Background the associated work into the following categories

Background

The Industrial
Internet of Things (Industrial IoT) has become one of the most popular
industrial technical paradigms and business concepts in recent years. With the
continuous integration of emerging information and communication technologies
(ICT), industry will experience a revolution in the way it operates
autonomously (Meng Z. et al., 2017). The envisioned industrial systems can potentially support
collaborative practices, which promises greater production flexibility and
product variability with minimized human intervention. For example, new
services such as real-time event processing or 24/7 access to tracking
information are introduced into the supply chain (Sanchez-Iborra, R. Cano, M.
2016). Having a comprehensive monitoring system throughout the entire
manufacturing and supply chain enables us to enrich the entire value-added
chain with valuable information, minimize losses in the event of unexpected
events and thus improve both business processes and the exchange of information
between stakeholders (business-to-business (B2B) networks) (Stock, T. Seliger,
G. 2016). Industrial IoT, includes machine learning and big data processing
technology, using the communication and automation technologies of the sensor
data of Machine-2-Machine (M2M), which have existed in the industrial
environment for years. What is changing is that the Industrial IoT concept
drives the automation industry to ensure greater interoperability of its
products. And that means it’s time to find standards for these technologies and
their applications.

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Related Work

The analysis of
Industrial IoT by modelling is to be seen as the best way of the study for a
better understanding of the challenges posed by such systems. Since the
Industrial IoT modeling is associated with a broad context, we categorize the
associated work into the following categories from i to iv

 

i.              
Research trends in the field of Industrial IoT

Sallai, G. first
summarized the challenges of the current Internet and drafts the visions and
current capabilities of the future Internet, then Sallai, G. identifies the
clusters of the relevant research topics and defines them as chapters of the
research activities of the future Internet in a layered model. It ranges from
basic research to Internet science, Internet engineering and Internet
applications and experiments of the future. Gubbi et al. present a
cloud-centric vision to implement the Industrial IoT worldwide. They discuss
the core technologies and application areas that can determine the future
direction of IoT research. While Jara et al. consider the challenges and
opportunities to extend the public IPv4 address space for the Internet of
Everything through IPv6 to support IoT capabilities.

While wireless
sensor networks (WSNs) form a virtual layer in which data about the physical
world can be retrieved from any computer system. Alcaraz et al. emphasize that
WSNs are an invaluable resource for realizing IoT’s vision of integration,
security and other issues. The acquisition, modelling, argumentation and
distribution of contexts with regard to sensor data and context-related
computation play a decisive role in IoT applications.

 

ii.             
Security and privacy challenges

Slavin et al. present the patterns of
security requirements that represent reusable security practices that software
engineers can apply to improve security in their systems. The paper proposes a
new method that combines an approach based on the examination cycle with the
notation of the feature diagram to examine only relevant patterns and quickly
select the most appropriate patterns for the situation. Skarmeta et al. propose
a distributed and capacity-based access control mechanism. It relies on public
key encryption to address certain security and privacy issues on the Internet
of Things. Their solution uses the optimized digital signature algorithm of the
elliptical curve in the Smart object. Babar et al. proves analyses of the
Internet of Things with regard to security, privacy and confidentiality and
propose the security model for the Internet of Things. Weber considers new security and data
protection challenges arising from international legislation relating to the
right to information, provisions prohibiting or otherwise restricting the
application of IT security law rules, in support of IoT usage mechanisms. Heer et al. discuss problems and possibilities to
apply known Internet protocols and security solutions in IOT. The authors also
describe the implementation model and basic security requirements and focus on
the technical limitations of standard IP security protocols.

 

 

iii.           
Security and data protection Energy issues within the IoT

Energy consumption (EC) is a major problem for IoT. Lanzisera
et al. offer a “Communication Power Supply” (CPS) to enable power and
control information communication between the device and the building
management system. Schmidt et al. describes the method of constructing sensor
node models based on a few simple measurements. They form a sample in which the
models are integrated into a simulation environment within the proposed runtime
framework to support model-based design. Measurements show that the proposed
model allows a significant reduction of EC. Zhou et al. a description of the
energy models (EMs) of the central parts of the WSN node such as processors,
radio frequency modules and sensors. EM is based on an event activation
mechanism. The authors first simulate the node components and then evaluate the
EC network protocol using this EM. The model presented here is suitable for the
EC WSN analysis, network protocol evaluation and WSN application development. Venckauskas
et al. present a configurable prototype of the IoT, which allows for various
experiments to be carried out to determine the relationship between energy and
safety in different IoT modes. The paper also presents the methodology of
energy measurement in the IoT unit. The methodology provides results in two
ways: ideal (without the influence of noise in the communication environment in
which IoT operates) and real (with the influence of noise). Friedman and
Krivolapov describe a study that deals with the combined energy and bandwidth
effect of the usage of Bluetooth and Wi-Fi connection in smartphones. The study
reveals some interesting effects and compromises. In particular, they
identified many situations where Wi-Fi is a better solution than Bluetooth, which
contrasts with previous reports. The study also identified several scenarios
that are better managed by Bluetooth. The conclusions of this study provide
information on preferred usage patterns that may be of interest to scientists,
researchers and smartphone developers.

 

 

iv.           
Quality of service

Shaoshuai et al. provides decision
making through a model for evaluating service quality. This template takes into
account both the system status and the user settings to improve the QoS
validity model. The calculated evaluation of the proposed model can be used as
a parameter for evaluating and selecting the service. Seal et al. claim that
users need a multidimensional QoS to meet the individual needs of several
systems. In this sense, the authors present a simple abstraction mechanism
consisting of the QoS function of each application. This function combines
different aspects of QoS for each user in a value that is used to define the
best method of interaction. Liang et al. aims at discontinuous
reception/transmission optimization (DRX/DTX) and asks how to maximize device
downtime while ensuring QoS for devices, especially in terms of bit rate,
packet delay and packet loss rate for IoT applications. proposed efficient
schemes  are provided to optimize the
DRX/DTX parameters and the device packages programmed with a base station. The
basic idea of the schema is a well-balanced relationship between QoS parameters
and DRX/DTX configurations. Simulation results show that schemes can guarantee
traffic bit rate, packet delay and packet loss rate while saving energy for the
user’s devices. Jin et al. introduces different IoT architectures for
intelligent urban applications and defines your desired QoS network. Since QoS
is one of the biggest network challenges, this topic focuses on wired and
wireless networks. Several studies within the framework of the WSM deal with
radio interface and interference problems.  

 

Aim                   

The aim
of this research is to provide
a study of wireless protocols for industrial IoT focusing on
performance, security and power efficiency
targeting to identifying the abstract security–energy relationships for the variety of wireless communication
protocols to provide the energy performance measurements (using the created
environment and the IoT unit) in order to test the feature models and to obtain
the concrete characteristics of the relationships.

 

Approach
& Methodology

The project will focus on analyzing wireless protocols for industrial IoT
focusing on performance, security and power efficiency.
In addition to the typical tasks of conducting a
literature review and thesis writing, we also envisage the
following research tasks (RT) in this project.

RQ1: What are the wireless protocol with
enhance performance, security
and power efficiency? Research efforts will focus on understanding and
utilising the relationship and dependencies between the performance, security and power efficiency.

RQ2: Experimentation/simulation
to test and validate the different wireless protocol.

References

Alcaraz
C., Najera P., Lopez J., Roman R.. “Wireless sensor net-works and the internet
of things: do we need a complete integration?.” Proceedings of the 1st
International Workshop on the Security of the Internet of Things; 2010.

 

Babar S.,
Mahalle P., Stango A., Prasad N., Prasad R.. “Proposed security model and
threat taxonomy for the Internet of Things (IoT).” Recent Trends in Network
Security and Applications Communications in Computer and Information Science
2010; vol: 89 pp420–429.

 

Fok C.L.,
Julien C., Roman G.C., Lu C.. “Challenges of satisfying multiple stakeholders:
quality of service in the Internet of Things”. Proceedings of the 2nd Workshop
on Software Engineering for Sensor Network Applications. 2011; pp. 56–60.

 

Heer T.,
Garcia-Morchon O., Hummen R., Keoh S.L., Kumar S.S., Wehrle K.. “Security
challenges in the IP-based Internet of Things”. Wireless Personal
Communications 2011; vol:61(3) pp. 527–542.

 

Friedman
R, Krivolapov Y. “On power and throughput tradeoffs of WiFi and Bluetooth in
smartphones”. IEEE Transactions on Mobile Computing 2013; vol:12(7) pp:1363–1376.

 

Jara A.J.,
Ladid L., Skarmeta A.. “The Internet of Everything through IPv6: an analysis of
challenges, solutions and opportunities.” Journal of Wireless Mobile Networks,
Ubiquitous Computing, and Dependable Applications (JoWUA) 2013 vol: 4(3) pp: 97–118.

Jin J.,
Gubbi J., Luo T., Palaniswami M.. “Network architecture and Quality of Service (QoS)
issues in the internet of things for a smart city.” Proceedings of the
International Symposium on Communications and Information Technologies
(ISCIT).IEEE. 2012 Oct.; 956–961.

 

Lanzisera
S., Weber A.R., Liao A., Pajak D., Meier A.K.. “Communicating power supplies:
bringing the internet to the ubiquitous energy gateways of electronic devices”.
IEEE Internet of Things Journal 2014; vol: 1(2) pp: 153–160.

 

Liang J.M.,
Chen J.J., Cheng H.H., Tseng Y.C.. “An energy-efficient sleep scheduling with
QoS consideration in 3GPP LTE-advanced networks for Internet of Things.” IEEE
Emerging and Selected Topics in Circuits and Systems 2013; vol:3(1) pp: 13–22.

 

Michael B., “Standards and Protocols for the Industrial
Internet of Things.” url: https://www.automationworld.com/article/topics/industrial-internet-things/standards-and-protocols-industrial-internet-things. PI North America, on February 19, 2015

 

Meng, Z.
Wu, Z. Gray, J.A.. “Collaboration-Oriented M2M Messaging Mechanism for the
Collaborative Automation between Machines in Future Industrial Networks.”
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Sallai
G. “Future Internet visions and research clusters.” Acta Polytechnica Hungarica
2014; vol: 11(7):5–24.

 

Sanchez-Iborra,
R. Cano, M. “State of the Art in LP-WAN Solutions for Industrial IoT Services”.
Sensors Journal 708 2016 VOL: 16, ISSN 1424-8220.

 

Schmidt
D, Kramer M, Kuhn T, When N. “Energy modelling in sensor networks”. Advance in
Radio Science 2007; vol:  5, 347–351.

 

Shaoshuai
F, Wenxiao S, Nan W, Yan L. MODM-based evaluation model of service quality in
the Internet of Things. Procedia Environmental Sciences 2011; vol 11. Pp :63–69.

 

Stock, T. Seliger, G. “Opportunities of sustainable
manufacturing in Industry 4.0”. Procedia
CIRP 2016, vol : 40,
pp: 536–541. ?

Skarmeta
AF, Hernández-Ramos JL, Moreno MV. “A decentralized approach for security and
privacy challenges in the Internet of Things”. IEEE World Forum on Internet of
Things. 2014 pp: 67–72.

 

Slavin
R, Lehker J-M, Niu J, Breaux TD. “Managing security requirements patterns using
feature diagram hierarchies”. Proceedings of the 22nd International
Requirements Engineering Conference (RE), IEEE. 2014 Aug; pp193–202.

 

Venckauskas
A, Jusas N, Kazanavicius E, Stuikys V. “Identification of dependency among
energy consumption and Wi-Fi protocol security levels within the prototype
module for the IoT”. Elektronika ir Elektrotechnika 2014; vol. 20(6): pp132–135.

 

Weber
RH. “Internet of Things: new security and privacy challenges”. Computer Law
& Security Review 2010; vol. 26(1) pp23–30.

 

Zhou HY,
Luo DY, Gao Y, Zuo DC. Modeling of node energy consumption for wireless sensor
networks. Wireless Sensor Network 2011; vol 3 pp 18–23.