SDN PROJECTS

In the contemporary years, there are many projects emerging in the domain of Software-Defined Networking (SDN). Along with a short explanation and major aims, we provide numerous SDN projects that are efficient and appropriate for research students:

  1. SDN-Based Network Slicing for 5G Networks

Aim: Specifically, in 5G networks, deploy dynamic network slicing for resource enhancement through the utilization of SDN.

Explanation:

  • To develop a multi-domain network topology, aim to employ Mininet.
  • Mainly, in an SDN controller such as ONOS, OpenDaylight, construct a network slicing application.
  • In order to allot resources dynamically to every slice, focus on implementing OpenFlow rules.

Evaluation Metrics: Bandwidth Allocation, Resource Utilization, Slice Latency.

  1. Traffic Engineering with Segment Routing in SDN Networks

Aim: To enhance traffic engineering in SDN networks, it is appreciable to deploy Segment Routing (SR).

Explanation:

  • In Mininet, configure an SDN network topology.
  • In an SDN controller like OpenDaylight, ONOS, construct a Segment Routing module.
  • To focus on congestion in terms of latency and bandwidth necessities, implement traffic engineering strategies.

Evaluation Metrics: Bandwidth, Path Utilization, Latency.

  1. Machine Learning-Based Intrusion Detection System in SDN

Aim: In an SDN network, apply an Intrusion Detection System (IDS) by means of employing machine learning.

Explanation:

  • In Mininet, arrange an SDN network.
  • An IDS module has to be created in an SDN controller such as POX, Ryu.
  • To categorize normal vs. malicious traffic, instruct a machine learning framework through the utilization of flow statistics.

Evaluation Metrics: Mitigation Time, Detection Rate, False Positives.

  1. Multi-Controller Coordination and Load Balancing in SDN

Aim: The main goal of this study is to deploy a multi-controller infrastructure and assess controller load balancing.

Explanation:

  • Aim to implement numerous SDN controllers like OpenDaylight, Ryu, ONOS.
  • To evaluate controller organization and load balancing, construct a Mininet topology.
  • It is appreciable to assess various controller placement methods and their influence on effectiveness.

Evaluation Metrics: Failover Time, Controller Latency, Scalability.

  1. Programmable Data Plane with P4 and SDN

Aim: Through employing SDN and P4 language, apply a programmable data plane.

Explanation:

  • By means of BMv2 (P4 software switch), develop a Mininet network.
  • Mainly, for convention packet forwarding, write a P4 program.
  • Through an SDN like OpenDaylight, ONOS, it is better to regulate the P4 switch.

Evaluation Metrics:  Flexibility, Packet Processing Latency, Throughput.

  1. SDN-Based Network Function Virtualization (NFV)

Aim: A network function virtualization model has to be deployed by means of utilizing SDN.

Explanation:

  • To develop a virtual network platform, employ Mininet.
  • By utilizing Docker containers, implement virtual network functions (VNFs).
  • Through an SDN controller, regulate and arrange VNFs.

Evaluation Metrics: Resource Utilization, VNF Deployment Time, Latency.

  1. Anomaly Detection and Mitigation in SDN Networks

Aim: By employing flow statistics that are gathered through an SDN controller, construct an anomaly identification and mitigation model.

Explanation:

  • To simulate a network topology, employ Mininet.
  • In an SDN controller such as Ryu, POX, focus on creating an anomaly identification module.
  • In order to detect and prevent abnormal congestion, implement machine learning frameworks.

Evaluation Metrics: Network Throughput, Detection Rate, False Positives.

  1. Intent-Based Networking for SDN Networks

Aim: Through the utilization of SDN, deploy an intent-based networking framework.

Explanation:

  • Aim to develop a Mininet network topology.
  • Mainly, in the SDN controller like ONOS, OpenDaylight, construct an intent-related application.
  • Through the controller, convert extensive intents into OpenFlow rules.

Evaluation Metrics: Latency, Intent Compliance Rate, Policy Enforcement Time.

  1. QoS Management with SDN for IoT Networks

Aim: For traffic precedence in IoT networks, apply a QoS management system by utilizing SDN.

Explanation:

  • Specifically, in Mininet, focus on developing a network topology.
  • In the SDN controller, construct a traffic categorization application.
  • To focus on congestion, implement OpenFlow rules (For instance., Sensors, VoIP, Video).

Evaluation Metrics: Jitter, Bandwidth, Latency, Packet Loss.

  1. Blockchain-Based Security Framework for SDN Networks

Aim: For protecting SDN networks, deploy a blockchain-related model.

Explanation:

  • To simulate a multi-domain SDN network, aim to utilize Mininet.
  • For SDN devices, apply a blockchain-related identity management framework.
  • To protect the controller-switch interaction, focus on creating a trust management module.

Evaluation Metrics: Scalability, Authentication Time, Latency.

  1. Edge Computing with SDN and NFV

Aim: For resource enhancement and low-delay applications, apply an edge computing infrastructure by employing NFV and SDN.

Explanation:

  • By means of edge nodes (For instance Virtual Machines, Raspberry Pi), develop a network topology.
  • In the SDN controller, construct a traffic routing application in order to direct congestion to edge nodes dynamically.
  • Through the utilization of Docker containers, implement virtual network functions at the edge.

Evaluation Metrics: Application Response Time, Latency, CPU/Memory Utilization.

  1. SDN-Based Traffic Monitoring and Visualization

Aim: In an SDN network, track and visualize network congestion.

Explanation:

  • By means of sFlow or NetFlow assistance, configure an SDN controller.
  • Focus on gathering network congestion data and conserve it in a database.
  • For actual-time visualization, create a web-related dashboard.

Evaluation Metrics: Bandwidth Usage, Traffic Volumes, Flow Count.

  1. Dynamic Network Access Control with OpenFlow

Aim: Through utilizing OpenFlow rules, apply dynamic network access control.

Explanation:

  • In Mininet, develop a network topology.
  • In an SDN controller like Ryu, POX, build a network access control application.
  • On the basis of predetermined strategies, implement flow regulations to dynamically permit/prevent user access.

Evaluation Metrics: Accuracy, Policy Compliance Rate, Access Control Latency.

What kind of programming languages are used in developing Software Defined Networking SDN?

Several programming languages play a crucial role in creating Software Defined Networking (SDN). The following is an extensive collection of suitable programming languages and their standard applications in SDN:

  1. Controller Development and Applications

Python

  • Controllers: POX, Ryu
  • Applications:
  • Load balancing, traffic engineering, network tracking, and safety applications.
  • Characteristics:
  • Python contains basic syntax and offers a valuable collection of networking libraries.
  • Specifically, for modelling and scripting, it is perfect and efficient.

Instance (Ryu Controller – Simple L2 Switch):

# ryu_simple_switch.py

from ryu.base import app_manager

from ryu.controller import ofp_event

from ryu.controller.handler import MAIN_DISPATCHER, set_ev_cls

from ryu.ofproto import ofproto_v1_3

from ryu.lib.packet import packet, ethernet

class SimpleSwitch(app_manager.RyuApp):

OFP_VERSIONS = [ofproto_v1_3.OFP_VERSION]

def __init__(self, *args, **kwargs):

super(SimpleSwitch, self).__init__(*args, **kwargs)

self.mac_to_port = {}

@set_ev_cls(ofp_event.EventOFPSwitchFeatures, MAIN_DISPATCHER)

def switch_features_handler(self, ev):

datapath = ev.msg.datapath

ofproto = datapath.ofproto

parser = datapath.ofproto_parser

match = parser.OFPMatch()

actions = [parser.OFPActionOutput(ofproto.OFPP_CONTROLLER, ofproto.OFPCML_NO_BUFFER)]

self.add_flow(datapath, 0, match, actions)

def add_flow(self, datapath, priority, match, actions, buffer_id=None):

ofproto = datapath.ofproto

parser = datapath.ofproto_parser

inst = [parser.OFPInstructionActions(ofproto.OFPIT_APPLY_ACTIONS, actions)]

mod = parser.OFPFlowMod(datapath=datapath, priority=priority, match=match, instructions=inst)

datapath.send_msg(mod)

@set_ev_cls(ofp_event.EventOFPPacketIn, MAIN_DISPATCHER)

def packet_in_handler(self, ev):

msg = ev.msg

datapath = msg.datapath

ofproto = datapath.ofproto

parser = datapath.ofproto_parser

in_port = msg.match[‘in_port’]

pkt = packet.Packet(msg.data)

eth = pkt.get_protocols(ethernet.ethernet)[0]

dst = eth.dst

src = eth.src

dpid = datapath.id

self.mac_to_port.setdefault(dpid, {})

self.mac_to_port[dpid][src] = in_port

if dst in self.mac_to_port[dpid]:

out_port = self.mac_to_port[dpid][dst]

else:

out_port = ofproto.OFPP_FLOOD

actions = [parser.OFPActionOutput(out_port)]

match = parser.OFPMatch(in_port=in_port, eth_dst=dst)

self.add_flow(datapath, 1, match, actions)

data = None

if msg.buffer_id == ofproto.OFP_NO_BUFFER:

data = msg.data

out = parser.OFPPacketOut(datapath=datapath, buffer_id=msg.buffer_id, in_port=in_port, actions=actions, data=data)

datapath.send_msg(out)

Java

  • Controllers: ONOS, OpenDaylight (ODL), Floodlight
  • Applications:
  • The major applications are topology discovery, intent-based networking, network arrangement, flow control.
  • Characteristics:
  • Java is described as an object-oriented, scalable programming language. It is suitable for complicated SDN controllers.

Instance (OpenDaylight – Simple Network App):

// Example Java application for OpenDaylight

import org.opendaylight.controller.md.sal.binding.api.DataBroker;

import org.opendaylight.controller.md.sal.binding.api.WriteTransaction;

import org.opendaylight.controller.md.sal.common.api.data.LogicalDatastoreType;

import org.opendaylight.yang.gen.v1.urn.opendaylight.inventory.rev130819.nodes.Node;

import org.opendaylight.yang.gen.v1.urn.opendaylight.inventory.rev130819.nodes.NodeKey;

import org.opendaylight.yangtools.yang.binding.InstanceIdentifier;

public class SimpleNetworkApp {

private final DataBroker dataBroker;

public SimpleNetworkApp(DataBroker dataBroker) {

this.dataBroker = dataBroker;

}

public void createNode(String nodeId) {

InstanceIdentifier<Node> nodeIID = InstanceIdentifier.builder(Nodes.class)

.child(Node.class, new NodeKey(new NodeId(nodeId)))

.build();

NodeBuilder nodeBuilder = new NodeBuilder();

nodeBuilder.setNodeId(new NodeId(nodeId));

WriteTransaction tx = dataBroker.newWriteOnlyTransaction();

tx.put(LogicalDatastoreType.CONFIGURATION, nodeIID, nodeBuilder.build());

tx.commit();

}

}

C/C++

  • Controllers: Trema, NOX
  • Applications:
  • High performance (for instance., switch management) is needed for low-level network applications.
  • Characteristics:
  • C/C++ is efficient and perfect for high-efficiency controllers and applications.
  • It facilitates minimal runtime overhead and direct memory management.

Instance (NOX Module):

#include “nox/coreapps.hh”

#include “nox/core.hh”

#include “nox/data.hh”

#include “nox/netmatch.hh”

class SimpleApp : public coreapp {

public:

SimpleApp() : coreapp(“SimpleApp”) {}

void install() {

match_rule rule;

rule.add_match(“dl_type”, ETHERTYPE_IP);

add_packet_handler(rule, boost::bind(&SimpleApp::handle_packet, this, _1));

}

void handle_packet(const match_rule &rule) {

// Packet handling logic

}

};

register_application(SimpleApp, “SimpleApp”);

  Go

  • Controllers: Kune-OVN, CORD, ONOS (partially)
  • Applications:
  • The key applications are network controllers and plugins for Kubernetes.
  • Characteristics:
  • Generally, Go assists for concurrency and lightweight goroutines.

  Instance (Go-based SDN Application):

package main

import (

“fmt”

“net/http”

)

func handleRequest(w http.ResponseWriter, r *http.Request) {

fmt.Fprintf(w, “Hello, SDN!”)

}

func main() {

http.HandleFunc(“/”, handleRequest)

http.ListenAndServe(“:8080”, nil)

}

  1. Programmable Data Planes

P4

  • Utility: It is employed in programming network packet processing pipelines.
  • Characteristics:
  • P4 is described as target-agnostic and protocol-independent.
  • Along with software targets and programmable switches, P4 is utilized.

Instance (P4 L2 Switch – basic.p4):

header ethernet_t {

bit<48> dstAddr;

bit<48> srcAddr;

bit<16> etherType;

}

struct headers {

ethernet_t ethernet;

}

parser MyParser(packet_in pkt, out headers hdr) {

state start {

pkt.extract(hdr.ethernet);

transition accept;

}

}

control MyIngress(inout headers hdr) {

apply {

if (hdr.ethernet.etherType == 0x0800) {

hdr.ethernet.dstAddr = hdr.ethernet.srcAddr;

}

}

}

control MyDeparser(packet_out pkt, in headers hdr) {

apply {

pkt.emit(hdr.ethernet);

}

}

control MySwitch(inout headers hdr) {

MyIngress() my_ingress;

MyDeparser() my_deparser;

apply {

my_ingress.apply();

my_deparser.apply();

}

}

MySwitch() main;

  C

  • Utility: By means of DPDK and XDP/eBPF, C is used in programming packet processing.
  • Characteristics:
  • C is a low-level, high-efficiency packet processing programming language.

Instance (eBPF XDP Program):

#include <linux/bpf.h>

#include <bpf/bpf_helpers.h>

 

SEC(“xdp”)

int xdp_prog_simple(struct xdp_md *ctx) {

void *data_end = (void *)(long)ctx->data_end;

void *data = (void *)(long)ctx->data;

 

struct ethhdr *eth = data;

if (eth + 1 > data_end)

return XDP_DROP;

 

if (eth->h_proto == bpf_htons(ETH_P_IP))

return XDP_PASS;

 

return XDP_DROP;

}

 

char _license[] SEC(“license”) = “GPL”;

  1. Network Orchestration and Configuration

YAML/JSON

  • Utility: It is employed in network arrangement documents, data frameworks, and API explanations.
  • Characteristics:
  • YAML/JSON is assistive among numerous environments, and it is examined as human-readable.

Instance (Kubernetes Network Policy – YAML):

apiVersion: networking.k8s.io/v1

kind: NetworkPolicy

metadata:

name: allow-frontend

namespace: my-app

spec:

podSelector:

matchLabels:

role: frontend

policyTypes:

– Ingress

ingress:

– from:

– podSelector:

matchLabels:

role: backend

YANG

  • Utility: For network arrangement, YANG is suitable and is considered as a data modelling language.
  • Characteristics:
  • YANG is assisted by NETCONF and standardized by IETF.
  • For OpenDaylight and other controllers, it describes data frameworks.

SDN Projects And Research Topics

SDN Projects For Research Students

Acquiring the appropriate SDN Projects For Research Students from professionals is highly recommended. Reach out to phdtopic.com for assistance, as we boast a team of top-notch experts and researchers who can enhance the quality of your work. Contact us for more info in this field.

  1. An integrated framework for software defined networking, caching, and computing
  2. Wildcard rules caching and cache replacement algorithms in software-defined networking
  3. Virtual function placement and traffic steering in flexible and dynamic software defined networks
  4. Attacks against network functions virtualization and software-defined networking: State-of-the-art
  5. Software defined networking for resilient communications in smart grid active distribution networks
  6. Secure group communications in vehicular networks: A software-defined network-enabled architecture and solution
  7. An integrated framework for software defined networking, caching, and computing
  8. Wildcard rules caching and cache replacement algorithms in software-defined networking
  9. Software defined networking for resilient communications in smart grid active distribution networks
  10. Secure group communications in vehicular networks: A software-defined network-enabled architecture and solution
  11. Cyber-sustainability of software-defined networks based on situational management
  12. SGS: Safe-guard scheme for protecting control plane against DDoS attacks in software-defined networking
  13. Enhancing the security of blockchain-based software defined networking through trust-based traffic fusion and filtration
  14. Software defined networking-based traffic engineering for data center networks
  15. Network-as-a-service in software-defined networks for end-to-end QoS provisioning
  16. Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks
  17. A new machine learning-based collaborative DDoS mitigation mechanism in software-defined network
  18. Towards QoE-driven multimedia service negotiation and path optimization with software defined networking
  19. Enabling software-defined networking for wireless mesh networks in smart environments
  20. On the load balanced controller placement problem in Software defined networks