181,640 research outputs found

    A Survey on the Contributions of Software-Defined Networking to Traffic Engineering

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    Since the appearance of OpenFlow back in 2008, software-defined networking (SDN) has gained momentum. Although there are some discrepancies between the standards developing organizations working with SDN about what SDN is and how it is defined, they all outline traffic engineering (TE) as a key application. One of the most common objectives of TE is the congestion minimization, where techniques such as traffic splitting among multiple paths or advanced reservation systems are used. In such a scenario, this manuscript surveys the role of a comprehensive list of SDN protocols in TE solutions, in order to assess how these protocols can benefit TE. The SDN protocols have been categorized using the SDN architecture proposed by the open networking foundation, which differentiates among data-controller plane interfaces, application-controller plane interfaces, and management interfaces, in order to state how the interface type in which they operate influences TE. In addition, the impact of the SDN protocols on TE has been evaluated by comparing them with the path computation element (PCE)-based architecture. The PCE-based architecture has been selected to measure the impact of SDN on TE because it is the most novel TE architecture until the date, and because it already defines a set of metrics to measure the performance of TE solutions. We conclude that using the three types of interfaces simultaneously will result in more powerful and enhanced TE solutions, since they benefit TE in complementary ways.European Commission through the Horizon 2020 Research and Innovation Programme (GN4) under Grant 691567 Spanish Ministry of Economy and Competitiveness under the Secure Deployment of Services Over SDN and NFV-based Networks Project S&NSEC under Grant TEC2013-47960-C4-3-

    Firewalls Policies Based on Software Defined Networking: A survey

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    Software-Defined Networking (SDN) introduces granularity, visibility and flexibility to networking, which separates the control-logic from networking devices. SDN programmatically modifies the functionality and behaviour of network devices. It separates control plane and data plane, and thus provides centralized control. Though SDN provides better performance but there are some security issues that need to be taken care of. This includes firewalls, monitoring applications, IDS(Intrusion detection systems) etc. Therefore, this research work reviews the related approaches which have been proposed by identifying their firewall scope, their practicability, their advantages and drawbacks related with SDN. This paper describes the firewall policies as the forth new security challenges.Keywords: Software defined networking, Architecture, OpenFlow, Firewalls, Anomaly detectio

    Resilience support in software-defined networking:a survey

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    Software-defined networking (SDN) is an architecture for computer networking that provides a clear separation between network control functions and forwarding operations. The abstractions supported by this architecture are intended to simplify the implementation of several tasks that are critical to network operation, such as routing and network management. Computer networks have an increasingly important societal role, requiring them to be resilient to a range of challenges. Previously, research into network resilience has focused on the mitigation of several types of challenges, such as natural disasters and attacks. Capitalizing on its benefits, including increased programmability and a clearer separation of concerns, significant attention has recently focused on the development of resilience mechanisms that use software-defined networking approaches. In this article, we present a survey that provides a structured overview of the resilience support that currently exists in this important area. We categorize the most recent research on this topic with respect to a number of resilience disciplines. Additionally, we discuss the lessons learned from this investigation, highlight the main challenges faced by SDNs moving forward, and outline the research trends in terms of solutions to mitigate these challenges

    Hybrid SDN Evolution: A Comprehensive Survey of the State-of-the-Art

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    Software-Defined Networking (SDN) is an evolutionary networking paradigm which has been adopted by large network and cloud providers, among which are Tech Giants. However, embracing a new and futuristic paradigm as an alternative to well-established and mature legacy networking paradigm requires a lot of time along with considerable financial resources and technical expertise. Consequently, many enterprises can not afford it. A compromise solution then is a hybrid networking environment (a.k.a. Hybrid SDN (hSDN)) in which SDN functionalities are leveraged while existing traditional network infrastructures are acknowledged. Recently, hSDN has been seen as a viable networking solution for a diverse range of businesses and organizations. Accordingly, the body of literature on hSDN research has improved remarkably. On this account, we present this paper as a comprehensive state-of-the-art survey which expands upon hSDN from many different perspectives

    GR-342 Integration of Blockchain in Computer Networking: Overview, Applications, and Future Perspectives for Software-defined Networking (SDN), Network Security and Protocols

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    The rapid advancement and increasing complexity of computer networks have created a need for robust, secure, and scalable solutions to manage and protect network resources. Blockchain, an emerging distributed ledger technology, offers enhanced security, transparency, and privacy preservation, making it a promising solution for addressing networking challenges. This paper presents a comprehensive survey of blockchain integration in computer networking, focusing on its potential applications, benefits, and future perspectives in Software-defined Networking (SDN), network security, and networking protocols. We identify that blockchain\u27s tamper-proof nature could significantly improve network security by mitigating risks associated with centralized control and single points of failure. The integration of blockchain in computer networking has the potential to increase trust and transparency among network participants, as it allows for secure, verifiable, and auditable transactions and communication. Blockchain also can streamline the management of Software-defined Networking (SDN) by enabling decentralized and automated network control, resource allocation, and orchestration. We also find that utilizing blockchain can address network challenges, such as mitigating DDoS attacks, enhancing intrusion detection and prevention, and securing routing protocols. However, we identify potential limitations of blockchain integration in computer networking, such as scalability challenges arising from the growing size of the distributed ledger and increasing network traffic. We emphasize the need for further research in optimizing consensus mechanisms, enhancing scalability and privacy preservation techniques interoperability, and facilitating standardization of networking protocols and practices

    The Challenges in SDN/ML Based Network Security : A Survey

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    Machine Learning is gaining popularity in the network security domain as many more network-enabled devices get connected, as malicious activities become stealthier, and as new technologies like Software Defined Networking (SDN) emerge. Sitting at the application layer and communicating with the control layer, machine learning based SDN security models exercise a huge influence on the routing/switching of the entire SDN. Compromising the models is consequently a very desirable goal. Previous surveys have been done on either adversarial machine learning or the general vulnerabilities of SDNs but not both. Through examination of the latest ML-based SDN security applications and a good look at ML/SDN specific vulnerabilities accompanied by common attack methods on ML, this paper serves as a unique survey, making a case for more secure development processes of ML-based SDN security applications.Comment: 8 pages. arXiv admin note: substantial text overlap with arXiv:1705.0056
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