Optimizing Computations and Allocations on High Performance and Cloud Computing Systems

Over the last decade, many research and development projects have focused on Cloud Computing systems. After forming around the early research papers and the first commercial cloud offerings in 2006-2008, the field has seen a tremendous progress and has provided the primary infrastructure and technology for applications at small, medium, and large scales. Cloud Computing systems have provided diverse on-demand resources to individual researchers and developers, groups and entire institutions, as well as commercial companies and government organizations. Clouds have also found their niche in scientific computing applications, offering attractive alternatives to High Performance Computing models and systems. While cloud economics and technologies have significantly matured recently, there is much active research revolving around topics such as optimality, usability, manageability, and reproducibility in the latest studies. This dissertation presents our findings and relevant developments at the intersection of Cloud Computing and such “flavors” of computing as High Performance Computing and High Throughput Computing. We primarily focus on optimality issues in this area and propose solutions that address the needs of individual researchers and research groups with limited computational and financial resources

Optimizing Computations and Allocations on High Performance and Cloud Computing Systems

Over the last decade, many research and development projects have focused on Cloud Computing systems. After forming around the early research papers and the first commercial cloud offerings in 2006-2008, the field has seen a tremendous progress and has provided the primary infrastructure and technology for applications at small, medium, and large scales. Cloud Computing systems have provided diverse on-demand resources to individual researchers and developers, groups and entire institutions, as well as commercial companies and government organizations. Clouds have also found their niche in scientific computing applications, offering attractive alternatives to High Performance Computing models and systems. While cloud economics and technologies have significantly matured recently, there is much active research revolving around topics such as optimality, usability, manageability, and reproducibility in the latest studies. This dissertation presents our findings and relevant developments at the intersection of Cloud Computing and such “flavors” of computing as High Performance Computing and High Throughput Computing. We primarily focus on optimality issues in this area and propose solutions that address the needs of individual researchers and research groups with limited computational and financial resources

QOE-AWARE CONTENT DISTRIBUTION SYSTEMS FOR ADAPTIVE BITRATE VIDEO STREAMING

A prodigious increase in video streaming content along with a simultaneous rise in end system capabilities has led to the proliferation of adaptive bit rate video streaming users in the Internet. Today, video streaming services range from Video-on-Demand services like traditional IP TV to more recent technologies such as immersive 3D experiences for live sports events. In order to meet the demands of these services, the multimedia and networking research community continues to strive toward efficiently delivering high quality content across the Internet while also trying to minimize content storage and delivery costs. The introduction of flexible and adaptable technologies such as compute and storage clouds, Network Function Virtualization and Software Defined Networking continue to fuel content provider revenue. Today, content providers such as Google and Facebook build their own Software-Defined WANs to efficiently serve millions of users worldwide, while NetFlix partners with ISPs such as ATT (using OpenConnect) and cloud providers such as Amazon EC2 to serve their content and manage the delivery of several petabytes of high-quality video content for millions of subscribers at a global scale, respectively. In recent years, the unprecedented growth of video traffic in the Internet has seen several innovative systems such as Software Defined Networks and Information Centric Networks as well as inventive protocols such as QUIC, in an effort to keep up with the effects of this remarkable growth. While most existing systems continue to sub-optimally satisfy user requirements, future video streaming systems will require optimal management of storage and bandwidth resources that are several orders of magnitude larger than what is implemented today. Moreover, Quality-of-Experience metrics are becoming increasingly fine-grained in order to accurately quantify diverse content and consumer needs. In this dissertation, we design and investigate innovative adaptive bit rate video streaming systems and analyze the implications of recent technologies on traditional streaming approaches using real-world experimentation methods. We provide useful insights for current and future content distribution network administrators to tackle Quality-of-Experience dilemmas and serve high quality video content to several users at a global scale. In order to show how Quality-of-Experience can benefit from core network architectural modifications, we design and evaluate prototypes for video streaming in Information Centric Networks and Software-Defined Networks. We also present a real-world, in-depth analysis of adaptive bitrate video streaming over protocols such as QUIC and MPQUIC to show how end-to-end protocol innovation can contribute to substantial Quality-of-Experience benefits for adaptive bit rate video streaming systems. We investigate a cross-layer approach based on QUIC and observe that application layer-based information can be successfully used to determine transport layer parameters for ABR streaming applications

Intent-based network slicing for SDN vertical services with assurance: Context, design and preliminary experiments

Network slicing is announced to be one of the key features for 5G infrastructures enabling network operators to provide network services with the flexibility and dynamicity necessary for the vertical services, while relying on Network Function Virtualization (NFV) and Software-defined Networking (SDN). On the other hand, vertical industries are attracted by flexibility and customization offered by operators through network slicing, especially if slices come with in-built SDN capabilities to programmatically connect their application components and if they are relieved of dealing with detailed technicalities of the underlying (virtual) infrastructure. In this paper, we present an Intent-based deployment of a NFV orchestration stack that allows for the setup of Qos-aware and SDN-enabled network slices toward effective service chaining in the vertical domain. The main aim of the work is to simplify and automate the deployment of tenant-managed SDN-enabled network slices through a declarative approach while abstracting the underlying implementation details and unburdening verticals to deal with technology-specific low-level networking directives. In our approach, the intent-based framework we propose is based on an ETSI NFV MANO platform and is assessed through a set of experimental results demonstrating its feasibility and effectiveness

Rumba : a Python framework for automating large-scale recursive internet experiments on GENI and FIRE+

It is not easy to design and run Convolutional Neural Networks (CNNs) due to: 1) finding the optimal number of filters (i.e., the width) at each layer is tricky, given an architecture; and 2) the computational intensity of CNNs impedes the deployment on computationally limited devices. Oracle Pruning is designed to remove the unimportant filters from a well-trained CNN, which estimates the filters’ importance by ablating them in turn and evaluating the model, thus delivers high accuracy but suffers from intolerable time complexity, and requires a given resulting width but cannot automatically find it. To address these problems, we propose Approximated Oracle Filter Pruning (AOFP), which keeps searching for the least important filters in a binary search manner, makes pruning attempts by masking out filters randomly, accumulates the resulting errors, and finetunes the model via a multi-path framework. As AOFP enables simultaneous pruning on multiple layers, we can prune an existing very deep CNN with acceptable time cost, negligible accuracy drop, and no heuristic knowledge, or re-design a model which exerts higher accuracy and faster inferenc

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

Performance Considerations of Network Functions Virtualization using Containers

The network performance of virtual machines plays a critical role in Network Functions Virtualization (NFV), and several technologies have been developed to address hardware-level virtualization shortcomings. Recent advances in operating system level virtualization and deployment platforms such as Docker have made containers an ideal candidate for high performance application encapsulation and deployment. However, Docker and other solutions typically use lower-performing networking mechanisms. In this paper, we explore the feasibility of using technologies designed to accelerate virtual machine networking with containers, in addition to quantifying the network performance of container-based VNFs compared to the state-of-the-art virtual machine solutions. Our results show that containerized applications can provide lower latency and delay variation, and can take advantage of high performance networking technologies previously only used for hardware virtualization

Scaling your experiments

National audienceThere is a wide range of options to experiment on distributed systems and networking. Simulators running on a laptop or self-made testbeds are sometimes enough, but our field usually targets large to very large systems with potentially millions or billions of elements. In such a case, relying on a laptop or a self-made testbed is impossible. To scale up our experimental research, we can rely on larger-scale infrastructures and testbeds.In a first part, this talk will provide an overview of the landscape of infrastructures and testbeds supporting experimental research in distributed systems and networking.In a second part, we will focus on SDN/NFV experimentation, and will provide some feedback about the current state of available experimentation tools targeting large scale systems

Improving Resilience of Communication in Information Dissemination for Time-Critical Applications

Severe weather impacts life and in this dire condition, people rely on communication, to organize relief and stay in touch with their loved ones. In such situations, cellular network infrastructure\footnote{We refer to cellular network infrastructure as infrastructure for the entirety of this document} might be affected due to power outage, link failures, etc. This urges us to look at Ad-hoc mode of communication, to offload major traffic partially or fully from the infrastructure, depending on the status of it. We look into threefold approach, ranging from the case where the infrastructure is completely unavailable, to where it has been replaced by make shift low capacity mobile cellular base station. First, we look into communication without infrastructure and timely, dissemination of weather alerts specific to geographical areas. We look into the specific case of floods as they affect significant number of people. Due to the nature of the problem we can utilize the properties of Information Centric Networking (ICN) in this context, namely: i) Flexibility and high failure resistance: Any node in the network that has the information can satisfy the query ii) Robust: Only sensor and car need to communicate iii) Fine grained geo-location specific information dissemination. We analyze how message forwarding using ICN on top of Ad hoc network, approach compares to the one based on infrastructure, that is less resilient in the case of disaster. In addition, we compare the performance of different message forwarding strategies in VANETs (Vehicular Adhoc Networks) using ICN. Our results show that ICN strategy outperforms the infrastructure-based approach as it is 100 times faster for 63\% of total messages delivered. Then we look into the case where we have the cellular network infrastructure, but it is being pressured due to rapid increase in volume of network traffic (as seen during a major event) or it has been replaced by low capacity mobile tower. In this case we look at offloading as much traffic as possible from the infrastructure to device-to-device communication. However, the host-oriented model of the TCP/IP-based Internet poses challenges to this communication pattern. A scheme that uses an ICN model to fetch content from nearby peers, increases the resiliency of the network in cases of outages and disasters. We collected content popularity statistics from social media to create a content request pattern and evaluate our approach through the simulation of realistic urban scenarios. Additionally, we analyze the scenario of large crowds in sports venues. Our simulation results show that we can offload traffic from the backhaul network by up to 51.7\%, suggesting an advantageous path to support the surge in traffic while keeping complexity and cost for the network operator at manageable levels. Finally, we look at adaptive bit-rate streaming (ABR) streaming, which has contributed significantly to the reduction of video playout stalling, mainly in highly variable bandwidth conditions. ABR clients continue to suffer from the variation of bit rate qualities over the duration of a streaming session. Similar to stalling, these variations in bit rate quality have a negative impact on the users’ Quality of Experience (QoE). We use a trace from a large-scale CDN to show that such quality changes occur in a significant amount of streaming sessions and investigate an ABR video segment retransmission approach to reduce the number of such quality changes. As the new HTTP/2 standard is becoming increasingly popular, we also see an increase in the usage of HTTP/2 as an alternative protocol for the transmission of web traffic including video streaming. Using various network conditions, we conduct a systematic comparison of existing transport layer approaches for HTTP/2 that is best suited for ABR segment retransmissions. Since it is well known that both protocols provide a series of improvements over HTTP/1.1, we perform experiments both in controlled environments and over transcontinental links in the Internet and find that these benefits also “trickle up” into the application layer when it comes to ABR video streaming where HTTP/2 retransmissions can significantly improve the average quality bitrate while simultaneously minimizing bit rate variations over the duration of a streaming session. Taking inspiration from the first two approaches, we take into account the resiliency of a multi-path approach and further look at a multi-path and multi-stream approach to ABR streaming and demonstrate that losses on one path have very little impact on the other from the same multi-path connection and this increases throughput and resiliency of communication