{"id":17485717,"url":"https://github.com/imanghd/computerperformanceevaluation","last_synced_at":"2026-04-19T10:31:49.610Z","repository":{"id":199891599,"uuid":"704024275","full_name":"iManGHD/ComputerPerformanceEvaluation","owner":"iManGHD","description":"Performance and Dependability Lab @ SUT","archived":false,"fork":false,"pushed_at":"2024-10-13T14:57:21.000Z","size":15304,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-10-20T10:03:37.111Z","etag":null,"topics":["hidden-markov-model","performance-analysis","probability","python","simulation"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/iManGHD.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-10-12T11:36:32.000Z","updated_at":"2024-10-13T14:57:24.000Z","dependencies_parsed_at":"2024-10-19T05:33:00.354Z","dependency_job_id":null,"html_url":"https://github.com/iManGHD/ComputerPerformanceEvaluation","commit_stats":null,"previous_names":["imanghd/performanceevaluation_fall_2023","imanghd/computerperformanceevaluation"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iManGHD%2FComputerPerformanceEvaluation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iManGHD%2FComputerPerformanceEvaluation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iManGHD%2FComputerPerformanceEvaluation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/iManGHD%2FComputerPerformanceEvaluation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/iManGHD","download_url":"https://codeload.github.com/iManGHD/ComputerPerformanceEvaluation/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246049619,"owners_count":20715510,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["hidden-markov-model","performance-analysis","probability","python","simulation"],"created_at":"2024-10-19T02:08:34.319Z","updated_at":"2026-04-19T10:31:49.574Z","avatar_url":"https://github.com/iManGHD.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ComputerPerformanceEvaluation\n\nThis repository serves as a comprehensive collection of all the projects, homework assignments, and resources related to the Performance Evaluation course I completed in my fifth semester of my Master's degree at Sharif University of Technology. The course was instructed by Prof. Ali Movaghar from the Department of Computer Engineering. \n\n## Homework 1: M/M/1/K Queue Analysis\n\n**Description:**  \nThis homework involves the analysis of an M/M/1/K queue system, focusing on its performance evaluation. The main task is to compute various performance metrics and analyze their implications.\n\n**Parameters:**\n- **Service Rate (μ):** The rate at which the service is provided.\n- **Arrival Rate (λ):** The rate at which arrivals occur.\n- **Queue Capacity (K):** Set to 14.\n\n**Key Aspects Covered:**\n- **Performance Metrics:** Calculation of the probability of having `n` customers in the system (`P_n`), average number of customers in the system (`N_c`), and probabilities of blocking (`P_b`) and dropping (`P_d`).\n- **Simulation Results:** Results showing the impact of varying parameters on system performance.\n- **Formulas Used:**\n  - `P_n(λ, μ)` for the probability of `n` customers.\n  - `N_c` for the average number of customers.\n  - Calculation of `P_b` and `P_d` using the provided formulas.\n- **Analysis:** Discussion on the impact of different parameters on system performance.\n\n## Homework 2: Round Robin Scheduling Analysis\n\n**Description:**  \nThis homework involves the analysis of the Round Robin scheduling algorithm within a queue system. It focuses on understanding how the Round Robin mechanism affects performance.\n\n**Key Aspects Covered:**\n- **Round Robin Scheduling:** Examination of the algorithm's performance in managing queues.\n- **Performance Metrics:** Analysis of average wait time and throughput under different configurations.\n- **Theoretical Evaluation:**\n  - Calculation of performance metrics with given parameters (μ and θ).\n  - Breakdown of theoretical results and their implications.\n  - Evaluation of the impact of different time slices and system configurations.\n\n## Homework 3: Theoretical Analysis\n\n**Description:**  \nThis is a theoretical assignment that involves detailed questions and answers related to queue systems. It aims to test understanding of queueing theory concepts and their applications.\n\n**Key Aspects Covered:**\n- **Theoretical Questions:** A set of questions designed to explore various aspects of queueing theory.\n- **Solutions:** Detailed answers and explanations for each question, providing insights into the theoretical aspects of queue systems.\n\n---\n\nFor further details on each homework, please refer to the corresponding files in this repository. Feel free to reach out if you have any questions or need additional information.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fimanghd%2Fcomputerperformanceevaluation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fimanghd%2Fcomputerperformanceevaluation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fimanghd%2Fcomputerperformanceevaluation/lists"}