BackgroundThe IndustrialInternet of Things (Industrial IoT) has become one of the most popularindustrial technical paradigms and business concepts in recent years.

With thecontinuous integration of emerging information and communication technologies(ICT), industry will experience a revolution in the way it operatesautonomously (Meng Z. et al., 2017). The envisioned industrial systems can potentially supportcollaborative practices, which promises greater production flexibility andproduct variability with minimized human intervention. For example, newservices such as real-time event processing or 24/7 access to trackinginformation are introduced into the supply chain (Sanchez-Iborra, R. Cano, M.2016).

Having a comprehensive monitoring system throughout the entiremanufacturing and supply chain enables us to enrich the entire value-addedchain with valuable information, minimize losses in the event of unexpectedevents and thus improve both business processes and the exchange of informationbetween stakeholders (business-to-business (B2B) networks) (Stock, T. Seliger,G. 2016). Industrial IoT, includes machine learning and big data processingtechnology, using the communication and automation technologies of the sensordata of Machine-2-Machine (M2M), which have existed in the industrialenvironment for years. What is changing is that the Industrial IoT conceptdrives the automation industry to ensure greater interoperability of itsproducts. And that means it’s time to find standards for these technologies andtheir applications.  Related WorkThe analysis ofIndustrial IoT by modelling is to be seen as the best way of the study for abetter understanding of the challenges posed by such systems. Since theIndustrial IoT modeling is associated with a broad context, we categorize theassociated work into the following categories from i to iv i.

              Research trends in the field of Industrial IoTSallai, G. firstsummarized the challenges of the current Internet and drafts the visions andcurrent capabilities of the future Internet, then Sallai, G. identifies theclusters of the relevant research topics and defines them as chapters of theresearch activities of the future Internet in a layered model. It ranges frombasic research to Internet science, Internet engineering and Internetapplications and experiments of the future. Gubbi et al. present acloud-centric vision to implement the Industrial IoT worldwide.

They discussthe core technologies and application areas that can determine the futuredirection of IoT research. While Jara et al. consider the challenges andopportunities to extend the public IPv4 address space for the Internet ofEverything through IPv6 to support IoT capabilities. While wirelesssensor networks (WSNs) form a virtual layer in which data about the physicalworld can be retrieved from any computer system. Alcaraz et al. emphasize thatWSNs are an invaluable resource for realizing IoT’s vision of integration,security and other issues. The acquisition, modelling, argumentation anddistribution of contexts with regard to sensor data and context-relatedcomputation play a decisive role in IoT applications.  ii.

             Security and privacy challenges Slavin et al. present the patterns ofsecurity requirements that represent reusable security practices that softwareengineers can apply to improve security in their systems. The paper proposes anew method that combines an approach based on the examination cycle with thenotation of the feature diagram to examine only relevant patterns and quicklyselect the most appropriate patterns for the situation. Skarmeta et al. proposea distributed and capacity-based access control mechanism. It relies on publickey encryption to address certain security and privacy issues on the Internetof Things. Their solution uses the optimized digital signature algorithm of theelliptical curve in the Smart object.

Babar et al. proves analyses of theInternet of Things with regard to security, privacy and confidentiality andpropose the security model for the Internet of Things. Weber considers new security and dataprotection challenges arising from international legislation relating to theright to information, provisions prohibiting or otherwise restricting theapplication of IT security law rules, in support of IoT usage mechanisms. Heer et al. discuss problems and possibilities toapply known Internet protocols and security solutions in IOT. The authors alsodescribe the implementation model and basic security requirements and focus onthe technical limitations of standard IP security protocols.  iii.           Security and data protection Energy issues within the IoTEnergy consumption (EC) is a major problem for IoT.

Lanziseraet al. offer a “Communication Power Supply” (CPS) to enable power andcontrol information communication between the device and the buildingmanagement system. Schmidt et al. describes the method of constructing sensornode models based on a few simple measurements. They form a sample in which themodels are integrated into a simulation environment within the proposed runtimeframework to support model-based design. Measurements show that the proposedmodel allows a significant reduction of EC. Zhou et al.

a description of theenergy models (EMs) of the central parts of the WSN node such as processors,radio frequency modules and sensors. EM is based on an event activationmechanism. The authors first simulate the node components and then evaluate theEC network protocol using this EM. The model presented here is suitable for theEC WSN analysis, network protocol evaluation and WSN application development.

Venckauskaset al. present a configurable prototype of the IoT, which allows for variousexperiments to be carried out to determine the relationship between energy andsafety in different IoT modes. The paper also presents the methodology ofenergy measurement in the IoT unit. The methodology provides results in twoways: ideal (without the influence of noise in the communication environment inwhich IoT operates) and real (with the influence of noise). Friedman andKrivolapov describe a study that deals with the combined energy and bandwidtheffect of the usage of Bluetooth and Wi-Fi connection in smartphones. The studyreveals some interesting effects and compromises. In particular, theyidentified many situations where Wi-Fi is a better solution than Bluetooth, whichcontrasts with previous reports. The study also identified several scenariosthat are better managed by Bluetooth.

The conclusions of this study provideinformation on preferred usage patterns that may be of interest to scientists,researchers and smartphone developers.  iv.           Quality of service Shaoshuai et al. provides decisionmaking through a model for evaluating service quality. This template takes intoaccount both the system status and the user settings to improve the QoSvalidity model. The calculated evaluation of the proposed model can be used asa parameter for evaluating and selecting the service. Seal et al. claim thatusers need a multidimensional QoS to meet the individual needs of severalsystems.

In this sense, the authors present a simple abstraction mechanismconsisting of the QoS function of each application. This function combinesdifferent aspects of QoS for each user in a value that is used to define thebest method of interaction. Liang et al. aims at discontinuousreception/transmission optimization (DRX/DTX) and asks how to maximize devicedowntime while ensuring QoS for devices, especially in terms of bit rate,packet delay and packet loss rate for IoT applications. proposed efficientschemes  are provided to optimize theDRX/DTX parameters and the device packages programmed with a base station. Thebasic idea of the schema is a well-balanced relationship between QoS parametersand DRX/DTX configurations. Simulation results show that schemes can guaranteetraffic bit rate, packet delay and packet loss rate while saving energy for theuser’s devices. Jin et al.

introduces different IoT architectures forintelligent urban applications and defines your desired QoS network. Since QoSis one of the biggest network challenges, this topic focuses on wired andwireless networks. Several studies within the framework of the WSM deal withradio interface and interference problems.   Aim                    The aimof this research is to providea study of wireless protocols for industrial IoT focusing onperformance, security and power efficiencytargeting to identifying the abstract security–energy relationships for the variety of wireless communicationprotocols to provide the energy performance measurements (using the createdenvironment and the IoT unit) in order to test the feature models and to obtainthe concrete characteristics of the relationships. Approach& MethodologyThe project will focus on analyzing wireless protocols for industrial IoTfocusing on performance, security and power efficiency.In addition to the typical tasks of conducting aliterature review and thesis writing, we also envisage thefollowing research tasks (RT) in this project.RQ1: What are the wireless protocol withenhance performance, securityand power efficiency? Research efforts will focus on understanding andutilising the relationship and dependencies between the performance, security and power efficiency.

RQ2: Experimentation/simulationto test and validate the different wireless protocol.Timeline Activities First Year Second Year S1 S2 S1 S2 Literature review Research design/experimentation Output 1=Results from Research design/experimentation from S1 of first year Data aggregation Research design/experimentation Output 2= Results from Research design/experimentation S1 of second year Output 3 = Results from Output 2 after Research design/experimentation Research design/experimentation Thesis compilation and final defence  Expected OutcomesAs part of thisresearch anticipated outcomes, we expect to have1.     Identifying a suitable wireless protocolsthat will enhance performance, security and power efficiency in industrial IoT.

2.     At least two research publications in the targeted journals andconferences in the table below.  Targeted Journals 1 IEEE Internet of Things Journal 2 Journal of Networks 3 International Journal of Communication Systems Targeted Conferences 1 International Conference on Advanced Technologies for Communications  2 International Telecommunication Networks and Applications Conference (ITNAC) 3 International Australasian Telecommunication Networks and Applications Conference (ATNAC)  ReferencesAlcarazC, Najera P, Lopez J, Roman R. Wireless sensor net-works and the internet ofthings: do we need a complete integration? Proceedings of the 1st InternationalWorkshop on the Security of the Internet of Things (SecIoT’10); 2010. Babar S,Mahalle P, Stango A, Prasad N, Prasad R. Proposed security model and threattaxonomy for the Internet of Things (IoT). Recent Trends in Network Securityand Applications Communications in Computer and Information Science 2010;89:420–429. Fok CL,Julien C, Roman GC, Lu C.

Challenges of satisfying multiple stakeholders:quality of service in the Internet of Things. Proceedings of the 2nd Workshopon Software Engineering for Sensor Network Applications. 2011; 56–60. Heer T,Garcia-Morchon O, Hummen R, Keoh SL, Kumar SS, Wehrle K. Security challenges inthe IP-based Internet of Things.

Wireless Personal Communications 2011;61(3):527–542.FriedmanR, Krivolapov Y. On power and throughput tradeoffs of WiFi and Bluetooth insmartphones. IEEE Transactions on Mobile Computing 2013; 12(7):1363–1376. Jara AJ,Ladid L, Skarmeta A. The Internet of Everything through IPv6: an analysis ofchallenges, solutions and opportunities.

Journal of Wireless Mobile Networks,Ubiquitous Computing, and Dependable Applications (JoWUA) 2013; 4(3):97–118.Jin J,Gubbi J, Luo T, Palaniswami M. Network architecture and QoS issues in theinternet of things for a smart city. Proceedings of the International Symposiumon Communications and Information Technologies (ISCIT).IEEE. 2012 Oct.;956–961. LanziseraS, Weber AR, Liao A, Pajak D, Meier AK.

Communicating power supplies: bringingthe internet to the ubiquitous energy gateways of electronic devices. IEEEInternet of Things Journal 2014; 1(2):153–160.  LiangJM, Chen JJ, Cheng HH, Tseng YC. An energy-efficient sleep scheduling with QoSconsideration in 3GPP LTE-advanced networks for Internet of Things. IEEEEmerging and Selected Topics in Circuits and Systems 2013; 3(1):13–22.  Michael Bowne, Standards and Protocols for the IndustrialInternet of Things.

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,A Collaboration-Oriented M2M Messaging Mechanism for theCollaborative Automation between Machines in Future Industrial Networks.doi:10.3390/s17112694.

Vol. 17, 2107, Pages:1424-8220 ISSN: 2694. SallaiG. Future Internet visions and research clusters. Acta Polytechnica Hungarica2014; 11(7):5–24. Sanchez-Iborra,R.

Cano, M. State of the Art in LP-WAN Solutions for Industrial IoT Services.Sensors}, VOL 16 2016, NO , Journal 708 http://www.mdpi.com/1424-8220/16/5/708,ISSN 1424-8220.

 SchmidtD, Kramer M, Kuhn T, When N. Energy modelling in sensor networks. Advance inRadio Science 2007; 5:347–351. ShaoshuaiF, Wenxiao S, Nan W, Yan L. MODM-based evaluation model of service quality inthe Internet of Things. Procedia Environmental Sciences 2011; 11:63–69. Stock, T. Seliger, G.

Opportunities of sustainablemanufacturing in Industry 4.0. ProcediaCIRP 2016, 40,536–541. ?SkarmetaAF, Hernández-Ramos JL, Moreno MV.

A decentralized approach for security andprivacy challenges in the Internet of Things. IEEE World Forum on Internet ofThings (WF-IoT) 2014 : 67–72. SlavinR, Lehker J-M, Niu J, Breaux TD. Managing security requirements patterns usingfeature diagram hierarchies.

Proceedings of the 22nd International RequirementsEngineering Conference (RE), IEEE. 2014 Aug; 193–202. VenckauskasA, Jusas N, Kazanavicius E, Stuikys V. Identification of dependency amongenergy consumption and Wi-Fi protocol security levels within the prototypemodule for the IoT. Elektronika ir Elektrotechnika 2014; 20(6):132–135.

 WeberRH. Internet of Things—new security and privacy challenges. Computer Law &Security Review 2010; 26(1):23–30.

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

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