Algorithmic Framework for QoS and TE in Virtual SDN Services

This paper proposes a Traffic Engineering (TE) scheme for routing in a target network topology that supports OpenFlow using a metric called congestion contribution and Software-Defined Networking (SDN). According to the network traffic volume has been increasing dramatically, it is clear that the congestion, which is caused by the imbalance of the traffic flow, can be occurred. Furthermore, an Interior Gateway Protocol (IGP) that is used for an Autonomous System (AS) also can cause congestion because it uses snapshot information of network topology to make the shortest path-based routing table. Due to the reasons mentioned above, much research on TE has been conducting to enhance the network performance. However, as an example of TE, the Multi-Protocol Label Switching (MPLS) using Resource Reservation Protocol (RSVP) is not flexible in reconfiguring the labeled path, and it has resource overhead that cannot be ignored. Thus, we propose a TE scheme using SDN to overcome the limitations in the target network. In order to show the feasibility of the proposed scheme, TE application predicts the bandwidth utilization for network devices in SDN networks. It also determines the near-optimized routing path for the maximization of the average bandwidth utilization with avoiding the congestion nodes. Our scheme can configure network devices (e.g., SDN switches) along the paths of traffic flows so that the SDN network can have maximum bandwidth utilization. Through experiments, it is shown that our proposed scheme can utilize the average bandwidth of the whole topology up to 66%.

Network virtualization is seen as a key networking paradigm for building diverse network services and architectures over a shared network infrastructure. Assigning network resources to virtual links and, more generally to virtual network topologies, efficiently and on-demand is one of the most challenging components of any network virtualization solution. This paper addresses the problem of on-line resource allocation of multiple virtual links on a Software Defined Network (SDN) infrastructure. The application context that is targeted is primarily the online provisioning of virtual overlay networks even if it can be broadened to address more general virtual networks. Considering an SDN physical infrastructure allows a complete freedom in choosing the optimal physical paths and the associated resources that support the virtual links with no interference from any other network function (such as routing). However, for the time being, forwarding in an SDN network is resource consuming with a noticeable impact on the size of the flow tables. Hence, forwarding (i.e. switching) resources should be carefully considered by the network resource allocation algorithm. This paper proposes a novel Integer-Linear formulation of the above cited problem by taking into account: (1) point-to-point as well as point-to-multipoint virtual links, each with an associated bandwidth requirement and a maximum transfer delay requirement, (2) two types of network resources, namely network links' bandwidth and nodes' switching resources, and (3) optionally, path splitting which allows a virtual link to be established on multiple physical paths. We report preliminary experimental results on a real network topology in an overloaded scenario (bandwidth requests largely exceed network capacity); they show that our algorithm outperforms shortest path heuristics with a gain on the admission rate (of virtual links requests) that ranges from 5 to 15% (compared to the most efficient heuristic) and with a computation time less than a few seconds.

The SDN (Software Defined Networking) service chaining can take advantage of the separation of control and forwarding in the SDN network, centrally manage and coordinate various physical and virtual resources to dynamically meet users’ complex network service needs. At present, most researches on SDN service chaining are about the service chaining protocol and composition structure, service chaining mapping and service chaining strategy description. However, there is no traceable data storage method for the stability of the performance of the service nodes. This paper proposes to use blockchain technology to ensure the reliable traceability of the service chaining data. Meanwhile, in order to improve the retrieval efficiency, this paper designs and implements the combination of virtual chain and Bloom filter, and through the design of smart contract to achieve the query rate of 584.7KB/s under the condition of using blockchain. Besides, the system can save 28.7% of the retrieval time in the case of a large number of service chaining data storage. These experimental results prove that the system design can be well applied in the service chaining scenario.

Data center operators are accepting software defined networking (SDN) to manage their networks, but it remains challenging how to provide desirable virtual SDN services to tenants in a public cloud. We design SVirt, which enables highly flexible virtual SDN in a multi-tenant cloud by a substrate-agnostic SDN virtualization architecture. By redesigning the physical switch's processing pipeline with a late-binding key extractor, SVirt supports virtual SDN switches with different processing pipelines simultaneously on a physical switch. In the control plane, SVirt enables many-to-one and one-to-many mapping when allocating the physical resource for a virtual network, which embraces arbitrary topology and TCAM resource demanded by a virtual network. In the data plane, SVirt explicitly carries the forwarding context information in the packets, overcoming the context-loss problem in a virtual SDN network. We develop a NetFPGA prototype of SVirt switch. Evaluations based on event-driven simulations and prototype-based experiments demonstrate that, compared with traditional approaches, SVirt significantly enhances the cloud's capability to accept various virtual SDN requests and improves the network's throughput.

Hybrid software-defined networking (SDN) networks are intermediates between traditional networks and SDN networks. However, since the hybrid control planes are structurally different from the single control plane, updating the hybrid SDN networks lacks effective techniques. In this paper, by utilizing the segment routing (SR) mechanism to update hybrid SDN networks and formalize the application of SR during updates, we propose a cooperative consistency update algorithm that can coordinate SR, two-phase commit techniques. The algorithm is capable of preserving consistency with low overhead and excellent applicability. When a network requires updating, the algorithm leverages the SR mechanism to stitch a new path using the available path segments; thus, flows can use the new path immediately. If the update cannot be completed with the SR mechanism alone, the algorithm can utilize the two-phase commit technique to update the nodes through duplication. Notably, our experiments based on real topologies indicate that, compared to prior techniques, the proposed algorithm can greatly reduce the TCAM overhead.

It is Software defined networking (SDN) is a new network approach which allows separation of the forwarding plane from the control plane in network architecture, that aids in the efficient control of data flow and gives network administrators a software- based method for managing and configuring the networks. In contrast to SDN, which provides a centralized controller, traditional network topologies require the individual configuration of each network device. Due to a centralized control functionality, SDN is increasingly used by businesses, telecom service providers, cloud providers, and many other users, as it encourages flexibility and scalability in the network while also assisting in streamlining operations. There is significant demand of SDN for effective and adaptable networks. SDN adoption has also been rising in the campuses and corporate sectors. This paper provides a concise overview of the Software Defined Networks (SDN) topic, which is essential for comprehending the fundamental principles of SDN in order to conduct research and implement SDN in many sectors. The initial focus is on the discussion of traditional networks, including their limitations, as well as the many issues encountered by industries. The topic of Software Defined Networks is explored, encompassing their necessity, historical background, architectural structure, interfaces, and models. Next, the many applications of Software-Defined Networking (SDN) are examined. Additionally, the various SDN case studies, vendors, setup issues with SDN, and current research fields were elucidated. The discussion focuses on the role of Software-Defined Networking (SDN) in Artificial Intelligence (AI), specifically addressing the issues associated with implementing SDN in AI.

Owing to the Network Function Virtualization (NFV) and Software-Defined Networks (SDN), Service Function Chain (SFC) has become a popular service in SDN and NFV-enabled network. However, as the Virtual Network Function (VNF) of each type is generally multi-instance and flows with SFC requests must traverse a series of specified VNFs in predefined orders, it is a challenge for dynamic SFC formation to optimally select VNF instances and construct paths. Moreover, the load balancing and end-to-end delay need to be paid attention to, when routing flows with SFC requests. Additionally, fine-grained scheduling for traffic at flow level needs differentiated routing which should take flow features into consideration. Unfortunately, traditional algorithms cannot fulfill all these requirements. In this paper, we study the Differentiated Routing Problem considering SFC (DRP-SFC) in SDN and NFV-enabled network. We formulate the DRP-SFC as a Binary Integer Programming (BIP) model aiming to minimize the resource consumption costs of flows with SFC requests. Then a novel routing algorithm, Resource Aware Routing Algorithm (RA-RA), is proposed to solve the DRP-SFC. Performance evaluation shows that RA-RA can efficiently solve the DRP-SFC and surpass the performance of other existing algorithms in acceptance rate, throughput, hop count and load balancing.

Accurate traffic and latency measurements are the foundation of many network management tasks, including traffic engineering and network provision, network diagnosis and fault recovery. However, SNMP-based traffic measurement techniques in traditional IP networks only provide measurements for link loads, which cannot lead to accurate measurements. For link latency measurement, it has been shown that a traditional IP network needs to deploy a large number of monitors to achieve accurate measurements. The software-defined network (SDN) architecture opens up new opportunities to tackle the traffic matrix estimation and latency measurement problems. For the traffic estimation problem, the counter in a flow table entry of an SDN switch can directly measure the size of a matched flow. This dramatically increases the number and type of flows that can be measured accurately. For link latency measurement, SDN switches provide flexible routing and hence allow even non-shortest paths to be measured in the network. This routing flexibility can reduce the number of monitors deployed in the network to achieve a complete measurement of all the link latencies. But the additional measurement capabilities of SDNs also have limitations: the flow table entries added for measurements must be limited due to the high cost of ternary content-addressable memory (TCAM), and the amount of additional traffic for measurement should also be confined. Under these constraints, this research investigates the traffic matrix estimation and link latency measurement problems for a pure SDN network and a hybrid SDN network. A hybrid network, which consists of SDN switches and conventional routers, will exist for some time to come since it is economically impossible to replace every conventional router overnight. For the traffic matrix estimation problem, we propose a new estimation framework, which can be used in both SDNs and hybrid SDNs. Performance evaluation results show that the new framework can achieve highly accurate traffic measurement with a small number of TCAM entries. For the link latency measurement problem, we first present minimum monitor placement schemes in hybrid SDNs. It has been shown that our schemes not only reduce the number of required monitors but also guarantee full link measurements even when link weights change. We then present two time-stamp-based link latency measurement schemes for pure SDNs and show that the proposed schemes can minimize the number of consumed TCAM entries and the amount of traffic generated for measurement.

Computer network conditions that are dynamic and also complex make network operators often make mistakes in the configuration of a network device. However, these mistakes can be resolved by the emergence of a centralized programming approach which is now known as Software Defined Network (SDN). In addition, with the development of information technology, several services in computer networks also grabbed a lot of attention from the world, such as video streaming services. A video streaming service that is so massive is capable of having an impact on data traffic on computer networks. In SDN networks, controllers are a core component of this architecture. Currently, many different types of SDN controllers can be used, however, choosing a controller in an SDN network must be an important concern. This is related to the performance of the SDN controller which is a requirement for SDN network development. This research will analyze the performance of the video streaming service using the Real-time Transport Protocol (RTP) streaming protocol in testing two SDN controllers, namely Pox and Opendaylight. Based on the tests that have been carried out, it produces Quality of Service (QoS) values in the form of throughput, delay, and jitter. The Pox controller excels in the value of QoS delay and throughput. As for the jitter value, both Pox and Opendaylight controllers have good indexes.

Virtual Private LAN Services (VPLS) is an Ethernet based VPN (Virtual Private Network) service which provides protocol independent and high speed multipoint-to-multipoint connectivity. In this article, we discuss the possibility to use emerging networks concepts such as Software Defined Networking (SDN) and Network Function Virtualization (NFV) to improve the performance, flexibility and adaptability of VPLS networks. SDN and NFV based VPLS (SoftVPLS) architectures offer new features such as centralized control, network programmability and abstraction to improve the performance, flexibility and automation of traffic, security and network management functions for future VPLS networks.

Popularity of Software Defined Network (SDN) technology is spreading rapidly and corporate networks are deploying to take advantages of its features. Control & Data planes are segregated in SDN and simple forwarding devices enabled with OpenFlow protocol is used to forward data planes. The responsibility of control planes are taken by controller into SDN network. The data packets are generated by source host and forwarded to destination host by seeing destination address of such packet without validating source host address. Flow of data packets is controlled by controller setting up required flow entries into flow table of forwarding devices. Initially forwarding devices do not have any security & control and they are not able to forward traffic generated by attached hosts. Data packets of attached hosts are sent to the controller by forwarding devices for generation of control packets and setup necessary flow entries into device flow table. Source IP spoofed attacks may be setup by attacker in this situation and perform different type of attacks. There are some techniques for prevention and mitigation from such attacks. In this study, we offer an analysis of available source address validation techniques for SDN environment. The study discussed various features, limitations and gaps of source address validation solutions and provided various areas in SDN Security for future research.

The evolution and advancements in Information and Communication Technologies (ICT) have enabled large scale distributed computing with a huge chunk of applications for massive number of users. This has obviously generated large volumes of data, thus severely burdening the processing capacity of computers as well as the inflexible traditional networks. State-of-the-art methods for addressing datacenter level performance fixes are yet found wanting for sufficiently addressing this huge processing, storage, and network movement with proprietary protocols for this voluminous data. In this chapter the works have focused on addressing the backend server performance through effective reducer placement, intelligent compression policy, handling slower tasks and in-network performance boosting techniques through effective traffic engineering, traffic classification, topology discovery, energy minimization and load balancing in datacenter-oriented applications. Hadoop, the defacto standard in distributed big data storage and processing, has been designed to store data with its Hadoop Distributed File System (HDFS) and processing engine MapReduce large datasets reliably. However, the processing performance of Hadoop is critically dependent on the time taken to transfer data during the shuffle generated during MapReduce. Also, during concurrent execution of tasks, slower tasks need to be properly identified and efficiently handled to improve the completion time of jobs. To overcome these limitations, three contributions have been made; (i) Compression of generated map outputs at a suitable time when all the map tasks are yet to be completed to shift the load of network onto the CPU; (ii) Placing the reducer onto the nodes where the computation done is highest based on a couple of counters, one maintained at the rack level and another at node level, to minimize the run-time data copying; and (iii) Placing the slower map tasks onto the nodes where the computation done is highest and network is handled by prioritizing. Software defined networking (SDN) has been a boon for next generation networking owing to the separation of control plane from the data plane. It has the capability to address the network requirements in a timely manner by setting flows for every to and fro data movement and gathering large network statistics at the controller to make informed decisions about the network. A core issue in the network for the controller is traffic classification, which can substantially assist SDN controllers towards efficient routing and traffic engineering decisions. This chapter presents a traffic classification scheme utilizing three classifiers namely Feed-forward Neural Network (FFNN), Logistic Regression (LR), Naïve Bayes and employing Particle Swarm Optimization (PSO) for improved traffic classification with less overhead and without overlooking the key Quality of Service (QoS) criterion. Also lowering energy minimization and link utilization has been an important criterion for lowering the operating cost of the network and effectively utilizing the network. This issue has been addressed in the chapter by formulating a multi-objective problem while simultaneously addressing the QoS constraints by proposing a metaheuristic, since no polynomial solution exists and hence an evolutionary based metaheuristic (Clonal Selection) based energy optimization scheme, namely, Clonal Selection Based Energy Minimization (CSEM) has been devised. The obtained results show the efficacy of the proposed traffic classification scheme and CSEM based solution as compared with the state-of-the-art techniques. SDN has been a promising newer network paradigm but security issues and expensive capital procurement of SDN limit its full deployment hence moving to a hybrid SDN (h-SDN) deployment is only logical moving forward. The usage of both centralized and decentralized paradigms in h-SDN with intrinsic issues of interoperability poses challenges to key issues of topology gathering by the controller for proper allocation of network resources and traffic engineering for optimum network performance. State-of-the-art protocols for topology gathering, such as Link Layer Discovery Protocol (LLDP) and Broadcast Domain Discovery Protocol (BDDP) require a huge number of messages and such schemes only gather link information of SDN devices leaving out legacy switches’ (LS) links which results in sub-optimal performance. This chapter provides novel schemes which unearth topology discovery by requiring fewer messages and gathering link information of all the devices in both single and multi-controller environments (might be used when scalability issue is prevalent in h-SDN). Traffic engineering problems in h-SDN are addressed by proper placement of SDN nodes in h-SDN by utilizing the analyzing key criterion of traffic details and the degree of a node while lowering the link utilization in real-time topologies. The results of the proposed schemes for topology discovery and SDN node placement demonstrate the merits as compared with the state-of-the-art protocols.

Challenges and solutions in Software Defined Networking: A survey

The design, management, and operation of network infrastructure have evolved during the last few years, leveraging on innovative technologies and architectures. With such a huge trend, due to the flexibility and significant economic potential of these technologies, software-defined networking (SDN) and network functions virtualization (NFV) are emerging as the most indispensable key catalysers. SDN/NFV enhancing the infrastructure agility, thus network operators and service providers are able to program their own network functions (e.g., gateways, routers, load balancers) on vendor-independent hardware substrate. One of the most important considerations in NFV deployment is how to allocate the virtual resources that are needed to provide flexible virtual network services in an NFV-based network infrastructure. Thus, the most important prerequisite for NFV deployment is achieved fast, scalable and dynamic composition and allocation of networks functions (NFs) to implement network services (NSs). We have proposed a revised RA algorithm that integrates embedding and scheduling of virtual network functions (VNFs) simultaneously. In this paper, performance evaluation of the revised RA algorithm is performed and the proposed algorithm is applied more effectively in NFV environment where the demand for resources is flexible and concentrated.

Software Defined Networking (SDN) has a potential to address a number of networking challenges, but still presents other financial and business challenges such as budget constraints, acceptability and trust amongst network operators. A hybrid SDN deployment is a conceivable solution, because it offers the benefits of SDN and traditional network capabilities, including budget constraints adaptability, falling back on time-tested traditional tools, central network programmability and will offer an organization a smooth transition to SDN. As modern-day communication has become an imperative feature of day to day business functions, there is a need to balance the network load to achieve improved network performance, minimizing delay and reduce the time taken for network response. In this paper, we develop and study multi-path load balancing in a hybrid SDN data plane. The load balancer’s performance is tested using four different hybrid SDN topologies, namely, Fat Tree, Ring, Mesh and Torus topology with the OpenDayLight controller. The main contribution of this work is a data plane congestion and link overloading load balancing testing and analysis for deployment (before or after network failure) in hybrid SDN environments. The obtained results display an improved overall network performance and reduced network delay.