758 research outputs found
Design and analysis of TCP AIMD in wireless networks
The class of additive-increase/multiplicative-decrease (AIMD) algorithms constitutes a key mechanism for congestion control in modern communication networks, like the current Internet. The algorithmic behaviour may, however, be distorted when wireless links are present. Specifically, spurious window reductions may be triggered due to packet reordering and non-congestive loss. In this paper, we develop a framework for AIMD in TCP to analyze the aforementioned problem. The framework enables a systematic analysis of the existing AIMD-based TCP variants and assists in the design of new TCP variants. It classifies the existing AIMD-based TCP variants into two main streams, known as compensators and differentiators, and develops a generic expression that covers the rate adaptation processes of both approaches. It further identifies a new approach in enhancing the performance of TCP, known as the compensation scheme. A tax-rebate approach is proposed as an approximation of the compensation scheme, and used to enhance the AIMD-based TCP variants to offer unified solutions for effective congestion control, sequencing control, and error control. In traditional wired networks, the new family of TCP variants with the proposed enhancements automatically preserves the same inter-flow fairness and TCP friendliness. We have conducted a series of simulations to examine their performance under various network scenarios. In most scenarios, significant performance gains are attained. © 2013 IEEE.published_or_final_versio
Evaluation Study for Delay and Link Utilization with the New-Additive Increase Multiplicative Decrease Congestion Avoidance and Control Algorithm
As the Internet becomes increasingly heterogeneous, the issue of congestion
avoidance and control becomes ever more important. And the queue length,
end-to-end delays and link utilization is some of the important things in term
of congestion avoidance and control mechanisms. In this work we continue to
study the performances of the New-AIMD (Additive Increase Multiplicative
Decrease) mechanism as one of the core protocols for TCP congestion avoidance
and control algorithm, we want to evaluate the effect of using the AIMD
algorithm after developing it to find a new approach, as we called it the
New-AIMD algorithm to measure the Queue length, delay and bottleneck link
utilization, and use the NCTUns simulator to get the results after make the
modification for the mechanism. And we will use the Droptail mechanism as the
active queue management mechanism (AQM) in the bottleneck router. After
implementation of our new approach with different number of flows, we expect
the delay will less when we measure the delay dependent on the throughput for
all the system, and also we expect to get end-to-end delay less. And we will
measure the second type of delay a (queuing delay), as we shown in the figure 1
bellow. Also we will measure the bottleneck link utilization, and we expect to
get high utilization for bottleneck link with using this mechanism, and avoid
the collisions in the link
Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-in Hybrid Electric Buses
We discuss a recently introduced ECO-driving concept known as SPONGE in the
context of Plug-in Hybrid Electric Buses (PHEB)'s.Examples are given to
illustrate the benefits of this approach to ECO-driving. Finally, distributed
algorithms to realise SPONGE are discussed, paying attention to the privacy
implications of the underlying optimisation problems.Comment: This paper is recently submitted to the IEEE Transactions on
Automation Science and Engineerin
FAST TCP: Motivation, Architecture, Algorithms, Performance
We describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties which the current TCP implementation has at large windows. We describe the architecture and summarize some of the algorithms implemented in our prototype. We characterize its equilibrium and stability properties. We evaluate it experimentally in terms of throughput, fairness, stability, and responsiveness
Reducing Congestion Effects by Multipath Routing in Wireless Networks
We propose a solution to improve fairness and increasethroughput in wireless networks with location information.Our approach consists of a multipath routing protocol, BiasedGeographical Routing (BGR), and two congestion controlalgorithms, In-Network Packet Scatter (IPS) and End-to-EndPacket Scatter (EPS), which leverage BGR to avoid the congestedareas of the network. BGR achieves good performancewhile incurring a communication overhead of just 1 byte perdata packet, and has a computational complexity similar togreedy geographic routing. IPS alleviates transient congestion bysplitting traffic immediately before the congested areas. In contrast,EPS alleviates long term congestion by splitting the flow atthe source, and performing rate control. EPS selects the pathsdynamically, and uses a less aggressive congestion controlmechanism on non-greedy paths to improve energy efficiency.Simulation and experimental results show that our solutionachieves its objectives. Extensive ns-2 simulations show that oursolution improves both fairness and throughput as compared tosingle path greedy routing. Our solution reduces the variance ofthroughput across all flows by 35%, reduction which is mainlyachieved by increasing throughput of long-range flows witharound 70%. Furthermore, overall network throughput increasesby approximately 10%. Experimental results on a 50-node testbed are consistent with our simulation results, suggestingthat BGR is effective in practice
Communication-efficient Distributed Multi-resource Allocation
In several smart city applications, multiple resources must be allocated
among competing agents that are coupled through such shared resources and are
constrained --- either through limitations of communication infrastructure or
privacy considerations. We propose a distributed algorithm to solve such
distributed multi-resource allocation problems with no direct inter-agent
communication. We do so by extending a recently introduced additive-increase
multiplicative-decrease (AIMD) algorithm, which only uses very little
communication between the system and agents. Namely, a control unit broadcasts
a one-bit signal to agents whenever one of the allocated resources exceeds
capacity. Agents then respond to this signal in a probabilistic manner. In the
proposed algorithm, each agent makes decision of its resource demand locally
and an agent is unaware of the resource allocation of other agents. In
empirical results, we observe that the average allocations converge over time
to optimal allocations.Comment: To appear in IEEE International Smart Cities Conference (ISC2 2018),
Kansas City, USA, September, 2018. arXiv admin note: substantial text overlap
with arXiv:1711.0197
Derandomized Distributed Multi-resource Allocation with Little Communication Overhead
We study a class of distributed optimization problems for multiple shared
resource allocation in Internet-connected devices. We propose a derandomized
version of an existing stochastic additive-increase and multiplicative-decrease
(AIMD) algorithm. The proposed solution uses one bit feedback signal for each
resource between the system and the Internet-connected devices and does not
require inter-device communication. Additionally, the Internet-connected
devices do not compromise their privacy and the solution does not dependent on
the number of participating devices. In the system, each Internet-connected
device has private cost functions which are strictly convex, twice continuously
differentiable and increasing. We show empirically that the long-term average
allocations of multiple shared resources converge to optimal allocations and
the system achieves minimum social cost. Furthermore, we show that the proposed
derandomized AIMD algorithm converges faster than the stochastic AIMD algorithm
and both the approaches provide approximately same solutions
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