internet of things: research directions
TRANSCRIPT
Davide NardoneMay, 2016
Internet of Things:Research Directions
PARTHENOPEUNIVERSITY
Research Directions for IoT
1. Introduction2. IoT vision and contexts3. The main IoT research directions:
A. Massive scalingB. Architecture and DependenciesC. Creating knowledge and Big DataD. RobustnessE. OpennessF. SecurityG. PrivacyH. Humans in the Loop
4. Conclusion
Outline
Research Directions for IoT
• Using the Internet as a global platform for communication, dialogue, calculation and the interconnection of devices has been shaping a new world: a combination of new methods and technologies which are the basis of a variety of smart context.
• The creation of these scenarios has been investigated from different and disjointed scientific communities as:• Mobile Computing (MB);• Pervasive Computing (PC);• Wireless Sensor Networks (WSN);• Cyber-Physical-Systems (CPS).
Introduction
Research Directions for IoT
• Since the technology progresses, the overlapping and the combination of topics and research questions has increased to such a point that there are no more specific definitions for the previous mentioned fields.
• Many researches in the fields of IoT, PC, MC, WSN and CPS often rely on underlying technologies such as Machine Learning, Real-Time Computing, Signal Processing, Security, etc.
It’s clear the need for cooperation between the several communities for the improvement and the resolution of various
interesting research problem regarding these environments.
Introduction (cont.)
Machine Learnig
Security Privacy
Research Directions for IoT
• For many people, the concept of Smart City is no longer a vision so far away.
• Many infrastructures are already equipped with no sensor and actuator able to: • Monitoring entire system and• Interact with each other, in order to exchange information
and so to improve the quality of one or more services.
IoT vision and contexts
Research Directions for IoT
• IoT: an essential and integrated infrastructure on which many application and services can be run.
• System of systems that synergistically interact with each other to create new and not predicable services.
IoT vision and contexts (cont.)
Research Directions for IoT
What is that vision?Examples
• Global transport systems• City without traffic lights and 3D transport
vehicles• Buildings that will control energy, health,
comfort• People with bionic fragments for detecting
physiologic parameters. • etc
Examples• Input: Biometric systems• Output: Holographic display
Some examples
Research Directions for IoT
• The continuing growth of the sensors and the improving of the related processes will produce continuous qualitative changes in different contexts.
IoT benefits
Research Directions for IoT
• Given the massive amount of devices connected today (~ 24 billion), the research [1] has reported that by 2020 the revenues achieved from the sale of smart devices and the services offered to them will be about $ 2,500 billion dollars.
Industry /use case Economic value1. Smart car $ 600 billions2. Clinical Remote Monitoring $ 350 billions3. Assisted Life $ 270 billions4. Home and Buildings Security $ 250 billions5. Car insurance “Pay-As-You-Drive” $ 245 billions6. New business models for car usage $ 225 billions7. Smart meters $ 105 billions8. Traffic management $ 100 billions9. Electric vehicle charging $ 75 billions10. Building automation systems $ 40 billions
IoT benefits (cont.)
Research Directions for IoT
IoT challenges and benefits
? Challenges ✓ Benefits• People / Society • Better and faster information• Security / Privacy • Improving education• Authority • Regulation / Legislation• Standard / Policies • Life quality• Resource Efficiency • Greater awareness• Technology Architecture /
Infrastructure• Increased production
• Costs • Wider experiences• Pollution / Prevention disasters • Better decision making• Innovation Management • Resource optimization• Energy / Power Consumption • Human error removal• Growth Data and analysis • More services
Research Directions for IoT
• The research area required to obtain such IoT vision requires a significant study into many directions.
Research
A. Massive scalingB. Architecture and
DependenciesC. Creating knowledge and Big
DataD. RobustnessE. OpennessF. SecurityG. PrivacyH. Humans in the Loop
Research Directions for IoT
• Recent studies [2] have estimated that ~50 billion devices will be connected to the internet by 2020.
A. Massive Scaling
Research Directions for IoT
Massive Scaling (cont.)• Some of the many questions that we ask are:
• Will be IPV6 enough?• Will emerge new standards and protocols?• How will the devices (including mobile devices) to be
discovered?• How will the real-time and reliability issues to be
supported?• etc.
It’s almost unlikely that any solution will be immediately become the norm!
Research Directions for IoT
Simulation of large-scale IoT systems (using particular operating system [3][4]) for the evaluation and optimization of specific aspects:
• Application Layer• Energy consumption• Code reuse• Network connection• etc.
Among the different existing approaches, a hybrid simulation environment based on a combination of framework with simulators at the system-level:• It would reduce the gap between the research and the
implementations; • It also would strengthen the simulation studies in the IoT
field.
Massive Scale Simulation
Research Directions for IoT
• Since billions of devices are connected to the internet, it’s necessary to provide an appropriate architecture that easily allow: connectivity, communication, control and useful applications.
MOBILE APPROACHAdvantages (+) Disadvantages (-)• Unlimited application development. • Interference problems due the
sharing of sensors and systems implementation among multiple applications.
• Automatic controls for the execution of an application on a specific platform.
• Dependence of IT methodologies based on the assumption about the environment, the hardware platform, naming, control and various semantic devices.
• How all these “objects” will interact with each other?
B. Architecture and Dependencies
Research Directions for IoT
Let’s suppose the integration of different systems responsible for the electricity management (control thermostats, windows, doors, etc.) and the health care (ECG measurement, temperature, sleep, activities, etc.).
Advantages• Information sharing: this would allow the electricity management
systems to regulate the temperature of the rooms according to the physiological status of the residents.
• Integration between systems: this would avoid unpleasant situations; for instance the system will deactivate medical devices to save power while they are used as suggested by the health care system.
• Sharing sensors and actuators: this would reduce the costs of implementing/distribution, improving the aesthetics of the rooms and reducing the flow of content.
Example: Architecture and Dependencies
Research Directions for IoT
Challenges• Each system has its own assumptions and strategies for its control.• A lack of knowledge about the other systems would cause many
conflicts when they are integrated without particular attention.
Example of interference• The health care system could detect depression and decide to turn on
all the lights. On the other hand, the electricity management system may decide to turn off the lights due to the absence of motion.
Example (cont.)
Research Directions for IoT
Research topics to be addressed• Development of new approaches for the detection
and resolution of dependencies between applications.
• Autonomous decentralized architecture inspired by the connection of sensor nodes.
• Introduction of cloud structures, architectures guided by events, disconnected operation and synchronization.
IoT: Architecture and Dependencies
Research Directions for IoT
• IoT is the next technological revolution that is estimated to produce over 44 Zettabyte of data (4.4e+10 Terabyte) by 2020 [5].
• Almost all the “objects” or devices will have an IP address, and will be connected to each other.
• Given the incredible amount of data generated, new mechanisms will be needed for:• Collecting and selecting data• Data pre-processing • Turn raw data into useful information• Extracting information• Data interpretation
C. Creating knowledge and Big Data
Research Directions for IoT
The main Big Data challenges in the IoT context are:• Reliability• Data security• Big Data collection• Identification of redundant data• Data interpretation and creation of useful information
that includes noise• Development of inference techniques that do not suffer
of the Bayesian and Dempster limitation• Correct data binding• Ect.
IoT & Big Data: Main challanges
Research Directions for IoT
• Reliability is one of the most important aspects of the use of Big Data.
Development of new calibration techniques and transport protocols:
• Ensure that following inference do not operate on incorrect data or data with too many missing data!
• Ensure “safe” operations of the actuators• Draw up good decisions.
Possible solutions• Associate a confidence level (in the form of probability) to
the information derived from the date.• Using Fuzzy Logic [4].• Minimizing the number of false negatives and false
positives.
IoT & Big Data: Reliability
Research Directions for IoT
• IoT has launched new security challenges that cannot be addressed by using traditional security mechanism.
• Addressing the security concerns of the IoT requires a paradigm shift.
For example, how do you deal with the situation where the fridge and coffee maker are equipped with hidden Wi-Fi access and spammers?
According to the experts, the problem of data security has two major aspects:
1. Confidentiality2. Protection
IoT & Big Data: Security
Research Directions for IoT
Companies need only to collect data related to their business, and this requires:• Filtering techniques on redundant data and protection data
techniques.• Efficient mechanisms that include software and protocols.Solutions• One approach is to use devices with sensors for data collections, in
combination with transport protocols such as: Message Queue Telemetry Transport (MQTT) and Data Distribution Service (DDS).
ExampleOne of the most important transportation companies in the world, UPS, uses sensors in its vehicle to improve delivery performance and reduce coast.• These data help UPS out in reducing fuel consumption, harmful
emissions and waste time.
IoT & Big Data: Big Data Collection
Research Directions for IoT
Problems in the collection of Big DataBy the statistic coming from [6], it’s shown the various challenges that companies have faced with the data collection activities.
19%
13%
9%22%
25%
12%
Big Data challenges Problems in data col-lection
Unreliable data collection
Slowness in data col-lection
Cumbersome amout of data to analyze properly
Techniques for analysis and data processing premature
Existing business pro-cesses not flexible for the efficient collection of data
Research Directions for IoT
• Not all device provide useful information.• It’s not easy to filter data in real-time.
53%47%
Rationale: Methods of inefficient data collec-
tion.Do not track their projects with quantifiable metricsThey do not measure the progress of their IoT projects
13%
87%
96% of organizations have diffi-culties to filter large amounts of
redundant data.Able to collecting data efficientlyRecognize the benefits for their business
Survey conducted by Parstream [6]
IoT & Big Data: Identifying redundant data
Research Directions for IoT
IoT offers an exciting prospect from the point of view of Big Data, but it’s necessary to:
• Optimize the entire setup for managing the IoT impact in the context of the Big Data.
• Solve the problems concerning the security & the privacy and the efficient data collection.
There’s hope that these issues may be efficiently solved since both IoT and the infrastructure for its management are in the early stages.
IoT & Big Data: Summary
Research Directions for IoT
IoT vision: Application based on sensors, actuators and communication distributed platforms connected to a network of “objects”.In such distributions it is common for devices to know:
• their positions• nearby devices cooperating having• synchronized clocks• Consistent parameter setting such as: sleep, wake, battery levels and
security key pairs.ChallengesThe deterioration of these conditions cause the break up of the clocks that:
• Causes the nodes to have different time shift, that leads to failures within the system.Solutions
Synchronization techniques are used in this context [7].
D. Robustness
Research Directions for IoT
• Although it is recognized that the synchronization of the clock is necessary, this simple concept is too general.
• More serious problem is the physical relocation of the sensor nodes.• (e.g., random-temporal displacement of one or more nodes)
The higher the entropy, the greater the disorder and less energy is available in the system to do useful things.
Robustness (cont.)
Research Directions for IoT
- Goal: Create a robust system that can cope with changes in its operations without suffering serious damage or loss of functions.
How can it possible to keep a persistent, dynamic and mobile IoT system?
- Method: The consistency services required (entropy) must to be combined with other approaches for producing a robust system, ensuring:
• Persistence: Automatic operations for organization, monitoring, diagnostic and repair.
• Dynamism and mobility: Methods for the development of reliable code, online tolerance errors and locally debbuging.
Robustness: consideration
Research Directions for IoT
The majority of sensor-based systems were closed systems.• (e.g., cars, planes, and ships have had network sensor systems
operating largely within the vehicle itself).
The capabilities of these systems are increasing rapidly.Some example are:
• Cars transmitting information assistance.• Airplanes sending technical real-time information.• Cars communicating with each other and control each other to
avoid collisions.• Doctors who interact in real-time with their patients analyzing
physiological data, automatically loaded.
In order to achieve such benefits, the systems requires openness, but…
What does it mean the Openness of such systems?
E. Openness
Research Directions for IoT
Research problems to the openness support• Rethinking of the current composition techniques, analysis and the
respective tools.• New communication interface to enable the efficient exchange on
information between the systems.• Difficulties with security and privacy.
It’s necessary to provide a “fair balance” between:Functionality, Security and Ease of Use.
Openness (cont.)
Research Directions for IoT
• Key issue which will become more and more intense every day.
• The greater the volume of sensitive data (Big Data’s V) that moves in IoT, the higher is the risk of data theft and identity, manipulation of devices, data faking, IP theft, etc.
F. Security
Problems• IoT products are often sold with old
embedded operating systems and software products.
• Many of these systems/software (designed to be safe) are still vulnerable.
Research Directions for IoT
The vulnerabilities found in the IoT have drawn attention to the topic of “security”. Some types of threats are:
• Failures of devices (disrupt services)• Violation of the privacy (steal
information)• Control of devices (take control)
IoT: Vulnerability
Research Directions for IoT
Given the particular nature of these devices, IoT has the following challenges to face:
1. Critical functions2. Replication3. Difficulty in repairing 4. Security assumptions5. Long life cycle6. etc.
What are the challenges to be addressed to ensure the security of embedded devices and to secure IoT?
Security: IoT challenges
Solutions used for standard computer do not solve the IoT security issues of embedded devices, due to the their
heterogeneity.
Research Directions for IoT
Security features Implementation on embedded devicesSecure boot Security standard that ensures that the device boots using
only secure software (software signature check).Secure code updates Safe methods for updating the code, bugging fixes, security
patches, etc. (use the signed code).Data security Prevent unauthorized access to the device, encrypting the
data storage and / or communication.Authentication All communications with devices should be authenticated
with strong passwords.Secure communication Communication to and from the devices must be secured
using encrypted protocols (SSH, SSL, etc.).Protection against cyber attacks
Integrated firewall to restrict communications to only trusted host, blocking hackers before they can launch attacks.
Intrusion detection and security monitoring
Detection and communication of disabled login attempts and other potential malicious activity.
Tamper detection on device New processors / cards that have capacity of device tampering detection.
Self Healing Methods for "healing" from cyber attacks (e.g., code updates).
Security requirements
Research Directions for IoT
• Significant hardware supports [8] encryption, authentication and key tampering.
• Ensure the connection between the gateway devices and the corporate network or factory.
• Greater effort to protect the IoT data, to ensure consumer privacy and functionality of the company.
• Solid action plan for the installation of security updates.
What is left to do?
Research Directions for IoT
IoT may become the term most in vogue of the day at the workplace.87% of the customers do not know what the IoT is [9], but they are aware of:
1. Granting of their personal (to retailers) data by means of devices.
2. Annoyed in sharing their data.Requirement for companies to
develop better criteria for communicating the utilization and
sharing data of its customers.
G. Privacy
Research Directions for IoT
Solutions1. Specific privacy policies for each domain / system
and2. Privacy reinforcement in the IoT infrastructure of the
IoT applications.IoT paradigm1. Expression of users' requests for accessing to the data
and the policies they have adopted.2. Assessment of the requests to ensure whether or not
their permission.
• Advantages: The ubiquity and interaction involved in IoT will provide many useful benefits and services.
• Disadvantages: It will create many circumstances for privacy violation.
Privacy (cont.)
Research Directions for IoT
The current legislation does not properly express the privacy policies for the following requirements:
1. Expression of different types of contexts (time, space, etc.).
2. Representation of different types of data owners (human and non-human entities).
3. Representation of high-level aggregation requests by anonymous functions.
4. The need to support not only adherence to privacy for queries of data, but also privacy on request to set a system’s parameters.
5. Allow dynamic changes in policies One of the main problem concerns the interaction between different systems (each with its own privacy policies), which
could give rise to many inconsistencies.
Privacy problems
Research Directions for IoT
DEF: Human-in-the-loop (HITL) is defined as a model that requires human interaction.• Many IoT applications involves the interaction between
objects and humans.
Advantages: HITL offers exciting opportunities to a wide range of applications (i.e. energy management, health care, etc.).Disadvantages: Hard modeling of human behavior because of its complex physiological, psychological and behavioral aspects.
New research is needed to:1. Increase the control of HITL in designing systems;2. Solve the following three challenges.
H. Human in the loop
Research Directions for IoT
First challenge• The need for a comprehensive understanding of the complete
spectrum of types of human-in-the-loop controls..
The wide heterogeneity and the subtle differences of HITL generates various problems in the creation of a single system.
The HITL applications can be classified into four categories:1. Global system control by human being (e.g., surveillance
monitoring).2. Passive monitoring of the human system, adopting
appropriate measures (e.g., eating habits).3. Modeling of human physiological parameters.4. Hybrids of 1, 2 and 3.
Main challenges of HITL (1)
Research Directions for IoT
Second challenge• The need for extensions to system identification or other
techniques to derive models of human behaviors..Advantages: The identification systems are very powerful tools for creating models.Disadvantages: Very difficult to apply to human behavior.Example:• If we were to use "identification techniques" to shape a human being
who is suffering from depressive illness, there would be many questions about:• Type of inputs;• Possible states;• Change states according to different physiological, psychological
and environmental states.The existence of a formal or estimated model of the "human
behavior" could help us to close the loop!
Main challenges of HITL (2)
Third challenge• Determining how to incorporate human behavior models into
the formal methodology of feedback control.
Example:• Optimization of human behavior based on reports of accidents and
incidents that occur during operation of an electric power system:• Components Models of Emotion (CME) for observing, recording,
and analyzing the emotional component of the operator's behavior.
• Simulation of the dynamic behavior of an operator in performing operations in a context that leads to an error.
If we could incorporate into the system such a behavioral model, we would be able to analyze various security features of
the entire system.
Research Directions for IoT
Main challenges of HITL (3)
Research Directions for IoT
• IoT is a chance to make our world smarter.• IoT is a very profitable field of application for companies. • IoT has a good implications in different application fields
(health, transport, etc.).• The ongoing research needs to intensify to benefit from the
above mentioned points and to solve new problems that arise due to:• Growing number of connected devices;• Openness of the systems;• Continuous privacy and security problems.
ExpectationsIt is hoped that there is more cooperation between the researchcommunities in order to:
• Solve the myriad of problems as soon as possible;• Avoid reinventing the wheel when a particular community solves a
problem.
Conclusion
Research Directions for IoT
[1] Gartner Says the Internet of Things Installed Base Will Grow to 26 Billion Units By 2020 (http://www.gartner.com/newsroom/id/2970017).[2] http://www.cisco.com/c/dam/en_us/about/ac79/docs/innov IoT_IBSG_0411FINAL.pdf[3] P. Levis, N. Lee, M. Welsh, and D. Culler. TOSSIM: Accurate and scalable simulation of entire TinyOS applications. In SenSys'03: Proceedings of the First International Conference on Embedded Networked Sensor Systems.[4] K. Shang, Z. Hossen. Applying fuzzy logic to risk assessment and decision-making[5] https://www.emc.com/leadership/digital-universe/2014iview/index.htm[6] Internet of things (Iot) Meets Big Data anD analytIcs: a survey of Iot stakeholDers. Sponsored by Parstream. December 12, 2013.[7] M. Maroti, B. Kusy, G. Simon, and A. Ledeczi, “The flooding time synchronization protocol,” in Proc. 2nd Int. Conf. Embedded Netw. Sens. Syst. (ACM SenSys’04), Nov. 2004.[8] S. Ravi, A. Raghunathan, and S. Chakradhar, “Tamper resistance mechanisms for secure, embedded systems,” in Proc. 17th Int. Conf. VLSI Des., 2004.[9] http://go.pardot.com/l/69102/2015-07-12/pxzlm.[10] http://www.globaltelecomsbusiness.com/article/2985699/Connected-devices-will-be-worth-45t.html[11] F. Osterlind, A. Dunkels, J. Eriksson, N. Finne, and T. Voigt. Cross-level sensor network simulation with cooja. In Local Computer Networks, Proceedings 2006 31st IEEE Conference.
References
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