SDN-based Routing Research Articles

Named Multipath Depth-First Search: An SDN-based Routing Strategy for Efficient Failure Handling and Content Delivery in NDN

Information-centric networking (ICN) architectures, such as named data networking (NDN), have emerged as potential solutions for efficiently retrieving and delivering content. However, challenges remain regarding routing scalability, resilience, and caching efficiency. Software-defined networking (SDN) offers opportunities to optimize NDN implementations through centralized control and programmability. In this paper, we propose Named Multipath DFS, an SDN-based routing and caching scheme for NDN networks. NMDFS leverages a centralized controller to pre-compute multipath routes and implement coordinated caching. We evaluate NMDFS on an emulated topology testbed against default NDN and Named-data link state routing. The results demonstrate significant improvements with NMDFS, reducing overhead signalling costs by 94% and 78%, respectively, compared with other schemes. Round-trip latencies for content retrieval were reduced by up to 98%. The SDN controller’s global network view and control are leveraged to optimize content caching through packet loss-driven adaptation and eliminate redundant messaging, leading to substantial performance gains.

Reduced network forwarding with controller enabled named software defined Internet of Mobile Things

Network communication is getting more advanced after massive experimentation and evaluations. Therefore, more devices have been introduced making the traditional network highly complex and difficult to manage. Hence, there is a need to overcome problems being faced by the network for communication during routing or forwarding. Researchers introduced Software Defined Network (SDN) and Named Data Networking (NDN) architectures to cope with the aforementioned issues. SDN decouples the control logic from the data logic. This decoupling provides better manageability and flexibility due to its programmable nature. NDN uses Interest and Data packets that operate only on the required content’s name. It no longer needs the IP addresses. Furthermore, the Internet of Mobile Things (IoMT) is continuously self-configuring and dynamic networks. The nodes in this network are mobile and have arbitrary motions. However, the problem in NDN-IoMT is that each node does packet broadcasting whenever a certain change occurs within the network which creates packet flooding. Therefore, to solve this issue, an optimized forwarding scheme, named Controller Enabled Reduced Forwarding (CERF) is proposed in this paper. CERF is an effective combination of all three domains (i.e. NDN, SDN, IoMT) to get maximum throughput and effectiveness within the network. The proposed CERF scheme mitigates the broadcasting over the network by using forwarding flows generated by the controller node. These flows let only selective nodes forward packets. Different performance metrics are used to evaluate the performance of the proposed scheme against native NDN and SDN-based routing schemes. These evaluations show satisfactory results of the proposed CERF scheme as compared to the others.

SDN-Based Routing Framework for Elephant and Mice Flows Using Unsupervised Machine Learning

Software-defined networks (SDNs) have the capabilities of controlling the efficient movement of data flows through a network to fulfill sufficient flow management and effective usage of network resources. Currently, most data center networks (DCNs) suffer from the exploitation of network resources by large packets (elephant flow) that enter the network at any time, which affects a particular flow (mice flow). Therefore, it is crucial to find a solution for identifying and finding an appropriate routing path in order to improve the network management system. This work proposes a SDN application to find the best path based on the type of flow using network performance metrics. These metrics are used to characterize and identify flows as elephant and mice by utilizing unsupervised machine learning (ML) and the thresholding method. A developed routing algorithm was proposed to select the path based on the type of flow. A validation test was performed by testing the proposed framework using different topologies of the DCN and comparing the performance of a SDN-Ryu controller with that of the proposed framework based on three factors: throughput, bandwidth, and data transfer rate. The results show that 70% of the time, the proposed framework has higher performance for different types of flows.

CBILEM: A novel energy aware mobility handling protocol for SDN based NDN-MANETs

Mobile Ad hoc Network (MANET) is the network where every node is considered mobile. The mobility nature of nodes in the wireless environment is the issue due to which packets are not able to reach from source to destinations and vice versa. Furthermore, Named Data Networks (NDN) is a new Internet architecture in which data transfer is made in terms of named content. This architecture is used in place of conventional Transmission Control Protocol/Internet Protocol. In it, the mobility of producer and consumer is the highlighted problem that results in packet drops and an increased number of retransmissions. Furthermore, Software Defined Networking (SDN) is the approach in which the control plane is separated from the data plane. It takes the functionality of the control plane from each node and gives it to the controller, which calculates the flow tables. However, the integration Software Defined Network with the Mobile Ad hoc Network provides the overall network's vision. To control the mobility issue of nodes, an SDN-based routing protocol, named Controller-Based Intelligent Location and Energy Manager (CBILEM) is proposed. Another contribution of this article is that only nodes with a sufficient amount of battery are allowed to take part in the communication process. It also reduces the problem of sudden unavailability of nodes in the network due to which transmission disruption is minimized. However, the proposed routing protocol considers mobility and energy sufficiency while fulfilling requests. Furthermore, extensive simulations are performed to evaluate the proposed protocol by using the ndnSIM simulator. However, the proposed protocol achieves better performance results as compared to the existing protocols.

LB-OPAR: Load balanced optimized predictive and adaptive routing for cooperative UAV networks

Cooperative ad-hoc UAV networks have been turning into the primary solution set for situations where establishing a communication infrastructure is not feasible. Search-and-rescue after a disaster and intelligence, surveillance, and reconnaissance (ISR) are two examples where the UAV nodes need to send their collected data cooperatively into a central decision maker unit. Recently proposed SDN-based solutions show incredible performance in managing different aspects of such networks. Alas, the routing problem for the highly dynamic UAV networks has not been addressed adequately. An optimal, reliable, and adaptive routing algorithm compatible with the SDN design and highly dynamic nature of such networks is required to improve the network performance. This paper proposes a load-balanced optimized predictive and adaptive routing (LB-OPAR), an SDN-based routing solution for cooperative UAV networks. LB-OPAR is the extension of our recently published routing algorithm (OPAR) that balances the network load and optimizes the network performance in terms of throughput, success rate, and flow completion time (FCT). We analytically model the routing problem in highly dynamic UAV network and propose a lightweight algorithmic solution to find the optimal solution with O(|E|2) time complexity where |E| is the total number of network links. We exhaustively evaluate the proposed algorithm’s performance using ns-3 network simulator. Results show that LB-OPAR outperforms the benchmark algorithms by 20% in FCT, by 30% in flow success rate on average, and up to 400% in throughput.11DISTRIBUTION STATEMENT A: Approved for Public Release; distribution unlimited AFRL-2021-1606 on 25 May 2021. Other requests shall be referred to AFRL/RIT 525 Brooks Rd Rome, NY 13441.

ASR-FANET: An adaptive SDN-based routing framework for FANET

Flying ad hoc network (FANET) is widely used in many military, commercial and civilian applications. Compared with mobile adhoc network (MANET) and vehicular ad hoc network (VANET), FANET holds unique characteristics such as high mobility, intermittent links and frequent topology changes, which cause a challenging task in the design of routing protocols. A novel adaptive software defined networking (SDN)-based routing framework for FANET called ASR-FANET is proposed in this article to solve the above challenges. The ASR-FANET framework is mainly composed of three important parts, which are the topology discovery mechanism, statistics gathering mechanism and route computation mechanism. In topology discovery mechanism, the periodic information about network topology is collected, including nodes and links. In statistics gathering mechanism, the status of the wireless network connection and flight statistics are collected. In route computation mechanism, the optimal path is calculated based on link costs. The performance of ASR-FANET framework is also has been evaluated by comprehensive simulations. The simulation results show that proposed framework is much better than other traditional protocols in packet delivery fraction, average end to end delay, normalized routing load, packet loss and throughput.

Energy-aware routing considering load balancing for SDN: a minimum graph-based Ant Colony Optimization

Software-Defined Network (SDN) technology is a network management approach that facilitates a high level of programmability and centralized manageability. By leveraging the control and data plane separation, an energy-aware routing model could be easily implemented in the networks. In the present paper, we propose a two-phase SDN-based routing mechanism that aims at minimizing energy consumption while providing a certain level of QoS for the users’ flows and realizing the link load balancing. To reduce the network energy consumption, a minimum graph-based Ant Colony Optimization (ACO) approach is used in the first phase. It prunes and optimizes the network tree by turning unnecessary switches off and providing an energy-minimized sub-graph that is responsible for the network existing flows. In the second phase, an innovative weighted routing approach is developed that guarantees the QoS requirements of the incoming flows and routes them so that to balance the loads on the links. We validated our proposed approach by conducting extensive simulations on different traffic patterns and scenarios with different thresholds. The results indicate that the proposed routing method considerably minimizes the network energy consumption, especially for congested traffics with mice-type flows. It can provide effective link load balancing while satisfying the users’ QoS requirements.

Analysis of routing protocols for software-defined vehicular ad hoc networks

With the rapid development of smart cities, intelligent transport systems (ITSs) have revolutionised the modern transportation system. Vehicular ad hoc networks (VANETs) have become the backbones of the ITS. These VANETs are characterised by high mobility and dynamically changing topology, leading to frequent link breaks. Thus, routing is an essential aspect of VANETs, contributing to the overall network performance. Some challenges regarding routing are diminished quality of service (QoS), heterogeneous networks, and security. These challenges are efficiently addressed by a networking paradigm called software define networking (SDN). In this paper, we present the current state of the art in SDN based routing along with its merits. Also, a novel taxonomy of such routing protocols based on the organisation of the SDN controller, QoS metric, security, heterogeneity, and type of communication is presented. We conclude the analysis with the benefits of SDN-based routing over the traditional network-based VANETs concerning QoS, security, and heterogeneity in the networks.

Cognitive Routing in Software-Defined Maritime Networks

Due to the constantly changing sea surface, there is a high risk of link fragility caused by sea waves when different marine users are intended to establish stable links for communication. To ensure stability with less delay, finding a stable route is one of the crucial aspects of maritime networks. In order to achieve this aim, we propose a routing protocol for cognitive maritime networks based on software-defined networking (SDN). This SDN-based cognitive routing protocol provides stable routes among different marine users. To provide the global view of the whole network, a main controller is placed close to the seashore, whereas the localized views are provided by the cluster heads. Autonomous surface vehicles are used as gateways under sparse network conditions to collect and transport data among clusters, and to and from the main controller. This is an SDN-based ship-to-ship communication scheme where two ships can only establish a link when they not only have consensus about a common idle channel but are also within the communication range of each other. We perform extensive simulations to test the proposed scheme with different parameters and find better performance in comparison with both SDN-based and non-SDN-based schemes in terms of end-to-end delay, packet delivery ratio, and routing overhead ratio.

LSEA: Software-Defined Networking-Based QoS-Aware Routing Mechanism for Live-Soccer Event Applications in Smart Cities

The smart cities provide a better connection between services and citizens based on new Internet technologies. During the building process of smart cities, some burgeoning applications have been emerging and changing the daily lifestyle of people, e.g., live streaming applications. Especially, the live-soccer event applications have attracted much attention and can improve people’s enjoyment of life to a great extent, such as the Europe five major league matches and FIFA world cup. For such applications, the traditional routing strategies cannot do Quality-of-Service (QoS) awareness, and thus, the network performance and the Quality of Experience (QoE) of users cannot be guaranteed. In this paper, we employ Software-Defined Networking (SDN) to make QoS awareness for the special live-soccer event applications, in which the QoS-aware routing mechanism is proposed, called LSEA. Meanwhile, delay, delay jitter, and packet loss rate are considered as three objects. On this basis, the improved Dijkstra routing algorithm and SDN-based disjoint routing algorithm are devised. Finally, the proposed LSEA is implemented over Mininet, and the experimental results demonstrate its feasibility and efficiency.

A New SDN-Based Routing Protocol for Improving Delay in Smart City Environments

The smart city is an ecosystem that interconnects various devices like sensors, actuators, mobiles, and vehicles. The intelligent and connected transportation system (ICTS) is an essential part of this ecosystem that provides new real-time applications. The emerging applications are based on Internet-of-Things (IoT) technologies, which bring out new challenges, such as heterogeneity and scalability, and they require innovative communication solutions. The existing routing protocols cannot achieve these requirements due to the surrounding knowledge supported by individual nodes and their neighbors, displaying partial visibility of the network. However, the issue grew ever more arduous to conceive routing protocols to satisfy the ever-changing network requirements due to its dynamic topology and its heterogeneity. Software-Defined Networking (SDN) offers the latest view of the entire network and the control of the network based on the application’s specifications. Nonetheless, one of the main problems that arise when using SDN is minimizing the transmission delay between ubiquitous nodes. In order to meet this constraint, a well-attended and realistic alternative is to adopt the Machine Learning (ML) algorithms as prediction solutions. In this paper, we propose a new routing protocol based on SDN and Naive Bayes solution to improve the delay. Simulation results show that our routing scheme outperforms the comparative ones in terms of end-to-end delay and packet delivery ratio.

Application-Aware SDN-Based Iterative Reconfigurable Routing Protocol for Internet of Things (IoT).

The central intelligence offered by Software Defined Networking (SDN) promise the smart and reliable reconfiguration which enables the scalability of dynamic enterprise networks. The decoupled forwarding plane and control plane of SDN infrastructure is a key feature that supports the SDN controller to extract the physical network topology information at runtime to formulate network reconfigurations. This SDN-based network reconfiguration enables application-aware routing capability for Internet of Thing (IoT). However, these IoT enabled SDN-based routing protocols face some performance limitations in iterative reconfiguration process due to complete centralized path selection mechanism To this end, in this paper, we propose SDN-Based Application-aware Distributed adaptive Flow Iterative Reconfiguring (SADFIR) routing protocol. The proposed routing protocol enables the distributed SDN iterative solver controller to maintain the load-balancing between flow reconfiguration and flow allocation cost. In particular, the proposed routing protocol of SADFIR implements multiple SDN controllers that collaborate with network devices at forwarding plane to develop appropriate clustering strategy for routing the sensed information. This distributed SDN controllers are assisted to clustering topology that successfully map the residual network resources and also enable unique multi-hop application-aware data transmission. In addition, the proposed SADFIR monitor the iterative reconfiguration settings according to the network traffic of heterogeneity-aware network devices. The simulation experiments are conducted in comparison with the state-of-the-art routing protocols which demonstrates that SADFIR is heterogeneity-aware which is able to adopt the different scales of network with maximum network lifetime.

CRetor: An SDN-Based Routing Scheme for Data Centers With Regular Topologies

The blooming of cloud computing leads to the rapid expansion of data center networks (DCN). Conventional link state routing algorithms like OSPF are widely adopted in data center networks, however, those routing algorithms bring great control overheads and long convergence time. Recently, topology-aware routing methods are considered to be efficient especially in data center networks with regular topologies. Lots of topology-aware routing methods (e.g., Fat-Tree and BCube) have been proposed for specific data center network topologies. This paper first proposes a formalized method to describe regular topologies and a regular Topology Description Language (TPDL) based on this method. TPDL is well designed to accurately define regular network topologies in a clear way leveraging their regularities. Based on the Software-Defined Networking (SDN) technology, this paper also proposes a novel topology-aware routing scheme: cRetor (controller-side REgular TOpology Routing scheme). Different from other topology-aware routing methods, cRetor is a TPDL-based general routing method, which means it is expected to work on different kinds of regular topologies. In this scheme, TDPL files are used as a priori knowledge to build an initial topology in the SDN controllers, which eliminates the process of topology discovery via Link Layer Discovery Protocol (LLDP) and hence relieves the bandwidth and processing burdens on controllers. Besides, we also apply the A-star algorithm to SDN controllers to speed up the routing selection, where TPDL's distance formulas act as the heuristic function. The experimental results show that cRetor outperforms LLDP-based SDN, OSPF and DCell in routing calculation performance, convergence speed, routing overheads and fault tolerance.

A joint energy- and QoS-aware routing mechanism for WMNs using software-defined networking paradigm

Providing energy conservation together with the quality of service (QoS) becomes more challenging in wireless mesh networks. A promising way to achieve this goal is to design a routing mechanism that takes both energy and QoS into account. On the other hand, software-defined networking (SDN) is an emerging network paradigm which separates the control plane from the data plane and facilitates a high level of programmability and manageability. In this paper, we propose FACOR, a novel SDN-based routing mechanism which aims at minimizing the energy consumption while providing a certain level of QoS for multimedia applications in wireless mesh networks. This technique is essentially suitable for battery-operated mesh nodes with solar panels. To obtain optimal paths, FACOR first estimates the cost of each network link using a fuzzy logic system. The fuzzy part takes parameters related to the quality of service and the energy in order to calculate the cost of the links. The routing problem is then formulated as an integer linear programming (ILP) model. Since ILP is NP-complete, we propose an ant colony optimization-based algorithm to solve the model. The proposed method is implemented in the well-known OpenDayLight controller and strictly follows a modular design for the sake of efficiency. Simulation results confirm the effectiveness of our mechanism which achieves a gain of about 17% and 10% in terms of network lifetime and PSNR, respectively, compared to other methods.

SDN-Based Routing for Backhauling in Ultra-Dense Networks

Ultra-Dense Network (UDN) deployment is considered a key element to achieve the requested capacity in future fifth-generation (5G) mobile networks. Backhaul networks in UDNs are formed by heterogeneous links with multi-hop connections and must handle massive traffic. Backhauling in future 5G networks may represent the capacity bottleneck. Therefore, there is the need for efficient and flexible routing schemes able to handle the dynamism of the traffic load in capacity-limited networks. Toward this goal, the emerging Software-Defined Network (SDN) paradigm provides an efficient solution, transferring the routing operation from the data plane switches to a central controller, thus achieving more flexibility, efficiency, and faster convergence time in comparison to conventional networks. This paper proposes and investigates an SDN-approach for an efficient routing in a capacity-limited backhaul network that carries data and control traffic of a heterogeneous UDN. The routing algorithm is centralized in the SDN controller and two different types of traffic flow are considered: data and control plane coordination traffic. The goal is to reduce or even to avoid the amount of traffic that the backhaul network is not able to support, distributing in a fair way the eventual lack of bandwidth among different access points. Simulation results show that with the considered approach the performance significantly improves, especially when there is an excess of traffic load in the network. Moreover, thanks to the SDN-based design, the network can reconfigure the traffic routing depending on the changing conditions.

CR-SDVN: A Cognitive Routing Protocol for Software-Defined Vehicular Networks

Due to the highly dynamic nature of cognitive vehicular networks, several sporadic links induce a long delay in the network. The selection of a stable route is therefore one of the key design factors to improve overall network stability, thereby reducing the end-to-end delay. Software-defined networking (SDN) is a novel approach that improves network intelligence. To this end, we propose a novel SDN-based routing protocol for cognitive vehicular networks that finds a stable route between source and destination. As this is a cognitive routing protocol, spectrum sensing is therefore the primary task of this algorithm to improve network stability by keeping primary user activity safe. We apply a belief propagation algorithm for channel selection. This is an SDN-based vehicular communications scheme where two nodes can only communicate when they have consensus about a common idle channel. The protocol has two phases: the registering phase and the route prediction phase. The SDN main controller (MC) is responsible for a global view of the network, whereas several local controllers (LCs) are responsible for localized global views of the network. This layering of controllers into two kinds (MC and LCs) improves the network performance in terms of end-to-end delay, high delivery ratio, and low overhead. We prove this in our simulation results by comparing our proposed scheme with two existing schemes (one with, and another without, SDN).

Cognitive Routing in Software-Defined Underwater Acoustic Networks

There are two different types of primary users (natural acoustic and artificial acoustic), and there is a long propagation delay for acoustic links in underwater cognitive acoustic networks (UCANs). Thus, the selection of a stable route is one of the key design factors for improving overall network stability, thereby reducing end-to-end delay. Software-defined networking (SDN) is a novel approach that improves network intelligence. To this end, we propose a novel SDN-based routing protocol for UCANs in order to find a stable route between source and destination. A main controller is placed in a surface buoy that is responsible for the global view of the network, whereas local controllers are placed in different autonomous underwater vehicles (AUVs) that are responsible for a localized view of the network. The AUVs have fixed trajectories, and sensor nodes within transmission range of the AUVs serve as gateways to relay the gathered information to the controllers. This is an SDN-based underwater communications scheme whereby two nodes can only communicate when they have a consensus about a common idle channel. To evaluate our proposed scheme, we perform extensive simulations and improve network performance in terms of end-to-end delay, delivery ratio, and overhead.