The Internet of Things “Hard” and “Soft” Technology Enablers

Authors:

Federico Mazzoli

Yihan Zhong

Huilian Zhang

Faculty Advisor: George Cybenko

Teaching Assistant: Alexandros Sofianos

ENGM178 Final Report

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Executive Summary

Some of the most well-known network experts agree that there is a new revolution of the Internet

coming in the next decade1. This revolution is called The Internet of Things (IoT), and it could potentially

be the most disrupting change to ever happen to the Internet.

Almost every machine will eventually be connected to the Internet, causing an immense amount of

data to be created and transmitted. It is expected that the number of interconnected devices will almost

triplicate by the year 20202. This will generate a value of at least $14 trillion in the next decade for

industries and companies related to IoT1.

Current network infrastructure is a fundamental limitation for satisfying the exponential increase in

traffic and Quality of Service requirements. A new and innovative technology must be developed and

deployed in the next five years in order to take advantage of this imminent revolution of

communications.

This report is an assessment of the technologies the client company will be advised to invest in the

next five years. Three technologies were selected out of seven candidates: Software Defined Networking

(SDN), Network Functions Virtualization (NFV), and Optical Packet Switching (OPS).

The methodology used to reach to this recommendation consisted of six steps. First, the technology

candidates where identified. Then, the criteria used to filter these technologies were selected. After

collecting data and information, an engineering and financial analysis was made. Finally, once the

potential partners where chosen to mitigate risks, the final recommendation was given.

These recommended technologies will provide huge improvements to networks. SDN is expected to

increase the network utilization by 8 times. Also, NFV might lower costs related to the deployment of

new network services by 45 times. Lastly, OPS will be able to reduce data packet loss two orders of

magnitude. In addition, both SDN and NFV will have a payback period of less than a year.

At the end of this report, the conclusion will summarize our technology assessment recommendation.

This includes the technologies chosen, how to approach to them, and whom to partner with.

1 Chambers, J. CEO Cisco (2013, February 18). The Possibilities of The Internet of Everything Economy #IoE.

http://blogs.cisco.com/news/the-possibilities-of-the-internet-of-everything-economy/ 2GSMA (2012, February 27). GSMA ANNOUNCES THE BUSINESS IMPACT OF CONNECTED DEVICES COULD BE WORTH

US$4.5 TRILLION IN 2020. http://www.gsma.com/newsroom/gsma-announces-the-business-impact-of-connected-devices-could-be-worth-us4-

5-trillion-in-2020

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Table of Contents Executive Summary .................................................................................................... 1

1 Introduction ........................................................................................................... 4 1.1 Background ................................................................................................................. 4 1.2 Need statement ........................................................................................................... 4 1.3 Client’s need ............................................................................................................... 4 1.4 Scope of the Assessment ........................................................................................... 4

2 Methodology ......................................................................................................... 5

3 Technology Candidates ........................................................................................ 6 3.1 Recommended Technologies ..................................................................................... 7

3.1.1 Software Defined Networking (SDN) ..................................................................... 7 3.1.2 Network Functions Virtualization (NFV) ................................................................. 8 3.1.3 Optical Packet Switching (OPS) ............................................................................ 9

3.2 Runner-ups ............................................................................................................... 10 3.2.1 Multi-Protocol Wireless Routers .......................................................................... 10 3.2.2 Opportunistic Networking ................................................................................... 10 3.2.3 Sequential Greedy Scheduling (SGS) .................................................................. 10 3.2.4 Super Dense Wave Division Multiplexing (SDWDM) ........................................... 11

4 Analysis ............................................................................................................... 11 4.1 Feasibility Analysis .................................................................................................... 11 4.2 Performance Analysis ............................................................................................... 12 4.3 Profitability Analysis .................................................................................................. 13

4.3.1 Model Assumptions ............................................................................................. 13 4.3.2 Estimated parameters values .............................................................................. 14 4.3.3 Net Cash Flow (NCF) Forecast ............................................................................ 14 4.3.4 Payback Period Analysis ..................................................................................... 15

5 Risk Mitigation .................................................................................................... 15 5.1 Partnership ................................................................................................................ 15 5.2 Product Pipeline ........................................................................................................ 17

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6 Conclusion .......................................................................................................... 18

Bibliography ............................................................................................................. 19

Appendix .................................................................................................................. 22

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1 Introduction 1.1 Background

The Internet of Things (IoT) refers to the next Internet evolution in which people, devices, and people

will be interconnected. Three types of local networks are used to make the IoT operational, people-to-

people, people-to-machine, and machine-to-machine. 3 The Internet is the primary means for

transmitting beyond a local site, or it can also serve as one of the local secondary networks

interconnecting people or machines.

1.2 Need statement By 2020, with the realization of the IoT (Internet of things), more than 24 billion devices will all be

interconnected with people and data.4 This is what IoT will look like: Everything will become intelligent

with the realization of IoT: our refrigerators will email us grocery lists; our alarm will tell the coffee maker

when to start the morning brew etc. However, with the significant increase in data nodes and traffic

volumes, the network technology will be the fundamental limitation for achieving IoT. Thus, there is a

need to assess which network technology will be able to cost effectively support the requirements and

increased traffic of IoT to overcome this limitation.

1.3 Client’s need Our client is the vice president of research and development at a medium sized network equipment

company. With the belief that the growth of IoT would be a new market opportunity, the company wants

to find out the best way to capitalize on it. They expect the outcome of this assessment should be the

technology that will result in the introduction of commercial products within 5 years and these products

would become profitable within 2 years following new product introduction. In addition, the client has

aske for a suggestion of an Internet service provider to have partnership with, based on our prediction

that for cable technologies or wireless technologies, which technology will be superior and more cost

effectively to support the requirement of IoT in the 2020 timeframe.

1.4 Scope of the Assessment Originally, our client asked us to perform an assessment on intelligent router technology to serve as

the basis for our recommendations. However, after full considerations, we think this may be too narrow

and might neglect other alternatives that might be more valuable to our clients. Therefore, we decided to

3 Dave Evans. How the Internet of Everything Will Change the World…for the Better #IoE [Infographic]. http://blogs.cisco.com/ioe/how-

the-internet-of-everything-will-change-the-worldfor-the-better-infographic/ 4 GSMA (2012, February 27). GSMA ANNOUNCES THE BUSINESS IMPACT OF CONNECTED DEVICES COULD BE WORTH

US$4.5 TRILLION IN 2020. http://www.gsma.com/newsroom/gsma-announces-the-business-impact-of-connected-devices-could-be-worth-us4-

5-trillion-in-2020

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set the boundaries for this assessment as network technologies, which include routing technologies and

infrastructure.

2 Methodology The methodology we used for the whole assessment project consisted of 6 steps:

1. Identify Technology Candidates To start research work for this project, we broke down this problem with the following structure:

In our preliminary research, through reading the academic papers, we found out 21 potential

candidates: Fast Packet Classification, Deficit Round Robbin, AOMDV Routing, Things Management,

Neural Network, Dynamic BW Allocation, Opportunistic Network, Feedback Loop Control, Cognitive

Network , Autonomic Network, Latency Multicasting Scheduling, MAPE, OOPDAL, Sequential Greedy

Scheduling, Open Flow, Multi-Protocol Routing, Super Dense Wave Division Multiplexing, Optimized,

Routing Lookup, Software Defined Network, Cognitive Network and ROADM. 6 candidates were

selected both in routing and infrastructure areas as our preliminary recommendation for further research.

With more in-depth research, we found another promising candidate called Network Functions

Virtualization (NFV). So in total we had 7 candidates for final selection.

2. Develop Criteria According to the need statement and our client’s interest, we developed a set of criteria to compare

and select the technology candidates.

Feasibility of each technology needs to be analyzed to assess whether the technology could be

commercialized and ready for market within 5 years from now.

Performance will be measured from engineering and economic perspectives to determine which

technology is more superior in order to meet the increasing demand of Internet traffic due to IoT

realization. More specifically, information about transmission bandwidth, data packet loss, network

capacity utilization operation cost and power consumption for each technology respectively need to be

collected for further comparison.

Increase  Network  Capacity&  Ef5iciency  

 Routing  Technology  

Hardware   Software  

Infrastructure  

Figure 1. Problem Breakdown

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Profitability is another key criterion due to the requirement of being profitable within 2 years after

commercialization. Payback analysis in specific is needed to measure profitability. Only technologies

with payback period less than 2 years will be selected.

3. Collect Data and Information The sources we used to collect relevant qualitative and quantitative data for further analysis include:

technical academic papers on state-of-development of these technologies; academic professors and

industry experts’ opinions; our client’s and its key competitor’s past 5 years annual reports; industry

reports on telecommunication equipment manufacturing, internet service providers, wired

telecommunication carriers, wireless telecommunication carriers and cable providers.

4. Conduct Analysis With the collected data and information, we analyzed the technologies in two aspects: engineering

performance analysis and economic performance analysis. One thing that should be noticed here is

since these technologies address different problems, they cannot be compared between each other. So

the engineering performance analysis we conducted mainly focused on how and to what extent, these

new technologies could improve the current situations. We compared the difference before and after

adoption of the new technology. For profitability analysis, we forecasted the net cash flow of each

technology in the coming years based on some economic assumptions and from our client’s historical

data and industry benchmark. Then we calculated the cumulative cash flow of them each year to serve

as the foundation for the payback period analysis. With the profitability analysis, those technologies that

could meet the criteria would be selected.

5. Mitigate Risk In this step, we forecasted some possible risks in future and provided some suggestions to manage

the risks, which included the partnership selection and product pipeline management.

6. Final Recommendation With the selected technologies and risk mitigation considerations, we derived a strategic plan to our

client as our final recommendation.

3 Technology Candidates As it can be seen in the interim report, six candidates were selected, and they were categorized by

the segment they were going to benefit: Enterprises, Mobile Carriers or Internet Service Providers. The

method used for choosing these candidates was identifying which development stage the technologies

were currently in, as well as the potential improvement they would provide to the network infrastructure.

After further research, we got to the conclusion that SDN –although in different applications- could

also be applied to Mobile Carriers and Internet Service Providers, not only Enterprises. Furthermore, a

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new technology called Network Functions Virtualization (NFV) was also assessed. This technology could

also be applied to the three segments. Both these two technologies, together with Optical Packet

Switching, are the technologies we recommend to invest.

The three technologies recommended will be explained in detail below, and the runner-ups will be

briefly explained. For further information about the runner-ups, please read the interim report.

3.1 Recommended Technologies 3.1.1 Software Defined Networking (SDN)

As the number of connected devices exponentially increases, networks will become much more

complex and expensive to maintain. Enterprises and Service Providers are looking for ways to increase

their network security and flexibility to reduce the rising operational costs caused by the increase in

network complexity, security problems derived from Bring Your Own Device (BYOD), or the deployment

of new services generated by IoT. SDN appears as the most promising emerging approach to this

problem, decoupling Data and Control Planes of network devices architecture using a vendor-agnostic

interface. 5

As shown in Fig.2, the Data (or Forwarding) Plane is a low-level layer which function is to forward the

incoming packets according to the information stored in a routing table. The Control Plane is concerned

in creating a map of the network, deciding how packets will be distributed and storing that information in

the routing table. Traditional network architecture allocates both layers inside the network device’s

firmware.

5 Bakshi, K., Cisco (2013). Considerations for Software Defined Networking (SDN): Approaches and Use Cases. In Aerospace Conference,

2013 IEEE. DOI: 10.1109/AERO.2013.6496914.

Figure 2. Software-Defined Network architecture.

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By switching to SDN architecture, the Control Plane of all the network devices of the enterprise’s

network could be centralized on a single separate device, communicating to all routers and switches

using a SDN Controller. This allows network managers to configure and optimize network resources very

quickly via custom-made SDN programs, as the dependency of proprietary software will disappear.

In addition, SDN allows the creation of virtualized networks. This means that a physical network

infrastructure could be split into several logically isolated networks that can be individually programmed

and managed. As a consequence, current cloud service providers, such as Amazon or Google, could

offer cloud networking as Infrastructure as a Services (IaaS).

Some of the biggest networking equipment providers such as Cisco and Juniper Networks are

already deploying their own SDN Controllers, as well as providing their products with SDN capabilities. It

is expected that SDN will become a standard in the next five years6, which is why network companies

are assigning resources to the software side of the business, as hardware equipment becomes a

commodity due to the new architecture.

3.1.2 Network Functions Virtualization (NFV) Current networks are formed by dedicated networking equipment that are expensive to maintain and

take considerable physical space, making new services deployment slow and expensive. Network

Functions Virtualization (NFV) aims to revolutionize how networks are designed by virtually consolidating

many network equipment types onto industry high volume servers, switches and storage.7

6 Dawson, P., Hill, N. (2013, July 31). Hype Cycle for Virtualization, 2013.

http://my.gartner.com/portal/server.pt?open=512&objID=260&mode=2&PageID=3460702&resId=2566317&ref=QuickSearch&content=html. 7 (2013, October 22th), Network Functions Virtualisation: An Introduction, Benefits, Enablers, Challenges & Call for Action, “SDN and

OpenFlow World Congress”, Darmstadt-Germany

Figure 3. Vision for Network Functions Virtualization7

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The Internet of Things will not only make the network more complex and harder to maintain, but it

will also generate a significant increase in the demand for new, innovative services. With the

implementation of this NFV, Service Providers could reduce to time of service deployments from months

or years, to a couple of days.8 This would not only lower the costs of new services deployment, but it

would also reduce risks and significantly increase their capacity to provide new services.

Although currently associated to telecoms, NFV could also be implemented into Enterprises. The

applications would be different though. NFV for Enterprises will enable more simple, cloud-like data

centers.9

3.1.3 Optical Packet Switching (OPS) One important problem that current system configuration is facing is the conversion loss of

bandwidth when optical signal was converted to electronic signal transmitting through a typical router. In

other words, the bottleneck at a switching node is the electronic. Thus, the ideal case is that every

packet transmitted and switched on Internet system is in purely optical form. Resolving data packet loss

issue from this bottleneck will increase the network capacity significantly. 10

Accessing Random Access Memory (RAM) is a necessary step to realize pure optical switching.

Currently, RAM cannot be accessed by optical signal using any specific technology. OPS pushes one

step further to pure optical switching. It requires a networking system to have an optical and an

electronic layer. 11 The OPS allows all IP packets to run over a pure optical layer which consists of fiber

switches and links. The realization of optimal interactions between two layers requires other two

components. The special ferroelectric material characteristics of compound Liuthium Niobate and the

polarization insensitiveness of Semiconductor Optical Amplifiers (SOA). However, these two

technologies are still in research stage and will not be able to be adopted within 5 years.12

8 Dor Skuler, Vice President & General Manager of CloudBand Business Unit at Alcatel-Lucent. “Future of Netwoks” documentary, Part 3. 9 Brad Brooks, SVP and CMO of Juniper Networks. Interview by Jude Chao.

http://www.enterprisenetworkingplanet.com/datacenter/junipers-take-on-sdn-and-nfv-1.html 10 Qiao ,C. and Yoo ,M., (1999) ,Optical Burst Switching (OBS) —A New Paradigm for an Optical Internet, J. High SpeedNetworks, vol. 8,

no. 1, pp. 69–84. 11 Yoo, M., Qiao ,C., Dixit, S, (2001, Feburary), Optical Burst Switching for Service Differentiation in the Next-Generation Optical Internet.

IEEE Communications Magazine 12 Qiao C., (2000, September), Labeled Optical Burst Switching for IP-over-WDM Integration, IEEE Commun. Mag., vol. 38, no. 9, pp.

104–14.

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3.2 Runner-ups 3.2.1 Multi-Protocol Wireless Routers

During the first years of the Internet of Things, as the number of connected devices increases, so will

the number of wireless protocols they use to communicate. Each manufacturer will use the protocol they

think is best, leaving the consumer with no choice but to adapt to this protocol heterogeneity.

A multi-protocol wireless router would allow consumers to connect all their devices using the same

wireless router, as it would be capable of communicating with most popular protocols such as Wifi,

Bluetooth, ZigBee, Z-Wave, RFID, NFC, and so on.

3.2.2 Opportunistic Networking Current cellular networks rely on the capacity of a single base station to satisfy the demand of all

connected devices in a certain radius. As the number of devices increases, congestion in high density

areas is more likely to happen. An approach to prevent this issue is the use of multi-hop ad hoc

networks. These systems rely on mobile nodes that are able to communicate with each other even if a

fixed route connecting them never exists. The most promising example of an ad hoc system is

Opportunistic Networks. 13 14

3.2.3 Sequential Greedy Scheduling (SGS) The main benefit that this technology brings is that an optimized data transmission path is also

calculated and scheduled ahead before a data packet is sent. In a networking system, there are many

routers to transmit data packets. A transmission path is always pre-determined by routing look-up table.

When data was transmitting through that set path, it does not have the flexibility to change path when

there is a roadblock in that pre-determined path, e.g. a loss data packets or an invalid web request.

These roadblocks will significantly slow down the transmission efficiency because the path rarely got

updated.15 16 The Sequential Greedy Scheduling allows a router to continuously check the availability of

the next router port it will send data packet to. Once every router in the system has this algorithm

implemented, the best path can always be calculated and adopted into the routing look-up table.

13 Georgakopoulos, A., Tsagkaris, K., Karvounas, D., Vlacheas, P. (2012, September). Cognitive Networks for Future Internet: Status and

Emerging Challenges. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6269156 14 Pelusi, L., Passarella, A., Conti, M. (2006, November). Opportunistic networking: data forwarding in disconnected mobile ad hoc

networks. In Communications Magazine, IEEE. Vol.44, N.11. 15 Petrovic , M. , Smiljanic, A. , and Blagojevi ,M., (2006), Design of the Switching Controller for the High-CapacityNon-Blocking Internet

Router, in Proc. IEEE ICCCAS, vol. 3, pp. 1701–1705. 16 Petrovic ,M., Blagojevic ,M. , Jokovic, V. , and Smiljanic ,A. , (2009 August), Design, implementation, and testing of the controller for

the terabit packet router”, in IEEE Transactions (VLSI) Systems, vol. 17, No. 8, pp 1157

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3.2.4 Super Dense Wave Division Multiplexing (SDWDM) Wave Division Multiplexing (WDM) is a mature technology to enable fiber optics to transmit

enormously amount of data – high bandwidth. WDM technology allows multiple light sources with

different wavelength to group together and transmit through a single fiber. 17 They will then be separated

and sent to optical receivers. Each light beam – usually from laser contains tons of data. Thus, the key to

increase the Internet traffic capacity is to pack more optical signals with different wavelengths into a

fiber, and that is the idea of Super Dense Wave Division Multiplexing (SDWDM). Rare-Earth material

doped fiber and laser source is a common approach for SDWDM.18

4 Analysis 4.1 Feasibility Analysis

Feasibility was the first criterion we applied to eliminate technology candidates that were not able to

be commercialized within 5 years.

For technologies (Multi-Protocol Router, SDWDM) that were already developed with its first

prototype in the market, we used 0-2 years as the time window for them to be grown. For emerging

technologies (SDN, NFV and OPS), their estimated time to market were based on the Gartner Hype

Cycle Report. For technologies (SGS, Opportunistic Networking) that could not be found in the

professional market forecast or industry reports, we calculated the time to market by adding two

periods. The first period used was the time between published year of the first paper related to the

technology and this year. The second period was the calculated average time to market estimation

provided by the industry reports. With these two periods, it is calculated that the average time between

concepts introduction and commercialization was about 7 years. Summary of the feasibility can be

found in Appendix table 9.

With our feasibility analysis, the Sequential Greedy Scheduling (SGS) and Opportunistic Networking

were eliminated. Although the time to market of Optical Packet Switching (OPS) was larger than 5 years,

we did not eliminate it here because we realized that its contribution for the whole Internet advancement

would be too significant to be ignored for our recommendation.

17 Ding, L. , Kai, G. ,Xu, Y., Zhao, C., Yuan, S. and Ge, C., (2001, April 27), Novel four-wavelength erbium-doped fiber laser as

multichannel source in WDM system,Rare-Earth-Doped Materials and Devices, V, 239 18 Masuda, H. , Kawai ,S. , Suzuki ,K. , and Aida ,K. , (2006), Wide-band WDM transmission using erbium-doped fluoride fiber and Raman

amplifiers, Optical Amplifiers and Their Applications

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4.2 Performance Analysis Internet of Things will bring many challenges to the Internet system such as causing a traffic jam and

enormously increasing power consumption due to heavily handling the Internet complexity due to the

huge amount of devices that will be interconnected. All five technologies address different problems, so

it was hard and meaningless to select a set of engineering metrics to compare each technology

candidate one by one and conclude which one will be more superior. Instead, we used various metrics

to compare before and after each technology adoption.

Transmission bandwidth values for Super Dense Wave Division Multiplexing (SDWDM) and data

packet loss measurements for Optical Packet Switching (OPS) were directly quoted from academic

article on peer reviewed journals. SDWDM would enable the Internet to have an 8 times larger

transmission bandwidth then that of today. OPS would be able to eliminate almost all data packet loss

(20dB) which means increasing the Internet capacity by 100 times. This would truly solve the problems

not only from Internet of Things but also High Definition video streaming demand in the future. Thus, this

is an emerging technology that our client must consider in the future even though it is not feasible in

years. Software Defined Networking (SDN) is known to be able to utilize network capacity better as

mentioned in the technology overview section. How much it can improve network resource utilization

cannot be measured in a testing environment and then be scaled it up to the real Internet System. In this

situation, quotes from field experts were used to estimate the improvement. It was estimated that

network utilization would be improved by 8 times after SDN is developed. For Network Functions

Virtualization (NFV), the major advantage is that it would enable an ultrafast service deployment. When a

network would be set up faster, operational cost used by our client is reduced. We estimated how much

it would cost nowadays to set up network service using number of technician and time needed.

Compared to today’s conventional system, NFV adoption would only require 45 times less money

because one technician and few minutes would be enough to set up any virtual network service. Multi-

Protocol Router would be basically an all-in-one device to replace routers working for each individual

protocols. The obvious and important benefit would be saving power consumption. The first prototype of

Multi-Protocol routers in the market consumes 3 times less power than all single protocol routers

combined.

It must be noted that the metrics used in performance analysis were different because each

technology addresses different issues. The importance of each metric would be very different depending

on which problem our client wants to focus on. Since all candidates demonstrated significant

improvements, we did not eliminate any using performance criterion. The table below is a summary of

the performance.

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Performance Improvement

Before Adoption

After Adoption Improvement

Super Dense Wave Division Multiplexing

Larger Transmission Bandwidth

0.78GHzxiii-xv 6.25GHzxiii-xv 8X

Optical Packet Switching Less Data Packet Loss ~20dBxvi-xvii ~0dBxvi-xvii 100X

Software Defined Networking

Higher Network Capacity Utilization

10%ix 80%ix 8X

Network Functions Virtualization

Lower Operation Cost

$3412500xxxi-

xxxiii $75000xxxi-

xxxiii 45X

Multi-Protocol Routers Lower Power Consumption 135Wxxxvii 49.5Wxvii 3X

4.3 Profitability Analysis 4.3.1 Model Assumptions

To evaluate whether the technology candidates could be profitable within 2 years following

introduction, we need to perform the payback period analysis. For payback period analysis, the

cumulative cash flow is needed. So we formed a net cash flow forecasting model. There’re 3 basic

assumptions of our model:

1. We assume that our client’s market share would remain the same without our recommended new

products.

2. With our recommended new products, our client our client’s market share of that market segment

will increase. With different market share, the revenue would be different and the difference would be

counted as the revenue from our new product.

3. All new products could be able to be launched by year 2015, since there are already some

prototype products in the market right now.

Table 1. Performance Analysis

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4.3.2 Estimated parameters values The input parameters for our forecasting model include initial investment, market size of each

segment, market share growth potential, and product contribution margin. 1. Initial investment. This means the investment expenditure needed for finishing the R&D project

and commercializing the new product. This would be the net cash flow of Year 0. Year 0 is when the

investment is made and there would be only cash outflow. The estimation of the investment

expenditure were based on recent similar product development projects of our client’s.

2. The market size of each segment in future. Different technologies will be applied to develop

different products. For our candidates, some can only be applied to a particular product line while some

can be applied to more than one product lines that could address different needs of different market

segments. For different product lines, the market size of each product line varies. Some market segment

may be so big that it is larger than any other segments. For the market size forecast data, we refer to the

forecasting data from Trefis.com19. To check its credibility, we compared the data analysis of our client’s

from this source and the data from our client’s previous annual reports and confirmed that this source

should be credible. Market size data of each product segment could be found in Appendix table 1.

3. The client’s current market share and the growth potential of each market segment. To

calculate how much revenue the new product could bring in, as we mentioned before, the revenue

difference from different market share because of the new product would be the key. The degree of how

the new product could increase the market share was based on the industry benchmark. To determine

the value of the industry benchmark, we compared several major players’ past 3 year’s market share

changes, including our client’s and Cisco’s. The client´s market share data could be found in Appendix

table 4. The industry benchmark of market share increase for one year could be found in Appendix table

2.

4. The contribution margin of the new product. To determine the cash inflow of each new product

option, besides revenue, we also need to estimate the contribution margin of the new product. And for

the analysis, we assumed that the new products would have at least the same contribution margin rate

with the current products. Considering the software solutions and hardware products’ contribution

margin might be different, we applied two different margin rates (Appendix table 3) to our candidates’ for

analysis, which will be determined by whether it’s software focused or hardware focused.

4.3.3 Net Cash Flow (NCF) Forecast With the assumptions established, Appendix table 5 is our Net Cash Flow forecast of each candidate

by 2020, the realization time of IoT.

19 http://www.trefis.com/company?hm=JNPR.trefis#/JNPR/n-0741/0915?div=true&from=rhs&c=top

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4.3.4 Payback Period Analysis After we had the Net Cash Flow forecast data, we then calculated the Cumulative Cash Flow of each

technology each year. And here is the result:

Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6

SDN -352 43.69 460.45 895.88 1345.25 1804.12 2272.56 NFV -352 4.33 379.25 770.75 1174.82 1587.73 2009.34 Multi-protocol routers

-176 -166.28 -156.18 -145.75 -135.00 -123.93 -112.58

SDWDM -176 -100.11 -20.54 62.78 149.23 238.18 329.68

According to our payback period analysis, only SDN and NFV could meet our client’s requirement of

being profitable within 2 years following introduction. The payback period of each technology could be

found in Appendix table 7.

5 Risk Mitigation 5.1 Partnership

Partnership with customers could decrease the investment risk and increase the probability of

achieving stable large volumes. Traditional Internet Service Providers provide internet access via wired

networks, while Mobile Carriers provide internet services via wireless network.

Table 2. Cumulative Cash Flow (millions)

Forecast

Figure 4. Cumulative Cash Flow Chart for Payback Period Analysis

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Originally, our client asked us to assess which technology will be more superior and more cost

effectively support the requirements of IoT: cable or wireless? In terms of speed and the capacity to

handle traffic: Fiber Optics is much faster than wireless. As it currently stands, Fiber Optics are achieving

speeds that are 250,000 times faster than wireless and in the experimental stages, fiber can carry 69,000

times more data than the entire bandwidth delivered by a wireless tower. 20 However, in terms of

profitability, wireless network are much more profitable than wired network. And the current trend is that

people prefer wireless network to fixed network. Regarding this question, cable or wireless, we think

these two technologies are complementary technologies, not competing ones. After all, to have a

successful wireless broadband network, you must build it on the back of a fast, high volume fixed

network.

And there are many companies who operate both, especially telecommunication carriers. So when it

comes to the partnership, we recommend choosing those. In terms of partnership selection, 5

companies were reviewed. The criteria we used for evaluation include: 1) their global market share, 2)

their based region and the sales contribution of that region. This is important since our client’s company

operates business in 3 regions: Americas, “APAC” (Asia Pacific), and “EMEA” (Europe, Middle East, and

Africa), we recommend having at least one partner in each region to lower the risk of sales fluctuations.

3) Their current relationship with our client. This would affect the possibility of successful partnership.

After further consideration, we recommend to partner with Verizon Communications Inc. for

Americas market, China Mobile Limited for APAC market, and Vodafone Group Plc. for EMEA market.

Detailed comparison information of these candidates could be found on Appendix table 6.

Internet of things is the future and it would benefit every one’s daily life by processing personal data

from smart machines or bio-implanted chips. On the other hand, it raises a big concern about security of

our personal information. Since the Edward Snowden revealed the mass surveillance issue, the debates

over information privacy had been fueled. Thus, there might be a risk that the progress of Internet of

Things revolution might slow down in US communication industry due to tighter government regulations.

To buffer this kind of risk, partnering with mobile carriers in China is necessary not only because of

the opportunity to expand business but also the Chinese government had legislated support policies to

IoT development in its 12th Five-Year Plan. Since it is already proven mobile carrier segment will

generate higher profit, China Mobile was selected as the best partner in China because its major

business focus is to provide mobile service.

20 http://www.qualcomm.com/common/documents/presentations/Web_LTE_Advanced_031210.pdf

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5.2 Product Pipeline Our selected technologies, SDN and NFV, are mainly software-focused and they are complimentary.

But given the current hardware division accounts for more than 80% of our client’s revenue, it would be

too risky to only produce the software products. Besides software products, we also recommend to

produce compatible hardware such as routers and switches. Additionally, bundling the software and

hardware products together might be a more appealing solution for sales.

In terms of product development strategy, since SDN and NFV can be applied to all three segments

(Enterprise, ISPs and Mobile carriers), with the Net Present Value (NPV) analysis on Appendix table 10,

we recommend to prioritize developing solutions for mobile carriers.

In long run, we recommend to develop new switches for Optical Packet Switching technology and

add it to the product pipeline. Our reasons are, firstly, the market size of network switches is really huge,

much larger than any other market segments (Appendix table 1). Secondly, our client is a new entrant to

this market segment, so its market share is quite low now. New product in this segment could help our

client to gain promising market share. In addition, as we analyzed before, Optical Packet Switching

would be a transformational technology. Even though it could not be introduced within 5 years from now

on, but it is still worth being explored from now on and probably we could have the first switches based

on that in 10 years.

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6 Conclusion Our recommendation is to develop Software Defined Networking and Network Function Virtualization

technologies in order to adapt to the imminent change in the network infrastructure. In addition, the

company should start investing in research for Optical Packet Switching, as it seems to be the most

promising technology to improve data switching in the next ten to fifteen years.

With the impending deployment of SDN technology, Enterprises and Service Providers will begin to

perceive networking equipment as a commodity, as the proprietary software installed in those devices

will cease to exist. In order to stay in the market, the company should shift their strategy to software

solutions, instead of hardware ones. This means, create SDN applications that the clients may apply on

top of vender-agnostic networking equipment.

A rising concern for telecommunication companies is the difficulty to deploy new network services,

as it could require new hardware equipment and accommodating them is becoming increasingly difficult,

both because of power consumption and lack of physical space. Also, the time required to install and

manually configure the devices makes this process time-consuming and expensive. NFV will solve all

these issues by virtually consolidating many network devices into high volume equipment. The company

should focus on creating NFV software applications to improve this technology and provide the clients

with the best tools to deploy new network services in the least amount of time.

Even though NFV doesn’t need of SDN to work and vise versa, they are highly complementary and

the combination of them will provide the best outcomes. Virtualizing the networking equipment and their

control plane will allow network managers to optimize the efficiency of their network. By having a

software-based network, new algorithms to improve its capacity and quality of service could be

developed.

In order to mitigate risks, we would recommend partnering with some telecommunications

companies distributed across the different markets of the globe. For the US market, Verizon is the best

possible candidate. In Europe, the company should partner with Vodafone. Finally, in the Asia-Pacific

market, China Mobile should be the first company to partner with.

The Internet of Thing will not only generate a considerable amount of problems to current networks,

but it will also create an enormous number of business opportunities. We strongly believe that our

recommendation will solve some of the problems derived from IoT, it will help your clients increase their

revenue by providing more services, and it will help the company align with the future of networks.

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Appendix

Product Market Segments (billions)21 2013 2014 2015 2016 2017 2018 2019 2020

Security & others

Global Blade Server 11.9 13.1 14.1 14.9 15.7 16.2 16.4 16.7

Global Enterprise WLAN

4.43 5 5.55 5.99 6.23 6.42 6.55 6.68

Total 16.33 18.1 19.65 20.89 21.93 22.62 22.95 23.38

Edge Router Total 7.13 7.63 8.09 8.49 8.92 9.27 9.55 9.84

Core Router Total 3.05 3.17 3.29 3.43 3.53 3.63 3.71 3.78 Enterprise router Total 3.52 3.59 3.70 3.84 3.97 4.09 4.21 4.32

Network Switches

Top-layer switches market size

1.24 1.3 1.38 1.45 1.52 1.59 1.63 1.67

Bottom-layer switches market size

18.9 19.5 20.3 21.1 21.8 22.4 23 23.4

Total 20.14 20.8 21.68 22.55 23.32 23.99 24.63 25.07

Network Service

PSD service % of product revenue

31.1% 31.1% 31.1% 31.1% 31.1% 31.1% 31.1% 31.1%

SSD service % of product revenue

46.5% 46.5% 46.5% 46.5% 46.5% 46.5% 46.5% 46.5%

22 http://www.trefis.com/company?hm=JNPR.trefis#/JNPR/n-0741/0915?div=true&from=rhs&c=top

Table 1. Client Market Size of Each Segment (billions)

Market Segments22 Industry benchmark of market share increase

Security & Others 1.70% Edge Router 1.50% Core Router 0.70% Enterprise router 0.50% Network Switches 0.81%

Product23 Contribution Margin Hardware-focused 40.10% Software-focused 40.20%

Market Segments Market share in Year 2012

Security & others 4.71%

Edge Router 16%

Core Router 27.70%

Enterprise router 6%

Network Switches 2.80%

22 http://www.trefis.com/company?hm=CSCO.trefis#/CSCO/n-0325?from=sankey 24Juniper Annual Report 2012

Table 2. Industry benchmark of market share increase

Table 3. Product Contribution Margin

Table 4. Client´s Market share in Year 2012

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Market

Segment 2015 2016 2017 2018 2019 2020

SDN

Security & Others 134.29 142.76 149.87 154.59 156.84 159.78

Edge Router 48.66 51.07 53.65 55.76 57.44 59.19 Core Router 9.24 9.63 9.91 10.19 10.41 10.61 Enterprise

router 7.42 7.70 7.96 8.20 8.44 8.66 Network Switches 70.42 73.24 75.75 77.92 80.00 81.43 Network Service 125.67 132.36 138.29 142.72 145.73 148.77

Total 395.69 416.76 435.42 449.37 458.87 468.44

NFV

Security & Others 107.43 114.21 119.90 123.67 125.47 127.82

Edge Router 48.66 51.07 53.65 55.76 57.44 59.19 Core Router 9.24 9.63 9.91 10.19 10.41 10.61 Enterprise

router 7.42 7.70 7.96 8.20 8.44 8.66 Network Switches 70.42 73.24 75.75 77.92 80.00 81.43 Network Service 113.17 119.07 124.34 128.33 131.14 133.90

Total 356.33 374.92 391.50 404.07 412.91 421.61

Multi-protocol routers

Enterprise router 7.42 7.70 7.96 8.20 8.44 8.66

Network Service 2.31 2.39 2.47 2.55 2.62 2.69

Total 9.72 10.09 10.43 10.75 11.07 11.35

SDWDM

Edge Router 48.66 51.07 53.65 55.76 57.44 59.19 Core Router 9.24 9.63 9.91 10.19 10.41 10.61

Network Service 18.00 18.87 19.76 20.50 21.09 21.70

Total 75.89 79.56 83.32 86.45 88.95 91.50

Table 5. Net Cash Flow Forecast (millions)

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Name Global Market Share

Based regions

Region Sales Contribution last year

Other information

Verizon Communications Inc.

5.50% Americas 52.4%

Verizon Communication Inc. accounted for 10.3% and 10.4% of our client's net revenues, respectively, in 2012 and 2010.

AT&T Inc. 4.20% Americas 52.4% AT&T and Cisco became alliance.

Vodafone Group Plc 4.00% EMEA 29.0%

Vodafone choses to partner with Infradata and our client to secure their network in 2005

China Mobile Limited 6.40% APAC 29.0%

China Mobile selected our client to capitalize on smartphone revolution for CMNET backbone in 2011.

NTT DoCoMo. 4.30% APAC 18.6%

NTT Communications choosed our client’s mobile security solutions to enable "Bring your own device" service.

Table 6. Partnership Candidates

Comparison

Table 7. Payback Period Summary

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2014 2015 2016 2017 2018 2019 2020 Year 0 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6

SDN -352 395.69 416.76 435.42 449.37 458.87 468.44 NFV -352 356.33 374.92 391.50 404.07 412.91 421.61 Multi-Protocol Routers

-176 9.72 10.09 10.43 10.75 11.07 11.35

SDWDM -176 75.89 79.56 83.32 86.45 88.95 91.50

Technology Years to Mainstream Adoption

MPR - Multi-protocol Router 0-2 yearsxxxvii

SDWDM - Super Dense Wave Division Multiplexing 0-2 yearsxiv-xv

NFV – Network Functions Virtualization 2-5 yearsi-ii

SDN – Software Define Networking 2-5 yearsi-ii

SGS - Sequential Greedy Scheduling >7 yearsxii

ON - Opportunistic Networking >7 yearsxiv

OPS - Optical Packet Switching >10 yearsxv-xvii

Table 8. Net Cash Flow (NCF) Forecast (millions)

Table 9. Feasibility Analysis

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Table 10 Net Present Value (millions)

Discount Rate = 4%

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