THE VBLOCK, THE IOT GATEWAY AND THE SENSORS

Sherif Mohsen Services Proposal Consultant Dell EMC [email protected] Table of Contents Introduction ...... 3 The Vblock ...... 3 Big Data and Vblock ...... 4 Mobile Computing ...... 6 Ubiquitous Computing and Pervasive Systems ...... 7 FOG Computing ...... 7 Windows 10 IoT Core ...... 8 Case Study ...... 9 Conclusion ...... 11 Bibliography ...... 12

Disclaimer: The views, processes or methodologies published in this article are those of the authors. They do not necessarily reflect Dell EMC’s views, processes or methodologies.

2016 EMC Proven Professional Knowledge Sharing 2

Introduction The IT world is radically changing with new technologies focused on extending the mobile device era to the era where everything has sensors. i.e. the Pervasive Systems era. The with its powerful components in processing, networking, storage, and management will always be a fundamental component of the IT world. This is where Vblock has revolutionized the data center ensuring customers can benefit from state-of-the-art components and integration of leading companies such as VMware, Cisco and Dell EMC. The Vblock is a single stop shop for a complete data center and the deployment and components’ flexibility ensure no time is wasted trying to get components from different vendors to work together, and whether a patch on a component will be supported with the rest of the ecosystem. The Release Certification Matrix and thousands of hours VCE engineers invest means the customer no longer needs the extensive effort of component assembly. However, we believe the next era of IT solutions holds more.

Sensors have the potential to generate billions of terabytes from everyday devices, from cars, to washing machines, to the air purifiers in our offices. This huge amount of data needs proportional processing capabilities and technologies. This can be done in the data center and projected to be expanded to include IoT Gateway devices which will be small hubs present in the streets to collect real-time data from the sensors, filter out this data, perform preliminary processing and may be capable of providing real-time insight and decision making. From the Gateway to the clustering of Raspberry PI projects utilizing Windows 10 IoT Core, we will discuss in this article the potential of providing IT capabilities, not only in the data center via Vblocks, but also extending this to include sensor devices and IoT Gateways. The Vblock The data center has always been a core part of IT infrastructure delivering compute, storage, networking, virtualization and management capabilities to IT consumers. This, coupled with the client-side compute, has been the cornerstone of the era where computers dominated the work experience. The next era of IT promises even more. The shift from Client Server IT models to an era where IT resources can be accessed in the Cloud, coupled with the increased proliferation of mobile and pervasive systems opens a window to a new world of opportunities.

From the data center perspective, converged infrastructure has basically provided organizations with a data center in a box. Much like a smartphone includes phone, email, camera, and GPS, converged infrastructure provides compute, storage, networking, virtualization and management in a single platform. For small and medium businesses (SMB), Hyper Converged Infrastructure provides a single data center in a box but at a smaller scale more convenient to this customer segment. (Akkiraju)

VCE Vblock accelerates time to deployment as customers no longer need to deal with different vendors, researching compatibility of different components, procuring components from different vendors, and going through the pain of integrating these components. Moreover, upgrading firmware of a single component must be verified with all others in the data center to ensure clean post-upgrade operations. VCE spares all this effort by providing all components from a

2016 EMC Proven Professional Knowledge Sharing 3 single vendor, doing the engineering work and compatibility tests in their labs and freeing up IT staff to more productive and innovative work. Moreover, it eliminates vendors finger-pointing if problems arise as customers have a single point of contact to refer to when facing any issues.

Vblock are leaders in this segment providing different offerings including the 100, 200, 300, 500 and 700 systems which provide organizations with choice and scale, from the smaller VNXe storage scaling to the midrange class VNX systems and extending to the enterprise class VMAX (10k, 20k, 40k,100k, 200k and 400k) systems, and from rack mount servers to Cisco UCS computing. The VxBlock systems take a further step by offering customers flexible choice of software-defined networking with VMware NSX or Cisco ACI (factory built), in addition to flexible storage deployments including VNX or VMAX3 storage systems. The VCE VxRack system 1000 and VxRail address the Hyper Converged infrastructure segment providing modular design and allowing for expansion as IT needs grow.

VCE Vscale architecture is an innovative solution which enable customers to treat data centers as modules that can be combined to scale and pool resources to unprecedented levels. The enabling technology behind this is the scalable spine-leaf network fabric. (VCE, 2015)

The image below offers a high level overview of this great technology enabler.

Figure 1 (VCE, 2016)

Big Data and Vblock Big Data has been a trending term over the past few years, and for good reason. As the term implies, Big Data represents a BIG amount of structured and unstructured data which is generated from many sources including web, social media, sensors and mobile (Figure 2). An IDC forecast expects the Big Data technology and Services market to grow at a 26.4% compound annual growth rate to $41.5 billion through 2018 (Big Data & Analytics - An IDC Four Pillar Research Area, 2016). This is huge and holds many opportunities for all players in the IT market. The main challenge with Big Data is how to analyze this huge amount of data and

2016 EMC Proven Professional Knowledge Sharing 4 generate insight that businesses/individuals can utilize to derive insight and make decisions based on this analysis. Some like to refer to the analysis of Big Data as the “divide and conquer” methodology which includes acquiring Big Data, organizing it and analyzing it. Simply said, data has to be divided, the different portions individually analyzed, and utilize the power of distributed computing and storage to put this data back together and generate the insight.

Figure 2 (www.ibmbigdatahub.com) Vblock provides an enterprise-level infrastructure which can be utilized with Big Data by integrating Isilon® for Scale-Out Network Attached Storage with native Hadoop Distributed File System (HDFS) integration to provide a much more resilient and scalable architecture than one which utilizes commodity hardware. Additionally, this provides a solution for customers who are looking for support of unstructured as well as traditional databases. Furthermore, Hadoop deployment can be virtualized with VMware vSphere Big Data Extension (BDE) which provides the advantage of advanced features that virtualization brings to today’s IT world.

Table 1 summarizes the features Vblock provide for support of Big Data and Analytics.

Solution Highlights Big Data and Analytics on Vblock System

Availability / Reliability Enterprise- and service provider-class, 6 x 9’s

Enterprise- and service provider-class, high configurability Performance / Scalability with dynamic and intelligent scaling Data-at-rest encryption, secure data transmission, multi- Security / Privacy level segregation, control, and isolation

2016 EMC Proven Professional Knowledge Sharing 5

Protocol Support HDFS 1/2, NFS, CIFS, FTP, HTTP

All data including structured and unstructured data, select Data / Analytic Support Dell EMC Symmetrix VMAX, VNX, and/or Isilon.

Multi-Tenancy Yes

Mixed Workload Yes

Integrated Support Yes

Virtualization Yes, as well as bare metal, implement vSphere BDE

Operations Management Yes with VCE Vision, Open API. System metrics available

Table 1 (TRANSFORM YOUR BUSINESS: BIG DATA AND ANALYTICS WITH VCE AND EMC, 2014)

Mobile Computing According to June 2014 Gartner Statistics, traditional PC sales are declining and mobile while tablets sales are rising (Figure 3). This means more users are generating data from mobile devices. Furthermore, in 2015 Google announced it “has shaken up its algorithm so that websites that are better to view on mobile will be prioritised in searches from phones.” (Google mobile-friendly pages will make searches on phone easier, but 'mobilegeddon' could hit small sites, 2015)

This is a clear indication of the trend shifting towards mobiles and tablets, especially as their processing capabilities are improving and many have the capability of accessing their resources over the cloud from their tablets. Of course there are also market players which provide a desktop experience on the tablet like the Microsoft Surface Pro which is virtually a PC in a Tablet form factor.

Figure 3 (Gartner, 2014)

2016 EMC Proven Professional Knowledge Sharing 6

Ubiquitous Computing and Pervasive Systems Ubiquitous computing and pervasive systems provide an opportunity to embed small inexpensive microprocessor devices which are always available, always on to collect real time attributes of everyday devices without the need of human interference and interaction as is the case with common mobile applications. Think of a car which contains many sensors and gathers real time information of performance metrics, then communicates this information to the manufacturer and the manufacturer can accordingly send recommendations to optimize car performance and fuel consumption. (techopedia, 2016)

This is not a new concept. Rolls Royce, which is not only famous for luxury cars but also for aircraft engines, has an engine monitoring system in their aircraft engines which involves sensors embedded in different parts of the engine and gathers and sends performance data. This provides insight to engine performance and the needed repairs, which contributes to better preventive maintenance procedures and avoids unneeded costly repairs which could involve unnecessary engine replacement. (Aircraft Engine Monitoring: How It Works And How It Could Help Malaysia Air 370 Crash Investigators, 2014)

Aircraft manufacturers also have similar systems. Boeing for example utilizes an Airline Health Management (AHM) system which collects aircraft performance metrics, relays this data to ground systems and analyzes this data to improve performance, fuel consumption and decrease carbon dioxide emissions. (Monitoring Real-Time Environmental Performance, 2009)

We can imagine that a large industry such as the airline industry has strong motives to implement such a technology; however what if all home appliances were able to gather performance metrics and send this data for analysis? B. K. Yoon, Samsung’s co- CEO announced during CES 2015 (a global consumer electronics and consumer technology tradeshow) “five years from now, every single piece of Samsung hardware will be an IoT device, whether it is an air purifier or an oven.” This means a very large volume of big data is expected to be generated and analyzed in the future and will encompass many discussions of the standards and its openness which will be the platform for this technology application. Whether this will prove beneficial to the consumer market is certainly an area of discussion; however, there is clear indication of market inclination towards IoT technology and its infrastructure will certainly play a growing role in IT in the future. (Samsung says all its products will be IoT enabled within 5 years, 2015) FOG Computing A field where a lot of work and research is taking place is to reduce the amount of data that is sent real time from ubiquitous, pervasive and mobile systems to the cloud and provide complementary computing, storage and networking capabilities at the edge. The expected significant increase in data generated from devices and the need to quickly and efficiently transform this data to useful information has exposed a very beneficial idea of creating a mini data center at the network edge which gathers data from devices, provides processing and analytics and responds and provides information to take action based on the insight gained. Data that requires further analysis and processing is sent over the cloud to the data center.

2016 EMC Proven Professional Knowledge Sharing 7

There are already products in the market tackling this segment. For example, Cisco has unveiled the IOx platform which brings computing to the network edge. As well, Intel has created its gateway solutions for the Internet of Things along with McAfee security and Wind River software businesses. (Burt) (Internet of Things (IoT)) Windows 10 IoT Core Microsoft also have plans to penetrate this new IT era. Here we will discuss two very interesting prospects; providing developers with a free platform for development and the new free OS for the Internet of Things.

A very interesting offering Microsoft has facilitated for developers is the ability to use a flavor of their Visual Studio for free. Visual Studio Community 2015 is their newest offering which is “A free, fully featured, and extensible IDE for creating modern applications for Windows, Android, and iOS, as well as web applications and cloud services” and “is free for individual developers, open source projects, academic research, education, and small professional teams.” The screenshot below from the Visual Studio website describes it all (Figure 4).

Figure 4 (Visual Studio Community, 2016)

In our opinion Microsoft realized the great success open source Android achieved and decided to take this further by allowing developers to embrace the well-known developing languages including C++, C#, JS and VB to virtually provide applications to different platforms. For the IoT, this is huge. Microsoft announced its new Windows 10 IoT Core in May 2015 which embraces ARM processors and is a very interesting option for Raspberry PI lovers. Today Raspberry PI can have Windows 10 IoT Core as its operating system and applications developed in the supported languages can be uploaded to the Raspberry PI from Visual Studio. This opens the door for the penetration of Microsoft technologies in the IoT arena and we believe there will be more use cases in the future. (Loeb)

We believe Windows 10 IoT Core will be a major player in the smart devices and gateways arena and already Microsoft has a development website with dedicated projects and sample use cases for Windows IoT (https://dev.windows.com/en-us/iot). (Windows 10 for the Internet of Your Things)

2016 EMC Proven Professional Knowledge Sharing 8

In the rest of this article we will discuss a sample use case to elaborate on how a complete system can be conceptually built, from the sensors to the data center Vblocks. Case Study This case study will involve a complete system which has the potential to automate the traffic monitoring process and generate actionable insight accordingly.

In the greater Cairo Metropolitan area around $8 billion is wasted due to traffic, a number expected to rise to $18 billion by 2030. This presents a significant waste and an area where there is a lot of room for improvement (Schafer, 2014). Furthermore, road traffic accidents cost Egypt 12000 lives each year. (WHO, 2016)

In the proposed system which will tackle road fatalities and traffic congestion, each motor vehicle licensed in Egypt will be fitted with a pervasive device which has an accelerometer on board, a small microprocessor in addition to the ability to communicate with 3G/4G networks and radio frequency identification (RFID). This device will beacon statistics of the vehicle to the Traffic Management Control Center and will communicate with Gateway hubs which will relay data to the Vblock systems in the data center. Another very important aspect of the system will be mobile applications which drivers can download from the respective stores and push messages will be sent to the drivers to provide different information on these applications.

The diagram below illustrates the system.

Figure 5

2016 EMC Proven Professional Knowledge Sharing 9

Cars in the proposed system will communicate big data via the network to the gateway which will perform high level analytics on the car speed and performance to determine whether the car is complying with speed limits and road safety regulations. If the Gateway analytics reveal the driver is not complying with road safety driving standards, a push message will be sent to the driver’s mobile app warning him to reduce his speed or alter his driving patterns. A fine system will be put in place to punish illegal driving pattern which risk people lives and properties.

Another aspect of the system is ensuring pedestrians are able to safely cross the roads at traffic lights. Traffic lights will be fitted with RFID reader devices which will detect car presence via probing the passive transponders that will be fitted in every car license plate (passive transponders have no batteries and are cheaper than active transponders). Small embedded systems will be utilized to communicate with the RFID reader in the traffic lights (the RFID reader detects car presence) and perform the computation and communication of traffic light status (red, yellow or green) and car status/position.

If the system determines traffic lights are red and a car has illegally passed, a message is sent to the nearest gateway which will send a push message informing the driver a fine has to be paid. The user will be able to open his mobile app and view detailed information of the fines, reason, date and time.

So far the proposed system has the potential to decrease traffic accidents and road fatalities by automating the process of traffic monitoring. In the next part we will discuss how traffic time wasted can be decreased to have a more optimized system on the roads.

Gateways fitted in streets will gather information on the number of vehicles passing certain areas and all statistics related to car performance. This will be communicated to the Traffic Control Center, and if the driver decides to use the mobile app for his journey, push messages will be sent based on automatically collected real time information of the traffic situation which will advise the driver to take an alternative route which will save time and petrol.

The statistics collected will be analyzed deeper in the data center by the Vblock system which will assist the ministry of transport with planning decisions. For example the system may detect that at a certain part of the road car speeds decrease although the traffic density is not high. Deep analytics can extract useful information that this part of the road is broken (and how severe this fault is and assign a priority for fixing it based on affected number of daily drivers etc.) and causes a bottleneck. This would assist implementing and prioritizing corrective actions. However the greater value in such a system is to gather enough data and generate enough insight which will assist with future planning of roads, pedestrian crossings, and public transport facilities that should be implemented. The aim is to limit subjective decisions taken by traffic personnel and empower informed decisions based on real time data and predictions generated from deep analytics by Vblock systems in the data center.

We believe the proposed system can have many applications in many countries around the world, with the highest benefit achieved in countries where traffic systems suffer the most waste and fatal accidents.

2016 EMC Proven Professional Knowledge Sharing 10

Conclusion This approach can be implemented in any area of business or government. The ability to use pervasive systems to collect performance, send this data to Gateways (mini data centers), utilize this data and send useful information to mobile apps, and finally sending this big data to the Vblock systems for deep analytics and long term informed decisions facilitation is an area that should be exploited in the future to save resources, money, and most important of all, lives.

2016 EMC Proven Professional Knowledge Sharing 11

Bibliography Aircraft Engine Monitoring: How It Works And How It Could Help Malaysia Air 370 Crash Investigators. (2014). Retrieved from http://www.forbes.com/sites/johngoglia/2014/03/13/aircraft-engine- monitoring-how-it-works-and-how-it-could-help-malaysia-air-370-crash-investigtors/

Akkiraju, P. (n.d.). Cloud Revolution. Retrieved from Silicon India: http://www.siliconindia.com/magazine_articles/Cloud_Revolution_-DHAC793762511.html

Big Data & Analytics - An IDC Four Pillar Research Area. (2016). Retrieved from http://www.idc.com/prodserv/4Pillars/bigdata

Burt, J. (n.d.). eWeek. Retrieved from Fog Computing Aims to Reduce Processing Burden of Cloud Systems: http://www.eweek.com/networking/fog-computing-aims-to-reduce-processing- burden-of-cloud-systems.html

Gartner. (2014). Gartner Says Worldwide Traditional PC, Tablet, Ultramobile and Mobile Phone Shipments to Grow 4.2 Percent in 2014. Retrieved from http://www.gartner.com/newsroom/id/2791017

Google mobile-friendly pages will make searches on phone easier, but 'mobilegeddon' could hit small sites. (2015). Retrieved from http://www.independent.co.uk/life-style/gadgets-and- tech/news/google-mobile-friendly-pages-will-make-searches-on-phone-easier-but- mobilegeddon-could-hit-small-10191885.html

Internet of Things (IoT). (n.d.). Retrieved from http://www.cisco.com/c/en/us/solutions/internet-of- things/iot-fog-computing.html

Loeb, L. (n.d.). Windows 10 IoT Core Targets Raspberry Pi Crowd. Retrieved from http://www.informationweek.com/software/operating-systems/windows-10-iot-core-targets- raspberry-pi-crowd/a/d-id/1321712

Monitoring Real-Time Environmental Performance. (2009). Retrieved from http://www.boeing.com/commercial/aeromagazine/articles/qtr_03_09/article_07_1.html

Samsung says all its products will be IoT enabled within 5 years. (2015). Retrieved from http://www.androidauthority.com/samsung-says-products-will-iot-enabled-within-5-years- 578576/

Schafer, H. (2014). The World Bank. Retrieved from Time is Money, especially on Cairo’s Streets: http://blogs.worldbank.org/arabvoices/time-money-especially-cairo-streets techopedia. (2016). Retrieved from Ubiquitous Computing: https://www.techopedia.com/definition/22702/ubiquitous-computing

2016 EMC Proven Professional Knowledge Sharing 12

TRANSFORM YOUR BUSINESS: BIG DATA AND ANALYTICS WITH VCE AND EMC. (2014). Retrieved from http://www.vce.com/asset/documents/big-data-analytics-solution-brief.pdf

VCE. (2015). VCE VSCALE™ ARCHITECTURE: FLEXIBILITY FOR WHATEVER THE FUTURE BRINGS. Retrieved from http://www.vce.com/asset/documents/vscale-architecture-value-whitepaper.pdf

VCE. (2016). VCE Vscale Architecture. Retrieved from http://www.vce.com/products/vscale/overview

Visual Studio Community. (2016). Retrieved from https://www.visualstudio.com/en-us/products/visual- studio-community-vs.aspx

WHO. (2016). World Health Organization. Retrieved from Road safety in Egypt: http://www.who.int/violence_injury_prevention/road_traffic/countrywork/egy/en/

Windows 10 for the Internet of Your Things. (n.d.). Retrieved from https://www.microsoft.com/en- us/WindowsForBusiness/windows-iot www.ibmbigdatahub.com. (n.d.). Retrieved from http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big- data.jpg?cm_mc_uid=63479486883614515555892&cm_mc_sid_50200000=1451555589

2016 EMC Proven Professional Knowledge Sharing 13

Dell EMC believes the information in this publication is accurate as of its publication date. The information is subject to change without notice.

THE INFORMATION IN THIS PUBLICATION IS PROVIDED “AS IS.” DELL EMC MAKES NO RESPRESENTATIONS OR WARRANTIES OF ANY KIND WITH RESPECT TO THE INFORMATION IN THIS PUBLICATION, AND SPECIFICALLY DISCLAIMS IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.

Use, copying and distribution of any Dell EMC software described in this publication requires an applicable software license.

Dell, EMC and other trademarks are trademarks of Dell Inc. or its subsidiaries.

2016 EMC Proven Professional Knowledge Sharing 14