156 research outputs found
TCP-Aware Backpressure Routing and Scheduling
In this work, we explore the performance of backpressure routing and
scheduling for TCP flows over wireless networks. TCP and backpressure are not
compatible due to a mismatch between the congestion control mechanism of TCP
and the queue size based routing and scheduling of the backpressure framework.
We propose a TCP-aware backpressure routing and scheduling that takes into
account the behavior of TCP flows. TCP-aware backpressure (i) provides
throughput optimality guarantees in the Lyapunov optimization framework, (ii)
gracefully combines TCP and backpressure without making any changes to the TCP
protocol, (iii) improves the throughput of TCP flows significantly, and (iv)
provides fairness across competing TCP flows
Accelerated Backpressure Algorithm
We develop an Accelerated Back Pressure (ABP) algorithm using Accelerated
Dual Descent (ADD), a distributed approximate Newton-like algorithm that only
uses local information. Our construction is based on writing the backpressure
algorithm as the solution to a network feasibility problem solved via
stochastic dual subgradient descent. We apply stochastic ADD in place of the
stochastic gradient descent algorithm. We prove that the ABP algorithm
guarantees stable queues. Our numerical experiments demonstrate a significant
improvement in convergence rate, especially when the packet arrival statistics
vary over time.Comment: 9 pages, 4 figures. A version of this work with significantly
extended proofs is being submitted for journal publicatio
Diff-Max: Separation of routing and scheduling in backpressure-based wireless networks
Original manuscript September 19, 2012Backpressure routing and scheduling, with throughput-optimal operation guarantee, is a promising technique to improve throughput in wireless multi-hop networks. Although backpressure is conceptually viewed as layered, the decisions of routing and scheduling are made jointly, which imposes several challenges in practice. In this work, we present Diff-Max, an approach that separates routing and scheduling and has three strengths: (i) Diff-Max improves throughput significantly, (ii) the separation of routing and scheduling makes practical implementation easier by minimizing cross-layer operations; i.e., routing is implemented in the network layer and scheduling is implemented in the link layer, and (iii) the separation of routing and scheduling leads to modularity; i.e., routing and scheduling are independent modules in Diff-Max, and one can continue to operate even if the other does not. Our approach is grounded in a network utility maximization (NUM) formulation and its solution. Based on the structure of Diff-Max, we propose two practical schemes: Diff-subMax and wDiff-subMax. We demonstrate the benefits of our schemes through simulation in ns-2.National Science Foundation (U.S.) (Grant CNS-0915988)United States. Office of Naval Research (Grant N00014-12-1-0064)United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-08-1-0238
Towards Fast-Convergence, Low-Delay and Low-Complexity Network Optimization
Distributed network optimization has been studied for well over a decade.
However, we still do not have a good idea of how to design schemes that can
simultaneously provide good performance across the dimensions of utility
optimality, convergence speed, and delay. To address these challenges, in this
paper, we propose a new algorithmic framework with all these metrics
approaching optimality. The salient features of our new algorithm are
three-fold: (i) fast convergence: it converges with only
iterations that is the fastest speed among all the existing algorithms; (ii)
low delay: it guarantees optimal utility with finite queue length; (iii) simple
implementation: the control variables of this algorithm are based on virtual
queues that do not require maintaining per-flow information. The new technique
builds on a kind of inexact Uzawa method in the Alternating Directional Method
of Multiplier, and provides a new theoretical path to prove global and linear
convergence rate of such a method without requiring the full rank assumption of
the constraint matrix
A Survey on Delay-Aware Resource Control for Wireless Systems --- Large Deviation Theory, Stochastic Lyapunov Drift and Distributed Stochastic Learning
In this tutorial paper, a comprehensive survey is given on several major
systematic approaches in dealing with delay-aware control problems, namely the
equivalent rate constraint approach, the Lyapunov stability drift approach and
the approximate Markov Decision Process (MDP) approach using stochastic
learning. These approaches essentially embrace most of the existing literature
regarding delay-aware resource control in wireless systems. They have their
relative pros and cons in terms of performance, complexity and implementation
issues. For each of the approaches, the problem setup, the general solution and
the design methodology are discussed. Applications of these approaches to
delay-aware resource allocation are illustrated with examples in single-hop
wireless networks. Furthermore, recent results regarding delay-aware multi-hop
routing designs in general multi-hop networks are elaborated. Finally, the
delay performance of the various approaches are compared through simulations
using an example of the uplink OFDMA systems.Comment: 58 pages, 8 figures; IEEE Transactions on Information Theory, 201
Analyzing Linear Communication Networks using the Ribosome Flow Model
The Ribosome Flow Model (RFM) describes the unidirectional movement of
interacting particles along a one-dimensional chain of sites. As a site becomes
fuller, the effective entry rate into this site decreases. The RFM has been
used to model and analyze mRNA translation, a biological process in which
ribosomes (the particles) move along the mRNA molecule (the chain), and decode
the genetic information into proteins.
Here we propose the RFM as an analytical framework for modeling and analyzing
linear communication networks. In this context, the moving particles are
data-packets, the chain of sites is a one dimensional set of ordered buffers,
and the decreasing entry rate to a fuller buffer represents a kind of
decentralized backpressure flow control. For an RFM with homogeneous link
capacities, we provide closed-form expressions for important network metrics
including the throughput and end-to-end delay. We use these results to analyze
the hop length and the transmission probability (in a contention access mode)
that minimize the end-to-end delay in a multihop linear network, and provide
closed-form expressions for the optimal parameter values
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