building on the strength in Hitachi Ltd’s portfolio of technologies. This was the subject of a post-lunch discussion between John Webster of Evaluator group, myself and Brian.

Brian talked about their storage economics professional services engagement. HDS has done over 1200 storage economics engagements and  have written books on the topic as well as have iPad apps to support it.  In addition, Brian mentioned that in a late The Info Pro survey, HDS was rated number 1 in value for storage products.

Brian talked some about HDS strategic planning frameworks one of which was an approach to identify investments to maximize share of IT spend across various market segments.  Since 2003 when HDS was 80% hardware revenue company to today where they are over 50% Software and Services revenue they seem to have broaden their portfolio extensively.

John Mansfield, EVP Global Solutions Strategy and Development and Sean Moser, VP Software Platforms Product Management spoke next and talked about HCP and HNAS integration over time. It was just 13 months ago that HDS acquired BlueArc and today they have integrated BlueArc technology into HUS VM and HUS storage systems (it was already the guts of HNAS).

They also talked about the success HDS is having with HCP their content platform. One bank they are working with plans to have 80% of their data in an HCP object store.

In addition there was a lot of discussion on UCP Pro and UCP Select, HDS’s converged server, storage and networking systems for VMware environments. With UCP Pro the whole package is ordered as a single SKU. In contrast, with UCP Select partners can order different components and put it together themselves.  HDS had a demo of their UCP Pro orchestration software under VMware vSphere 5.1 vCenter that allowed VMware admins to completely provision, manage and monitor servers, storage and networking for their converged infrastructure.

They also talked about their new Hitachi Accelerated Flash storage which is an implementation of a Flash JBOD using MLC NAND but with extensive Hitachi/HDS intellectual property. Together with VSP microcode changes, the new flash JBOD provides great performance (1 Million IOPS) in a standard rack.  The technology was developed specifically by Hitachi for HDS storage systems.

Mike Walkey SVP Global Partners and Alliances got up next and talked about their vertical oriented channel strategy.  HDS is looking for channel partners perspective the questions that can expand their reach to new markets, providing services along with the equipment and that can make a difference to these markets.  They have been spending more time and money on vertical shows such as VMworld, SAPhire, etc. rather than horizontal storage shows (such as SNW). Mike mentioned key high level partnerships with Microsoft, VMware, Oracle, and SAP as helping to drive solutions into these markets.

Hicham Abhessamad, SVP, Global Services got up next and talked about the level of excellence available from HDS services.  He indicated that professional services grew by 34% y/y while managed services grew 114% y/y.  He related a McKinsey study that showed that IT budget priorities will change over the next couple of years away from pure infrastructure to more analytics and collaboration.  Hicham talked about a couple of large installations of HDS storage and what they are doing with it.

There were a few sessions of one on ones with HDS executives and couple of other speakers later in the day mainly on NDA topics.  That’s about all I took notes on.  I was losing steam toward the end of the day.

Comments?

Insecure SHA-1 imperils Internet security, PKI, and most password systems

Posted on by Ray in Data security, Information economy, Networking, Scenario planning, Strategic Inflection Points, Strategic planning, Strategy, System effectiveness, System quality, Systems
safe 'n green by Robert S. Donovan (cc) (from flickr)
safe ‘n green by Robert S. Donovan (cc) (from flickr)

I suppose it’s inevitable but surprising nonetheless.  A recent article Faster computation will damage the Internet’s integrity in MIT Technology Review indicates that by 2018, SHA-1 will be crackable by any determined large  organization. Similarly, just a few years later,  perhaps by 2021 a much smaller organization will have the computational power to crack SHA-1 hash codes.

What’s a hash?

Cryptographic hash functions like SHA-1 are designed such that, when a string of characters is “hash”ed they generate a binary value which has a couple of great properties:

  • Irreversibility – given a text string and a “hash_value” generated by hashing “text_string”, there is no way to determine what the “text_string” was from its hash_value.
  • Uniqueness – given two or more text strings, “text_string1” and “text_string2” they should generate two unique hash values, “hash_value1” and “hash_value2”.

Although hash functions are designed to be irreversible that doesn’t mean that they couldn’t be broken via a brute force attack. For example, if one were to try every known text string, sooner or later one would come up with a “text_string1” that hashes to “hash_value1”.

But perhaps even more serious, the SHA-1 algorithm is prone to hash collisions  which makes fails the uniqueness property above.  That is, there are a few “text_string1″s that hash to the same “hash_value1”.

All this wouldn’t be much of a problem except that with Moore’s law in force and continuing for the next 6 years or so we will have processing power in chips capable of doing a brute force attack against SHA-1 to find text_strings that match any specific hash value.

So what’s the big deal?

Well it turns out that SHA-1 algorithms underpin almost all secure data transmissions today. That is, most Public-key infrastructure (PKI) depend on SHA-1 to sign digital certificates.  And although that’s pretty bad, what’s even worse is that Secure Socket Layer/Transport Layer Security (SSL/TLS) used by “https://” websites the world over also depend on SHA-1 to send key information used to encrypt/decrypt secure Internet transactions.

On top of all that, many of today’s secure systems with passwords, use SHA-1 to hash passwords and instead of storing actual passwords in plain-text on their password files, they only store the SHA-1 hash of the passwords.  As such, by 2021, anyone that can read the hashed password file can retrieve any password in plain text.

What all this means is that by 2018 for some and 2021 or thereabouts for just about anybody else, todays secure internet traffic, PKI and most system passwords will no longer be secure.

What needs to be done

It turns out that NSA knew about the failings of SHA-1 quite awhile ago and as such, NIST released SHA-2 as a new hash algorithm and its functional replacement.  Probably just in time, this month, NIST announced a winner for a new SHA-3 algorithm as a functional replacement for SHA-2.

This may take awhile, what needs to be done is to have all digital certificates that use SHA-1, be invalidated with new ones generated using SHA-2 or SHA-3.  And of course, TLS and SSL Internet functionality all have to be re-coded to recognize and use SHA-2 or SHA-3, instead of SHA-1.

Finally, for most of those password systems, users will need to re-login and have their password hashes changed over from SHA-1 to SHA-2 or SHA-3.

Naturally, in order to use SHA-2 or SHA-3 many systems may need to be upgraded to later levels of code.  Seems like Y2K all over again, only this time it’s security that’s going to crash.  It’s good to be in the consulting business, again.

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But the real problem IMHO, is Moore’s law.  If it continues to double processing power/transistor density every two years or so, how long before SHA-2 or SHA-3 succumb to same sorts of brute force attacks?  Given that, we appear destined to change hashing, encryption and other security algorithms every decade or so until Moore’s law slows down or god forbid, stops altogether.

Comments?

 

DNA as storage, the end of evolution – part 2

Posted on by Ray in Distributed computing, Strategic Inflection Points, Strategic planning

I had talked about DNA programming/computing previously (see my DNA computing and the end of natural evolution post) and today we have an example of  another step along this journey.  A new story in today’s Science News titled DNA used as rewriteable data storage in cells discusses another capability needed for computation, namely information storage.

The new synthetic biology “logic” is able to record, erase and overwrite (DNA) data in an E. coli cell.  DNA information storage like this brings us one step closer to a universal biologic Turing machine or computational engine.

Apparently the new process uses enzymes to “flip” a small segment of DNA to read backwards and then with another set of enzymes, flip it back again.  With another application of synthetic biology, they were able to have the cell fluoresce in different colors depending on whether the DNA segment was reversed or in its normal orientation.

To top it all off, the DNA data storage device was inheritable.   Scientists showed that the data device was still present in the 100th generation of the cell they originally modified.  How’s that for persistent storage.

The universal biological Turing machine

Let’s see, my universal Turing machine parts list includes:

  • Tape or infinite memory device = DNA memory device – Check (todays post, well maybe not infinite, but certainly single bits today, bytes next year, so it’s only a matter of time before it’s KB)
  • Read head or ability to read out memory information = biological read head – Check (todays post, it can fluoresce, therefore it can be read)
  • State register = biologic counter  – Check (seems to have been discovered in 2009, see Science News article Engineered DNA counts it out, don’t know how I missed that)
  • State transition table or program = biological programming – Check (previous post plus today’s post, able to compute a new state from a given previous state and current data and write or rewrite data).

As far as I can tell this means we could construct an equivalent to a universal turing machine with today’s synthetic biology. Which of course means we could perform  just about any computation ever conceived within a single cell AND all generations of the cell would inherit this ability.

End of natural evolution, …

Gosh the possibilities of this new synthetic biological turing machine are both frightening and astonishing.  My original post talked about how adding ECC like functionality plus a ECC codeword to human DNA strand would spell the end of natural evolution for our species.

I suppose the one comforting thought is that flipping DNA segments takes hours rather than nano-seconds which means biological computation will never displace electronic/optronic computation.  But biological computation really doesn’t have to.  All it has to do is repair DNA mutations over the course of days, weeks and/or years, before it has a chance to propagate in order to end natural evolution.

…,  the dawn of un-natural evolution

Of course with such capabilities, “un-natural” or programmed evolution is quite possible but is it entirely desireable.  With such capabilities we could readily change a cell’s DNA to whatever we desire it to be.

My real problem is its inheritability.  It’s one thing to muck with a persons genome, it’s another thing to muck with their children’s, children’s, children’s, … DNA.

Let’s say you were able to change someone’s DNA to become a super-athelete, super-brain or super-beautiful/handsome person.  (Moving from a single cell’s DNA to a whole person’s is a leap, but not outside the realm of possibility).   Over time, any such changes would accumulate and could confer an seemingly un-assailable advantage to an individual’s gene line.

There’s probably some time to think these things through and set up some sort of policies, guidelines, and/or regulations environment around the use of the technology before capabilities get out of hand.

In my mind this goes well beyond genetically modified organisms (GMO) organisms that are just static changes to a gene line.  Programming gene lines to repair DNA, alter DNA, or even to make better copies, seems to me to be an order of magnitude increase in new capabilities taking us to genetically programmed organisms that has the potential to end evolution itself.

We need to have some serious discussions before it goes that far.

Comments?

Image: E. coli GFP by KitKor

Why EMC is doing Project Lightening and Thunder

Posted on by Ray in Data efficiency, Distributed computing, Market dynamics, Scenario planning, SSD storage, Storage performance, Strategic Inflection Points, Strategic planning, System effectiveness, Visionary leadershp
Picture of atmospheric lightening striking ground near a building at night
rayo 3 by El Garza (cc) (from Flickr)

Although technically Project Lightening and Thunder represent some interesting offshoots of EMC software, hardware and system prowess,  I wonder why they would decide to go after this particular market space.

There are plenty of alternative offerings in the PCIe NAND memory card space.  Moreover, the PCIe card caching functionality, while interesting is not that hard to replicate and such software capability is not a serious barrier of entry for HP, IBM, NetApp and many, many others.  And the margins cannot be that great.

So why get into this low margin business?

I can see a couple of reasons why EMC might want to do this.

  • Believing in the commoditization of storage performance.  I have had this debate with a number of analysts over the years but there remain many out there that firmly believe that storage performance will become a commodity sooner, rather than later.  By entering the PCIe NAND card IO buffer space, EMC can create a beachhead in this movement that helps them build market awareness, higher manufacturing volumes, and support expertise.  As such, when the inevitable happens and high margins for enterprise storage start to deteriorate, EMC will be able to capitalize on this hard won, operational effectiveness.
  • Moving up the IO stack.  From an applications IO request to the disk device that actually services it is a long journey with multiple places to make money.  Currently, EMC has a significant share of everything that happens after the fabric switch whether it is FC,  iSCSI, NFS or CIFS.  What they don’t have is a significant share in the switch infrastructure or anywhere on the other (host side) of that interface stack.  Yes they have Avamar, Networker, Documentum, and other software that help manage, secure and protect IO activity together with other significant investments in RSA and VMware.   But these represent adjacent market spaces rather than primary IO stack endeavors.  Lightening represents a hybrid software/hardware solution that moves EMC up the IO stack to inside the server.  As such, it represents yet another opportunity to profit from all the IO going on in the data center.
  • Making big data more effective.  The fact that Hadoop doesn’t really need or use high end storage has not been lost to most storage vendors.  With Lightening, EMC has a storage enhancement offering that can readily improve  Hadoop cluster processing.  Something like Lightening’s caching software could easily be tailored to enhance HDFS file access mode and thus, speed up cluster processing.  If Hadoop and big data are to be the next big consumer of storage, then speeding cluster processing will certainly help and profiting by doing this only makes sense.
  • Believing that SSDs will transform storage. To many of us the age of disks is waning.  SSDs, in some form or another, will be the underlying technology for the next age of storage.  The densities, performance and energy efficiency of current NAND based SSD technology are commendable but they will only get better over time.  The capabilities brought about by such technology will certainly transform the storage industry as we know it, if they haven’t already.  But where SSD technology actually emerges is still being played out in the market place.  Many believe that when industry transitions like this happen it’s best to be engaged everywhere change is likely to happen, hoping that at least some of them will succeed. Perhaps PCIe SSD cards may not take over all server IO activity but if it does, not being there or being late will certainly hurt a company’s chances to profit from it.

There may be more reasons I missed here but these seem to be the main ones.  Of the above, I think the last one, SSD rules the next transition is most important to EMC.

They have been successful in the past during other industry transitions.  If anything they have shown similar indications with their acquisitions by buying into transitions if they don’t own them, witness Data Domain, RSA, and VMware.  So I suspect the view in EMC is that doubling down on SSDs will enable them to ride out the next storm and be in a profitable place for the next change, whatever that might be.

And following lightening, Project Thunder

Similarly, Project Thunder seems to represent EMC doubling their bet yet again on the SSDs.  Just about every month I talk to another storage startup coming out in the market providing another new take on storage using every form of SSD imaginable.

However, Project Thunder as envisioned today is not storage, but rather some form of external shared memory.  I have heard this before, in the IBM mainframe space about 15-20 years ago.  At that time shared external memory was going to handle all mainframe IO processing and the only storage left was going to be bulk archive or migration storage – a big threat to the non-IBM mainframe storage vendors at the time.

One problem then was that the shared DRAM memory of the time was way more expensive than sophisticated disk storage and the price wasn’t coming down fast enough to counteract increased demand.  The other problem was making shared memory work with all the existing mainframe applications was not easy.  IBM at least had control over the OS, HW and most of the larger applications at the time.  Yet they still struggled to make it usable and effective, probably some lesson here for EMC.

Fast forward 20 years and NAND based SSDs are the right hardware technology to make  inexpensive shared memory happen.  In addition, the road map for NAND and other SSD technologies looks poised to continue the capacity increase and price reductions necessary to compete effectively with disk in the long run.

However, the challenges then and now seem as much to do with software that makes shared external memory universally effective as with the hardware technology to implement it.  Providing a new storage tier in Linux, Windows and/or VMware is easier said than done. Most recent successes have usually been offshoots of SCSI (iSCSI, FCoE, etc).  Nevertheless, if it was good for mainframes then, it certainly good for Linux, Windows and VMware today.

And that seems to be where Thunder is heading, I think.

Comments?

 

Comments?

How has IBM research changed?

Posted on by Ray in Corporate growth, Data science, Executive leadership, Information economy, R&D measures, SSD storage, Strategic Inflection Points, Strategic planning, Strategy, Visionary leadershp
20111207-204420.jpg
IBM Neuromorphic Chip (from Wired story)

What does Watson, Neuromorphic chips and race track memory have in common. They have all emerged out of IBM research labs.

I have been wondering for some time now how it is that a company known for it’s cutting edge research but lack of product breakthrough has transformed itself into an innovation machine.

There has been a sea change in the research at IBM that is behind the recent productization of tecnology.

Talking the past couple of days with various IBMers at STGs Smarter Computing Forum, I have formulate a preliminary hypothesis.

At first I heard that there was a change in the way research is reviewed for product potential. Nowadays, it almost takes a business case for research projects to be approved and funded. And the business case needs to contain a plan as to how it will eventually reach profitability for any project.

In the past it was often said that IBM invented a lot of technology but productized only a little of it. Much of their technology would emerge in other peoples products and IBM would not recieve anything for their efforts (other than some belated recognition for their research contribution).

Nowadays, its more likely that research not productized by IBM is at least licensed from them after they have patented the crucial technologies that underpin the advance. But it’s just as likely if it has something to do with IT, the project will end up as a product.

One executive at STG sees three phases to IBM research spanning the last 50 years or so.

Phase I The ivory tower:

IBM research during the Ivory Tower Era looked a lot like research universities but without the tenure of true professorships. Much of the research of this era was in materials and pure mathematics.

I suppose one example of this period was Mandlebrot and fractals. It probably had a lot of applications but little of them ended up in IBM products and mostly it advanced the theory and practice of pure mathematics/systems science.

Such research had little to do with the problems of IT or IBM’s customers. The fact that it created pretty pictures and a way of seeing nature in a different light was an advance to mankind but it didn’t have much if any of an impact to IBM’s bottom line.

Phase II Joint project teams

In IBM research’s phase II, the decision process on which research to move forward on now had people from not just IBM research but also product division people. At least now there could be a discussion across IBM’s various divisions on how the technology could enhance customer outcomes. I am certain profitability wasn’t often discussed but at least it was no longer purposefully ignored.

I suppose over time these discussions became more grounded in fact and business cases rather than just the belief in the value of the research for research sake. Technological roadmaps and projects were now looked at from how well they could impact customer outcomes and how such technology enabled new products and solutions to come to market.

Phase III Researchers and product people intermingle

The final step in IBM transformation of research involved the human element. People started moving around.

Researchers were assigned to the field and to product groups and product people were brought into the research organization. By doing this, ideas could cross fertilize, applications could be envisioned and the last finishing touches needed by new technology could be envisioned, funded and implemented. This probably led to the most productive transition of researchers into product developers.

On the flip side when researchers returned back from their multi-year product/field assignments they brought a new found appreciation of problems encountered in the real world. That combined with their in depth understanding of where technology could go helped show the path that could take research projects into new more fruitful (at least to IBM customers) arenas. This movement of people provided the final piece in grounding research in areas that could solve customer problems.

In the end, many research projects at IBM may fail but if they succeed they have the potential to make change IT as we know it.

I heard today that there were 700 to 800 projects in IBM research today if any of them have the potential we see in the products shown today like Watson in Healthcare and Neuromorphic chips, exciting times are ahead.

Smart windows

Posted on by Ray in Energy efficiency, Strategic Inflection Points, Strategic planning, System effectiveness
perfection, brasilia april 2006 by seier+seier (cc) (from Flickr)
perfection, brasilia april 2006 by seier+seier (cc) (from Flickr)

Heard a story yesterday about Smart Windows on NPR .  They were talking about new smart glass technology which uses a nano-crystal film coating to window panes that can change heat transmission characteristics of the glass.

Apparently the nano-crystal film can electronically change their orientation to reflect or transmit heat. Thus their heat transmissivity could be changed by supplying a low-voltage current to the window coating.

Problems with todays windows

The problem with todays Low-E glass windows today is that they reflect heat year round. In summer that’s great, but if it’s winter or cold and there is abundant sunlight, this stinks.  With smart windows that can change their heat transmission, one can have the best of Low-E glass and dumb windows.

Integrating current smart windows could be problematic

The story went on to discuss that ideally the smart windows would somehow be tied into a building’s heating/cooling systems used to trigger the changes to the nano-crystal coating.  Seems like a good idea for a new building construction but not so good for current housing and commercial buildings due to the retrofit requirements.

Also, the fact that a building/house is heating mode doesn’t necessarily indicate that windows should transmit heat.  The only time they should really do that is when sunlight is hitting the window pain and it’s cold out.

Ideally a building with smart glass on all four sides would have windows to the east transmit heat on winter mornings but reflect heat the rest of the day, windows to the south transmit heat most of a winter daylight times, those to the west transmit during the afternoon, and windows to the north reflect heat all the time.  But any heat transmission would only if it was a sunny day.

Smart-er window design

For the current 130.6M houses and 4.7M commercial buildings already constructed in the USA it would be better if the smart window systems were isolated and separate from a buildings other systems and somehow more self-contained/passively-managed.

This could be done by including solar photo-voltaics tied to a thermocouple/thermoelectric device in the window that would trigger heat transmission only during sunlight and its cold outside. That way we could use the solar voltaics to power the transition to heat-transmitting as well.  The smart window would even be better if it somehow could be designed to require the solar power to keep it transmitting heat.  That way as the sunlight stops shining on the window, it starts reflecting heat.

TCO of smart-er windows

While any self-contained/passively managed smart-er window might cost more up front than a dumber smart window just connected to the buildings thermostat, it would probably be cheaper when all costs are accounted for.

  • With a non-self contained smart window, one needs an even smarter thermostat (driving a signal when in heating mode even though the furnace was not needed),  one has to run (low-voltage) wiring to plug into each and every smart window in a building and each window still requires some logic to transmit/transform the signal from the buildings thermostat to the window’s nano-crystal film.
  • With a self-contained smart window, one would need include additional control logic, a solar photovoltaic strip/cell and a thermocouple but it wouldn’t need to plug into any other building system.
Of course the nice thing about the self-contained, smarter window future changes to smart thermostats could be undertaken without impacting the smart windows (see my post on Smarter thermostats make for smarter grids).  And, the changes to current building codes to support all that additional wiring and plugs would not need to occur.
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What do you think?


Server virtualization vs. storage virtualization

Posted on by Ray in Block Storage, Cloud storage, Disk storage, File Storage, Information economy, Market dynamics, Server virtualization, SSD storage, Storage architecture, storage economics, Storage performance, Strategic Inflection Points, Strategic planning, System effectiveness, Visionary leadershp
Functional Fusion? by Cain Novocaine (cc) (from Flickr)
Functional Fusion? by Cain Novocaine (cc) (from Flickr)

One can only be perplexed by the seemingly overwelming adoption of server virtualization and contrast that with the ho-hum, almost underwelming adoption of storage virtualization.  Why is there this significant a difference?

I think the problem is partly due to the lack of an common understanding of storage performance utilization.

Why server virtualization succeeded

One significant driver of server virtualization is the precipitous drop in server utilization that occurred over the last decade when running single applications on a physical server.  It was nothing to see real processor utilization of less than 10% and consequently it was easy to envision that executing 5-10 applications on the single server. And what’s more each new generation of server kept getting more powerful, handling double the MIPs every 18 months or so driven by Moore’s law.

The other factor was that application workloads weren’t increasing that much. Yes new applications would come online but they seldom consumed an inordinate amount of MIPs and were often similar to what was already present. So application processing growth while not flatlining, was expanding at a relatively slow speed.

Why storage virtualization has failed

Data on the other hand continues its never ending exponential growth. Doubling every 3-5 years or less. And the fact that you have more data, almost always requires more storage hardware to support the IOPs being required to support it.

In the past the storage IOP rates was intrinsically tied to the number of disk heads available to service the load.  Although disk performance grew it wasn’t doubling every 18 months, and real per disk performance was actually going down over time, measured as the amount of IOPS per GB.

This drove proliferation of disk spindles and as such, storage subsystems in the data center. Storage virtualization couldn’t reduce the number of spindles required to support the workload.

Thus, if you look at storage performance from the perspective of % IOPS one could support per disk, most  sophisticated systems were running anywhere from 75% to 150% (based on DRAM caching).

Paradigm shift ahead

But SSDs can change this dynamic considerably.  A typical SSD can sustain 10-100K IOPs and there is some liklihood that this will increase with each generation that comes out but the application requirements will not increase as fast.  Hence, , there is a high liklihood that normal data center utilisation of SSD storage perfomance will start to drop below 50% or more, when that happens. -torage virtualization may start to make a lot more sense.

Maybe when (SSD) data storage starts moving more in line with Moore’s law, storage virtualization will become a more dominant paradigm for data center storage use.

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Any bets on who the VMware of storage virtualization will be?

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