Course Name: Internet of Things

Course Code: ECO501

Dr. Sanjay Kumar

Faculty (IF) of Electronics Engineering
Department of Electronics Engineering,
Indian Institute of Technology (ISM) Dhanbad
Website: www.sanjaysihag.com
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 Module 4:

Introduction to Software Defined Networking (SDN); SDN for IoT, Data

Handling and Analytics, Cloud Computing.

Study material will be available on: www.sanjaysihag.com/teaching

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 Introduction to SDN

Software-Defined Networking (SDN) is an approach to how we implement networks, which matters because it
impacts the pace of innovation.

SDN does not directly address any of the technical challenges of routing, congestion control, traffic engineering,
security, mobility, reliability, or real-time communication, but it does open new opportunities to create and
deploy innovative solutions to these and similar problems.

A network in which the control plane is physically separate from the forwarding plane, and a single
control plane controls several forwarding devices.

Network Virtualization

The first widely-adopted use case for SDN was to virtualize the network. Virtual networks, including both
Virtual Private Networks (VPNs) and Virtual Local Area Networks (VLANs).

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 Open Shortest Path First (OSPF) is a routing protocol that's used to
direct traffic on IP networks.
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 Introduction to SDN

A typical network virtualization system looks

similar to show in Fig. The Network
Virtualization Controller is an SDN controller
that exposes a northbound API by which
networks can be created, monitored and
modified.

It connects to virtual switches running on

hosts-in this case, hypervisors supporting
virtual machines.

An example network virtualization system. Virtual networks are created by programming

wherein the virtual switches to forward
packets, with appropriate encapsulation, from
host to host across the underlay network.

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 Basic Architecture of SDN

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 Architectural Components
SDN Application

SDN Applications are programs that explicitly, directly, and programmatically communicate their network
requirements and desired network behavior to the SDN Controller via a northbound interface (NBI).

In addition, they may consume an abstracted view of the network for their internal decision-making purposes.
An SDN Application consists of one SDN Application Logic and one or more NBI Drivers.

SDN Applications may themselves expose another layer of abstracted network control, thus offering one or more
higher-level NBIs through respective NBI agents.

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 Architectural Components

SDN Controller

The SDN Controller is a logically centralized entity in charge of (i) translating the requirements from the SDN
Application layer down to the SDN Data paths and (ii) providing the SDN Applications with an abstract view of
the network.

An SDN Controller consists of one or more NBI Agents, the SDN Control Logic, and the Control to Data-Plane
Interface (CDPI) driver.

Definition as a logically centralized entity neither prescribes nor precludes implementation details such as the
federation of multiple controllers, the hierarchical connection of controllers, communication interfaces between
controllers, nor virtualization or slicing of network resources.

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 Architectural Components
SDN Datapath

The SDN Datapath is a logical network device that exposes visibility and uncontested control over its
advertised forwarding and data processing capabilities. The logical representation may encompass all or a
subset of the physical substrate resources.

An SDN Datapath comprises a CDPI agent and a set of one or more traffic forwarding engines and zero or
more traffic processing functions. These engines and functions may include simple forwarding between the
datapath’s external interfaces or internal traffic processing or termination functions. One or more SDN
Datapaths may be contained in a single (physical) network element-an integrated physical combination of
communications resources, managed as a unit.

An SDN Datapath may also be defined across multiple physical network elements. This logical definition
neither prescribes nor precludes implementation details such as the logical to physical mapping, management of
shared physical resources, virtualization or slicing of the SDN Datapath, interoperability with non-SDN
networking, nor the data processing functionality, which can include OSI layer 4-7 functions.

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 Architectural Components

SDN Control to Data-Plane Interface (CDPI)

The SDN CDPI is the interface defined between an SDN Controller and an SDN Datapath, which provides at
least (i) programmatic control of all forwarding operations, (ii) capabilities advertisement, (iii) statistics
reporting, and (iv) event notification. One value of SDN lies in the expectation that the CDPI is implemented in
an open, vendor-neutral and interoperable way.

SDN Northbound Interfaces (NBI)

SDN NBIs are interfaces between SDN Applications and SDN Controllers and typically provide abstract
network views and enable direct expression of network behavior and requirements.

This may occur at any level of abstraction (latitude) and across different sets of functionality (longitude). One
value of SDN lies in the expectation that these interfaces are implemented in an open, vendor-neutral and
interoperable way.

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 Basic Architecture of SDN
SDN is an approach to building networks that favors programmable commodity hardware, with the intelligence
that controls packet forwarding and other network operations implemented in software.

Realizing such a design is independent of any particular protocol stack, but instead requires a set of open
Application Programming Interface (APIs) and a new collection of software components that support those APIs.

Overall architecture of the SDN software stack

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 Basic Architecture of SDN

Figures include two open interfaces: one between the Control Apps and the Network OS, and a second between
the Network OS and the underlying programmable switches.

These two interfaces are depicted as “API shims” in Fig, and in the context of the exemplar components,
correspond to a combination of gNMI, gNOI and Flow Objective in the first case, and a combination of gNMI,
gNOI and either P4Runtime or OpenFlow in the second case. gRPC, an open source remote procedure call
framework, is shown as the transport protocol for these APIs-an implementation choice, but one that we will
generally assume from here on. (Note that OpenFlow, unlike the other protocols, does not run over gRPC.)

gNMI stands for gRPC Network Management Interface. It's a

protocol that uses Google's remote procedure call (RPC) The gNMI service defines operations for configuration
framework, gRPC, to manage network devices. gNMI allows management, operational state retrieval, and bulk data
users to configure and retrieve operational data from network collection through streaming telemetry. gNOI only
devices using model-driven capabilities. allows the adoption of services that a device supports.

gNOI stands for Google Remote Procedure Call (gRPC)

Network Operations Interface. It's a collection of
microservices that each correspond to a set of operations.

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 Switch vs Host Implementation

End-to-End Perspective of a Software-Defined Network, including the end hosts and the Virtual Machines (VMs) they host.

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 Switch vs Host Implementation

Figure shows a perspective by focusing on an end-to-end path through the network, connecting Virtual Machines
(VMs).

This perspective highlights two important aspects of the system. The first re-enforces the point we’ve been
making: that the Network OS (e.g., ONOS) is network-wide, while the Switch OS (e.g., Stratum) is per-switch.

The second is that part of the SDN software stack runs on the end hosts. In particular, there is a Virtual Switch
(vSwitch)-typically implemented in software as part of the hypervisor running on the server that is responsible for
forwarding packets to and from the VMs.

Just like a physical switch, the vSwitch forwards packets from input port to output port, but these are virtual ports
connected to VMs (or containers) rather than physical ports connected to physical machines.

In the case of both chips, a pair of P4 programs defines the forwarding pipeline. The first (forward.p4) specifies
the forwarding behavior. The second (arch.p4) specifies the logical architecture of the target forwarding chip. The
P4 compiler generates target files that are loaded into both the Network OS and the switch.

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 SDN for IoT

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 SDN for IoT

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 SDN for IoT

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 SDN for IoT

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 SDN for IoT

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 SDN for IoT

SNMP: Simple Network Management Protocol is a standard protocol that allows users to monitor and
manage devices on IP networks.
CLI: Command Line Interface, which is a text-based user interface that allows you to interact with a
computer's operating system by entering commands.
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 SDN for IoT

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 SDN for IoT

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 SDN for IoT

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 SDN for IoT

IoT-on-SDN service and requirement framework with BGP enabled Intra/Inter Autonomous System
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 SDN for IoT

IToSD process and services provisioning framework with DevOps characteristics.

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 SDN for IoT

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 SDN in Data Handling and Analytics
SDN can be used for data handling and analytics in multiple ways, such as:

Network performance: SDN can provide real-time visibility into network performance, which can help organizations
identify and troubleshoot issues.

Network resource control: SDN can help prioritize critical applications and ensure consistent quality of service (QoS).

Network segmentation: SDN can segment different virtual networks within a single physical network, or connect different
physical networks into a single virtual network.

Compliance and policy enforcement: SDN can automate compliance policies and regulations to ensure that network
configurations meet security and regulatory requirements.

Security: SDN can help detect suspicious network activity.

Big data application performance: SDN can help improve the performance of big data applications.

Big data traffic engineering: SDN can help with traffic engineering.

Cross-layer design: SDN can help with cross-layer design.

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 SDN for Big Data Handling and Analytics

SDN can greatly facilitate big data acquisition,

transmission, storage, and processing.

Hadoop is an open source framework based on Java that

manages the storage and processing of large amounts of
data for applications. Hadoop uses distributed storage and
parallel processing to handle big data and analytics jobs,
breaking workloads down into smaller workloads that can
be run at the same time.
Good features of SDN that can benefit big data applications.
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 SDN for Big Data Handling and Analytics

Fig. describe a dynamic traffic engineering system architecture with

3 4 SDN and big data, which consists of four components: a data center
network, an SDN controller, a traffic engineering manager, and big
data applications. In the data center network, there are many servers
and SDN switches/routers, which is considered to be a target network
of the traffic engineering system. The SDN switches/routers in the data
center network report their big traffic data and failure status to the
2 SDN controller through the control/data plane interface. The SDN
controller aggregates and summarizes the collected big traffic data
information, and sends it to the big data applications. Big data
(A data center network) analytics, which leverages analytical methods to obtain insights from
the big traffic data, then gives guidance to the traffic engineering
1
manager, which derives the traffic engineering policies. According to
these traffic engineering policies, the SDN controller changes
switching behavior of the SDN devices by updating their flow tables,
Many servers and SDN and turns on/off devices and links in the data center network to
switches/routers minimize power consumption and link congestion.

Dynamic traffic engineering system architecture with SDN

and big data.
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 SDN for Big Data Handling and Analytics

Cross-layer design with SDN and big data.

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 SDN for Big Data Handling and Analytics

Potential attacks can be launched on the three layers of SDN.

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 SDN for Big Data Handling and Analytics

SDN-based intra- and inter-data-center networks with big data.

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 Thank You!!!

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