Bounded Delay Scheduling with Packet Dependencies

A common situation occurring when dealing with multimedia traffic is having large data frames fragmented into smaller IP packets, and having these packets sent independently through the network. For real-time multimedia traffic, dropping even few packets of a frame may render the entire frame useless. Such traffic is usually modeled as having {\em inter-packet dependencies}. We study the problem of scheduling traffic with such dependencies, where each packet has a deadline by which it should arrive at its destination. Such deadlines are common for real-time multimedia applications, and are derived from stringent delay constraints posed by the application. The figure of merit in such environments is maximizing the system's {\em goodput}, namely, the number of frames successfully delivered. We study online algorithms for the problem of maximizing goodput of delay-bounded traffic with inter-packet dependencies, and use competitive analysis to evaluate their performance. We present competitive algorithms for the problem, as well as matching lower bounds that are tight up to a constant factor. We further present the results of a simulation study which further validates our algorithmic approach and shows that insights arising from our analysis are indeed manifested in practice

Differentiated Predictive Fair Service for TCP Flows

The majority of the traffic (bytes) flowing over the Internet today have been attributed to the Transmission Control Protocol (TCP). This strong presence of TCP has recently spurred further investigations into its congestion avoidance mechanism and its effect on the performance of short and long data transfers. At the same time, the rising interest in enhancing Internet services while keeping the implementation cost low has led to several service-differentiation proposals. In such service-differentiation architectures, much of the complexity is placed only in access routers, which classify and mark packets from different flows. Core routers can then allocate enough resources to each class of packets so as to satisfy delivery requirements, such as predictable (consistent) and fair service. In this paper, we investigate the interaction among short and long TCP flows, and how TCP service can be improved by employing a low-cost service-differentiation scheme. Through control-theoretic arguments and extensive simulations, we show the utility of isolating TCP flows into two classes based on their lifetime/size, namely one class of short flows and another of long flows. With such class-based isolation, short and long TCP flows have separate service queues at routers. This protects each class of flows from the other as they possess different characteristics, such as burstiness of arrivals/departures and congestion/sending window dynamics. We show the benefits of isolation, in terms of better predictability and fairness, over traditional shared queueing systems with both tail-drop and Random-Early-Drop (RED) packet dropping policies. The proposed class-based isolation of TCP flows has several advantages: (1) the implementation cost is low since it only requires core routers to maintain per-class (rather than per-flow) state; (2) it promises to be an effective traffic engineering tool for improved predictability and fairness for both short and long TCP flows; and (3) stringent delay requirements of short interactive transfers can be met by increasing the amount of resources allocated to the class of short flows.National Science Foundation (CAREER ANI-0096045, MRI EIA-9871022

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

RIFO: Pushing the Efficiency of Programmable Packet Schedulers

Packet scheduling is a fundamental networking task that recently received renewed attention in the context of programmable data planes. Programmable packet scheduling systems such as those based on Push-In First-Out (PIFO) abstraction enabled flexible scheduling policies, but are too resource-expensive for large-scale line rate operation. This prompted research into practical programmable schedulers (e.g., SP-PIFO, AIFO) approximating PIFO behavior on regular hardware. Yet, their scalability remains limited due to extensive number of memory operations. To address this, we design an effective yet resource-efficient packet scheduler, Range-In First-Out (RIFO), which uses only three mutable memory cells and one FIFO queue per PIFO queue. RIFO is based on multi-criteria decision-making principles and uses small guaranteed admission buffers. Our large-scale simulations in Netbench demonstrate that despite using fewer resources, RIFO generally achieves competitive flow completion times across all studied workloads, and is especially effective in workloads with a significant share of large flows, reducing flow completion time up to 2.9x in Datamining workloads compared to state-of-the-art solutions. Our prototype implementation using P4 on Tofino switches requires only 650 lines of code, is scalable, and runs at line rate

G-Snoop: Enhancing TCP performance over wireless networks

Focusing on a general wireless network where a wireless link can be at any link along the sender-to-receiver path, a new TCP enhancement scheme, called Generalized-Snoop (G-Snoop), is proposed. Since many existing applications are built on top of TCP, it is essential that any TCP enhancement scheme should be transparent to the end-systems as well as the fixed networks. To achieve this, G-Snoop only needs to be implemented at the wireless gateways, no other parts of the network require modifications. With G-Snoop, TCP senders are shielded from non-congestion packet loss and thus no unnecessary congestion control mechanisms will be performed. Simulation results show that significant throughout gain can be obtained with G-Snoop.published_or_final_versio