A Study of Application-awareness in Software-defined Data Center Networks

A data center (DC) has been a fundamental infrastructure for academia and industry for many years. Applications in DC have diverse requirements on communication. There are huge demands on data center network (DCN) control frameworks (CFs) for coordinating communication traffic. Simultaneously satisfying all demands is difficult and inefficient using existing traditional network devices and protocols. Recently, the agile software-defined Networking (SDN) is introduced to DCN for speeding up the development of the DCNCF. Application-awareness preserves the application semantics including the collective goals of communications. Previous works have illustrated that application-aware DCNCFs can much more efficiently allocate network resources by explicitly considering applications needs. A transfer application task level application-aware software-defined DCNCF (SDDCNCF) for OpenFlow software-defined DCN (SDDCN) for big data exchange is designed. The SDDCNCF achieves application-aware load balancing, short average transfer application task completion time, and high link utilization. The SDDCNCF is immediately deployable on SDDCN which consists of OpenFlow 1.3 switches. The Big Data Research Integration with Cyberinfrastructure for LSU (BIC-LSU) project adopts the SDDCNCF to construct a 40Gb/s high-speed storage area network to efficiently transfer big data for accelerating big data related researches at Louisiana State University. On the basis of the success of BIC-LSU, a coflow level application-aware SD- DCNCF for OpenFlow-based storage area networks, MinCOF, is designed. MinCOF incorporates all desirable features of existing coflow scheduling and routing frame- works and requires minimal changes on hosts. To avoid the architectural limitation of the OpenFlow SDN implementation, a coflow level application-aware SDDCNCF using fast packet processing library, Coflourish, is designed. Coflourish exploits congestion feedback assistances from SDN switches in the DCN to schedule coflows and can smoothly co-exist with arbitrary applications in a shared DCN. Coflourish is implemented using the fast packet processing library on an SDN switch, Open vSwitch with DPDK. Simulation and experiment results indicate that Coflourish effectively shortens average application completion time

Performance modeling of virtual switching systems

International audienceVirtual switches are a key elements within the new paradigms of Software Defined Networking (SDN) and Network Function Virtualization (NFV). Unlike proprietary networking appliances, virtual switches come with a high level of flexibility in the management of their physical resources such as the number of CPU cores, their allocation to the switching function, and the capacities of the RX queues, which gives the opportunity for an efficient sizing of the system resources. We propose a model for the performance evaluation of a virtual switch. Our model resorts to servers with vacation to capture the involved interactions between queues resulting from the implemented polling strategies. The solution to the model is found using a simple fixed-point iteration and it provides estimates for customary performance metrics such as the attained throughput, the packet latency, the buffer occupancy and the packet loss rate. In the tens of explored examples, the predictions of the model were found to be accurate, thereby allowing their use for the purpose of sizing problems

An Approach for Fast Fault Detection in Virtual Network

The diversity of applications in cloud computing and the dynamic nature of environment deployment makes virtual machines, containers, and distributed software systems to often have various software failures, which make it impossible to provide external services normally. Whether it is cloud management or distributed application itself, it takes a few seconds to find the fault of protocol class detection methods on the management or control surfaces of distributed applications, hundreds of milliseconds to find the fault of protocol class detection methods based on user interfaces, and the main time from the failure to recovery of distributed software systems is spent in detecting the fault. Therefore, timely discovery of faults (virtual machines, containers, software) is the key to subsequent fault diagnosis, isolation and recovery. Considering the network connection of virtual machines/containers in cloud infrastructure, more and more intelligent virtual network cards are used to connect virtual network elements (Virtual Router or Virtual Switch). This paper studies a fault detection mechanism of virtual machines, containers and distributed software based on the message driven mode of virtual network elements. Taking advantage of the VIRTIO message queue memory sharing feature between the front-end and back-end in the virtual network card of the virtualization network element and the virtual machine or container it detects in the same server in the cloud network, when the virtualization network element sends packets to the virtual machine or container, quickly check whether the message on the queue header of the previously sent VIRTIO message has been received and processed. If it has not been received and processed beyond a certain time threshold, it indicates that the virtual machine, the container and distributed software have failed. The method in this paper can significantly improve the fault detection performance of virtual machine/container/distributed application (from the second pole to the millisecond level) for a large number of business message scenarios, and provide faster fault detection for the rapid convergence of virtual network traffic, migration of computing nodes, and high availability of distributed applications

A new model for DPDK-based virtual switches

International audienceIn an SDN/NFV-enabled network, the behavior of virtual switches is a major concern in determining the overall network performance. The prominent open-source solution for virtual switching is Open vSwitch while the DPDK library has been developed to accelerate the packet processing. In this paper, we develop a general framework for the modeling and the analysis of DPDK-based virtual switches, taking into account the switch-over times (amount of time needed for a CPU core to switch from one input queue to another). Our model delivers performance metrics such as the buffer occupancy, the loss rate and the sojourn time of a packet in RX queues. We compare our new model with two existing models. Numerical results show that our model combines the accuracy of one model and the efficiency of the other

High performance network function virtualization for user-oriented services

The Network Function Virtualization (NFV) paradigm proposes to transform those network functions today running on dedicated and often closed appliances (e.g., firewall, wan accelerator) into pure software images, called Virtual Network Functions (VNFs), which can be consolidated and executed on high-volume standard servers. In this context, this dissertation focuses on the possibility of enabling each single end user (and not only network operators) to set up network services by means of NFV, allowing him to custoimize the set of services that are active on his Internet connection. This goal mainly requires to address flexibility and performance issues. Regarding to the former, it is important: (i) to support services including both network (e.g., firewall) and cloud (e.g., storage server) applications; (ii) to allow the user to define the service with an intuitive and high-level abstraction, hiding infrastructure-layer details. Instead, with respect to performance, multiple software-based services operating on the user's traffic should not introduce penalties in the user’s Internet experience. This dissertation solves the above issues by proposing a number of improvements in the context of Network Function Virtualization, both in terms of high level models and architectures to define and instantiate network services, and in terms of mechanisms to efficiently interconnect VNFs. Experimental results demonstrate that the goal of allowing end users to deploy services operating on their own traffic is feasible without impacting the Internet experience

Scalable and Reliable Middlebox Deployment

Middleboxes are pervasive in modern computer networks providing functionalities beyond mere packet forwarding. Load balancers, intrusion detection systems, and network address translators are typical examples of middleboxes. Despite their benefits, middleboxes come with several challenges with respect to their scalability and reliability. The goal of this thesis is to devise middlebox deployment solutions that are cost effective, scalable, and fault tolerant. The thesis includes three main contributions: First, distributed service function chaining with multiple instances of a middlebox deployed on different physical servers to optimize resource usage; Second, Constellation, a geo-distributed middlebox framework enabling a middlebox application to operate with high performance across wide area networks; Third, a fault tolerant service function chaining system

Improving the performance of Virtualized Network Services based on NFV and SDN

Network Functions Virtualisation (NFV) proposes to move all the traditional network appliances, which require dedicated physical machine, onto virtualised environment (e.g,. Virtual Machine). In this way, many of the current physical devices present in the infrastructure are replaced with standard high volume servers, which could be located in Datacenters, at the edge of the network and in the end user premises. This enables a reduction of the required physical resources thanks to the use of virtualization technologies, already used in cloud computing, and allows services to be more dynamic and scalable. However, differently from traditional cloud applications which are rather demanding in terms of CPU power, network applications are mostly I/O bound, hence the virtualization technologies in use (either standard VM-based or lightweight ones) need to be improved to maximize the network performance. A series of Virtual Network Functions (VNFs) can be connected to each other thanks to Software-Defined Networks (SDN) technologies (e.g., OpenFlow) to create a Network Function Forwarding Graph (NF-FG) that processes the network traffic in the configured order of the graph. Using NF-FGs it is possible to create arbitrary chains of services, and transparently configure different virtualized network services, which can be dynamically instantiated and rearranges depending on the requested service and its requirements. However, the above virtualized technologies are rather demanding in terms of hardware resources (mainly CPU and memory), which may have a non-negligible impact on the cost of providing the services according to this paradigm. This thesis will investigate this problem, proposing a set of solutions that enable the novel NFV paradigm to be efficiently used, hence being able to guarantee both flexibility and efficiency in future network services

Sketching as a Tool for Efficient Networked Systems

Today, computer systems need to cope with the explosive growth of data in the world. For instance, in data-center networks, monitoring systems are used to measure traffic statistics at high speed; and in financial technology companies, distributed processing systems are deployed to support graph analytics. To fulfill the requirements of handling such large datasets, we build efficient networked systems in a distributed manner most of the time. Ideally, we expect the systems to meet service-level objectives (SLOs) using the least amount of resource. However, existing systems constructed with conventional in-memory algorithms face the following challenges: (1) excessive resource requirements (e.g., CPU, ASIC, and memory) with high cost; (2) infeasibility in a larger scale; (3) processing the data too slowly to meet the objectives. To address these challenges, we propose sketching techniques as a tool to build more efficient networked systems. Sketching algorithms aim to process the data with one or several passes in an online, streaming fashion (e.g., a stream of network packets), and compute highly accurate results. With sketching, we only maintain a compact summary of the entire data and provide theoretical guarantees on error bounds. This dissertation argues for a sketching based design for large-scale networked systems, and demonstrates the benefits in three application contexts: (i) Network monitoring: we build generic monitoring frameworks that support a range of applications on both software and hardware with universal sketches. (ii) Graph pattern mining: we develop a swift, approximate graph pattern miner that scales to very large graphs by leveraging graph sketching techniques. (iii) Halo finding in N-body simulations: we design scalable halo finders on CPU and GPU by leveraging sketch-based heavy hitter algorithms

QoS-aware architectures, technologies, and middleware for the cloud continuum

The recent trend of moving Cloud Computing capabilities to the Edge of the network is reshaping how applications and their middleware supports are designed, deployed, and operated. This new model envisions a continuum of virtual resources between the traditional cloud and the network edge, which is potentially more suitable to meet the heterogeneous Quality of Service (QoS) requirements of diverse application domains and next-generation applications. Several classes of advanced Internet of Things (IoT) applications, e.g., in the industrial manufacturing domain, are expected to serve a wide range of applications with heterogeneous QoS requirements and call for QoS management systems to guarantee/control performance indicators, even in the presence of real-world factors such as limited bandwidth and concurrent virtual resource utilization. The present dissertation proposes a comprehensive QoS-aware architecture that addresses the challenges of integrating cloud infrastructure with edge nodes in IoT applications. The architecture provides end-to-end QoS support by incorporating several components for managing physical and virtual resources. The proposed architecture features: i) a multilevel middleware for resolving the convergence between Operational Technology (OT) and Information Technology (IT), ii) an end-to-end QoS management approach compliant with the Time-Sensitive Networking (TSN) standard, iii) new approaches for virtualized network environments, such as running TSN-based applications under Ultra-low Latency (ULL) constraints in virtual and 5G environments, and iv) an accelerated and deterministic container overlay network architecture. Additionally, the QoS-aware architecture includes two novel middlewares: i) a middleware that transparently integrates multiple acceleration technologies in heterogeneous Edge contexts and ii) a QoS-aware middleware for Serverless platforms that leverages coordination of various QoS mechanisms and virtualized Function-as-a-Service (FaaS) invocation stack to manage end-to-end QoS metrics. Finally, all architecture components were tested and evaluated by leveraging realistic testbeds, demonstrating the efficacy of the proposed solutions