전체 글29 [Data Networking] Traffic Theory - a brief introduction Organization 1. Traffic Theory for Queuing Systems 2. Model of an Internet Router & Random Process 3. Offered Traffic 4. Stability Condition 5. Markow Chains of Queuing Sysems States 6. M/M/1 Queuing System 7. M/M/N Queuing System 9. M/M/N/0 Loss System Traffic theory allows us to calculate performance metrics for communication networks from analytical models. Queuing Models: analytical models t.. 2023. 1. 15. [Data Networking] Performance Analysis - a brief introduction Organization 1. Packet Switched (PS) Network 2. Netwrok Perfomance Analysis 3. PS Switched Network 4. Types of Delay 5. Packet Loss 6. Throughput 7. Stop & Wait / window / small and large window protocol 8. Goodput In order to use the resources in a network efficiently, we send the information in packets. Network resources are the bandwidth and the switching elements such as routers. In packet s.. 2023. 1. 14. [Data Networking] Protocols, OSI Protocol Stack Organization 1. Definition of protocols 2. Protocol Stack 3. Adding Network elements: Switch 4. Example What is a protocol? - an analogy In a typical daily life conversation, we can observe clear rules Alice and Bob are following while talking to make this conversation a successful conversation. Rules Do not talk at the same time Request requires reponse Specific requests require spefici respons.. 2023. 1. 13. [Stochastische Signale] 마르코프 부등식, 체비쇼프 부등식, 조건독립확률, 마르코프 체인, Organization 1. Markow-Ungleichung 2. Tschebyschow-Ungleichung 3. Das schwache Gesetz der großen Zahlen 4. Bedingte Unabhängigkeit 5. Markowketten 11.4 Markow-Ungleichung 마르코프 부등식은 확률론에서 평균 정보를 이용해(= 기댓값) 자료가 어떤 구간에 위치할 확률이 얼마나 되는 지를 표현할 수 있는 공식이다. 어떠한 자료 X에 대한 E[X]와 Var[X]가 주어졌다고 가정하자. 이때 자료 X가 특정 구간에 위치할 확률이 임의의 식으로 나타낼수 있는가? 아니다, 왜냐하면 확률분포에 따라 답이 그때그때 달라지기 때문이다. 예를들어 X가 Normalverteilung/정규분포를.. 2023. 1. 11. 이전 1 2 3 4 5 ··· 8 다음
