Size-based scheduling for TCP flows: Implementation and performance evaluation

Marin, Andrea; Rossi, Sabina; Zen, Carlo

doi:10.1016/j.comnet.2020.107574

Cited by 8 publications

(8 citation statements)

References 28 publications

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“…In a studied Markovian model, each state emits a distinct symbol, facilitating the deduction of state transitions directly from an observation series. In the context of [13,14], the Markovian model generates the TCP flag-combination sequences observed in packets transmitted by the client to a server within the TCP connection. Thus, each state corresponds to a particular arrangement of TCP flags, and each transition represents the receipt of a new packet within the existing TCP connection.…”

Section: State Of the Artmentioning

confidence: 99%

Assessment of Communication Resource Allocation by the Transmission Control Protocol for the Target Virtual Connection under Competitive Conditions

Kovtun,

Grochla

et al. 2024

Electronics

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The mathematical framework presented in this article focuses on the controlled-transmission protocol’s asynchronous process of bandwidth allocation for the target virtual connection implemented under competition for communication resources. The studied process is formalized as a two-dimensional discrete Markovian chain, taking into account the distributions of queue lengths of TCP data fragments from competing client nodes. Such a chain describes the dynamics of filling the stack of transmitted but unacknowledged data fragments of the investigated end device. Distributions of the chain states were found for various ratios of the target virtual-connection bandwidth, transmission-protocol parameters, and communication-channel characteristics. Analytical dependencies for computing the performance of the target virtual connection for different operating modes were obtained. The results of experiments conducted based on the obtained analytical constructions showed that the performance of the virtual connection with a selective repeat mode is mainly determined by the data-loss intensity, the queue size distribution in transit nodes, and the ratio between the protocol window size and the route length.

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Section: State Of the Artmentioning

confidence: 99%

Assessment of Communication Resource Allocation by the Transmission Control Protocol for the Target Virtual Connection under Competitive Conditions

Kovtun,

Grochla

et al. 2024

Electronics

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“…literature has contended with this question in settings like network switches [96], web servers [57], GPU cluster scheduling [54], and TCP ow scheduling [86].…”

Section: Publications Covered In This Thesismentioning

confidence: 99%

“…Some systems limit preemption in a more subtle way than age checkpoints: they have limited priority levels (LPL). For instance, network switches often have a xed number of priority levels built into their hardware [96], and other computer systems have similar constraints [54,57,86]. In terms of SOAP policies, LPL means that a rank function's range must be a nite set.…”

Section: Limited Priority Levelsmentioning

confidence: 99%

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A New Toolbox for Scheduling Theory

Scully

2022

SIGMETRICS Perform. Eval. Rev.

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Queueing delays are ubiquitous in many domains, including computer systems, service systems, communication networks, supply chains, and transportation. Queueing and scheduling theory provide a rigorous basis for understanding how to reduce delays with scheduling, including evaluating policy performance and guiding policy design. Unfortunately, stateof- the-art theory fails to address many practical concerns. For example, scheduling theory seldom treats nontrivial preemption limitations, and there is very little theory for scheduling in multiserver queues. My thesis presents two new, broadly applicable tools that greatly expand the reach of scheduling theory, using each to solve multiple open problems. The first tool, called "SOAP", is a new unifying theory of scheduling in single-server queues, specifically the M/G/1 model. SOAP characterizes the delay distribution of a broad space of policies, most of which have never been analyzed before. Such policies include the Gittins index policy, which minimizes mean delay in low-information settings, and many policies with preemption limitations. The second tool, called "WINE", is a new queueing identity that complements Little's law. WINE enables a new method of analyzing complex queueing systems by relating them to simpler systems. This results in the first delay bounds for Shortest Remaining Processing Time (SRPT) and the Gittins policy in multiserver queues, specifically the M/G/k model. This abstract gives a brief overview of my thesis, describing what the SOAP and WINE tools do, the key ideas underlying them, and the open problems they help solve.

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“…Packet scheduling is performed to avoid congestion by selecting optimal paths and sub-flows [14]. Queue scheduling and path scheduling are also performed for congestion avoidance [15]. Several challenges are present in packet scheduling such as high consumption of bandwidth, high transmission delay, and degradation of throughput which…”

Section: Introductionmentioning

confidence: 99%

Cross-Layer based TCP Performance Enhancement in IoT Networks

Parween¹,

Hussain²

2022

IJACSA

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Transmission Control Protocol (TCP) used multiple paths for performing transmission of data simultaneously to improve its performance. However, previous TCP protocols in Internet of Things (IoT) networks experienced difficulty to transmit a greater number of subflows. To overcome the above issues, we introduced cross-layer framework to perform efficient packet scheduling and congestion control for increasing the performance of TCP in IoT networks. Initially, the proposed IoT network is constructed based on grid topology using Manhattan distance which improves the scalability and flexibility of the network. After network construction, packet scheduling is performed by considering numerous parameters such as bandwidth, delay, buffer rate, etc., using fitness based proportional fair (FPF) scheduling algorithm and selecting best subflow to reduce the transmission delay. The scheduled subflow is sent over an optimal path to improve the throughput and goodput. After packet scheduling, congestion control in TCP is performed using cooperative constraint approximation 3 + (CoCoA3 + -TCP) algorithm in which three stages are employed namely congestion detection, fast retransmission, and recovery. The congestion detection in TCP-IoT environment is performed by considering several parameters in which cat and mouse-based optimization (CMO) is utilized to adaptively estimate retransmission timeout (RTO) for reducing the delay and improving the convergence during retransmission. Fast retransmission and recovery are performed to improve the network performance by adjusting the congestion window size thereby avoiding congestion. The simulation of cross-layer approach is carried out using network simulator (NS-3.26) and the simulation results show that the proposed work outperforms high TCP performance in terms of throughput, goodput, packet loss, and transmission delay, jitter, and congestion window size.

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Size-based scheduling for TCP flows: Implementation and performance evaluation

Cited by 8 publications

References 28 publications

Assessment of Communication Resource Allocation by the Transmission Control Protocol for the Target Virtual Connection under Competitive Conditions

Assessment of Communication Resource Allocation by the Transmission Control Protocol for the Target Virtual Connection under Competitive Conditions

A New Toolbox for Scheduling Theory

Cross-Layer based TCP Performance Enhancement in IoT Networks

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