Welcome!

Containers Expo Blog Authors: Liz McMillan, Pat Romanski, Stefan Bernbo, John Esposito, Flint Brenton

Related Topics: @CloudExpo

@CloudExpo: Article

Cloud Computing Expo: Cloud Optimized Storage Solutions

The basic ideology of COSS is to ingest significant amounts of both structured and unstructured content

The basic ideology of Cloud Optimized Storage Solutions, as noted in the three previous installments, is to ingest significant amounts of both structured and unstructured content and, operating within the confines of SLAs and tiering, provide this data back to users with acceptable performance.

In the previous three Cloud Optimized Storage Solution (COSS) articles in this series, I’ve discussed the content being stored, the method of storage, as well as principles derived from data tiering.  Today, I want to jump ahead a bit and discuss how neural networks and heuristics can impact the processing of object and file data for the cloud.

One of the more recent advancements within computing has been the application of heuristics and neural networking. Heuristics is defined as being “…an educational method in which learning takes place through discoveries that result from investigations…“ While heuristics has historically been used in such products like anti-virus software, it provides an incredible wealth of capability and technology for the COSS solution. Similarly, neural networks provide capacitive understanding of processing layers and optimizations that learn patterns based on underlying statistical data. How do these two technologies apply to COSS?

The basic ideology of COSS, as noted in the previous parts of this paper, is to ingest significant amounts of both structured and unstructured content and, operating within the confines of SLAs and tiering, provide this data back to users with acceptable performance. While fairly reductionistic in nature, it is how the data is allocated to storage that provides the greatest insight into the impact that neural nets and heuristics can potentially have. To illustrate this point, here is a graphical example of file placement within COSS without using heuristics.

As seen below, data is submitted to COSS by API or other integration point, meta data is calculated for said object based on pre-defined categories of content understanding (i.e. “Movies”) and content is placed in Tier 1 for faster access and greater availability. Policy is enacted on this movie object such that it is automatically moved from Tier 1 to Tier 2 after a fixed period of time and again to Tier 3 based on similar time constraints. Globally, policy is additional set for compression, encryption, deduplication, and optimizations and this is applied for content at rest as well as incoming data. Once data has been moved from tier to tier, there is no really process for retrieving that data and promoting it to a different tier based on access or usage patterns.



While this example is extremely reductionistic, it highlights the particular areas where neural nets and heuristics can be applied to approve both the way that data is ingested but also how it is maintained across its lifespan (i.e until delete). In essence, COSS, under this particular model, is administrator-enforced. Here, then, is an example of data ingest to COSS with neural nets and heuristics enabled:

Almost immediately, it becomes apparent that COSS is taking a more active role in the ingest and storage allocation for the file data. Instead of having a global category created (i.e. “Movies”), COSS applies bit-patterning and packet inspection to the data being ingested to determine file composition. Such inspection has several significant implications: less time spent applying policy enhancements such as deduplication/encyption (storage processor intensive) and more time optimizing content layout and placement within tiers (default becomes Tier 2: accessibility and performance). Once the data is inspected, it is determined to be of a certain type (i.e. application/x-octet stream) and placed in a default tier (Tier 2). COSS recognizes that this data is already in a compressed state and rules out compression and deduplication policies and potentially, depending on source/API mapping, rules out encryption policies. Once data is at rest on Tier 2, COSS watches file access patterns to determine when and how it is being accessed. If statistical trending against that file starts showing increased access, COSS will promote the file to a higher tier for more adequate performance and access. If the trending notices a decline in traffic to that file, it can demote it to Tier 2, Tier 3, etc. without affecting surrounding data.

Implications for Global Implementations

The examples above highlighted policies and actions on a single file or object but when it is extrapolated out to the COSS system on a global level, it becomes a much more powerful tool. In essence, the heuristic database and neural network capabilities can be applied to linked COSS systems for global replication and file/object processing. As patterning is completed against file types and categories are created or designed by the engine, the resulting database can be asynchronously updated to other members of the larger COSS network. This replication would make use of recursive heuristic database updates to ensure consistency against the other COSS members and to ensure that data residing across all COSS members was categorized and tagged appropriately. Additionally, since one of the mechanisms for data protection with COSS is to utilize multiple data replicas for redundancy, it serves the additional purpose of spreading the database for protection purposes.

Implications for Heuristic Processing and Control

The additional processing overhead that heuristic analysis brings to the fore an added layer of complexity in implementation and design. Given that COSS is designed to utilize commodity hardware with the differentiating feature being the actual software “brains,” the added performance burden of a heuristic model might seem untenable for basic implementations. However, as recent research has shown, the simple addition of a General Purpose Graphical Processing Unit (GPGPU) to the COSS hardware to offload these more complex routines would fit within the paradigm of commodity hardware. By coding to specific GPGPU routines (as evidenced by the research into WPA key decode, for example) based on nVidia’s CUDA specifications, for example, the heuristic branch paths could be removed from the general storage operation paths handled by the storage system processor. Since each GPGPU typically has ownership of a local, low latency cache (e.g. GDDR4) and has multiple programmable vector units, the ability to process large sets of data is assured.

One area that would need to be addressed with the use of GPGPUs for heuristic programming is the issue of redundancy. Given that no methodology currently exists to maintain GPGPU functionality across two discrete units in a single system, either the programming path would need to account for multiple GPGPU engines within the general I/O complex or it would need to be designed into the heuristic path. In a clustered front end I/O stack (a la EMC’s Atmos), it would be a simple matter of having a GPGPU per individual node member with the overall software stack to process the heuristic path in a parallel fashion.

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.

Comments (0)

Share your thoughts on this story.

Add your comment
You must be signed in to add a comment. Sign-in | Register

In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.


@ThingsExpo Stories
In addition to all the benefits, IoT is also bringing new kind of customer experience challenges - cars that unlock themselves, thermostats turning houses into saunas and baby video monitors broadcasting over the internet. This list can only increase because while IoT services should be intuitive and simple to use, the delivery ecosystem is a myriad of potential problems as IoT explodes complexity. So finding a performance issue is like finding the proverbial needle in the haystack.
Machine Learning helps make complex systems more efficient. By applying advanced Machine Learning techniques such as Cognitive Fingerprinting, wind project operators can utilize these tools to learn from collected data, detect regular patterns, and optimize their own operations. In his session at 18th Cloud Expo, Stuart Gillen, Director of Business Development at SparkCognition, discussed how research has demonstrated the value of Machine Learning in delivering next generation analytics to imp...
Whether your IoT service is connecting cars, homes, appliances, wearable, cameras or other devices, one question hangs in the balance – how do you actually make money from this service? The ability to turn your IoT service into profit requires the ability to create a monetization strategy that is flexible, scalable and working for you in real-time. It must be a transparent, smoothly implemented strategy that all stakeholders – from customers to the board – will be able to understand and comprehe...
Extracting business value from Internet of Things (IoT) data doesn’t happen overnight. There are several requirements that must be satisfied, including IoT device enablement, data analysis, real-time detection of complex events and automated orchestration of actions. Unfortunately, too many companies fall short in achieving their business goals by implementing incomplete solutions or not focusing on tangible use cases. In his general session at @ThingsExpo, Dave McCarthy, Director of Products...
The cloud market growth today is largely in public clouds. While there is a lot of spend in IT departments in virtualization, these aren’t yet translating into a true “cloud” experience within the enterprise. What is stopping the growth of the “private cloud” market? In his general session at 18th Cloud Expo, Nara Rajagopalan, CEO of Accelerite, explored the challenges in deploying, managing, and getting adoption for a private cloud within an enterprise. What are the key differences between wh...
Ask someone to architect an Internet of Things (IoT) solution and you are guaranteed to see a reference to the cloud. This would lead you to believe that IoT requires the cloud to exist. However, there are many IoT use cases where the cloud is not feasible or desirable. In his session at @ThingsExpo, Dave McCarthy, Director of Products at Bsquare Corporation, will discuss the strategies that exist to extend intelligence directly to IoT devices and sensors, freeing them from the constraints of ...
The IoT is changing the way enterprises conduct business. In his session at @ThingsExpo, Eric Hoffman, Vice President at EastBanc Technologies, discussed how businesses can gain an edge over competitors by empowering consumers to take control through IoT. He cited examples such as a Washington, D.C.-based sports club that leveraged IoT and the cloud to develop a comprehensive booking system. He also highlighted how IoT can revitalize and restore outdated business models, making them profitable ...
IoT offers a value of almost $4 trillion to the manufacturing industry through platforms that can improve margins, optimize operations & drive high performance work teams. By using IoT technologies as a foundation, manufacturing customers are integrating worker safety with manufacturing systems, driving deep collaboration and utilizing analytics to exponentially increased per-unit margins. However, as Benoit Lheureux, the VP for Research at Gartner points out, “IoT project implementers often ...
When people aren’t talking about VMs and containers, they’re talking about serverless architecture. Serverless is about no maintenance. It means you are not worried about low-level infrastructural and operational details. An event-driven serverless platform is a great use case for IoT. In his session at @ThingsExpo, Animesh Singh, an STSM and Lead for IBM Cloud Platform and Infrastructure, will detail how to build a distributed serverless, polyglot, microservices framework using open source tec...
The idea of comparing data in motion (at the sensor level) to data at rest (in a Big Data server warehouse) with predictive analytics in the cloud is very appealing to the industrial IoT sector. The problem Big Data vendors have, however, is access to that data in motion at the sensor location. In his session at @ThingsExpo, Scott Allen, CMO of FreeWave, discussed how as IoT is increasingly adopted by industrial markets, there is going to be an increased demand for sensor data from the outermos...
CenturyLink has announced that application server solutions from GENBAND are now available as part of CenturyLink’s Networx contracts. The General Services Administration (GSA)’s Networx program includes the largest telecommunications contract vehicles ever awarded by the federal government. CenturyLink recently secured an extension through spring 2020 of its offerings available to federal government agencies via GSA’s Networx Universal and Enterprise contracts. GENBAND’s EXPERiUS™ Application...
A strange thing is happening along the way to the Internet of Things, namely far too many devices to work with and manage. It has become clear that we'll need much higher efficiency user experiences that can allow us to more easily and scalably work with the thousands of devices that will soon be in each of our lives. Enter the conversational interface revolution, combining bots we can literally talk with, gesture to, and even direct with our thoughts, with embedded artificial intelligence, wh...
"delaPlex is a software development company. We do team-based outsourcing development," explained Mark Rivers, COO and Co-founder of delaPlex Software, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
"We work in the area of Big Data analytics and Big Data analytics is a very crowded space - you have Hadoop, ETL, warehousing, visualization and there's a lot of effort trying to get these tools to talk to each other," explained Mukund Deshpande, head of the Analytics practice at Accelerite, in this SYS-CON.tv interview at 18th Cloud Expo, held June 7-9, 2016, at the Javits Center in New York City, NY.
Cloud Expo, Inc. has announced today that Andi Mann returns to 'DevOps at Cloud Expo 2016' as Conference Chair The @DevOpsSummit at Cloud Expo will take place on November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. "DevOps is set to be one of the most profound disruptions to hit IT in decades," said Andi Mann. "It is a natural extension of cloud computing, and I have seen both firsthand and in independent research the fantastic results DevOps delivers. So I am excited t...
The cloud promises new levels of agility and cost-savings for Big Data, data warehousing and analytics. But it’s challenging to understand all the options – from IaaS and PaaS to newer services like HaaS (Hadoop as a Service) and BDaaS (Big Data as a Service). In her session at @BigDataExpo at @ThingsExpo, Hannah Smalltree, a director at Cazena, provided an educational overview of emerging “as-a-service” options for Big Data in the cloud. This is critical background for IT and data profession...
Connected devices and the industrial internet are growing exponentially every year with Cisco expecting 50 billion devices to be in operation by 2020. In this period of growth, location-based insights are becoming invaluable to many businesses as they adopt new connected technologies. Knowing when and where these devices connect from is critical for a number of scenarios in supply chain management, disaster management, emergency response, M2M, location marketing and more. In his session at @Th...
In his keynote at 18th Cloud Expo, Andrew Keys, Co-Founder of ConsenSys Enterprise, provided an overview of the evolution of the Internet and the Database and the future of their combination – the Blockchain. Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life sett...
IoT is rapidly changing the way enterprises are using data to improve business decision-making. In order to derive business value, organizations must unlock insights from the data gathered and then act on these. In their session at @ThingsExpo, Eric Hoffman, Vice President at EastBanc Technologies, and Peter Shashkin, Head of Development Department at EastBanc Technologies, discussed how one organization leveraged IoT, cloud technology and data analysis to improve customer experiences and effi...
Basho Technologies has announced the latest release of Basho Riak TS, version 1.3. Riak TS is an enterprise-grade NoSQL database optimized for Internet of Things (IoT). The open source version enables developers to download the software for free and use it in production as well as make contributions to the code and develop applications around Riak TS. Enhancements to Riak TS make it quick, easy and cost-effective to spin up an instance to test new ideas and build IoT applications. In addition to...