Software Defined Networking for IoT

Internet of things (IoT) poses challenges that are different from traditional Internet in different aspects — heterogeneous communication technologies, application-specific QoS requirements, massive influx of data, and unpredictable network conditions. On the other hand, software-defined networking (SDN) is a promising approach to control the network in a unified manner using rule-based management. The abstractions provided by SDN enable holistic control of the network using high-level policies, without being concerned about low-level configuration issues. Hence, it is advantageous to address the heterogeneity and application-specific requirements of IoT.

We study the application and impact of softwarization on IoT networks from different perspectives: access networks, edge networks, and wide area networks. We also develop and analyze models to characterize the performance of softwarized networks.


Software Defined Access Networks

Situation-Aware Protocol Switching

In this work, we propose a situation-aware protocol switching scheme in software-defined wireless sensor networks (SDWSNs). The proposed scheme consists of two phases — determination of an appropriate routing protocol and deployment of the protocol at the nodes.

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Software-Defined WSN Prototype

In this work, we propose a software-defined wireless sensor network (Soft-WSN) architecture, which enables the sensor devices/networks to be configured in real time for application-aware service provisioning in IoT.

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Software Defined Edge Networks

Flow-table Overflow Reduction

In this work, we attempt to address the question “Is it possible to reduce flow-table overflow in an SDIoT network, while simultaneously preserving the QoS of IoT flows?”

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Task Offloading

In this work, we present a dynamic task offloading scheme in software-defined access-networks (SDANs) where IoT devices are connected to fog computing nodes by multi-hop IoT access-points.

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Traffic Engineering with Minimum APs

In this work, we attempt to address these questions: (a) Can we place the flow-rules at APs in an adaptive manner according to the movement of the users in the network? (b) Can we utilize the existing rule-space to deploy flow-rules, while minimizing the number of activated APs in the network?

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Q-Flag: QoS-Aware Flow-Rule Aggregation in Software-Defined IoT Networks

In this paper, we address the problem of flow-rule overflow in software-defined IoT networks, by proposing a QoS-aware flow-rule aggregation scheme to achieve satisfactory trade-off among flow-rule compression and its impact on the QoS.

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Blockchain-Enabled SDN for Securing Fog-Based Resource-Constrained IoT

Software-Defined Network (SDN) is vital in simplifying the dynamic network characteristics and device management. However, the centralized architecture of SDN opens the scope for malicious attacks on the controllers. To mitigate such attacks in real-time, we propose an SDN architecture for resource-constrained devices in a fog-enabled IoT environment using a private blockchain (pBC) network.

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BIND: Blockchain-Based Flow-Table Partitioning in Distributed Multi-Tenant Software-Defined Networks

This paper presents the problem of flow-table partitioning in distributed multi-tenant software-defined networks (SDNs) having Internet-of-things (IoT) devices. We propose a utility game-based scheme, named BIND, for dynamic flowtable partitioning. To ensure cooperation among the controllers and to avoid monopoly, we introduce the use of a blockchain among the multi-tenant controllers. Additionally, using BIND, we ensure that each controller gets a fair chance for flowrule replacement. Moreover, network sustainability is ensured in BIND, while minimizing the flow-rule replacement in the flowtables and multi-tenant SDN.


FlowMan: QoS-Aware Dynamic Data Flow Management in Software-Defined Networks

This paper presents the problem of data flow management in the presence of heterogeneous flows — elephant and mice flows in software-defined networks (SDNs). We propose a game theory-based heterogeneous data flow management scheme, named FlowMan. In FlowMan, initially, we use a generalized Nash bargaining game to obtain a sub-optimal problem, which is NP-complete in nature. By solving it, we get the Pareto optimal solution for data-rate associated with each switch. Thereafter, we use a heuristic method to decide the flow-association with the switches, distributedly, which, in turn, helps to get a Pareto optimal solution.


M-JAW: Mobility-Based Jamming Avoidance in Wireless Sensor Networks

This paper presents the problem of jamming avoidance for ensuring quality-of-service (QoS) in terms of the network lifetime and overhead in wireless sensor networks (WSNs). We propose a mobility model using Single-Leader-Multiple-Followers Stackelberg game theory to avoid the jamming affected region.


Software Defined Wide Area Networks

Traffic-Aware Routing

In this work, we propose a traffic-aware quality-of-service (QoS) routing scheme in software-defined internet of things (SDIoT) network. The proposed scheme exploits the unique features of software-defined networking (SDN), such as flow-based nature, and network flexibility, in order to fulfill QoS requirements of each flow in the network.

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Minimize Control Overhead

Control overhead is an important issue in softwaredefined network (SDN). In this work, we propose a dynamic traffic engineering scheme to minimize the control overhead at the SDN controller, while minimizing the number of control messages.

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Adaptive Flow-Rule Placement

In this work, we propose an adaptive flow-rule placement scheme, FlowStat, in a software-defined network (SDN) with an aim to provide per-flow statistics to SDN controller while enhancing overall network performance.

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Flow-Rule Aggregation

In this work, we apply the concept of tensor decomposition in order to aggregate flow-rules and improve the available capacity of switches in software defined networking

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Reduce Rule Duplication

In this paper, we address the issue of rule duplication during network updates in software-defined networking. The proposed approach guarantees that highly loaded switches are updated first, and ensures packet-level consistency by implementing a multilevel queuing approach.

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Dynamic Controller Assignment

In this paper, we propose a dynamic controller assignment scheme while considering flow-specific requirements, with an aim to minimize controller response time in softwaredefined networks (SDN). We adopt the concept of FlowVisor, in which a virtualized platform acts as a manager between control- and data planes of SDN architecture.

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Consistent Flow Migration

In this paper, we present a traffic-aware consistent approach for flow migration in Software Defined Networking (SDN). The proposed scheme considers heterogeneous traffic to determine a consistent flow migration schedule. In a large-scale network, majority of traffic flows are latency sensitive.

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Software-Defined Networking for IoTs

In this paper, we provide a comprehensive survey of different SDNbased technologies, which are useful to fulfill the requirements of IoT, from different networking aspects - edge, access, core, and data center networking.

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Data Plane Load Reduction

In this paper, we present a traffic-aware flow migrtion approach, which reduces data plane load in Software Defined Networking (SDN) during a network update. The proposed load reduction strategy prioritizes traffic flows based on QoS demands and aims to avoid link congestion and rule-space overflow during flow migraion.

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Control Plane Load Reduction

In this paper, we propose a scheme to address the problem of load management in the control plane of Software Defined Internet of Things (SDIoT) networks. In SDIoT, multiple controllers are deployed to enhance network scalability. The proposed scheme estimates control plane load based on the mobility and activation model of IoT devices.

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Performance Analysis of Software Defined Networks

Buffer Size Evaluation

In this work, we address the problem of minimum buffer size evaluation of an OpenFlow system in softwaredefined networks (SDNs), while ensuring optimum packet waiting time.

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Probabilistic Performance Bounds

In this work, we propose Markov chain-based analytical model, named AMOPE, for analyzing packet flow through an OpenFlow switch, while defining the probabilistic bounds on performance analysis.

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Software Defined Networks for Vehicular Network

Mobility-Aware Task Offloading

In this paper, we propose a mobility-aware task offloading scheme, named as Soft-VAN, with an aim to minimize task computation delay in a software-defined vehicular network.

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Mobility-Aware Conroller Placement

In this paper, we propose a mobility-aware scheme, named MobiPlace, to address the controller placement problem (CPP) at the Road Side Units (RSUs) in Software-Defined Vehicular Networks (SDVNs). MobiPlace places local controllersat the selected RSUs to reduce the operational delay experiencedin traditional SDVN architecture, where controllers are placed at the cloud.

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