Introspection Analaysis of Availability ver0_1-1.pptx
1. Introspection of availability in Service
based Smart systems using
Internet of things (IoT)
IRCDIDC (7th May’22)
Author
Hariharan Ramalingam,
Research Scholar – PhD,
Department of Banking technology,
School of Management,
Pondicherry University.
Co-Author
Dr. V. Prasanna Venkatesan,
Professor,
Department of Banking Technology,
School of Management,
Pondicherry University.
3. Introduction
The drive for automation which enables the Open-ended systems to closed loop is showing improvement
◦ Overall efficiency,
◦ Productivity and
◦ Opportunity to add smartness to systems
in Large Enterprise, Small medium business and homes
Controller Process
Input
Controller
Output
Process
input
Process
Output
Open Ended Systems
Examples: Electric Hand Drier, Automatic Washing
machine, Toasters
Controller Process
Input
Controller
Output
Process
input
Output
Closed Ended Systems
Examples: Servo voltage stabilizer, Water level
controller, Cooling system in the car
Feedback
4. Introduction
Internet of Things –
Technology and Applications
Internet of things (IoT)
Combination of sensors, actuators & controller
forms IoT device.
Enables physical objects to connect to internet
which opens up opportunities for variety of
domain applications.
Works as device (node) and gateway
combination.
Multiple nodes connects to gateway. Each node
acts as a data aggregator point and links to
internet.
Topology based IoT deployment such as P2P,
Star, Mesh cater to different domain
applications.
Wireless communication Protocols used in IoT
are Bluetooth, MQTT, Wifi, Zigbee.
Challenges include Security, Power,
Connectivity/Bandwidth and Interoperability.
Applications range from Smart home, Smart
factory, Connected health, Smart retail etc
4
IoT System
5. Challenges / Opportunities in current systems
The case of service-based systems such as Retail bank Automated Teller Machines (ATM),
◦ The ATM manufacturers faces wide range of challenge while deploying & providing
maintenance which makes uptime as the main design challenge that demands
availability [1].
Conventional systems have challenges such as downtime which is due to
◦ Service outages,
◦ Power outages,
◦ IT attacks by hackers and other impacts [2].
Downtime losses are significant and it impacts customers, stakeholders and brand image.
This range of domains include Healthcare, Banking, Automotive, Retail etc.
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6. Literature Survey
Dr.Sujata Rao, Mr. Hrushikesh Mane discussed the incidents related to ATMs and the study which includes monitoring health of devices.
The purpose of the study is to improve on the overall availability of self-service terminals and downtime minimization.
Shaun S.Wang & Ulrik Franke analyzes and presents the Enterprise IT down time impacts on cost, durations and highlights the same in a
supply chain environment. They also discuss the Mean time to Failure (MTTF) and Mean time to Repair (MTTR) relating to availability in
Enterprise.
Davies E.I. & Anireh, V.I.E has simulated & implemented a smart home system using IoT with Rapid Application Development (RAD)
methodology. Their discussion is on using the RAD model to implement the overall system with reduced development time.
Deepa Rajendra Sangolli et al. proposes a platform design followed by implementation of High availability in Edge computing platform.
The platform as mentioned in the research paper minimizes service down time and ensures high availability in edge services with light
weight service management and reduction in latency.
Udhaya Kumar Dayalan et al., discusses IoT Gateway solution that achieves negligible overhead in terms of latency, CPU and RAM
usage when compared to other gateways. The authors compare available gateways in the market (Cloud based) and their features.
Bhawna Ahlawat et al., discusses the IoT system model, challenges and threats at various IoT system layers with techniques used to
identify the threats.
Hariharan Ramalingam & Dr. Prasanna Venkatesan discusses the analysis & characteristics of IoT Gateway system. Here the authors
bring in different scenarios of edge computing gateway deployment in a remote location.
Dimitrios Sespanos & Marilyn Wolf in their book titled “Internet of Things (IoT) system” details the architecture, algorithms,
methodologies. One their highlights is on the design parameters consideration for IoT based systems which is references towards building
IoT based systems.
7. Literature Survey
Hariharan Ramalingam & Dr. Prasanna Venkatesan discusses the frame work for banking services using edge computing and
blockchain use cases. The authors details framework parameters such as understandability, security, availability, Quality of Service
(QoS) and Service Coherence Time (SCT) for improving retail banking services and overall customer experience.
Tilak, Sameer et al., discusses the sensor models and related cases studies with focus on sensor network architecture,
communication models and data delivery methods.
On Green IoT – Energy saving practices (Rushan Arshad et al.), Use cases ( S.H.Alsamhi et al.) authors details the investigation
with applied use cases. Energy savings is a critical design parameter for Smart systems.
On IoT Security - survey (Luis Puche Rondon et al.), Type of IoT security attacks (PLS Jayalaxmi et al.), Security & Forensics –
challenges & opportunities (Conti, Mauro et al.) the authors discuss the security solutions for Smart homes, smart buildings with
support from IoT systems. Details of attacks at various layers of IoT system based on the vulnerabilities and their comparative
solutions are discussed.
Keisuke Sato et al. details the model for IoT System using feedback control theory and discusses the performances in real time.
Use cases such as smart cars, Smart Train station, smart buildings are referred as IoT applications for discussion.
Shensheng and Yi Xie discusses the availability performance improving method with numerical illustration that proposes
increasing system full service and decrease system unavailability. The authors details health case IoT system use cases for
numerical evaluation & discussion.
8. Literature Survey
V. Alcacer & V. Cruz-Machado presents a literature review on Industry 4.0 and details the technologies for manufacturing system.
This paper brings out the advantages of moving to Industry 4.0 over conventional system.
Krupitzer Christian et al. discusses the classification of predictive maintenance in the context of Industry 4.0 with recent
developments based on structured literate survey.
Radoslaw Wolniak presents the analysis of System down time in an automotive production environment and related causes
analysis.
B.Sai Subrahmanya & S. Neeraja discusses on the design of a Smart warehousing using IoT system which tracks, monitors and
manages the inventory of parts.
A. Kanawaday and A. Sane discusses on ML/IoT based Predictive maintenance of Industrial system which could prevent machine
failures and minimize the down time.
Kuldeep Nagiya & Mangey Ram discusses the ATM characteristics with identified state transitions, reliability analysis, Mean time
to failure (MTTF) analysis, Sensitivity analysis.
Hariharan Ramalingam & Dr.V. Prasanna Venkatesan discusses & details the edge computing use cases for retail banks with
various banking services available.
9. IoT system opportunities and identified design parameters
Application Challenges in legacy Systems Solution with IoT system Design Parameters added using IoT
system
Industrial Systems Motor/ equipment failures resolution is
reactive and adds to service delay.
Monitor quality of product & state of
equipment.
Collects data for predicting motor
failures.
Alert System
Analysis system
Service latency
Reliability & Availability
Security & Safety
Smart Buildings Increase in Operations costs from
HVAC and light systems. Structural
repairs are reactive.
Monitor people location and manage
HVAC, lighting system usage.
Monitor structural Health
Energy savings
Alert system
Sensor network
Service latency
Security & Safety
Smart Cities Traffic management, Public services
are reactive.
Monitor pedestrian and vehicular
traffic for effective traffic management.
Integrate data from smart buildings for
Proactive services.
Sensor Network
Alert System
Analysis System
Service latency
Reliability & Availability
Security & Safety
Automotive Mechanical, electrical systems which
drive more fuel consumption and
emissions.
Monitor state of the vehicle using
networked sensors and reduce fuel
consumption, emission.
Improve safety with connected Smart
city data.
Sensor network
Alert System
Analysis System
Control System
Reliability & Availability
Service life time
Smart Banking Downtime recovery take time and
impacts services.
Challenges in security & safety.
Monitoring Retail bank ATMs,
infrastructure for failures, security,
safety and energy savings.
Alert System
Analysis System
Service latency
Reliability
Availability
Security & Safety
10. Design Parameter Descriptions
Sensor network – Set of sensors that gathers data and sends data to remote applications for services with support from wireless protocols function
for communication [10].
Alert system – Alerts are generated on a particular event or criteria as designed from the sensor data processed.
Analysis system – Ongoing analysis is done on data generated by the sensors using the edge devices or gateway systems. The reports can be
generated as desired periodically from the system.
Control system – Control algorithms use the sensor data to generate outputs for actuators.
Energy Savings – Energy efficient systems can be enabled using IoT system by minimizing energy consumption and Operation on demand by
monitoring using sensors [11], [12].
Service Latency – Based on sensor data from the edge, Gateway system can communicate to the cloud-based service applications. The service
latency influences customer experience and operational efficiency of the system. Similar parameter called Service coherence time is discussed for
customer experience [9].
Reliability – Reliability of the system components can be improved using subjective usage and can influence overall lifetime of the system.
Availability – System down time challenges can be overcome using IoT system. Data analysis for predictive failure, switching to functional backup
systems during system failures, improved service latency for system service calls can ensure availability.
Security – Secure systems ensure protection from threats and access to critical data. Sensors can detect physical threats or anomalies and
generate alerts as required, trigger security protocols for protection of system & environment [13], [14], [15].
Safety – System can incur damages due to various factors and can present safety risk for the environment & Customer. Sensors can monitor safety
violations or damages and send alerts for recovery.
17. Use case: Smart cars versus Conventional cars
Conventional cars are typically controlled by manual with semi automation for some parts but not connected to external
control or aware of an nearby automotive. So vehicle movement is managed by manual. Violation of traffic rules is not
detection or captured in these systems.
Whereas as a comparison in the IoT integrated smart cars the system has control system feedback responses from sensors
which responds based on centralized communications between the smart cars. Continuous monitoring and management of
automotive is done which prevents vehicles accidents, traffic congestions and ensuring availability of services improves
overall.
18. Use case: Smart patient monitoring system versus conventional system
Hospitals do operate with procedures starting from outpatient, emergency and consultancy services.
• The conventional system of patient monitoring allows communication which are manual dependent and has its own
challenges. When number of patients increases managing the inflow and admission process is cumbersome, also challenges
the priority of admission based on criticality of the patients.
• Smart patient monitoring with connected IoT system constantly monitors patients’ vitals, movement and updated services
applications which in turn triggers alerts, records history and facilitates the logistics. Smart system with IoT ensures
availability of services which improves the overall quality of services
19. Future Research
The research area for smart system has many potential areas which includes the computing, analytics in the edge, services that
run in the cloud and overall automation which includes use cases in robotics, blockchain, Predictive analytics to prevent
industrial system down time and Wellness based services which connects to lifestyle improvements, the case of Industry 4.0
with predictive maintenance [23] is the future.
The real time IoT will drive research and critical design parameter identification such as resilience which makes it a Smart
IoT system.
IoT engagement drives further opportunities in Banking using wearables, smart branches, electronic surveillance system for
banks, leasing finance automation [24].
20. Conclusion
The models and analysis of design parameter such as availability for smart system versus the conventional system were represented
utilizing the feedback control theory.
Considering the feedback control theory, we discussed the system model with IoT system (Smart system) and related
applications/use cases as examples.
Field data can be integrated to the models and discussed to understand the numerical data on smart system versus conventional
system.
The system represented separately as smart system and conventional system models, are analyzed and combined to implement the
whole IoT system modeling.
Specific cases in smart cars and patient monitoring were highlighted with reference to the models discussed.
Overall system modeling covers the benefits of smart systems (with IoT) over conventional systems and can be applied to other use
cases in Smart Healthcare, Smart city and Security applications.
21. References
[1] Dr. Sujata Rao & Mr. Hrushikesh Mane, “ATM Availability Management System”, IOSR Journal of Computer
Engineering (IOSR-JCE), 2018.
[2] Shaun S.Wang et al., ”Enterprise IT service downtime cost and risk transfer in a supply chain”, SPRINGER,
“Operations Management Research”, 2020.
[3] Davies E.I. & Anireh, V.I.E, “Design and Implementation of Smart home System using Internet of things”, Journal
of Digital Innovations & Contemporary Research in Science, Engineering and Technology, Vol.7, No.1, 2019.
[4] Deepa Rajendra Sangoli et al.,”Enabling High Availability Edge Computing Platform”, 7th IEEE International
Conference on Mobile Cloud Computing, services, Engineering (MobileCloud), 2019.
[5] Udhaya Kumar Dayalan et al., “VeerEdge: Towards an Edge centric IoT Gateway”, IEEE/ACM 21st International
Symposium on Cluster, Cloud and Internet Computing (CCGrid), 2021.
[6] Bhawna Ahlawat et al.,”IoT System Model, challenges and Threats”, International Journal of Scientific &
technology research”, ISSN 2277-8616, Vol 9.,Issue 03, 2020.
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22. References
[7] Hariharan Ramalingam & Dr.V. Prasanna Venkatesan, “Analysis of current trends in Internet of things Gateway and Edge data processing characteristics”, IJERT, ISSN:
2278-0181, Vol.8, Issue 07, 2019.
[8] Dimitrios Serpanos, Marilyn Wolf, “Internet of Things (IoT) Systems – Architecture, Algorithm and Methodologies”, Springer, 2018. https://doi.org/10.1007/978-3-
319-69715-4
[9] Hariharan Ramalingam & Dr.V. Prasanna Venkatesan, “Improving customer experience in Retail banks with framework for banking services applied in edge
computing and blockchain use cases”, International virtual conference on Banking and financial technology 2020, Dept. of Banking Technology, School of Management,
Pondicherry University, 2020.
[10] Tilak, Sameer, Nael B. Abu-Ghazaleh, and Wendi Heinzelman. "A taxonomy of wireless micro-sensor network models." ACM SIGMOBILE Mobile Computing and
Communications Review 6.2 (2002): 28-36.
[11] S.H.Alsamhi et al., ”Green IoT using UAV in B5G networks: A Review of Application and strategies”, Cornell University, https://arxiv.org/abs/2103.17043, 2021.
[12] Rushan Arshad et.al, “Green IoT: An Investigation on energy saving practices for 2020 and Beyond”, IEEE Access, 2017.
[13] Luis Puche Rondon et al.,” Survey on Enterprise Internet of Things System (E-IoT): A security perspective”, ELSEVIER, 2022.
https://doi.org/10.1016/j.adhoc.2021.102728.
[14] PLS Jayalaxmi et al., “A Taxonomy of security issues in IIoT: Scoping review for existing solution, future implications and research challenges”, IEEE Access, 2021.
[15] Conti, Mauro, et al. "Internet of Things security and forensics: Challenges and opportunities." Future Generation Computer Systems 78 (2018): 544-546.
[16] Keisuke Sato et al., “A Modeling technique utilizing feedback control theory for performance evaluation of IoT system in real time”, IEEE, 2015.
22
23. References
[17] Shensheng and Yi Xie, “Availability Modeling and performance improving of a healthcare IoT system”, MDPI, 2021.
https://doi.org/10.3390/iot2020016
[18] V. Alcacer & V. Cruz-Machado, “Scanning the Industry 4.0: A Literature review on technologies for manufacturing Systems”,
Engineering Science and Technology, ELSEVIER, 2019.
[19] Radoslaw Wolnaik, “Downtime in the Automotive industry Production Process – Cause analysis”, ISSN 1335-1745, Quality Innovation
Prosperity (QIP), 2019. DOI:10.12776/QIP.V2312.1259.
[20] B. Sai Subrahmanya Tejesh, S. Neeraja, “Warehousing inventory management system using IoT and Open source framework”,
ELSEVIER, Alexandria Engineering Journal, 2018.
[21] A. Kanawaday and A. Sane, "Machine learning for predictive maintenance of industrial machines using IoT sensor data," 2017 8th IEEE
International Conference on Software Engineering and Service Science (ICSESS), 2017, pp. 87-90, doi: 10.1109/ICSESS.2017.8342870.
[22] Kuldeep Naginya et al., “ATM analysis under host bank system through telephone network”, World Journal of Modeling and
Simulation, Vol.14, 2018, ISSN 1 746-7233.
[23] Krupitzer, Christian, et al. "A survey on predictive maintenance for industry 4.0." arXiv preprint arXiv:2002.08224 (2020).
[24] Hariharan Ramalingam, Dr.V.Prasanna Venkatesan, “Conceptual analysis of Internet of Things use cases in Banking domain”, IEEE R10
Conference (TENCON 2019), IEEE, 2019.
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