cfv

1. CHAPTER 1
INTRODUCTION
Testbed is a real experimental set up which helps researchers, industrialists and
students to test and validate their research findings or protocols or algorithms
developed. There are two kinds of result validation: simulation and real experimental
testbeds. The testbeds are broadly classified based on their field say industrial or
research. Furthermore, it gets its name based on the field it is associated with say
wireless sensor network testbeds, sensor testbeds, actuator testbeds etc.,
There are so many new technologies coming up, but when investigated, all of
them had roots from the previous technologies. For instance, Cloud had its roots from
web services, big data from databases. Similarly one another popular technology
Internet of Things (IoT) has its roots deep in sensor and actuator networks or in simple
to say, Wireless Sensor Actuator Networks (WSAN) [1]. IoT is predicted to be the web
4.0 version or in other words the “future internet” [2].
Research work in the field of Wireless Sensor Networks (WSN) [3] is very
exhaustive and deep because of the scope for many new sensor based developments [4]
and their challenges [5] associated because of its constrained nature [6]. The nature of
operation of WSN is unique in the sense; it is constrained on energy, computation and
memory. Research has been carried out in energy optimization techniques at various
level including routing aspects [7]. But, the interesting fact is most of the research
validations were performed on simulators as against real testbeds. The reasons being:
heavy infrastructure cost, lack of reusability, lack of interoperability, proprietorship [8]
and many more. Still there were few research proposals validated on experimental
testbeds.
As IoT was considered extension of WSN in most cases, any research proposal
of IoT was also validated on WSN testbeds. Though there is similarities in features like

2. 2
constrained on memory, energy etc., but there are some prominent differences too [9].
This demands an exclusive testbed model for IoT system as such. This chapter will
introduce the basics of IoT, its features, its ingredients, its challenges and the
justification for the need for an open source IoT testbed [10] against its proprietary
counterparts in WSN.
1.1 INTERNET OF THINGS
IoT [11] is all about connecting anything, anytime and anywhere in the world.
It is estimated that the number of internet connected things in the world would rise to
50 billionby2020 [12]. The IoT is anemerging topic of technical, social, and economic
significance. Consumer products, durable goods, cars and trucks, industrial and utility
components, sensors, and other everyday objects are being combined with internet
connectivity and powerful data analytic capabilities, that promise to transform the way
we work, live, and play. Projections for the impact of IoT on the Internet and economy
are impressive, with some anticipating as many as 100 billion connected IoT devices
and a global economic impact of more than $11 trillion by 2025 [13].
1.2 INGREDIENTS OF IoT
IoT is a technology aiming at interconnecting everything in the world via the
internet backbone to achieve seamless connectivity. It uses IPv6 to uniquely identify
everything/device which it encounters. The whole idea of interconnection is to exploit
services across boundaries. Various existing technologies were able to provide efficient
solutions but in silos. Thus, IoT attempts to bridge the gaps be it across devices or
application or network or communication medium. IoT is a culmination of embedded
systems, sensors, actuators, cloud communicated via wired or wireless means to
achieve smart solution [14] to various fields be it smart home, smart irrigation, smart
electricity, smart cities [15], smart “X” (X can be substituted with almost any word,
that is the power of IoT solutions). There are many components which are very

3. 3
important in the building up of an IoT solution [16], but sensors and actuators take the
front seat. Sensors and Actuators are explained in the following topic.
1.2.1 Sensors and Actuators
Sensors are input devices. The sensors are capable of sensing parameters like
temperature, humidity, pressure, acceleration etc., Actuators are output devices capable
of reacting to commands. Testbeds comprises of exhaustive set of input and output
devices. Examples for actuators can be LED, buzzers, relays etc.,
 LED: Light Emitting Diode (LED) the most basic way of representing the
output. Long legs (+ve) connected to output pin and short legs (-ve) connected
to ground. When the value in the output pin goes high, LED Glows. Figure 1.1
is the image of an LED.
Figure 1.1 LED
 Buzzer: It is usually a piezo electric buzzer. Connect as the same way as an
LED. The +ve goes to output pin and –ve goes to ground. Figure 1.2 is the
image of a Buzzer.
Figure 1.2 Buzzer

4. 4
 LM35: Linear Monolithic (LM35) is an analog temperature sensor. The
conversion formula between analog reading and temperature in celsius
temperature = value/9.31, where value is the analog reading received from
the LM35. This is much suitable for microcontroller boards which support
analog pins, e.g. Arduino. Figure 1.3 is the image of LM35.
Figure 1.3 LM35- Analog temperature sensor
 DHT11: Digital Humidity Temperature (DHT11) is a digital temperature
sensor. This sensor is suitable to measure temperature and humidity. They
can provide 20 to 80% humidity readings and 0 to 50 degrees temperature
readings with 5% and (+/-) 2% accuracy respectively. The input voltage
ranges between 3 to 5 volts. Their pins can be configured as input or output
as needed. Figure 1.4 is the image of DHT11.
Figure 1.4 DHT11-Digital temperature sensor
 LDR: Light Dependent Resistor (LDR) is also known as photocell or photo
resistor. It is made of high resistance semiconductor. The name signify their
way of working. The resistance varies based on light incident on it. The

5. 5
resistance decreases on increased light intensity (few hundred ohms) and the
resistance increases on diminished light intensity (MΩ). This phenomenon is
called as photoconductivity. They can be employed in variety of
applications like detector and switching circuits. Figure 1.5 is the image of
LDR.
Figure 1.5 Light Dependent Resistor(LDR)
 IR PAIR: Infra Red (IR) pair has an IR LED and IR photodiode. The IR LED
transmits infrared light and the IR photo diode is a photo resister sensitive to IR
light. The IR photodiode is basically reverse biased, so care to be taken during
connection. Also the combination of IR pair can be used replicate a proximity
sensor. Figure 1.6 is the image of IR pair.
Figure 1.6 IR LED and IR photodiode
1.3 FEATURES OF IoT
IoT [17] have very interesting features when compared to other counterparts
who took their places in Gartner’s prediction like Big Data, Cloud, Quantum

6. 6
Computing, and Smart Robots. IoT has spared no technological field left to collaborate
with. All the technologies listed here have distinctive boundaries which is not the case
with IoT. Thus, one could see overlapping features and every domain expert would feel
connected in collaboration with IoT with much ease.
1.3.1 Sensing and Actuating
Sensors, Actuators are the important components as far as IoT is concerned.
Sensors are basic input devices which help sense various environmental parameters like
temperature, humidity, pressure and many more. With the collected readings necessary
actions can be taken using output devices, the actuators. The actuator can be as simple
as a LED or as complex as a robotic arm [18].
1.3.2 Communication
Communication is considered very important in the transportation of data
measured at one end to reach the other. IoT works comfortable with anycommunication
technologies. For instance, wireless (Wi-Fi), wired (Ethernet), IR, zigbee, etc.,
1.3.3 Processing, Assimilation and DecisionMaking
The data collected from the sensors before sent to the actuators will encounter
processing based on the application demand. The processing can basically happen at
three levels: low, middle and high. Low level processing is technically called as edge
computing as it happens locally within the device or in the premises of measurement.
Middle is the processing which happens at the level of gateway. Normally this is named
as Fog computing [19]. It gets its name as it is above ground and below the cloud. High
level processing mostly happens remotely. Cloud computing is the technologydeployed
to do this kind of processing.
1.3.4 Storage
Data storage is very vital in the context of IoT. The data accumulated for a long
period of time eventually contributes to legacy data sets which can be the inputs for
data analysts and data scientists. Depending on the infrastructure and nature of the data,

7. 7
it can be stored at three different levels. They can be stored at the device, gateway or
cloud [20].
1.4 CHARACTERISTICS OF IoT
It becomes extremely difficult to bring out the characteristics of IoT, for the
reason it is tricky to draw finite boundaries for IoT as a technology. Given any
technology for that matter, IoT has a root manifested or its branches spread out.
However, attempts have been made to justify agreeable characteristics for IoT namely
heterogeneity, dynamicity, scalability, interoperability, energy requirements, smartness
and data centricity. As it is already discussed, name any domain or technology, there
will be a role and relationship to IoT. However, recent observations have categorized
few of them based on its priorities as important characters for an IoT system.
1.4.1 Heterogeneity
The variety of sensors and actuators with which an IoT system has to interact is
so vast that it is inevitable that it supports heterogeneity. Thus an IoT system has to
work across all verticals for seamless interconnection and communication thereby [21].
1.4.2 Dynamicity
IoT comprises of things or devices which need to react or respond to events or
environmental changes. The primary objective of an IoT system is much more than
mere automation, which demands smartness. Thus, dynamicity becomes an inevitable
quality for an IoT system.
1.4.3 Scalability
The IoT system comprises of components which are energy constrained. This
brings in situation wherein the nodes or devices may fail. In those cases, the system
should be able to cope up failure and also accept new nodes to match the loss of few of
them. Sometimes it becomes the need of the hour to expand horizontally the existing

8. 8
infrastructure to support growing demands. IoT does this gracefully to grow or shrink
in its network size making scalability a feature.
1.4.4 Interoperability
Having said heterogeneity is the qualityof an IoT system, it is natural that it has
to support interoperability. IoT achieves it via standard data exchange formats and
standardized protocols to an extent possible. But, Gartner’s prediction [22] confirms
IoT at its peak of inflation and notifies that it may take a few more years for a highly
reliable standard. Till then it would be managed with adaptation layers or middleware
systems [23] or gateways [24]. According to researchers it is considered too early to
talk about standard hardware or software or protocol for an IoT system. As of now
every company or industry is working to create their version of IoT to suit their
requirements in their respective fields [25].
1.4.5 Energy Requirements
IoT systems have their applications in all the important fields including
wearable and portable devices. Some IoT devices will be deployed in remote areas like
forest, volcanoes, mountain peaks etc., adding up problem to the already energy
constraint nature of these systems. Recent innovations have started incorporating
energy harvesting mechanisms as part of IoT devices. IoT have penetrated in to medical
field [26], which requires more of energy efficient and portable devices. IBM have
come up with IBM Watson IoT based Health solution [27]. The advent of IoT is
transforming every field to its next dimension, particularly health sector which is the
basic necessity for every human being [28] [29] [30]. Thoughtful research have started
of late in medical industry to design IoT based medical devices tailor made based on
the needs of the patient, disease and the treatment [31]. Also Samsung have developed
an IoTbased medical platform to prove the importance of IoT in the field of healthcare
[32].
1.4.6 Smartness
IoT is smartness. Every IoT system default prefixes the word “smart” to any of
its application. Examples can be smart house, smart grid, smart city etc., The challenge

9. 9
is how to add smartness factor in to these dumb things. Artificial Intelligence and
Machine Learning experts are working very close with IoT systems to add the needed
smartness. Researchers are also discussing the transition of M2M towards IoT [33].
1.4.7 Data Centric vs. Address Centric
Personal computers can be reached with the help of IP address. They are more
of an address centric system. Simple WSN’s are mostly looked for their data and not
interested in which sensor provides it. But, IoT in other hand needs to identify as well
communicate the data. This makes IoT a special category neither traditional computer
systems nor mere sensor networks. IoT is best of both worlds. Thus IoT is a data cum
address centric system. Example canbe a user needs to know the temperature of a room
(data centric) and/or to update a firmware (address centric) as well.
1.4.8 Connectivity and Availability
As the main aim of an IoT system is to interconnect the various system outputs
as inputs to other systems, connectivity becomes an important feature. Connectivity
promises round the clock availability of services to varied users. Example, the weather
forecast station can feed its predictions about rain to the sensors in the garden to decide
about switching on or off the sprinkler. This needs uninterrupted connectivity. This is
the reason why IoT relies on the solid backbone of connectivity, the internet, though
there are other mediums to communicate. IoT systems do include features like fault
tolerance, resilience and to some extent redundancy.
1.4.9 Ease of Use
Everything developed has one undeniable goal, help solve problems thus serve
humankind directly or indirectly. Anysystem deployed, if demands huge learning curve
would not really solve instead complicate. Thus it is very important for IoT systems to
have a rich user interface developed with meticulous design.
1.4.10 Security
IoT systems so far focused mostly on making things smarter, expansion of
services and ease of usage. Iota of work has gone in the security aspect of an IoT system

10. 10
[34]. Though there are securityat all levels at which an IoT system interacts, forgetting
the very point of the vulnerability of the IoT end device. The security compromised at
the device level is definitely a deadly breach, sometimes fatal. Researchers have started
taking the area of security in the context of IoT in its serious consideration [35]. There
exist effective security algorithms, but the challenge being they cannot be applied to
IoT systems as they are energy and memory constrained in most cases [36].
1.5 NEED FOR OPEN SOURCE IoT TESTBEDS
Testbeds as already highlighted plays a very important role in the field of
research. It becomes inevitable to subject the research model for testing and validation
through some kind of standard testing tool. Research proposals which needs to
converted to a product or deployed in any real time environment or real time device is
strongly recommended to validate on these kinds of real testbeds as against traditional
simulators. Thus it makes research on testbeds even more vital and meaningful.
Most of the existing testbeds are not indigenous or in other words from the
scratch IoT testbeds [35]. 90% of the existing testbeds which are used for testing IoT
systems are basically designed with WSN in mind [37]. Most of them have homogenous
devices [38]. Even if they are heterogeneous, they are proprietary. This complicates
scaling and switch over farther more reachable. Interoperability and reusability have
become questionable [39].
This paved the way for this researchto come up with opensource heterogeneous
IoT testbed framework withenhanced algorithms to improve reusability, scalability and
utilization factor. Utilization factor is usually defined as how much time a system is
really accessible for usage against its total availability.
1.6 MOTIVATION AND PROBLEM STATEMENT
The applications of IoT, the breakthrough technology, are countless and its
development involves various people of different knowledge bases and different skill

11. 11
sets [40]. The amount of sensors, actuators and devices which goes in the making of
IoT is so huge, that one can realize that there is under exploitation when compared to
the enormous cost invested in the sensor and actuator infrastructure. Also, an
extraordinary amount of data will be generated from these applications [41] [28] on
which a large amount of analytics can be done by data analysts [42]. These analysts
consider the data to be the end product of IoT systems and work on the same. A
considerable amount of time is spent by them in developing or implementing the IoT
systems that generate this data [43]. At the same time, the IoT raises significant
challenges that could stand in the way of realizing its potential benefits like
proprietorship, interoperability issues, demand for heterogeneity, difficulty in switch
over or migration, vendor lock-in etc.,
This research work attempts to design, develop and implement a performance
enhanced heterogeneous, open source IoT testbed which can be offered as service to
users irrespective of their level of skill set. Thus this work proposes a solution
mitigating the existing problems, by providing a testbed as well as a development
environment as a service over the internet to end users and developers. The end users
are thus abstracted from the underlying complexities involved in developing the IoT
system, allowing them to focus on what they do best.
1.7 OBJECTIVES AND SCOPE OF THE WORK
The main objective of the thesis is to design a utility based open IoT testbed
cum development framework and study its impact on utilization, performance and time.
The focal point of this thesis is providing solutions for the challenges behind the
proprietary vendor lock in, insufficient control, lack of concurrency and diminished
reusability. In nutshell the objectives can be listed as:
1. Investigate the characteristics, technologies and methodologies of existing
testbeds, identify the gaps and to design and implement a utility based open
IoT testbed cum development framework architecture with appropriate
maneuvering at physical and logical dimensions.

12. 12
2. Develop, load and test necessary platform independent (Application
Programming Interface) API’s to achieve utility based service model
3. Develop a control plane driven model with number based service mapping
and appropriate algorithms for dynamic resource discovery, orchestration
and conflict resolve
4. Proposing an event collaboration model of sensor service, instance based
actuator service, OTA platform service with appropriate algorithms and
API’s and to achieve the enhancement in performance as well as reduction
in response time
5. Finally, to develop a feedback based ranking model, aiming towards better
utilization, reliability and performance. Also, appropriate tool is employed
to understand the mostly used services, most demanded cluster of services
and user usage pattern
1.7.1 DevelopOpen IoT Testbed as a Service Utility
Utility computing means 'on-demand computing' that follows a pay-as-you-go
model. You pay only when you need them or use only when you need them. Utility
comprises of services, but can offer in a metered or controlled manner. This research
contribution proposes a framework/model that can enable the same. The advantages of
this framework are, the utility enhances resource utilization through virtualization and
reduces CAPEX and OPEX. Inorder to offer testbed as a utility this research work have
designed algorithms to offer sensors, actuators and platforms as service.
The proposed testbed is developed with open source boards to achieve
interoperability and heterogeneity which also overcomes the challenges of vendor lock-
in namely: fear of obsolescence, shifting or migration issues, deters innovation and
dynamicity, lack of interoperability, lack of standardization and lack of open source
entities. The proposed framework is realized with a live experimental set up which
provides a better orchestration of services through software defined control plane,
enhanced concurrency and improved reusability through virtualization of sensors,
actuators and platforms.

13. 13
1.7.2 DevelopAPI’s to Achieve Utility BasedModels/Services
Message Queuing Telemetry and Transport (MQTT) an application layer
protocol (publisher/subscriber model) is very supportive for API development. This
standard protocol can be used to aggregate data from different sensors/actuators and
given to the user in a format they request. MQTT interoperability in different platforms
is the challenge here. This is resolved by deploying open source boards with various
MQTT clients.
1.7.3 Achieve Concurrency on Actuator And Platform
Since an actuator may be connected to multiple platforms (Raspberry
Pi/Arduino etc.,) simultaneous requests across platforms must be streamlined based on
access policy. The virtual plane is designed which comprises of one virtual object for
each instance and each instance is assigned a unique topic name as against the existing
models which have provided one topic per actuator.
1.7.4 Develop a Control Plane to Achieve Resource/Service Discovery And
Orchestration and Conflict Resolve
The proposed framework encompasses a control plane which can receive the
user commands, and will initiate discovery of resources and update the details with the
database for future reference or legacy data or for data analysts to work on. Also,
orchestration of resources based on demand is achieved.
To resolve interference at hardware level (actuators) in case of there is only one
instance available and still there many users willing to book. Here simultaneous access
of the same actuator should be streamlined. This again, is taken care of by a separate
module in the control plane which uses the proposed Acquire/Release lock model to
achieve reusability in a time-sharing model by booking their slots.
Thus, this research work have envisioned a control plane that can discover the
sensors and actuators in the network and identify the services they offer, orchestrate
and resolve conflict if any.

14. 14
The achieved results have proved improvement in performance and thereby
enhancing reusability but with negligible trade-offs.
1.7.5 Event Collaboration BasedSensor Data as Service
Sensors are data sources. Since sensors are virtualized (same sensor shared with
multiple users), data from different sensor instances should be sent to respective users
using MQTT [Publisher (sensor)-Subscriber (user) model], also taking care of
concurrency (multiple subscribe requests at the same time).
The above model is available in existing frameworks. The difference brought in
the proposed research framework is detailed as given below.
1. Parameterized topic is proposed as against sensor based topic.
2. Sensor level storage proposed as against sensor client level storage. This
provides less overhead, enhanced performance and reduced access time.
3. Dynamic data formats based on user choice (PDF, CSV, JSON, XML or to
store in other databases) as against fixed standard formats.
1.7.6 Instance BasedActuator as Service
The proposed framework comprises of analgorithm formulated to offer actuator
as a service. Usually there are two issues which are overlooked in current models:
1. Multiple commands to a single actuator
2. Commands to many actuator instances
There were many models that have provided only data as service [44] [45] [46].
Minimal research has been carried out on this genre. Even if provided, there is vendor
lock in or no third-party support (plug and play) or demands domain expertise or
sufficient skill set. There is still issue in resolving conflicts on multiple requests and on
the aspect of mapping commands among multiple actuator instances (concurrency). The
proposed framework overcomes all the above-mentioned challenges and accepts
commands initiated through the API’s designed and implemented in this research

15. 15
model. A novel algorithm is proposed to resolve multi actuator conflict at the control
plane level and have proved improvement through performance graphs with negligible
overhead.
1.7.7 OTA Platform as Service
This will allow developers to deploy their code using OTA (Over The Air)
programming. This provides remote access to the proposed testbed and one can use the
testbed for the period the user will need.
1.7.8 Platform Independent API as Service
The proposed framework incorporates indigenous APIs for all the sensors and
actuators. If anyone needs more sensors and actuators, dynamic demand based creation
of APIs is a possibility. Scalability is a possibility through this approach. This research
work clearly demonstrates the difference in time accessing locally and remotely using
API’s. Though there is little more time needed when accessed remotely, but it is very
much acceptable when compared to utilization and reusability factor. The needed
graphs are provided to prove and substantiate the proposal.
1.7.9 Feedback Ranking BasedTestbed Utilization Analysis
A ranking model [47] is formulated to provide the best resources to users,
analyze the utilization factor of the testbed through performance based feedback and
failure model. The categorization is done based on Academician, Industrialist, Data
analyst, Researcher and Novice user. A script is developed to analyze local network log
with the feedback scores, whose results proved that the testbed was considerably
reliable irrespective of reported failure rates. It was observed from the log that there at
times network failure at the client end have resulted in low scores (False negative). A
discriminative analysis is carried out to find the mostly used services and factor analysis
to conclude which set of services is mostly used by which set of users. These results
gave an idea of the prospective research domains and deployment extensions for future.

16. 16
1.8 OVERVIEW OF THE THESIS
The purpose of this work is to design and implement an IoT testbed framework
with enhanced performance. Figure 1.7 represents organization of thesis. Thus the
chapters for the thesis is formulated
Figure 1.7 Organizationof thesis
as such, Chapter 1 is dedicated for introduction to IoT, testbeds and motivation behind
this research which lead to the problem statement. Chapter 2 elaborates about state of
the art research in the area IoT testbeds and the service models. Chapter 3, Chapter 4,
Chapter 5 and Chapter 6 highlights the research contributions through the proposed
solutions, implementation and experimental results. Chapter 7 concludes the research
work followed by list of references and the research publications of the proposed
research work.