SlideShare a Scribd company logo
Dr Mallikarjunaswamy N J
1
INTERNET OF THINGS
MODULE-3
By
Dr. Mallikarjunaswamy N J
IP as the IoT Network Layer:
 The Business Case for IP
 The Need for Optimization
 Optimizing IP for IoT
 Profiles and Compliances
Dr Mallikarjunaswamy N J
2
The Key Advantages of
Internet Protocol
 1. Open and standards-based:
 2. Versatile:
 3. Ubiquitous:
 4. Scalable:
 5. Manageable and highly secure:
 6. Stable and resilient:
 7. Consumers’ market adoption:
 8. The innovation factor:
Dr Mallikarjunaswamy N J
3
Adoption or Adaptation of the Internet
Protocol:
 Adaptation means application layered gateways (ALGs) must be implemented to ensure the
translation between non-IP and IP layers.
 Adoption involves replacing all non-IP layers with their IP layer counterparts, simplifying the
deployment model and operations.
 Supervisory control and data acquisition (SCADA) applications are typical examples of
vertical market deployments that operate both the IP adaptation model and the adoption
model.
 SCADA is an automation control system for remote monitoring and control of equipment.
 Implementations that make use of IP adaptation have SCADA devices attached through serial
interfaces to a gateway tunneling or translating the traffic.
 With the IP adoption model, SCADA devices are attached via Ethernet to switches and
routers.
 Another example is a ZigBee solution that runs a non-IP stack between devices and a ZigBee
gateway that forwards traffic to an application server.
 A ZigBee gateway often acts as a translator between the ZigBee and IP protocol stacks.
Dr Mallikarjunaswamy N J
4
which model is best suited for
last-mile connectivity:
 Bidirectional versus unidirectional data flow:
 Overhead for last-mile communications paths:
 Data flow model:
 Network diversity:
Dr Mallikarjunaswamy N J
5
The Need for Optimization:
 Constrained Nodes:
 IoT node may be required to communicate through an unreliable path.
 power consumption is a key characteristic of constrained nodes.
 Many IoT devices are battery powered, with lifetime battery requirements varying from a few
months to 10+ years.
 This drives the selection of networking technologies since high-speed ones, such as Ethernet,
Wi-Fi, and cellular, are not (yet) capable of multi-year battery life.
 Current capabilities practically allow less than a year for these technologies on battery-
powered nodes.
 power consumption is much less of a concern on nodes that do not require batteries as an
energy source.
Dr Mallikarjunaswamy N J
6
IoT constrained nodes can be classified as
follows:
1. Devices that are very constrained in resources, may communicate infrequently
to transmit a few bytes, and may have limited security and management
capabilities:
2. Devices with enough power and capacities to implement a stripped downIP
stack or non-IP stack:
3. Devices that are similar to generic PCs in terms of computing and power
resources but have constrained networking capacities, such as bandwidth:
Dr Mallikarjunaswamy N J
7
Constrained Networks:
 limited by low-power, low-bandwidth links
 high latency and a high potential for packet loss
 They operate between a few kbps and a few hundred kbps.
 unpredictable errors and even loss of connectivity
 packet delivery rate (PDR) to oscillate between low and high percentages.
 highly stable and fast links are available.
 limited by low-power, low-bandwidth links (wireless and wired).
Dr Mallikarjunaswamy N J
8
IP Versions:
 For 20+ years, the IETF has been working on transitioning the Internet
 from IP version 4 to IP version 6.
 The main driving force has been the lack of address space in IPv4 as the
Internet has grown.
 IPv6 has a much larger range of addresses that should not be exhausted for
the foreseeable future.
 Today, both versions of IP run over the Internet, but most traffic is still
IPv4 based.
 A variety of factors dictate whether IPv4, IPv6, or both can be used in an
IoT solution.
 Most often these factors include a legacy protocol or technology that
supports only IPv4.
Dr Mallikarjunaswamy N J
9
The following are some of the main factors applicable to
IPv4 and IPv6 support in an IoT solution:
 Application Protocol:
 Cellular Provider and Technology:
 Serial Communications:
 IPv6 Adaptation Layer:
Dr Mallikarjunaswamy N J
10
IPv6 Adaptation Layer:
Optimizing IP for IoT:
Dr Mallikarjunaswamy N J
11
From 6LoWPAN to 6Lo:
Dr Mallikarjunaswamy N J
12
6LoWPAN
Dr Mallikarjunaswamy N J
13
Figure shows the sub headers related to compression,
fragmentation, and mesh addressing.
Dr Mallikarjunaswamy N J
14
6LoWPAN
Dr Mallikarjunaswamy N J
15
Fragmentation:
 The maximum transmission unit (MTU)for an IPv6 network must be at
least 1280 bytes.
 The term MTU defines the size of the largest protocol data unit that can be
passed.
 For IEEE 802.15.4, 127 bytes is the MTU.
 In IPv6, with a much larger MTU, is carried inside the 802.15.4 frame with
a much smaller one.
 Toremedy this situation, large IPv6 packets must be fragmented across
multiple 802.15.4 frames at Layer 2.
Dr Mallikarjunaswamy N J
16
Fragmentation
 The fragment header utilized by 6LoWPAN is composed of three primary
fields:
 Datagram Size, Datagram Tag, and Datagram Offset.
 The 1-byte Datagram Size field specifies the total size of the unfragmented
payload.
 Datagram Tag identifies the set of fragments for a payload.
 Finally, the Datagram Offset field delineates how far into apayload a
particular fragment occurs.
 Figure provides an overview of a 6LoWPAN fragmentation header.
Dr Mallikarjunaswamy N J
17
6lOWPAN Fragmentation Header
Dr Mallikarjunaswamy N J
18
6lOWPAN Fragmentation
Header
Dr Mallikarjunaswamy N J
19
Mesh Addressing:
 The purpose of the 6LoWPAN mesh addressing function is to
forward packets over multiple hops.
 Three fields are defined for this header: Hop Limit, Source
Address, and Destination Address.
 hop limit for mesh addressing also provides an upper limit on
how many times the frame can be forwarded.
 Each hop decrements this value by 1 as it is forwarded.
 Once the value hits 0, it is dropped and no longer forwarded.
Dr Mallikarjunaswamy N J
20
6LoWPAN Mesh Addressing
Header
Dr Mallikarjunaswamy N J
21
6TiSCH:
 IEEE 802.15.4e, Time-Slotted Channel Hopping (TSCH), is an
add-on to the Media Access Control (MAC) portion of the IEEE
802.15.4 standard, with direct inheritance from other standards,
such as WirelessHART and ISA100.11a.
 Devices implementing IEEE 802.15.4e TSCH communicate by
following a Time Division Multiple Access (TDMA) schedule.
 An allocation of a unit of bandwidth or time slot is scheduled
between neighbor nodes.
Dr Mallikarjunaswamy N J
22
The 6TiSCH architecture defines four schedule
management mechanisms:
 Static scheduling: (Slotted aloha)
 Neighbor-to-neighbor scheduling: (add and
delete cells)
 Remote monitoring and scheduling
management: (management entity
responsible to allocate time slots )
 Hop-by-hop scheduling: (source node is
responsible to allocate time slots &
resources) Dr Mallikarjunaswamy N J
23
four schedule management
mechanisms:
Dr Mallikarjunaswamy N J
24
There are three 6TiSCH forwarding
models:
 Track Forwarding (TF):
 A “track” in this model is a unidirectional path between a source and
a destination.
 Fragment forwarding (FF):
 IPv6 packets can get fragmented at source node and reassemble at
des.
 IPv6 Forwarding (6F):
 Maintains IPv6 routing table to give priority to the pkts(QOS) and to avoid
collision of pkts(RED).
Dr Mallikarjunaswamy N J
25
RPL:
 RPL (Routing Protocol for Low Power and Lossy Networks ):
 In an RPL network, each node acts as a router and becomes part of a
mesh network.
 Ø Routing is performed at the IP layer.
 Ø Each node examines every received IPv6 packet anddetermines
the next-hop destination based on the information contained in the
IPv6 header.
 Ø Noinformation from the MAC-layer header is needed to perform
next-hop determination.
Dr Mallikarjunaswamy N J
26
The protocol defines two modes:
 Storing mode:
 Non-storing mode:
Dr Mallikarjunaswamy N J
27
RPL Modes
Dr Mallikarjunaswamy N J
28
RPL (Routing Protocol for Low Power and
Lossy Networks ):
Dr Mallikarjunaswamy N J
29
DAG and DODAG
Comparison
Dr Mallikarjunaswamy N J
30
Figure shows how DAO and DIO messages move both up and down the
DODAG, depending on the exact message type.
Dr Mallikarjunaswamy N J
31
DIO & DAO
Dr Mallikarjunaswamy N J
32
RPL Headers:
 Specific network layer headers are defined for datagrams being forwarded
within an RPL domain.
 Ø One of the headers is standardized in RFC 6553, “The Routing Protocol
for Low- Power and Lossy Networks (RPL) Option for Carrying RPL
Information in Data- Plane Datagrams,” and the other is discussed in RFC
6554, “An IPv6 Routing Header for Source Routes with the Routing
Protocol for Low-Power and Lossy Networks
 The RPL option is carried in the IPv6 Hop-by-Hop header.
 Ø The purpose of this header is to leverage data-plane packets for loop
detection in a RPL instance.
 Ø DODAGs only have single paths and should be loop free.
 Ø RFC 6554 specifies the Source Routing Header (SRH) for use between
RPL routers.

Dr Mallikarjunaswamy N J
33
Metrics: (RPL Metrics)
1. Expected Transmission Count
(ETX):
2. Hop Count: (higher hop counts)
3. Latency: (low Latency)
4. Link Quality Level: (high level of quality)
5. Link Color: (link more or less desirable)
6. Node State and Attribute: (high workload &
CPU)
7. Node Energy: (low power)
8. Throughput: (maximum)Dr Mallikarjunaswamy N J
34
Authentication and Encryption on Constrained Nodes:
 the Authentication and Authorization for Constrained Environments (ACE)
working group is tasked with evaluating the applicability of existing
authentication and authorization protocols and documenting their
suitability for certain constrained-environment use cases.
 Ø Once the candidate solutions are validated, the ACE working group will
focus its work on CoAP with the Datagram Transport Layer Security
(DTLS) protocol.
 Ø The ACE working group expects to produce a standardized solution for
authentication and authorization that enables authorized access (Get, Put,
Post, Delete) to resources identified by a URI and hosted on a resource
server in constrained environments.
Dr Mallikarjunaswamy N J
35
DICE:
 Ø New generations of constrained nodes implementing an IP stack over
constrained access networks are expected to run an optimized IP protocol
stack.
 Ø For example, when implementing UDP at the transport layer, the IETF
Constrained Application Protocol (CoAP) should be used at the application
layer.
 Ø In constrained environments secured by DTLS, CoAP can be used
to control resources on a device.
Dr Mallikarjunaswamy N J
36
Application Protocols for IoT
 This chapter focuses on how higher-layer IoT protocols are transported.
Specifically, this chapter includes the following sections:
 The Transport Layer:
 IP-based networks use either TCP or UDP.
 With the TCP/IP protocol, two main protocols are specified for the
transport layer:
 Transmission Control Protocol (TCP):
 User Datagram Protocol (UDP):
Dr Mallikarjunaswamy N J
37
IoT Application Transport Methods:
1. Application layer protocol not present:
 Lower layers transport data so application layer not needed
2. Supervisory control and data acquisition
(SCADA):
 Monitoring and controlling remote physical equipment
3 Generic web-based protocols: (wifi, Ethernet, etc )
4. IoT application layer protocols: (MQTT)
 Reduces number of connection b/w peripheral devices
Dr Mallikarjunaswamy N J
38
MQTT: Message Queuing
Telemetry Transport
Dr Mallikarjunaswamy N J
39
Dr Mallikarjunaswamy N J
40
MQTT: Message Queuing
Telemetry Transport

More Related Content

What's hot

Introduction to IoT Architectures and Protocols
Introduction to IoT Architectures and ProtocolsIntroduction to IoT Architectures and Protocols
Introduction to IoT Architectures and Protocols
Abdullah Alfadhly
 
Mobile transport layer - traditional TCP
Mobile transport layer - traditional TCPMobile transport layer - traditional TCP
Mobile transport layer - traditional TCP
Vishal Tandel
 
Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...
Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...
Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...
Selvaraj Seerangan
 
Firewall presentation
Firewall presentationFirewall presentation
Firewall presentation
Amandeep Kaur
 
Mac protocols
Mac protocolsMac protocols
Mac protocols
juno susi
 
Unit 2 Smart Objects _IOT by Dr.M.K.Jayanthi.pdf
Unit 2 Smart Objects _IOT  by Dr.M.K.Jayanthi.pdfUnit 2 Smart Objects _IOT  by Dr.M.K.Jayanthi.pdf
Unit 2 Smart Objects _IOT by Dr.M.K.Jayanthi.pdf
Jayanthi Kannan MK
 
Agent discovery& registration
Agent discovery& registrationAgent discovery& registration
Agent discovery& registration
rajisri2
 
MOBILE Ad-Hoc NETWORK (MANET)
MOBILE Ad-Hoc NETWORK (MANET)MOBILE Ad-Hoc NETWORK (MANET)
MOBILE Ad-Hoc NETWORK (MANET)
Monodip Singha Roy
 
Security issues and attacks in wireless sensor networks
Security issues and attacks in wireless sensor networksSecurity issues and attacks in wireless sensor networks
Security issues and attacks in wireless sensor networks
Md Waresul Islam
 
Iot and cloud computing
Iot and cloud computingIot and cloud computing
Iot and cloud computing
eteshagarwal1
 
MANET in Mobile Computing
MANET in Mobile ComputingMANET in Mobile Computing
MANET in Mobile Computing
KABILESH RAMAR
 
WSN IN IOT
WSN IN IOTWSN IN IOT
WSN IN IOT
skumartarget
 
Cloud computing protocol
Cloud computing protocolCloud computing protocol
Cloud computing protocol
Kartik Kalpande Patil
 
IOT - Design Principles of Connected Devices
IOT - Design Principles of Connected DevicesIOT - Design Principles of Connected Devices
IOT - Design Principles of Connected Devices
Devyani Vasistha
 
IEEE 802.11 Architecture and Services
IEEE 802.11 Architecture and ServicesIEEE 802.11 Architecture and Services
IEEE 802.11 Architecture and Services
Sayed Chhattan Shah
 
Sensors in IOT
Sensors in IOTSensors in IOT
Sensors in IOT
ATS SBGI MIRAJ
 
Wireless application protocol ppt
Wireless application protocol  pptWireless application protocol  ppt
Wireless application protocol ppt
OECLIB Odisha Electronics Control Library
 
Alternative metrics
Alternative metricsAlternative metrics
Alternative metrics
Parthipan Parthi
 
Seminar ppt fog comp
Seminar ppt fog compSeminar ppt fog comp
Seminar ppt fog comp
Mahantesh Hiremath
 
connecting smart object in IoT.pptx
connecting smart object in IoT.pptxconnecting smart object in IoT.pptx
connecting smart object in IoT.pptx
AnisZahirahAzman
 

What's hot (20)

Introduction to IoT Architectures and Protocols
Introduction to IoT Architectures and ProtocolsIntroduction to IoT Architectures and Protocols
Introduction to IoT Architectures and Protocols
 
Mobile transport layer - traditional TCP
Mobile transport layer - traditional TCPMobile transport layer - traditional TCP
Mobile transport layer - traditional TCP
 
Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...
Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...
Unit 2,3,4 _ Internet of Things A Hands-On Approach (Arshdeep Bahga, Vijay Ma...
 
Firewall presentation
Firewall presentationFirewall presentation
Firewall presentation
 
Mac protocols
Mac protocolsMac protocols
Mac protocols
 
Unit 2 Smart Objects _IOT by Dr.M.K.Jayanthi.pdf
Unit 2 Smart Objects _IOT  by Dr.M.K.Jayanthi.pdfUnit 2 Smart Objects _IOT  by Dr.M.K.Jayanthi.pdf
Unit 2 Smart Objects _IOT by Dr.M.K.Jayanthi.pdf
 
Agent discovery& registration
Agent discovery& registrationAgent discovery& registration
Agent discovery& registration
 
MOBILE Ad-Hoc NETWORK (MANET)
MOBILE Ad-Hoc NETWORK (MANET)MOBILE Ad-Hoc NETWORK (MANET)
MOBILE Ad-Hoc NETWORK (MANET)
 
Security issues and attacks in wireless sensor networks
Security issues and attacks in wireless sensor networksSecurity issues and attacks in wireless sensor networks
Security issues and attacks in wireless sensor networks
 
Iot and cloud computing
Iot and cloud computingIot and cloud computing
Iot and cloud computing
 
MANET in Mobile Computing
MANET in Mobile ComputingMANET in Mobile Computing
MANET in Mobile Computing
 
WSN IN IOT
WSN IN IOTWSN IN IOT
WSN IN IOT
 
Cloud computing protocol
Cloud computing protocolCloud computing protocol
Cloud computing protocol
 
IOT - Design Principles of Connected Devices
IOT - Design Principles of Connected DevicesIOT - Design Principles of Connected Devices
IOT - Design Principles of Connected Devices
 
IEEE 802.11 Architecture and Services
IEEE 802.11 Architecture and ServicesIEEE 802.11 Architecture and Services
IEEE 802.11 Architecture and Services
 
Sensors in IOT
Sensors in IOTSensors in IOT
Sensors in IOT
 
Wireless application protocol ppt
Wireless application protocol  pptWireless application protocol  ppt
Wireless application protocol ppt
 
Alternative metrics
Alternative metricsAlternative metrics
Alternative metrics
 
Seminar ppt fog comp
Seminar ppt fog compSeminar ppt fog comp
Seminar ppt fog comp
 
connecting smart object in IoT.pptx
connecting smart object in IoT.pptxconnecting smart object in IoT.pptx
connecting smart object in IoT.pptx
 

Similar to Module 3 INTERNET OF THINGS

IOT - Unit 3.pptx
IOT - Unit 3.pptxIOT - Unit 3.pptx
IOT - Unit 3.pptx
PallaviPatil580306
 
Implementation_and_Analysis_of_the_6LoWPAN.pdf
Implementation_and_Analysis_of_the_6LoWPAN.pdfImplementation_and_Analysis_of_the_6LoWPAN.pdf
Implementation_and_Analysis_of_the_6LoWPAN.pdf
IUA
 
Congestion and Energy Aware Multipath Load Balancing Routing for LLNS
Congestion and Energy Aware Multipath Load Balancing Routing for LLNSCongestion and Energy Aware Multipath Load Balancing Routing for LLNS
Congestion and Energy Aware Multipath Load Balancing Routing for LLNS
IJCNCJournal
 
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNS
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNSCONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNS
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNS
IJCNCJournal
 
Performance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdf
Performance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdfPerformance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdf
Performance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdf
IUA
 
Swry013
Swry013Swry013
6 lowpan
6 lowpan6 lowpan
6 lowpan
Siva Kumar
 
The support of multipath routing in IPv6-based internet of things
The support of multipath routing in IPv6-based  internet of things The support of multipath routing in IPv6-based  internet of things
The support of multipath routing in IPv6-based internet of things
IJECEIAES
 
IJSRED-V1I1P4
IJSRED-V1I1P4IJSRED-V1I1P4
IJSRED-V1I1P4
IJSRED
 
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACK
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACKAN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACK
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACK
IJCNCJournal
 
An Experimental Study of IoT Networks Under Internal Routing Attack
An Experimental Study of IoT Networks Under Internal Routing AttackAn Experimental Study of IoT Networks Under Internal Routing Attack
An Experimental Study of IoT Networks Under Internal Routing Attack
IJCNCJournal
 
Energy and Load Aware Routing Protocol for Internet of Things
Energy and Load Aware Routing Protocol for Internet of ThingsEnergy and Load Aware Routing Protocol for Internet of Things
Energy and Load Aware Routing Protocol for Internet of Things
IJAAS Team
 
M017147275
M017147275M017147275
M017147275
IOSR Journals
 
Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...
Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...
Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...
IOSR Journals
 
ANALYSIS OF IPV6 TRANSITION TECHNOLOGIES
ANALYSIS OF IPV6 TRANSITION TECHNOLOGIESANALYSIS OF IPV6 TRANSITION TECHNOLOGIES
ANALYSIS OF IPV6 TRANSITION TECHNOLOGIES
IJCNCJournal
 
Efficient End-to-End Secure Key Management Protocol for Internet of Things
Efficient End-to-End Secure Key Management Protocol for Internet of Things Efficient End-to-End Secure Key Management Protocol for Internet of Things
Efficient End-to-End Secure Key Management Protocol for Internet of Things
IJECEIAES
 
Respond 3 of your colleagues postings in one or more of the fol.docx
 Respond  3 of your colleagues postings in one or more of the fol.docx Respond  3 of your colleagues postings in one or more of the fol.docx
Respond 3 of your colleagues postings in one or more of the fol.docx
aryan532920
 
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGSTRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
pijans
 
Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.
Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.
Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.
pijans
 
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGSTRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
pijans
 

Similar to Module 3 INTERNET OF THINGS (20)

IOT - Unit 3.pptx
IOT - Unit 3.pptxIOT - Unit 3.pptx
IOT - Unit 3.pptx
 
Implementation_and_Analysis_of_the_6LoWPAN.pdf
Implementation_and_Analysis_of_the_6LoWPAN.pdfImplementation_and_Analysis_of_the_6LoWPAN.pdf
Implementation_and_Analysis_of_the_6LoWPAN.pdf
 
Congestion and Energy Aware Multipath Load Balancing Routing for LLNS
Congestion and Energy Aware Multipath Load Balancing Routing for LLNSCongestion and Energy Aware Multipath Load Balancing Routing for LLNS
Congestion and Energy Aware Multipath Load Balancing Routing for LLNS
 
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNS
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNSCONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNS
CONGESTION AND ENERGY AWARE MULTIPATH LOAD BALANCING ROUTING FOR LLNS
 
Performance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdf
Performance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdfPerformance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdf
Performance-Evaluation-of-RPL-Routes-and-DODAG-Construction-for-IoTs .pdf
 
Swry013
Swry013Swry013
Swry013
 
6 lowpan
6 lowpan6 lowpan
6 lowpan
 
The support of multipath routing in IPv6-based internet of things
The support of multipath routing in IPv6-based  internet of things The support of multipath routing in IPv6-based  internet of things
The support of multipath routing in IPv6-based internet of things
 
IJSRED-V1I1P4
IJSRED-V1I1P4IJSRED-V1I1P4
IJSRED-V1I1P4
 
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACK
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACKAN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACK
AN EXPERIMENTAL STUDY OF IOT NETWORKS UNDER INTERNAL ROUTING ATTACK
 
An Experimental Study of IoT Networks Under Internal Routing Attack
An Experimental Study of IoT Networks Under Internal Routing AttackAn Experimental Study of IoT Networks Under Internal Routing Attack
An Experimental Study of IoT Networks Under Internal Routing Attack
 
Energy and Load Aware Routing Protocol for Internet of Things
Energy and Load Aware Routing Protocol for Internet of ThingsEnergy and Load Aware Routing Protocol for Internet of Things
Energy and Load Aware Routing Protocol for Internet of Things
 
M017147275
M017147275M017147275
M017147275
 
Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...
Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...
Performance Evaluation of IPv4 Vs Ipv6 and Tunnelling Techniques Using Optimi...
 
ANALYSIS OF IPV6 TRANSITION TECHNOLOGIES
ANALYSIS OF IPV6 TRANSITION TECHNOLOGIESANALYSIS OF IPV6 TRANSITION TECHNOLOGIES
ANALYSIS OF IPV6 TRANSITION TECHNOLOGIES
 
Efficient End-to-End Secure Key Management Protocol for Internet of Things
Efficient End-to-End Secure Key Management Protocol for Internet of Things Efficient End-to-End Secure Key Management Protocol for Internet of Things
Efficient End-to-End Secure Key Management Protocol for Internet of Things
 
Respond 3 of your colleagues postings in one or more of the fol.docx
 Respond  3 of your colleagues postings in one or more of the fol.docx Respond  3 of your colleagues postings in one or more of the fol.docx
Respond 3 of your colleagues postings in one or more of the fol.docx
 
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGSTRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
 
Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.
Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.
Trustbased Routing Metric for RPL Routing Protocol in the Internet of Things.
 
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGSTRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
TRUST BASED ROUTING METRIC FOR RPL ROUTING PROTOCOL IN THE INTERNET OF THINGS
 

Recently uploaded

Engine Lubrication performance System.pdf
Engine Lubrication performance System.pdfEngine Lubrication performance System.pdf
Engine Lubrication performance System.pdf
mamamaam477
 
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Sinan KOZAK
 
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
ihlasbinance2003
 
Understanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine LearningUnderstanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine Learning
SUTEJAS
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
gerogepatton
 
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
bijceesjournal
 
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.pptUnit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
KrishnaveniKrishnara1
 
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball playEric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
enizeyimana36
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
co23btech11018
 
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
171ticu
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
MIGUELANGEL966976
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Christina Lin
 
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
Yasser Mahgoub
 
Engineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdfEngineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdf
abbyasa1014
 
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptxML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
JamalHussainArman
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
gerogepatton
 
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
IJECEIAES
 
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
University of Maribor
 
Question paper of renewable energy sources
Question paper of renewable energy sourcesQuestion paper of renewable energy sources
Question paper of renewable energy sources
mahammadsalmanmech
 
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
insn4465
 

Recently uploaded (20)

Engine Lubrication performance System.pdf
Engine Lubrication performance System.pdfEngine Lubrication performance System.pdf
Engine Lubrication performance System.pdf
 
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
 
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
5214-1693458878915-Unit 6 2023 to 2024 academic year assignment (AutoRecovere...
 
Understanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine LearningUnderstanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine Learning
 
International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...International Conference on NLP, Artificial Intelligence, Machine Learning an...
International Conference on NLP, Artificial Intelligence, Machine Learning an...
 
Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...Comparative analysis between traditional aquaponics and reconstructed aquapon...
Comparative analysis between traditional aquaponics and reconstructed aquapon...
 
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.pptUnit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
 
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball playEric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
Eric Nizeyimana's document 2006 from gicumbi to ttc nyamata handball play
 
Computational Engineering IITH Presentation
Computational Engineering IITH PresentationComputational Engineering IITH Presentation
Computational Engineering IITH Presentation
 
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样官方认证美国密歇根州立大学毕业证学位证书原版一模一样
官方认证美国密歇根州立大学毕业证学位证书原版一模一样
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
 
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
 
Engineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdfEngineering Drawings Lecture Detail Drawings 2014.pdf
Engineering Drawings Lecture Detail Drawings 2014.pdf
 
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptxML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
 
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELDEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
 
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
 
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...
 
Question paper of renewable energy sources
Question paper of renewable energy sourcesQuestion paper of renewable energy sources
Question paper of renewable energy sources
 
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
 

Module 3 INTERNET OF THINGS

  • 1. Dr Mallikarjunaswamy N J 1 INTERNET OF THINGS MODULE-3 By Dr. Mallikarjunaswamy N J
  • 2. IP as the IoT Network Layer:  The Business Case for IP  The Need for Optimization  Optimizing IP for IoT  Profiles and Compliances Dr Mallikarjunaswamy N J 2
  • 3. The Key Advantages of Internet Protocol  1. Open and standards-based:  2. Versatile:  3. Ubiquitous:  4. Scalable:  5. Manageable and highly secure:  6. Stable and resilient:  7. Consumers’ market adoption:  8. The innovation factor: Dr Mallikarjunaswamy N J 3
  • 4. Adoption or Adaptation of the Internet Protocol:  Adaptation means application layered gateways (ALGs) must be implemented to ensure the translation between non-IP and IP layers.  Adoption involves replacing all non-IP layers with their IP layer counterparts, simplifying the deployment model and operations.  Supervisory control and data acquisition (SCADA) applications are typical examples of vertical market deployments that operate both the IP adaptation model and the adoption model.  SCADA is an automation control system for remote monitoring and control of equipment.  Implementations that make use of IP adaptation have SCADA devices attached through serial interfaces to a gateway tunneling or translating the traffic.  With the IP adoption model, SCADA devices are attached via Ethernet to switches and routers.  Another example is a ZigBee solution that runs a non-IP stack between devices and a ZigBee gateway that forwards traffic to an application server.  A ZigBee gateway often acts as a translator between the ZigBee and IP protocol stacks. Dr Mallikarjunaswamy N J 4
  • 5. which model is best suited for last-mile connectivity:  Bidirectional versus unidirectional data flow:  Overhead for last-mile communications paths:  Data flow model:  Network diversity: Dr Mallikarjunaswamy N J 5
  • 6. The Need for Optimization:  Constrained Nodes:  IoT node may be required to communicate through an unreliable path.  power consumption is a key characteristic of constrained nodes.  Many IoT devices are battery powered, with lifetime battery requirements varying from a few months to 10+ years.  This drives the selection of networking technologies since high-speed ones, such as Ethernet, Wi-Fi, and cellular, are not (yet) capable of multi-year battery life.  Current capabilities practically allow less than a year for these technologies on battery- powered nodes.  power consumption is much less of a concern on nodes that do not require batteries as an energy source. Dr Mallikarjunaswamy N J 6
  • 7. IoT constrained nodes can be classified as follows: 1. Devices that are very constrained in resources, may communicate infrequently to transmit a few bytes, and may have limited security and management capabilities: 2. Devices with enough power and capacities to implement a stripped downIP stack or non-IP stack: 3. Devices that are similar to generic PCs in terms of computing and power resources but have constrained networking capacities, such as bandwidth: Dr Mallikarjunaswamy N J 7
  • 8. Constrained Networks:  limited by low-power, low-bandwidth links  high latency and a high potential for packet loss  They operate between a few kbps and a few hundred kbps.  unpredictable errors and even loss of connectivity  packet delivery rate (PDR) to oscillate between low and high percentages.  highly stable and fast links are available.  limited by low-power, low-bandwidth links (wireless and wired). Dr Mallikarjunaswamy N J 8
  • 9. IP Versions:  For 20+ years, the IETF has been working on transitioning the Internet  from IP version 4 to IP version 6.  The main driving force has been the lack of address space in IPv4 as the Internet has grown.  IPv6 has a much larger range of addresses that should not be exhausted for the foreseeable future.  Today, both versions of IP run over the Internet, but most traffic is still IPv4 based.  A variety of factors dictate whether IPv4, IPv6, or both can be used in an IoT solution.  Most often these factors include a legacy protocol or technology that supports only IPv4. Dr Mallikarjunaswamy N J 9
  • 10. The following are some of the main factors applicable to IPv4 and IPv6 support in an IoT solution:  Application Protocol:  Cellular Provider and Technology:  Serial Communications:  IPv6 Adaptation Layer: Dr Mallikarjunaswamy N J 10
  • 11. IPv6 Adaptation Layer: Optimizing IP for IoT: Dr Mallikarjunaswamy N J 11
  • 12. From 6LoWPAN to 6Lo: Dr Mallikarjunaswamy N J 12
  • 14. Figure shows the sub headers related to compression, fragmentation, and mesh addressing. Dr Mallikarjunaswamy N J 14
  • 16. Fragmentation:  The maximum transmission unit (MTU)for an IPv6 network must be at least 1280 bytes.  The term MTU defines the size of the largest protocol data unit that can be passed.  For IEEE 802.15.4, 127 bytes is the MTU.  In IPv6, with a much larger MTU, is carried inside the 802.15.4 frame with a much smaller one.  Toremedy this situation, large IPv6 packets must be fragmented across multiple 802.15.4 frames at Layer 2. Dr Mallikarjunaswamy N J 16
  • 17. Fragmentation  The fragment header utilized by 6LoWPAN is composed of three primary fields:  Datagram Size, Datagram Tag, and Datagram Offset.  The 1-byte Datagram Size field specifies the total size of the unfragmented payload.  Datagram Tag identifies the set of fragments for a payload.  Finally, the Datagram Offset field delineates how far into apayload a particular fragment occurs.  Figure provides an overview of a 6LoWPAN fragmentation header. Dr Mallikarjunaswamy N J 17
  • 18. 6lOWPAN Fragmentation Header Dr Mallikarjunaswamy N J 18
  • 20. Mesh Addressing:  The purpose of the 6LoWPAN mesh addressing function is to forward packets over multiple hops.  Three fields are defined for this header: Hop Limit, Source Address, and Destination Address.  hop limit for mesh addressing also provides an upper limit on how many times the frame can be forwarded.  Each hop decrements this value by 1 as it is forwarded.  Once the value hits 0, it is dropped and no longer forwarded. Dr Mallikarjunaswamy N J 20
  • 21. 6LoWPAN Mesh Addressing Header Dr Mallikarjunaswamy N J 21
  • 22. 6TiSCH:  IEEE 802.15.4e, Time-Slotted Channel Hopping (TSCH), is an add-on to the Media Access Control (MAC) portion of the IEEE 802.15.4 standard, with direct inheritance from other standards, such as WirelessHART and ISA100.11a.  Devices implementing IEEE 802.15.4e TSCH communicate by following a Time Division Multiple Access (TDMA) schedule.  An allocation of a unit of bandwidth or time slot is scheduled between neighbor nodes. Dr Mallikarjunaswamy N J 22
  • 23. The 6TiSCH architecture defines four schedule management mechanisms:  Static scheduling: (Slotted aloha)  Neighbor-to-neighbor scheduling: (add and delete cells)  Remote monitoring and scheduling management: (management entity responsible to allocate time slots )  Hop-by-hop scheduling: (source node is responsible to allocate time slots & resources) Dr Mallikarjunaswamy N J 23
  • 24. four schedule management mechanisms: Dr Mallikarjunaswamy N J 24
  • 25. There are three 6TiSCH forwarding models:  Track Forwarding (TF):  A “track” in this model is a unidirectional path between a source and a destination.  Fragment forwarding (FF):  IPv6 packets can get fragmented at source node and reassemble at des.  IPv6 Forwarding (6F):  Maintains IPv6 routing table to give priority to the pkts(QOS) and to avoid collision of pkts(RED). Dr Mallikarjunaswamy N J 25
  • 26. RPL:  RPL (Routing Protocol for Low Power and Lossy Networks ):  In an RPL network, each node acts as a router and becomes part of a mesh network.  Ø Routing is performed at the IP layer.  Ø Each node examines every received IPv6 packet anddetermines the next-hop destination based on the information contained in the IPv6 header.  Ø Noinformation from the MAC-layer header is needed to perform next-hop determination. Dr Mallikarjunaswamy N J 26
  • 27. The protocol defines two modes:  Storing mode:  Non-storing mode: Dr Mallikarjunaswamy N J 27
  • 29. RPL (Routing Protocol for Low Power and Lossy Networks ): Dr Mallikarjunaswamy N J 29
  • 30. DAG and DODAG Comparison Dr Mallikarjunaswamy N J 30
  • 31. Figure shows how DAO and DIO messages move both up and down the DODAG, depending on the exact message type. Dr Mallikarjunaswamy N J 31
  • 32. DIO & DAO Dr Mallikarjunaswamy N J 32
  • 33. RPL Headers:  Specific network layer headers are defined for datagrams being forwarded within an RPL domain.  Ø One of the headers is standardized in RFC 6553, “The Routing Protocol for Low- Power and Lossy Networks (RPL) Option for Carrying RPL Information in Data- Plane Datagrams,” and the other is discussed in RFC 6554, “An IPv6 Routing Header for Source Routes with the Routing Protocol for Low-Power and Lossy Networks  The RPL option is carried in the IPv6 Hop-by-Hop header.  Ø The purpose of this header is to leverage data-plane packets for loop detection in a RPL instance.  Ø DODAGs only have single paths and should be loop free.  Ø RFC 6554 specifies the Source Routing Header (SRH) for use between RPL routers.  Dr Mallikarjunaswamy N J 33
  • 34. Metrics: (RPL Metrics) 1. Expected Transmission Count (ETX): 2. Hop Count: (higher hop counts) 3. Latency: (low Latency) 4. Link Quality Level: (high level of quality) 5. Link Color: (link more or less desirable) 6. Node State and Attribute: (high workload & CPU) 7. Node Energy: (low power) 8. Throughput: (maximum)Dr Mallikarjunaswamy N J 34
  • 35. Authentication and Encryption on Constrained Nodes:  the Authentication and Authorization for Constrained Environments (ACE) working group is tasked with evaluating the applicability of existing authentication and authorization protocols and documenting their suitability for certain constrained-environment use cases.  Ø Once the candidate solutions are validated, the ACE working group will focus its work on CoAP with the Datagram Transport Layer Security (DTLS) protocol.  Ø The ACE working group expects to produce a standardized solution for authentication and authorization that enables authorized access (Get, Put, Post, Delete) to resources identified by a URI and hosted on a resource server in constrained environments. Dr Mallikarjunaswamy N J 35
  • 36. DICE:  Ø New generations of constrained nodes implementing an IP stack over constrained access networks are expected to run an optimized IP protocol stack.  Ø For example, when implementing UDP at the transport layer, the IETF Constrained Application Protocol (CoAP) should be used at the application layer.  Ø In constrained environments secured by DTLS, CoAP can be used to control resources on a device. Dr Mallikarjunaswamy N J 36
  • 37. Application Protocols for IoT  This chapter focuses on how higher-layer IoT protocols are transported. Specifically, this chapter includes the following sections:  The Transport Layer:  IP-based networks use either TCP or UDP.  With the TCP/IP protocol, two main protocols are specified for the transport layer:  Transmission Control Protocol (TCP):  User Datagram Protocol (UDP): Dr Mallikarjunaswamy N J 37
  • 38. IoT Application Transport Methods: 1. Application layer protocol not present:  Lower layers transport data so application layer not needed 2. Supervisory control and data acquisition (SCADA):  Monitoring and controlling remote physical equipment 3 Generic web-based protocols: (wifi, Ethernet, etc ) 4. IoT application layer protocols: (MQTT)  Reduces number of connection b/w peripheral devices Dr Mallikarjunaswamy N J 38
  • 39. MQTT: Message Queuing Telemetry Transport Dr Mallikarjunaswamy N J 39
  • 40. Dr Mallikarjunaswamy N J 40 MQTT: Message Queuing Telemetry Transport