Internet of things Emerging Network Technology Assessment 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

4. 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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5. 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

7. set the boundaries for this assessment as network technologies, which include routing technologies and
infrastructure.
2 Methodology
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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:
Increase(Network(
Capacity(Ef5iciency(
(Routing(
Technology(
Hardware( Software(
Infrastructure(
Figure 1. Problem Breakdown
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.

8. 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
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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

9. 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
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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
Figure 2. Software-Defined Network architecture.
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.

10. 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
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Figure 3. Vision for Network Functions Virtualization7
6 Dawson, P., Hill, N. (2013, July 31). Hype Cycle for Virtualization, 2013.
http://my.gartner.com/portal/server.pt?open=512objID=260mode=2PageID=3460702resId=2566317ref=QuickSearchcontent=html.
7 (2013, October 22th), Network Functions Virtualisation: An Introduction, Benefits, Enablers, Challenges Call for Action, “SDN and
OpenFlow World Congress”, Darmstadt-Germany

11. 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.
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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
Table 1. Performance Analysis
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.

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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 RD 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=truefrom=rhsc=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
-176 -166.28 -156.18 -145.75 -135.00 -123.93 -112.58
routers
SDWDM -176 -100.11 -20.54 62.78 149.23 238.18 329.68
Table 2. Cumulative Cash Flow (millions)
Forecast
Figure 4. Cumulative Cash Flow Chart for Payback Period Analysis
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.

18. 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.
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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%
Table 1. Client Market Size of Each Segment (billions)
22 http://www.trefis.com/company?hm=JNPR.trefis#/JNPR/n-0741/0915?div=truefrom=rhsc=top

25. 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%
Table 2. Industry benchmark of market share increase
Product23 Contribution Margin
Hardware-focused 40.10%
Software-focused 40.20%
Table 3. Product Contribution Margin
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%
Table 4. Client´s Market share in Year 2012
22 http://www.trefis.com/company?hm=CSCO.trefis#/CSCO/n-0325?from=sankey
24Juniper Annual Report 2012

26. Market
Segment 2015 2016 2017 2018 2019 2020
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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
Communicati
ons 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.
ATT Inc. 4.20% Americas 52.4% ATT 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
Table 8. Net Cash Flow (NCF) Forecast (millions)
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 9. Feasibility Analysis

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Discount Rate = 4%
Table 10 Net Present Value (millions)

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