Admission control in Flow-Aware Networking (FAN) architectures under GridFTP traffic

This is the author’s version of a work that was accepted for publication in Optical Switching and Networking. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Optical Switching and Networking, 6, 9 (2009) DOI: 10.1016/j.osn.2008.05.003Selected papers from First International Symposium on Advanced Networks and Telecommunication Systems, ANTS 2007Computing and networking resources virtualization is the main objective of Grid services. Such a concept is already used in the context of Web-services on the Internet. In the next few years, a large number of applications belonging to various domains (biotechnology, banking, finance, car and aircraft manufacturing, nuclear energy etc.) will also benefit from Grid services. Admission control is a key functionality for Quality of Service (QoS) provision in IP networks, and more specifically for Grid services provision. Service differentiation (DS) is a widely deployed technique on the Internet. It operates at the packet level on a best-effort mode. Flow-Aware Networking (FAN) that operates at the scale of the IP flows relies on implicit flow differentiation through priority fair queuing (PFQ). It may be seen as an alternative to DS. A Grid session may be seen as a succession of parallel TCP/IP flows characterized by data transfers with much larger volume than usual TCP/IP flows. In this paper, we propose an extension of FAN for the Grid environment called Grid over FAN (GoFAN). We compare, by means of computer simulations, the efficiency of Grid over DS (GoDS) and GoFAN. Two variants of GoFAN architectures based on different fair queuing algorithms are considered. As a first step, we provide two short surveys on QoS for Grid environment and on QoS in IP networks respectively

Data Movement Challenges and Solutions with Software Defined Networking

With the recent rise in cloud computing, applications are routinely accessing and interacting with data on remote resources. Interaction with such remote resources for the operation of media-rich applications in mobile environments is also on the rise. As a result, the performance of the underlying network infrastructure can have a significant impact on the quality of service experienced by the user. Despite receiving significant attention from both academia and industry, computer networks still face a number of challenges. Users oftentimes report and complain about poor experiences with their devices and applications, which can oftentimes be attributed to network performance when downloading or uploading application data. This dissertation investigates problems that arise with data movement across computer networks and proposes novel solutions to address these issues through software defined networking (SDN). SDN is lauded to be the paradigm of choice for next generation networks. While academia explores use cases in various contexts, industry has focused on data center and wide area networks. There is a significant range of complex and application-specific network services that can potentially benefit from SDN, but introduction and adoption of such solutions remains slow in production networks. One impeding factor is the lack of a simple yet expressive enough framework applicable to all SDN services across production network domains. Without a uniform framework, SDN developers create disjoint solutions, resulting in untenable management and maintenance overhead. The SDN-based solutions developed in this dissertation make use of a common agent-based approach. The architecture facilitates application-oriented SDN design with an abstraction composed of software agents on top of the underlying network. There are three key components modern and future networks require to deliver exceptional data transfer performance to the end user: (1) user and application mobility, (2) high throughput data transfer, and (3) efficient and scalable content distribution. Meeting these key components will not only ensure the network can provide robust and reliable end-to-end connectivity, but also that network resources will be used efficiently. First, mobility support is critical for user applications to maintain connectivity to remote, cloud-based resources. Today\u27s network users are frequently accessing such resources while on the go, transitioning from network to network with the expectation that their applications will continue to operate seamlessly. As users perform handovers between heterogeneous networks or between networks across administrative domains, the application becomes responsible for maintaining or establishing new connections to remote resources. Although application developers often account for such handovers, the result is oftentimes visible to the user through diminished quality of service (e.g. rebuffering in video streaming applications). Many intra-domain handover solutions exist for handovers in WiFi and cellular networks, such as mobile IP, but they are architecturally complex and have not been integrated to form a scalable, inter-domain solution. A scalable framework is proposed that leverages SDN features to implement both horizontal and vertical handovers for heterogeneous wireless networks within and across administrative domains. User devices can select an appropriate network using an on-board virtual SDN implementation that manages available network interfaces. An SDN-based counterpart operates in the network core and edge to handle user migrations as they transition from one edge attachment point to another. The framework was developed and deployed as an extension to the Global Environment for Network Innovations (GENI) testbed; however, the framework can be deployed on any OpenFlow enabled network. Evaluation revealed users can maintain existing application connections without breaking the sockets and requiring the application to recover. Second, high throughput data transfer is essential for user applications to acquire large remote data sets. As data sizes become increasingly large, often combined with their locations being far from the applications, the well known impact of lower Transmission Control Protocol (TCP) throughput over large delay-bandwidth product paths becomes more significant to these applications. While myriads of solutions exist to alleviate the problem, they require specialized software and/or network stacks at both the application host and the remote data server, making it hard to scale up to a large range of applications and execution environments. This results in high throughput data transfer that is available to only a select subset of network users who have access to such specialized software. An SDN based solution called Steroid OpenFlow Service (SOS) has been proposed as a network service that transparently increases the throughput of TCP-based data transfers across large networks. SOS shifts the complexity of high performance data transfer from the end user to the network; users do not need to configure anything on the client and server machines participating in the data transfer. The SOS architecture supports seamless high performance data transfer at scale for multiple users and for high bandwidth connections. Emphasis is placed on the use of SOS as a part of a larger, richer data transfer ecosystem, complementing and compounding the efforts of existing data transfer solutions. Non-TCP-based solutions, such as Aspera, can operate seamlessly alongside an SOS deployment, while those based on TCP, such as wget, curl, and GridFTP, can leverage SOS for throughput improvement beyond what a single TCP connection can provide. Through extensive evaluation in real-world environments, the SOS architecture is proven to be flexibly deployable on a variety of network architectures, from cloud-based, to production networks, to scaled up, high performance data center environments. Evaluation showed that the SOS architecture scales linearly through the addition of SOS “agents†to the SOS deployment, providing data transfer performance improvement to multiple users simultaneously. An individual data transfer enhanced by SOS was shown to have increased throughput nearly forty times the same data transfer without SOS assistance. Third, efficient and scalable video content distribution is imperative as the demand for multimedia content over the Internet increases. Current state of the art solutions consist of vast content distribution networks (CDNs) where content is oftentimes hosted in duplicate at various geographically distributed locations. Although CDNs are useful for the dissemination of static content, they do not provide a clear and scalable model for the on demand production and distribution of live, streaming content. IP multicast is a popular solution to scalable video content distribution; however, it is seldom used due to deployment and operational complexity. Inspired from the distributed design of todays CDNs and the distribution trees used by IP multicast, a SDN based framework called GENI Cinema (GC) is proposed to allow for the distribution of live video content at scale. GC allows for the efficient management and distribution of live video content at scale without the added architectural complexity and inefficiencies inherent to contemporary solutions such as IP multicast. GC has been deployed as an experimental, nation-wide live video distribution service using the GENI network, broadcasting live and prerecorded video streams from conferences for remote attendees, from the classroom for distance education, and for live sporting events. GC clients can easily and efficiently switch back and forth between video streams with improved switching latency latency over cable, satellite, and other live video providers. The real world dep loyments and evaluation of the proposed solutions show how SDN can be used as a novel way to solve current data transfer problems across computer networks. In addition, this dissertation is expected to provide guidance for designing, deploying, and debugging SDN-based applications across a variety of network topologies

An SDN-based firewall shunt for data-intensive science applications

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2016Data-intensive research computing requires the capability to transfer les over long distances at high throughput. Stateful rewalls introduce su cient packet loss to prevent researchers from fully exploiting high bandwidth-delay network links [25]. To work around this challenge, the science DMZ design [19] trades o stateful packet ltering capability for loss-free forwarding via an ordinary Ethernet switch. We propose a novel extension to the science DMZ design, which uses an SDN-based rewall. This report introduces NFShunt, a rewall based on Linux's Net lter combined with OpenFlow switching. Implemented as an OpenFlow 1.0 controller coupled to Net lter's connection tracking, NFShunt allows the bypass-switching policy to be expressed as part of an iptables rewall rule-set. Our implementation is described in detail, and latency of the control-plane mechanism is reported. TCP throughput and packet loss is shown at various round-trip latencies, with comparisons to pure switching, as well as to a high-end Cisco rewall. Cost, as well as operations and maintenance aspects, are compared and analysed. The results support reported observations regarding rewall introduced packet-loss, and indicate that the SDN design of NFShunt is a technically viable and cost-e ective approach to enhancing a traditional rewall to meet the performance needs of data-intensive researchersGS201

Review of Path Selection Algorithms with Link Quality and Critical Switch Aware for Heterogeneous Traffic in SDN

Software Defined Networking (SDN) introduced network management flexibility that eludes traditional network architecture. Nevertheless, the pervasive demand for various cloud computing services with different levels of Quality of Service requirements in our contemporary world made network service provisioning challenging. One of these challenges is path selection (PS) for routing heterogeneous traffic with end-to-end quality of service support specific to each traffic class. The challenge had gotten the research community\u27s attention to the extent that many PSAs were proposed. However, a gap still exists that calls for further study. This paper reviews the existing PSA and the Baseline Shortest Path Algorithms (BSPA) upon which many relevant PSA(s) are built to help identify these gaps. The paper categorizes the PSAs into four, based on their path selection criteria, (1) PSAs that use static or dynamic link quality to guide PSD, (2) PSAs that consider the criticality of switch in terms of an update operation, FlowTable limitation or port capacity to guide PSD, (3) PSAs that consider flow variabilities to guide PSD and (4) The PSAs that use ML optimization in their PSD. We then reviewed and compared the techniques\u27 design in each category against the identified SDN PSA design objectives, solution approach, BSPA, and validation approaches. Finally, the paper recommends directions for further research

Future of networking is the future of Big Data, The

2019 Summer.Includes bibliographical references.Scientific domains such as Climate Science, High Energy Particle Physics (HEP), Genomics, Biology, and many others are increasingly moving towards data-oriented workflows where each of these communities generates, stores and uses massive datasets that reach into terabytes and petabytes, and projected soon to reach exabytes. These communities are also increasingly moving towards a global collaborative model where scientists routinely exchange a significant amount of data. The sheer volume of data and associated complexities associated with maintaining, transferring, and using them, continue to push the limits of the current technologies in multiple dimensions - storage, analysis, networking, and security. This thesis tackles the networking aspect of big-data science. Networking is the glue that binds all the components of modern scientific workflows, and these communities are becoming increasingly dependent on high-speed, highly reliable networks. The network, as the common layer across big-science communities, provides an ideal place for implementing common services. Big-science applications also need to work closely with the network to ensure optimal usage of resources, intelligent routing of requests, and data. Finally, as more communities move towards data-intensive, connected workflows - adopting a service model where the network provides some of the common services reduces not only application complexity but also the necessity of duplicate implementations. Named Data Networking (NDN) is a new network architecture whose service model aligns better with the needs of these data-oriented applications. NDN's name based paradigm makes it easier to provide intelligent features at the network layer rather than at the application layer. This thesis shows that NDN can push several standard features to the network. This work is the first attempt to apply NDN in the context of large scientific data; in the process, this thesis touches upon scientific data naming, name discovery, real-world deployment of NDN for scientific data, feasibility studies, and the designs of in-network protocols for big-data science

Efficient High Performance Protocols For Long Distance Big Data File Transfer

Data sets are collected daily in large amounts (Big Data) and they are increasing rapidly due to various use cases and the number of devices used. Researchers require easy access to Big Data in order to analyze and process it. At some point this data may need to be transferred over the network to various distant locations for further processing and analysis by researchers around the globe. Such data transfers require the use of data transfer protocols that would ensure efficient and fast delivery on high speed networks. There have been several new data transfer protocols introduced which are either TCP-based or UDP-based, and the literature has some comparative analysis studies on such protocols, but not a side-by-side comparison of the protocols used in this work. I considered several data transfer protocols and congestion control mechanisms GridFTP, FASP, QUIC, BBR, and LEDBAT, which are potential candidates for comparison in various scenarios. These protocols aim to utilize the available bandwidth fairly among competing flows and to provide reduced packet loss, reduced latency, and fast delivery of data. In this thesis, I have investigated the behaviour and performance of the data transfer protocols in various scenarios. These scenarios included transfers with various file sizes, multiple flows, background and competing traffic. The results show that FASP and GridFTP had the best performance among all the protocols in most of the scenarios, especially for long distance transfers with large bandwidth delay product (BDP). The performance of QUIC was the lowest due to the nature of its current implementation, which limits the size of the transferred data and the bandwidth used. TCP BBR performed well in short distance scenarios, but its performance degraded as the distance increased. The performance of LEDBAT was unpredictable, so a complete evaluation was not possible. Comparing the performance of protocols with background traffic and competing traffic showed that most of the protocols were fair except for FASP, which was aggressive. Also, the resource utilization for each protocol on the sender and receiver side was measured with QUIC and FASP having the highest CPU utilization

End-to-end quality of service provisioning in multilayer and multidomain environments

Tesis doctoral inédita. Universidad Autónoma de Madrid, Escuela Politécnica Superior, marzo de 200

Data availability in challenging networking environments in presence of failures

This Doctoral thesis presents research on improving data availability in challenging networking environments where failures frequently occur. The thesis discusses the data retrieval and transfer mechanisms in challenging networks such as the Grid and the delay-tolerant networking (DTN). The Grid concept has gained adaptation as a solution to high-performance computing challenges that are faced in international research collaborations. Challenging networking is a novel research area in communications. The first part of the thesis introduces the challenges of data availability in environment where resources are scarce. The focus is especially on the challenges faced in the Grid and in the challenging networking scenarios. A literature overview is given to explain the most important research findings and the state of the standardization work in the field. The experimental part of the thesis consists of eight scientific publications and explains how they contribute to research in the field. Focus in on explaining how data transfer mechanisms have been improved from the application and networking layer points of views. Experimental methods for the Grid scenarios comprise of running a newly developed storage application on the existing research infrastructure. A network simulator is extended for the experimentation with challenging networking mechanisms in a network formed by mobile users. The simulator enables to investigate network behavior with a large number of nodes, and with conditions that are difficult to re-instantiate. As a result, recommendations are given for data retrieval and transfer design for the Grid and mobile networks. These recommendations can guide both system architects and application developers in their work. In the case of the Grid research, the results give first indications on the applicability of the erasure correcting codes for data storage and retrieval with the existing Grid data storage tools. In the case of the challenging networks, the results show how an application-aware communication approach can be used to improve data retrieval and communications. Recommendations are presented to enable efficient transfer and management of data items that are large compared to available resources