A recent CCF‑A conference paper reveals that an adaptive K‑value backoff lock, derived from queueing theory and implemented in Apache RocketMQ, can replace both spin and mutex locks, achieving up to 37.58% performance gains on x86 CPUs and 32.82% on ARM while reducing CPU usage and resource consumption.
This article explores the two‑stage LLM inference pipeline, introduces TTFT and TPOT metrics, explains the motivation for prefilling‑decoding separation, presents experimental comparisons between split and merged architectures, and details optimization techniques and parallel‑strategy modeling for DistServe.
This article compiles recent model articles for students, summarizing key resources on probability models, including Monte Carlo simulation, Markov processes, queueing theory, and Bayesian methods, with links to detailed explanations and applications.
Using queueing theory and traffic flow equations, this article builds a mathematical model to explain why travel times during the Mid‑Autumn and National Day holidays can be three times longer than normal, analyzing highway speed, vehicle density, entry/exit delays, and sensitivity of key parameters.
This article introduces core queueing theory concepts such as Kendall notation, M/M/1 and M/M/c models, Little’s Law, Erlang formulas, and demonstrates their practical application through a detailed Python simulation of a bank service system.
This article introduces queueing theory, explains its mathematical models—including input, service, and queueing rules—covers the Kendall notation and outlines the main performance indicators such as queue length, waiting time, busy period, and utilization.
This article compiles recent resources on probability and statistical modeling, covering Monte Carlo simulation, Markov processes, queueing theory, and Bayesian methods, providing direct links to each detailed write‑up for students and researchers seeking comprehensive study material.
This curated list groups recent explanatory and simulation model articles—covering clustering analysis, linear regression, queueing theory, Markov chains, and Monte Carlo methods—into easy-to-navigate sections for quick reference, helping students and practitioners locate relevant resources efficiently.
This article models a single-mechanic repair shop as a single-server queue with exponentially distributed arrivals and uniformly distributed service times, then uses Python to simulate one workday and 1,000 workdays, reporting average daily serviced customers and average customer waiting time.
This article derives the theoretical model of a multi‑server queueing system, detailing Poisson arrivals, exponential service times, state balance equations, and formulas for average queue length, system size, waiting and sojourn times.
This article introduces the fundamentals of queueing theory, covering basic models, the structure of input and service processes, Kendall notation, and the primary performance indicators used to evaluate and optimize queueing systems.
This article walks through the theoretical derivation of the classic M/M/1 queueing model, detailing arrival and service rates, state balance equations, performance metrics such as utilization, average number in system, average waiting time, and average residence time, with illustrative formulas and explanations.
