Downstream Bandwidth Management for Emerging DOCSIS-based Networks

In this dissertation, we consider the downstream bandwidth management in the context of emerging DOCSIS-based cable networks. The latest DOCSIS 3.1 standard for cable access networks represents a significant change to cable networks. For downstream, the current 6 MHz channel size is replaced by a much larger 192 MHz channel which potentially can provide data rates up to 10 Gbps. Further, the current standard requires equipment to support a relatively new form of active queue management (AQM) referred to as delay-based AQM. Given that more than 50 million households (and climbing) use cable for Internet access, a clear understanding of the impacts of bandwidth management strategies used in these emerging networks is crucial. Further, given the scope of the change provided by emerging cable systems, now is the time to develop and introduce innovative new methods for managing bandwidth. With this motivation, we address research questions pertaining to next generation of cable access networks. The cable industry has had to deal with the problem of a small number of subscribers who utilize the majority of network resources. This problem will grow as access rates increase to gigabits per second. Fundamentally this is a problem on how to manage data flows in a fair manner and provide protection. A well known performance issue in the Internet, referred to as bufferbloat, has received significant attention recently. High throughput network flows need sufficiently large buffer to keep the pipe full and absorb occasional burstiness. Standard practice however has led to equipment offering very large unmanaged buffers that can result in sustained queue levels increasing packet latency. One reason why these problems continue to plague cable access networks is the desire for low complexity and easily explainable (to access network subscribers and to the Federal Communications Commission) bandwidth management. This research begins by evaluating modern delay-based AQM algorithms in downstream DOCSIS 3.0 environments with a focus on fairness and application performance capabilities of single queue AQMs. We are especially interested in delay-based AQM schemes that have been proposed to combat the bufferbloat problem. Our evaluation involves a variety of scenarios that include tiered services and application workloads. Based on our results, we show that in scenarios involving realistic workloads, modern delay-based AQMs can effectively mitigate bufferbloat. However they do not address the other problem related to managing the fairness. To address the combined problem of fairness and bufferbloat, we propose a novel approach to bandwidth management that provides a compromise among the conflicting requirements. We introduce a flow quantization method referred to as adaptive bandwidth binning where flows that are observed to consume similar levels of bandwidth are grouped together with the system managed through a hierarchical scheduler designed to approximate weighted fairness while addressing bufferbloat. Based on a simulation study that considers many system experimental parameters including workloads and network configurations, we provide evidence of the efficacy of the idea. Our results suggest that the scheme is able to provide long term fairness and low delay with a performance close to that of a reference approach based on fair queueing. A further contribution is our idea for replacing `tiered\u27 levels of service based on service rates with tiering based on weights. The application of our bandwidth binning scheme offers a timely and innovative alternative to broadband service that leverages the potential offered by emerging DOCSIS-based cable systems

Evaluation of the Impact of Packet Drops due to AQM over Capacity Limited Paths

Postprin

DOWNSTREAM RESOURCE ALLOCATION IN DOCSIS 3.0 CHANNEL BONDED NETWORKS

Modern broadband internet access cable systems follow the Data Over Cable System Interface Specification (DOCSIS) for data transfer between the individual cable modem (CM) and the Internet. The newest version of DOCSIS, version 3.0, provides an abstraction referred to as bonding groups to help manage bandwidth and to increase bandwidth to each user beyond that available within a single 6MHz. television channel. Channel bonding allows more than one channel to be used by a CM to provide a virtual channel of much greater bandwidth. This combining of channels into bonding groups, especially when channels overlap between more than one bonding group, complicates the resource allocation problem within these networks. The goal of resource allocation in this research is twofold, to provide for fairness among users while at the same time making maximum possible utilization of the available system bandwidth. The problem of resource allocation in computer networks has been widely studied by the academic community. Past work has studied resource allocation in many network types, however application in a DOCSIS channel bonded network has not been explored. This research begins by first developing a definition of fairness in a channel bonded system. After providing a theoretical definition of fairness we implement simulations of different scheduling disciplines and evaluate their performance against this theoretical ideal. The complexity caused by overlapped channels requires even the simplest scheduling algorithms to be modified to work correctly. We then develop an algorithm to maximize the use of the available system bandwidth. The approach involves using competitive analysis techniques and an online algorithm to dynamically reassign flows among the available channels. Bandwidth usage and demand requests are monitored for bandwidth that is underutilized, and demand that is unsatisfied, and real time changes are made to the flow-to-channel mappings to improve the utilization of the total available bandwidth. The contribution of this research is to provide a working definition of fairness in a channel bonded environment, the implementation of several scheduling disciplines and evaluation of their adherence to that definition, and development of an algorithm to improve overall bandwidth utilization of the system

FAST Copper for Broadband Access

FAST Copper is a multi-year, U.S. NSF funded project that started in 2004, and is jointly pursued by the research groups of Mung Chiang at Princeton University, John Cioffi at Stanford University, and Alexander Fraser at Fraser Research Lab, and in collaboration with several industrial partners including AT&T. The goal of the FAST Copper Project is to provide ubiquitous, 100 Mbps, fiber/DSL broadband access to everyone in the US with a phone line. This goal will be achieved through two threads of research: dynamic and joint optimization of resources in Frequency, Amplitude, Space, and Time (thus the name 'FAST') to overcome the attenuation and crosstalk bottlenecks, and the integration of communication, networking, computation, modeling, and distributed information management and control for the multi-user twisted pair network

WiMAX Scheduling Algorithm Key Issue and Design Challenges: Survey

In recent time to satisfy the growing demand of broadband wireless access by using scare Resource of bandwidth is a biggest challenge for Researchers, in this time WiMAX (Worldwide Interopretability for Microwave Access) emerged as a better solution to fulfill that demand. WiMAX provides faster internet connectivity in Urban Areas as well as remote areas also where to deploy the DSL (Digital Subscriber Line) or other wired technology is difficult task. WiMAX structure is based on IEEE 802.16 OSI standard and defines the PMP (Point to Multipoint) and Mesh modes for transmission of information. To provide authentic services for voice, data and videos WiMAX define the various QoS parameters at Media Access Control (MAC) layer. In order to meet the QoS requirement Novel scheduling approach are required. In these papers efforts are made to examine and compare the various scheduling algorithm and its design challenges to implement the effective scheduling algorithm. It also discusses the various QoS parameters associated with scheduling approaches. DOI: 10.17762/ijritcc2321-8169.15083