Joint energy efficiency and load balancing optimization in hybrid IP/SDN networks

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.

Software Defined Networking (SDN) has emerged as a new paradigm that offers the programmability required to dynamically configure and control a network. In this paper, we present a path assignment method based on load balancing(PA-LB) for a centralized controller to calculate optimal end-to-end virtual paths over the underlying network infrastructure, considering multiple requests and load balance simultaneously. In the paper, theoretical analysis shows that the path selection is NP-hard, and strongly polynomial time inapproximable under the assumption P not equal to NP. We also give a constant-factor polynomial time approximation algorithm for this problem under some bounded parameters. Extensive simulation results, over a wide range of underlying network topologies and input parameters, demonstrate that the proposed method outperforms traditional shortest path first (SPF) approaches not only in paths mapping number, but also in network load balance. Under the condition of limited resources, such as bandwidth, the proposed method has a better performance with the increase of the number of nodes. Moreover, optimal load balance can be kept in the network, in order to avoid network congestion and minimize the average packet transmission latency.

Software Defined Networking (SDN) paradigm brings flexibility and programmability to the network management. Deploying a set of SDN controllers to manage a Wide Area Network is challenging as it implies to determine the right number of controllers to install and their locations within the network in addition to minimize the effect of their failures. In this paper, we give a methodology that should be taken into consideration to provide a fault tolerance in SDN networks. In this paper a new model is proposed. The model is called load balancing to support fault tolerance using feedback control for SDNs (LBFTFB). LBFTFB uses feedback control theoretic techniques and uses least squares regression to find the goodness of the model. LBFTFB provides load balancing constraints for several level of backup controllers. Cascading controller failures is one of the popular controller failures. The LBFTFB model reduces the cascading failure problem effect. In order to test the efficiency of the proposed model, a reference model was used. The reference model used is the HyperFlow model. The HyperFlow model is a distributed control plane for OpenFlow. HyperFlow is an application developed on the top of the NOX controller, to enable logically centralized multi-controller architectures. Experimented were conducted to compare the performance of LBFTFB when compared to the HyperFlow. This is an ongoing research. Tentative emulation results show promising controlled results indicating that LBFTFB model outperforms the HyperFlow by 16% on average in terms of packet loss and packet delays.

Large-scale IT infrastructures are highly energy-intensive systems. To mitigate the environmental impact of networks, it is crucial to design energy-aware traffic engineering strategies that make the best use of a network’s redundancy in order to maximize energy savings. The Software-Defined Networking (SDN) paradigm is a powerful tool that eases network management by decoupling the control and data planes. Because of its flexibility and controllability, SDN is nowadays widely adopted in data centers and enterprise networks. In this paper, we provide energy-aware traffic solutions for SDNs. We conducted extensive experiments on real switches for a thorough power consumption characterisation. Thanks to this preliminary study, we could fully characterize the solution space of a performance-constrained energy optimization problem. We formulate two optimization problems for the selective activation of switches and ports under hard constraints on traffic demand, considering both a static and dynamic traffic scenario. We show that the proposed problems are NP-hard and provide two polynomial-time heuristics for the static and dynamic case, respectively. Through simulations, we show that our solution outperforms previous approaches in all the considered settings.

With each passing day, the information and communication technologies are evolving with more and more information shared across the globe using the internet superhighway. The threats to information, while connected to the cyber world are getting more targeted, voluminous, and sophisticated requiring new antifragile and resilient network security mechanisms. Whether the information is being processed in the application, in transit within the network or residing in the storage, it is equally susceptible to attack at every level of abstraction and cannot be handled in isolation as the case has been with conventional security mechanisms. The advent of Software-Defined Networks (SDN) has given a new outlook to information protection, where the network can aid in the design of a system that is secure and dependable in case of cyber threats. The nature of SDN, mainly its programmability and centrality of network information and control has led us to think of security in an antifragile perspective. Our networks can now thrive and grow stronger when they are exposed to volatility by overwhelming cyber threats. However, SDN infrastructure itself is susceptible to severe threats that may mutilate the provision of its usability as security provider. Both these perspectives of “Security with SDN” and “Security for SDN” have invited research and innovations, yet both these approaches remain disintegrated, failing to support each other. The contribution of this paper is threefold, with first reviewing the current state of the art work for both perspectives of SDN security. Second, it advocates the necessity and introduces a novel approach of antifragile cyber security within SDN paradigm and finally it proposes a unified model for integrating both approaches of “Security with SDN” and “Security for SDN” to achieve the overall objective of protecting our information from cyber threats in this globally connected internetwork.

It is difficult to manage traditional networks due to network growth, an increase in user numbers, and the emergence of new technologies like big data and cloud computing. Consequently, it is required to alter the current network design. SDN is a well-liked architecture because it offers customizable control and centralized management in data centers. To achieve scalability and dependability, it was necessary to propose the geographical dispersal of a logically centralized control plane due to the huge scale of networks. Software-defined networking (SDN) load-balancing optimization has been studied for a long time. Many approaches to the load-balancing conundrum have been put forth by researchers, but very few have taken the impact of transmission delay between controllers and switches under heavy network load into account. In this article we elaborate the various techniques of load balancing in SDN those working on different areas like multi-controller, switch migration, multi-agent, strategy, time sharing, prediction, reinforcement learning etc. We discuss the methods used along with the advantages and disadvantages of various costs, service quality, and network performance metrics.

Artificial intelligence based load balancing in SDN: A comprehensive survey

The proliferation of multimedia devices and video content availability is producing an increase in video content consumption. Video is now the most significant slice of all Internet traffic produced, and it is still growing. However, Over-The-Top (OTT) video is the one significantly increasing its strength, causing infrastructural and business challenges to Telecommunication Operators (Telcos), which provide traditional video services. Telcos must improve their network infrastructure to sustain future demand for OTT video content while improving user perceived Quality-of-Experience (QoE). A meaningful way to accomplish that is to distribute hardware appliances compatible with the Software-Defined Networking (SDN) paradigm throughout the network, improving flexibility and capacity while introducing new ways of content delivery.Towards this objective, this paper proposes an SDN load balancing approach to distribute OTT video requests through multiple servers. The load balancing decision is performed at the edge of the network influenced by the client's QoE. Comparing to a traditional load balancing scheme, the proposed method outperforms the non-SDN approaches in scenarios in which the server-side infrastructure starts to become stressed.

Software-Defined Networking (SDN) is revolutionizing network architecture by decoupling the control and data planes, enabling centralized control, programmability, and automation. This paper explores methods to optimize network performance through SDN, focusing on traffic engineering, load balancing, and dynamic routing. We present a comprehensive overview of existing techniques and propose an optimization framework that leverages real-time data analytics and machine learning to enhance throughput, reduce latency, and improve resource utilization. Experimental results from simulation environments demonstrate significant performance improvements when applying the proposed methods. This paper explores the role of SDN in optimizing network performance. It highlights key architectural components, examines practical implementation strategies, and evaluates performance metrics and case studies that demonstrate the effectiveness of SDN in real-world scenarios. Ultimately, the goal is to provide a comprehensive understanding of how SDN can be used to create smarter, more responsive, and efficient networks

Content delivery such as P2P or video streaming generates the main part of the Internet traffic and Content Centric Network (CCN) appears as an appropriate architecture to satisfy the user needs. However, the lack of scalable routing scheme is one of the main obstacles that slows down a large deployment of CCN at an Internet-scale. In this paper we propose to use the Software-Defined Networking (SDN) paradigm to decouple data plane and control plane and present SRSC, a new routing scheme for CCN. Our solution is a clean-slate approach using only CCN messages and the SDN paradigm. We implemented our solution into the NS-3 simulator and perform simulations of our proposal. SRSC shows better performances than the flooding scheme used by default in CCN: it reduces the number of messages, while still improves CCN caching performances.

Energy aware routing aims at reducing the energy consumption of ISP networks. The idea is to adapt routing to the traffic load in order to turn off some hardware. However, it implies to make dynamic changes to routing configurations which is almost impossible with legacy protocols. The Software Defined Network (SDN) paradigm bears the promise of allowing a dynamic optimization with its centralized controller. In this work, we propose SENAtoR, an algorithm to enable energy aware routing in a scenario of progressive migration from legacy to SDN hardware. Since in real life, turning off network equipments is a delicate task as it can lead to packet losses, SENAtoR provides also several features to safely enable energy saving services: tunneling for fast rerouting, smooth node disabling and detection of both traffic spikes and link failures. We validate our solution by extensive simulations and by experimentation. We show that SENAtoR can be progressively deployed in a network using the SDN paradigm. It allows to reduce the energy consumption of ISP networks by 5 to 35% depending on the penetration of SDN hardware, while diminishing the packet loss rate compared to legacy protocols.

Network is dynamic and requires update in the operation. However, many confusions and problems can be caused by careless schedule in the update process. Although the problem has been investigated for many years in traditional networks where the control plane is distributed, software defined networking (SDN) brings new opportunities and solutions to this problem by the separation of control and data plane, as well as the centralized control. This paper makes a survey on the problems caused by network update, including forwarding loop, forwarding black hole, link congestion, network policy violation, etc., as well as the state-of-the-art SDN solutions to these problems. Furthermore, we summarize the network configuration strength and discuss the open issues of network update in the SDN paradigm.

In this era wireless technology gaining more popularity, people prefer wireless communication over wired communication due to mobility, scalability and ease of access. However, the traditional wireless network is complex, vendor dependent and inadequate feasibility to incorporate new services, protocols, and APIs. The rapid growth in wireless network raises many thoughtful challenges for network and telecom operators. On such grounds, Innovation of Software Defined Network (SDN) and network function virtualization (NFV) for mobile network opens a new arena of research. This research article presents future mobile Internet architecture (FMIA) with the integration of twin technologies, SDN and NFV that enable rapid access to Internet services. Moreover, the network manager can control services provided by ISPs through proposed architecture.

Load balancing distributes incoming network traffic across multiple controllers that improve the availability of the internet for users. The load balancing is responsible to maintain the internet availability to users in 24 hours by 7 days a week. However, the internet become unavailable since the load balancer is inflexibility, costly, and non-programmable for settings adjustment especially in managing the network traffic congestion. An increasing user using mobile devices and cloud facilities, the current load balancer has limitations and demands for the deployment of a Software-Defined Network (SDN). SDN decouples network control, applications, network services, and forwarding roles; hence makes the network more flexible, affordable, and programmable. Furthermore, it has been found that SDN load balancing performs intelligent action, efficient and maintains better QoS (Quality of Service) performance. This study proposes the application of SDN-based Load Balancing since it provides pre-defined servers in the server-farm that receive the arrived Internet Protocol (IP) data packet from various clients in the same number of loads and process orders for each server. Experiments have been conducted using Mininet™ and based on several scenarios (Scenario A, Scenario B, and Scenario C) of network topologies. Parameters used to evaluate the load balancing in SDN are throughput, delay, and jitter. Findings indicated that scenario A gives a high throughput, scenario B and C produce a low jitter values and scenario C produces the lowest delay. The impact of SDN brings a multi-path adaptive direction in finding the best route for a better network performance.

The new network paradigm of Software Defined Networking (SDN) has been widely adopted. Due to its inherent advantages, SDN has been widely used in various network fields such as data centers, WAN, enterprise, Optical Networks and energy Internet. Among them, SDN-based energy Internet systems are receiving more and more attention. But at the same time, some problems and challenges are gradually becoming more prominent. The SDN-based energy Internet is a distributed architecture for renewable energy, so the traditional centralized electric energy trading model will no longer apply. The blockchain has been rapidly developed and applied in various domains by virtue of its decentralization, coordinated autonomy, and non-tamperability. We propose an SDN-based energy Internet distributed energy trading scheme supported by blockchain technology. The proposed scheme achieves a reasonable match of the transaction objects under the premise of protecting privacy. Finally, we conducted a comprehensive, systematic security and applicability analysis of the proposed solution, further confirming that the system meets our design goals.