WiFi MAC Models David Malone

Size: px
Start display at page:

Download "WiFi MAC Models David Malone"

Transcription

1 WiFi MAC Models David Malone November 26, MACSI Hamilton Institute, NUIM, Ireland

2 Talk outline Introducing the CSMA/CA MAC. Finite load model and its predictions. Issues with standard 82.11, leading to 82.11e. Finite load 82.11e model and its predictions. Beyond infrastructure mode networks. Why do these models work? Hamilton Institute, NUIM, Ireland 1

3 The MAC Data Ack Select Random Number in [,31] Pause Counter Resume Counter Expires; Transmit Decrement counter SIFS DIFS SIFS DIFS Figure 1: MAC operation Hamilton Institute, NUIM, Ireland 2

4 82.11 MAC Summary After transmission choose rand(, CW 1). Wait until medium idle for DIFS(5µs), While idle count down in slots (2µs). Transmission when counter gets to, ACK after SIFS (1µs). If ACK then CW = CW min else CW = 2. Ideally produces even distribution of packet transmission. Hamilton Institute, NUIM, Ireland 3

5 Modelling approaches P-persistent: approximate the back-off distribution be a geometric with the same mean. Exemplified by Marco Conti and co-authors. Asymptotic full system analysis: Bordenave, McDonald and Proutiere + Sharma, Ganesh and Key. Bianchi s mean-field Markov model: treat stations individually; network relationship between stations gives a set of coupling equations. In simplest form: constant transmission probability τ gives throughput S = nτ(1 τ) n 1, (1) and collision probability 1 p = (1 τ) n 1. (2) Hamilton Institute, NUIM, Ireland 4

6 Mean-field Markov Overview Mean field approximation: each individual station s impact on overall network is small. Assume a fixed probability of collision given attempted transmission p. Each station s back-off counter then a Markov chain. Stationary distribution gives the probability the station attempts transmission in a typical slot τ(p). Network coupling then gives a system of equations relating all stations p and τ, which determines everything. Real-time quantities determined through a relation involving the average real-time that passes during a counter decrement. Following to appear in IEEE/ACM ToN (Duffy, Leith, Malone). Hamilton Institute, NUIM, Ireland 5

7 Mean-field Markov Model s Chain (1 q)(1 p) (1 q)(1 p) (1 q) q(1 p)(1 p)(1 q) (1 q) (1 q) (1 q) (,) e (,1) e (, CW 2) e (, CW 1) e q(1 p) q q(1 p)p qp q q (,) 1 (,1) 1 (, CW 2) 1 (, CW 1) q(1 p) p (1,) 1 (1,1) 1 1 (1, 2CW 2) (1, 2CW 1) p Figure 2: Individual s Markov Chain Hamilton Institute, NUIM, Ireland 6

8 Mean-field Markov Model Solution Stationary distribution of Markov chain gives: ( τ(p, q, W, m) = η 1 q 2 ) W q2 (1 p), (3) (1 p)(1 q)(1 (1 q) W ) 1 q where ( ) η = (1 q) + q2 W (W +1) 2(1 (1 q) W ) + q(w +1) q 2 W 2(1 q) + p(1 q) q(1 1 (1 q) W ( ) ( ) p)2 pq + 2 W 2(1 q)(1 p) (1 1 (1 q) W p)2 1 p p(2p) 2W m 1 1 2p + 1. Hamilton Institute, NUIM, Ireland 7

9 Network coupling For given loads q 1,...,q n, define τ j = τ(p j,q j, W, m) and then n coupling equations: 1 p i = j i(1 τ j ). Solve to determine (p 1, τ 1 ),...,(p n,τ n ). If all packets are the same length, L bytes taking T L time on the medium, then S i = τ i (1 p i )L n i=1 (1 τ i)δ + (1 n i=1 (1 τ i))t L. Hamilton Institute, NUIM, Ireland 8

10 Relating q to offered load Taking lim q 1 models saturation. For small buffers, a crude approximation: q = min(expected slot length/mean inter-packet time,1). If packets arrive a Poisson manner with rate λ l, then q l is 1 exp( λ l Expected slot length). Possible to produce a relation of this sort that uses conditional information. Hamilton Institute, NUIM, Ireland 9

11 Model Predictions.35.3 normalised throughput normalised total offered load 16 stations (sim) (model unif) (model Pois) (model Cond) 2 stations (sim) (model unif) (model Pois) (model Cond) 24 stations (sim) (model unif) (model Pois) (model Cond) Throughput as the traffic arrival rate is varied. Results for three load relationships (uniform, Poisson and conditional) shown. Hamilton Institute, NUIM, Ireland 1

12 Model Predictions.2.18 model class 1 model class 2 simulation normalised per-node throughput total offered normalised load Normalized per-station throughput, where n 1 = 12, n 2 = 24. The offered load of a class 2 station is 1/4 of a class 1 station. Hamilton Institute, NUIM, Ireland 11

13 TCP Upload Scenario Access Point Stations with competing TCP uploads Figure 3: Competing TCP uploads. Hamilton Institute, NUIM, Ireland 12

14 TCP Uploads TCP throughput (Mbps) Number of the upstream connection Figure 4: Competing TCP uploads, 1 stations (NS2 simulation, MAC, 3s duration). Hamilton Institute, NUIM, Ireland 13

15 The 82.11e MAC The three most significant 82.11e MAC parameters on traffic prioritization are TXOP, W and AIFS. Four traffic classes per station. Station transmits for max duration TXOP (one packet without 82.11e). Per class, W is 2 n, n {,1,...}. Per class, AIFS = DIFS + kδ, k { 2, 1,, 1,...}. Hamilton Institute, NUIM, Ireland 14

16 The MAC Data Ack Select Random Number in [,W 1] Pause Counter Resume Counter Expires; Transmit Decrement counter SIFS AIFS SIFS AIFS Figure 5: MAC operation Hamilton Institute, NUIM, Ireland 15

17 Existing 82.11e models Saturated 82.11e multi-class models. R. Battiti and Bo Li, University of Trento Technical Report DIT-3-24 (23). J.W. Robinson and T.S. Randhawa, IEEE JSAC 22:5 (24). Z. Kong, D. H.K. Tsang, B. Bensaou and D. Gao, IEEE JSAC 22:1 (24). Following (maybe!) to appear in IEEE Trans. Mob. Computing, with Clifford, Duffy, Foy, Leith and Malone. Hamilton Institute, NUIM, Ireland 16

18 Modelling 82.11e Added complications: Need hold states for AIFS. P h = (1 n 1 j=1 (1 τ(1) j ) n 2 j=1 (1 τ(2) j )) 1 + (1 n 1 j=1 (1 τ(1) j ) n 2 j=1 (1 τ(2) j )) D i=1 P i S 1 D i=1 P i S 1. (4) Hamilton Institute, NUIM, Ireland 17

19 New coupling equations 1 p (1) i = (1 τ (1) j )(P h + (1 P h ) j i 1 p (2) i = n 1 j=1 n 2 j=1 (1 τ (2) j )) (5) (1 τ (1) j ) (1 τ (2) j ). (6) j i Hamilton Institute, NUIM, Ireland 18

20 How good is it?.25 model class 1 model class 2 simulation.25 model class 1 model class 2 simulation.25 model class 1 model class 2 simulation Per station throughput (Mbps) Per station throughput (Mbps) Per station throughput (Mbps) Total offered load (Mbps) (a) D = Total offered load (Mbps) (b) D = Total offered load (Mbps) (c) D = 4 Throughput for a station in each class vs. offered load. 1 class 1 stations offering one quarter the load of 2 class 2 stations. Range of D values, the difference in AIFS between class 2 and class 1 (NS2 simulation and model predictions, 82.11e MAC, 11Mbps PHY, 1s duration. ). Hamilton Institute, NUIM, Ireland 19

21 How good is it?.25 model class 1 model class 2 simulation.25 model class 1 model class 2 simulation.25 model class 1 model class 2 simulation Per station throughput (Mbps) Per station throughput (Mbps) Per station throughput (Mbps) Total offered load (Mbps) (d) W (1) = 32, W (2) = Total offered load (Mbps) (e) W (1) = 32, W (2) = Total offered load (Mbps) (f) W (1) = 32,W (2) = 256 Throughput for a station in each class vs. offered load. There are 1 class 1 stations each offering one quarter the load of 2 class 2 stations. Range of W values (NS2 simulation and model predictions, 82.11e MAC 11Mbps PHY, 1s duration). Hamilton Institute, NUIM, Ireland 2

22 How do you use it? 6 5 W 1 =1 W 1 =2 W 1 =4 W 1 =8 W 1 =16 W 1 = W 1 =1 W 1 =2 W 1 =4 W 1 =8 W 1 =16 W 1 =32 Throughput of Data Stations (Mbps) Ratio of lost traffic to offered load Difference in AIFS Difference in AIFS (g) Data throughput (h) ACK loss 1 stations (15 byte packets) and AP transmitting (6 byte packets) at half achieved data rate. Hamilton Institute, NUIM, Ireland 21

23 Does it work? TCP Throughput (Mbps) TCP Throughput (Mbps) Number of the upstream connection Number of the upstream connection Competing TCP uploads, 12 stations experiment without and with prioritization (82.11e MAC, 3s duration). Hamilton Institute, NUIM, Ireland 22

24 Why stop with single infrastructure mode network? Basic behavior of individual stations is independent of the network in which they exist. Change the network coupling, change the network. Hamilton Institute, NUIM, Ireland 23

25 Typical mesh issue throughput (Mbs) NS r 1 NS r #conversations Example of aggregate throughput vs number of voice calls for the multi-hop 82.11b WLAN topology. Voice packets are transported between l 1 1 and l 2 1,...,l 2 N by node r 1 /r 2 which denotes a relay station with two radios. Hamilton Institute, NUIM, Ireland 24

26 Mesh Following in IEEE Comms. Letters (26), (Duffy, Leith, Li and Malone). M distinct local zones on common frequency. For n {1,..., M} local stations L n = {l n 1,...} and relay stations R n = {r n,...}. Mean field gives for each station c R n L n : 1 p c = b R n L n, b =c (1 τ b ). (7) The stationary probability the medium is idle is p idle = b R n L n (1 τ b ). The mean state length is E n = p idle σ + L(1 p idle ), where each packet takes L seconds and idle slot-length is σ seconds. Added difficulty: for each n, l L n, q l is given, but q r is not known a priori for each relay station. Hamilton Institute, NUIM, Ireland 25

27 Mesh The parameter q r is determined through relay traffic. For each n, l L n, a fixed route f l from its zone to a destination zone. f l = {l, s 1...,s m, d}. If m =, then l and d are in the same zone and no relaying occurs. We assume routes are predetermined by an appropriate wireless routing protocol. Hamilton Institute, NUIM, Ireland 26

28 Mesh For each s L n R n, let E(s) = E n. For k {1,...,m} Let Q l,sk be offered load from l arriving at s k and Q sk be the total load offered to s k. From these we calculate: S sk = τ s k (1 p sk ) E n and then assume: Q sk+1 = Q l,sk Q sk S sk to calculate the load in the next network. Hamilton Institute, NUIM, Ireland 27

29 Buffering Limitations of small buffers particularly apparent in mesh. Need to introduce queue empty probability to model queue: r n. Model queues as M/G/1. E(B(p)) = W 2(1 2p) (1 p p(2p)m ). (8) r n = min(1, B(p n )log(1 q n )) (9) Simply replaces τ(p) relation. To appear, IEEE Comms. Letters (27), (Duffy, Ganesh). Seeing some interaction between buffering and service. Hamilton Institute, NUIM, Ireland 28

30 Unfairness One conversation, N data stations 5 4 Conv. throughput, small buffer Data throughput, when conversation has small buffer Conv. throughput, large buffer Data throughput, when conversation has large buffer 64 kbps Throughput (kbps) 3 2 <-- Mean delay, conv., large buffer Delay (milli seconds) Number of data stations, N Figure 6: NS packet-level simulation results and model predictions Hamilton Institute, NUIM, Ireland 29

31 Understanding the Models Models are inexact in several ways. Constant p replaces complex Markov chain with direct sum. Throughput relationship assumes independent. Do assumptions hold or are stationary distributions similar? Hamilton Institute, NUIM, Ireland 3

32 Is p constant?.6.5 Average P(col) P(col on 1st tx) P(col on 2nd tx) 1./32 1./ Probability.3 Probability Offered Load (per station, pps, 496B UDP payload) (a) 2 Stations Average P(col) P(col on 1st tx) P(col on 2nd tx) Offered Load (per station, pps, 486B UDP payload) (b) 1 Stations Figure 7: Measured collision probabilities as offered load is varied. Hamilton Institute, NUIM, Ireland 31

33 Independence of Transmissions Throughput (Kbps) Throughput (measured) Throughput (model) Throughput (model + measured Ts/Tc) Throughput (model + measured Ts/Tc/p) Number of STA(s) Figure 8: Overall throughput in a network of saturated stations as the number of stations is varied. The measured values are compared to model predictions. Hamilton Institute, NUIM, Ireland 32

34 Conclusions 82.11/82.11e CSMA/CA models that are simple, solvable, yet complex enough to predict data throughput. Model gives insight into MAC behavior. Model gives insight into effect of 82.11e parameters. Prioritization schemes can now be designed quickly based on the model. Extensible to network scenarios. Interesting questions on buffering and foundations remain to be answered. Hamilton Institute, NUIM, Ireland 33

Giuseppe Bianchi, Ilenia Tinnirello

Giuseppe Bianchi, Ilenia Tinnirello Capacity of WLAN Networs Summary Per-node throughput in case of: Full connected networs each node sees all the others Generic networ topology not all nodes are visible Performance Analysis of single-hop

More information

Performance Analysis of the IEEE e Block ACK Scheme in a Noisy Channel

Performance Analysis of the IEEE e Block ACK Scheme in a Noisy Channel Performance Analysis of the IEEE 802.11e Block ACK Scheme in a Noisy Channel Tianji Li, Qiang Ni, Hamilton Institute, NUIM, Ireland. Thierry Turletti, Planete Group, INRIA, France. Yang Xiao, University

More information

Performance analysis of IEEE WLANs with saturated and unsaturated sources

Performance analysis of IEEE WLANs with saturated and unsaturated sources Performance analysis of IEEE 82.11 WLANs with saturated and unsaturated sources Suong H. Nguyen, Hai L. Vu, Lachlan L. H. Andrew Centre for Advanced Internet Architectures, Technical Report 11811A Swinburne

More information

Giuseppe Bianchi, Ilenia Tinnirello

Giuseppe Bianchi, Ilenia Tinnirello Capacity of WLAN Networs Summary Ł Ł Ł Ł Arbitrary networ capacity [Gupta & Kumar The Capacity of Wireless Networs ] Ł! Ł "! Receiver Model Ł Ł # Ł $%&% Ł $% '( * &%* r (1+ r Ł + 1 / n 1 / n log n Area

More information

Wireless Internet Exercises

Wireless Internet Exercises Wireless Internet Exercises Prof. Alessandro Redondi 2018-05-28 1 WLAN 1.1 Exercise 1 A Wi-Fi network has the following features: Physical layer transmission rate: 54 Mbps MAC layer header: 28 bytes MAC

More information

On the Validity of IEEE MAC Modeling Hypotheses

On the Validity of IEEE MAC Modeling Hypotheses On the Validity of IEEE 82.11 MAC Modeling Hypotheses K. D. Huang, K. R. Duffy and D. Malone Hamilton Institute, National University of Ireland, Maynooth, Ireland. Corresponding author: ken.duffy@nuim.ie

More information

Performance Evaluation of Deadline Monotonic Policy over protocol

Performance Evaluation of Deadline Monotonic Policy over protocol Performance Evaluation of Deadline Monotonic Policy over 80. protocol Ines El Korbi and Leila Azouz Saidane National School of Computer Science University of Manouba, 00 Tunisia Emails: ines.korbi@gmail.com

More information

Service differentiation without prioritization in IEEE WLANs

Service differentiation without prioritization in IEEE WLANs Service differentiation without prioritization in IEEE 8. WLANs Suong H. Nguyen, Student Member, IEEE, Hai L. Vu, Senior Member, IEEE, and Lachlan L. H. Andrew, Senior Member, IEEE Abstract Wireless LANs

More information

Modeling Approximations for an IEEE WLAN under Poisson MAC-Level Arrivals

Modeling Approximations for an IEEE WLAN under Poisson MAC-Level Arrivals Modeling Approximations for an IEEE 802.11 WLAN under Poisson MAC-Level Arrivals Ioannis Koukoutsidis 1 and Vasilios A. Siris 1,2 1 FORTH-ICS, P.O. Box 1385, 71110 Heraklion, Crete, Greece 2 Computer Science

More information

Performance analysis of IEEE WLANs with saturated and unsaturated sources

Performance analysis of IEEE WLANs with saturated and unsaturated sources 1 Performance analysis of IEEE 8.11 WLANs with saturated and unsaturated sources Suong H. Nguyen, Student Member, IEEE, Hai L. Vu, Senior Member, IEEE, and Lachlan L. H. Andrew, Senior Member, IEEE Abstract

More information

Mean Field Markov Models of Wireless Local Area Networks

Mean Field Markov Models of Wireless Local Area Networks Mean Field Markov Models of Wireless Local Area Networks Ken R. Duffy 26 th September 2010; revised 8 th April 2010. To appear in Markov Processes and Related Fields Abstract In 1998, Giuseppe Bianchi

More information

Mathematical Analysis of IEEE Energy Efficiency

Mathematical Analysis of IEEE Energy Efficiency Information Engineering Department University of Padova Mathematical Analysis of IEEE 802.11 Energy Efficiency A. Zanella and F. De Pellegrini IEEE WPMC 2004 Padova, Sept. 12 15, 2004 A. Zanella and F.

More information

requests/sec. The total channel load is requests/sec. Using slot as the time unit, the total channel load is 50 ( ) = 1

requests/sec. The total channel load is requests/sec. Using slot as the time unit, the total channel load is 50 ( ) = 1 Prof. X. Shen E&CE 70 : Examples #2 Problem Consider the following Aloha systems. (a) A group of N users share a 56 kbps pure Aloha channel. Each user generates at a Passion rate of one 000-bit packet

More information

A Comprehensive Study of the IEEE e Enhanced Distributed Control Access (EDCA) Function. Chunyu Hu and Jennifer C. Hou.

A Comprehensive Study of the IEEE e Enhanced Distributed Control Access (EDCA) Function. Chunyu Hu and Jennifer C. Hou. Report No. UIUCDCS-R-26-27 UILU-ENG-26-743 A Comprehensive Study of the IEEE 82.e Enhanced Distributed Control Access EDCA) Function by Chunyu Hu and Jennifer C. Hou April 26 A Comprehensive Study of the

More information

Detecting Stations Cheating on Backoff Rules in Networks Using Sequential Analysis

Detecting Stations Cheating on Backoff Rules in Networks Using Sequential Analysis Detecting Stations Cheating on Backoff Rules in 82.11 Networks Using Sequential Analysis Yanxia Rong Department of Computer Science George Washington University Washington DC Email: yxrong@gwu.edu Sang-Kyu

More information

NICTA Short Course. Network Analysis. Vijay Sivaraman. Day 1 Queueing Systems and Markov Chains. Network Analysis, 2008s2 1-1

NICTA Short Course. Network Analysis. Vijay Sivaraman. Day 1 Queueing Systems and Markov Chains. Network Analysis, 2008s2 1-1 NICTA Short Course Network Analysis Vijay Sivaraman Day 1 Queueing Systems and Markov Chains Network Analysis, 2008s2 1-1 Outline Why a short course on mathematical analysis? Limited current course offering

More information

Max-min Fairness in Mesh Networks

Max-min Fairness in Mesh Networks Max-min Fairness in 802. Mesh Networks Douglas J. Leith, Qizhi Cao, Vijay G. Subramanian Hamilton Institute, NUI Maynooth arxiv:002.58v2 [cs.ni] 3 Mar 200 Abstract In this paper we build upon the recent

More information

Flow-level performance of wireless data networks

Flow-level performance of wireless data networks Flow-level performance of wireless data networks Aleksi Penttinen Department of Communications and Networking, TKK Helsinki University of Technology CLOWN seminar 28.8.08 1/31 Outline 1. Flow-level model

More information

Exact Distribution of Access Delay in IEEE DCF MAC

Exact Distribution of Access Delay in IEEE DCF MAC Exact Distribution of Access Delay in IEEE 8.11 DCF MAC Teerawat Issariyakul, Dusit Niyato, Ekram Hossain, and Attahiru Sule Alfa University of Manitoba and TRLabs Winnipeg, MB, Canada. Email: teerawat,

More information

Lecture 7: Simulation of Markov Processes. Pasi Lassila Department of Communications and Networking

Lecture 7: Simulation of Markov Processes. Pasi Lassila Department of Communications and Networking Lecture 7: Simulation of Markov Processes Pasi Lassila Department of Communications and Networking Contents Markov processes theory recap Elementary queuing models for data networks Simulation of Markov

More information

Chapter 5. Elementary Performance Analysis

Chapter 5. Elementary Performance Analysis Chapter 5 Elementary Performance Analysis 1 5.0 2 5.1 Ref: Mischa Schwartz Telecommunication Networks Addison-Wesley publishing company 1988 3 4 p t T m T P(k)= 5 6 5.2 : arrived rate : service rate 7

More information

1. WiMAX Wi-Fi Wi-Fi (AP) Wi-Fi 1 1 AP AP WLAN [1] [1] [1] WLAN [4] WLAN WLAN WLAN 1 WLAN WLAN WLAN N =3 [1] W

1. WiMAX Wi-Fi Wi-Fi (AP) Wi-Fi 1 1 AP AP WLAN [1] [1] [1] WLAN [4] WLAN WLAN WLAN 1 WLAN WLAN WLAN N =3 [1] W [] LAN 263 8522 1-33 514-857 1577 NEC 211-8666 1753 464-861 E-mail: {aoki@, kmr@faculty., shioda@faculty., sekiya@faculty.}chiba-u.jp, k.sanada@elec.mie-u.ac.jp 一般社団法人 電子情報通信学会 信学技報 THE INSTITUTE OF ELECTRONICS,

More information

Optimization of IEEE Multirate Wireless LAN

Optimization of IEEE Multirate Wireless LAN JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 26 77-785 (200) Optimization of IEEE 802 Multirate Wireless LAN A V BABU LILLYKUTTY JACOB AND S ABDUL SUBHAN Department of Electronics and Communication Engineering

More information

Modeling the Effect of Transmission Errors on TCP Controlled Transfers over Infrastructure Wireless LANs

Modeling the Effect of Transmission Errors on TCP Controlled Transfers over Infrastructure Wireless LANs Modeling the Effect of Transmission Errors on TCP Controlled Transfers over Infrastructure 8 Wireless LANs ABSTRACT Subhashini Krishnasamy Dept of Electrical Communication Engg Indian Institute of Science,

More information

Solutions to COMP9334 Week 8 Sample Problems

Solutions to COMP9334 Week 8 Sample Problems Solutions to COMP9334 Week 8 Sample Problems Problem 1: Customers arrive at a grocery store s checkout counter according to a Poisson process with rate 1 per minute. Each customer carries a number of items

More information

Outline Network structure and objectives Routing Routing protocol protocol System analysis Results Conclusion Slide 2

Outline Network structure and objectives Routing Routing protocol protocol System analysis Results Conclusion Slide 2 2007 Radio and Wireless Symposium 9 11 January 2007, Long Beach, CA. Lifetime-Aware Hierarchical Wireless Sensor Network Architecture with Mobile Overlays Maryam Soltan, Morteza Maleki, and Massoud Pedram

More information

Tuning the TCP Timeout Mechanism in Wireless Networks to Maximize Throughput via Stochastic Stopping Time Methods

Tuning the TCP Timeout Mechanism in Wireless Networks to Maximize Throughput via Stochastic Stopping Time Methods Tuning the TCP Timeout Mechanism in Wireless Networks to Maximize Throughput via Stochastic Stopping Time Methods George Papageorgiou and John S. Baras Abstract We present an optimization problem that

More information

Performance Evaluation of Queuing Systems

Performance Evaluation of Queuing Systems Performance Evaluation of Queuing Systems Introduction to Queuing Systems System Performance Measures & Little s Law Equilibrium Solution of Birth-Death Processes Analysis of Single-Station Queuing Systems

More information

Queueing Theory I Summary! Little s Law! Queueing System Notation! Stationary Analysis of Elementary Queueing Systems " M/M/1 " M/M/m " M/M/1/K "

Queueing Theory I Summary! Little s Law! Queueing System Notation! Stationary Analysis of Elementary Queueing Systems  M/M/1  M/M/m  M/M/1/K Queueing Theory I Summary Little s Law Queueing System Notation Stationary Analysis of Elementary Queueing Systems " M/M/1 " M/M/m " M/M/1/K " Little s Law a(t): the process that counts the number of arrivals

More information

Power Controlled FCFS Splitting Algorithm for Wireless Networks

Power Controlled FCFS Splitting Algorithm for Wireless Networks Power Controlled FCFS Splitting Algorithm for Wireless Networks Ashutosh Deepak Gore Abhay Karandikar Department of Electrical Engineering Indian Institute of Technology - Bombay COMNET Workshop, July

More information

ATM VP-Based Ring Network Exclusive Video or Data Traffics

ATM VP-Based Ring Network Exclusive Video or Data Traffics ATM VP-Based Ring Network Exclusive Video or Data Traffics In this chapter, the performance characteristic of the proposed ATM VP-Based Ring Network exclusive video or data traffic is studied. The maximum

More information

Introduction to Markov Chains, Queuing Theory, and Network Performance

Introduction to Markov Chains, Queuing Theory, and Network Performance Introduction to Markov Chains, Queuing Theory, and Network Performance Marceau Coupechoux Telecom ParisTech, departement Informatique et Réseaux marceau.coupechoux@telecom-paristech.fr IT.2403 Modélisation

More information

Approximate Queueing Model for Multi-rate Multi-user MIMO systems.

Approximate Queueing Model for Multi-rate Multi-user MIMO systems. An Approximate Queueing Model for Multi-rate Multi-user MIMO systems Boris Bellalta,Vanesa Daza, Miquel Oliver Abstract A queueing model for Multi-rate Multi-user MIMO systems is presented. The model is

More information

Introduction to queuing theory

Introduction to queuing theory Introduction to queuing theory Claude Rigault ENST claude.rigault@enst.fr Introduction to Queuing theory 1 Outline The problem The number of clients in a system The client process Delay processes Loss

More information

On Selfish Behavior in CSMA/CA Networks

On Selfish Behavior in CSMA/CA Networks On Selfish Behavior in CSMA/CA Networks Mario Čagalj1 Saurabh Ganeriwal 2 Imad Aad 1 Jean-Pierre Hubaux 1 1 LCA-IC-EPFL 2 NESL-EE-UCLA March 17, 2005 - IEEE Infocom 2005 - Introduction CSMA/CA is the most

More information

A POMDP Framework for Cognitive MAC Based on Primary Feedback Exploitation

A POMDP Framework for Cognitive MAC Based on Primary Feedback Exploitation A POMDP Framework for Cognitive MAC Based on Primary Feedback Exploitation Karim G. Seddik and Amr A. El-Sherif 2 Electronics and Communications Engineering Department, American University in Cairo, New

More information

Modeling and Simulation NETW 707

Modeling and Simulation NETW 707 Modeling and Simulation NETW 707 Lecture 6 ARQ Modeling: Modeling Error/Flow Control Course Instructor: Dr.-Ing. Maggie Mashaly maggie.ezzat@guc.edu.eg C3.220 1 Data Link Layer Data Link Layer provides

More information

What maths can tell us about WiFi (and vice versa)?

What maths can tell us about WiFi (and vice versa)? What maths can tell us about WiFi (and vice versa)? David Malone 28 January 2009 1 The Plan Do a little mathematical modeling. Interested in 802.11 (WiFi). Example MAC layer. Detour

More information

TCP over Cognitive Radio Channels

TCP over Cognitive Radio Channels 1/43 TCP over Cognitive Radio Channels Sudheer Poojary Department of ECE, Indian Institute of Science, Bangalore IEEE-IISc I-YES seminar 19 May 2016 2/43 Acknowledgments The work presented here was done

More information

On the MAC for Power-Line Communications: Modeling Assumptions and Performance Tradeoffs

On the MAC for Power-Line Communications: Modeling Assumptions and Performance Tradeoffs On the MAC for Power-Line Communications: Modeling Assumptions and Performance Tradeoffs Technical Report Christina Vlachou, Albert Banchs, Julien Herzen, Patrick Thiran EPFL, Switzerland, Institute IMDEA

More information

Optimal Association of Stations and APs in an IEEE WLAN

Optimal Association of Stations and APs in an IEEE WLAN Optimal Association of Stations and APs in an IEEE 802. WLAN Anurag Kumar and Vinod Kumar Abstract We propose a maximum utility based formulation for the problem of optimal association of wireless stations

More information

Information in Aloha Networks

Information in Aloha Networks Achieving Proportional Fairness using Local Information in Aloha Networks Koushik Kar, Saswati Sarkar, Leandros Tassiulas Abstract We address the problem of attaining proportionally fair rates using Aloha

More information

TRANSMISSION STRATEGIES FOR SINGLE-DESTINATION WIRELESS NETWORKS

TRANSMISSION STRATEGIES FOR SINGLE-DESTINATION WIRELESS NETWORKS The 20 Military Communications Conference - Track - Waveforms and Signal Processing TRANSMISSION STRATEGIES FOR SINGLE-DESTINATION WIRELESS NETWORKS Gam D. Nguyen, Jeffrey E. Wieselthier 2, Sastry Kompella,

More information

Open Loop Optimal Control of Base Station Activation for Green Networks

Open Loop Optimal Control of Base Station Activation for Green Networks Open Loop Optimal Control of Base Station Activation for Green etworks Sreenath Ramanath, Veeraruna Kavitha,2 and Eitan Altman IRIA, Sophia-Antipolis, France, 2 Universite d Avignon, Avignon, France Abstract

More information

Multiaccess Communication

Multiaccess Communication Information Networks p. 1 Multiaccess Communication Satellite systems, radio networks (WLAN), Ethernet segment The received signal is the sum of attenuated transmitted signals from a set of other nodes,

More information

Performance of Random Medium Access Control An asymptotic approach

Performance of Random Medium Access Control An asymptotic approach Performance of Random Medium Access Control An asymptotic approach Charles Bordenave CNRS & Math. Dept. of Toulouse Univ., France charles.bordenave@math.univtoulouse.fr David McDonald Math. Dept. of Ottawa

More information

Min Congestion Control for High- Speed Heterogeneous Networks. JetMax: Scalable Max-Min

Min Congestion Control for High- Speed Heterogeneous Networks. JetMax: Scalable Max-Min JetMax: Scalable Max-Min Min Congestion Control for High- Speed Heterogeneous Networks Yueping Zhang Joint work with Derek Leonard and Dmitri Loguinov Internet Research Lab Department of Computer Science

More information

A Stochastic Model for TCP with Stationary Random Losses

A Stochastic Model for TCP with Stationary Random Losses A Stochastic Model for TCP with Stationary Random Losses Eitan Altman, Kostya Avrachenkov Chadi Barakat INRIA Sophia Antipolis - France ACM SIGCOMM August 31, 2000 Stockholm, Sweden Introduction Outline

More information

Delay and throughput analysis of tree algorithms for random access over noisy collision channels

Delay and throughput analysis of tree algorithms for random access over noisy collision channels Delay and throughput analysis of tree algorithms for random access over noisy collision channels Benny Van Houdt, Robbe Block To cite this version: Benny Van Houdt, Robbe Block. Delay and throughput analysis

More information

ANALYSIS OF THE RTS/CTS MULTIPLE ACCESS SCHEME WITH CAPTURE EFFECT

ANALYSIS OF THE RTS/CTS MULTIPLE ACCESS SCHEME WITH CAPTURE EFFECT ANALYSIS OF THE RTS/CTS MULTIPLE ACCESS SCHEME WITH CAPTURE EFFECT Chin Keong Ho Eindhoven University of Technology Eindhoven, The Netherlands Jean-Paul M. G. Linnartz Philips Research Laboratories Eindhoven,

More information

A New Technique for Link Utilization Estimation

A New Technique for Link Utilization Estimation A New Technique for Link Utilization Estimation in Packet Data Networks using SNMP Variables S. Amarnath and Anurag Kumar* Dept. of Electrical Communication Engineering Indian Institute of Science, Bangalore

More information

Mixed Stochastic and Event Flows

Mixed Stochastic and Event Flows Simulation Mixed and Event Flows Modeling for Simulation Dynamics Robert G. Cole 1, George Riley 2, Derya Cansever 3 and William Yurcick 4 1 Johns Hopkins University 2 Georgia Institue of Technology 3

More information

How do Wireless Chains Behave? The Impact of MAC Interactions

How do Wireless Chains Behave? The Impact of MAC Interactions The Impact of MAC Interactions S. Razak 1 Vinay Kolar 2 N. Abu-Ghazaleh 1 K. Harras 1 1 Department of Computer Science Carnegie Mellon University, Qatar 2 Department of Wireless Networks RWTH Aachen University,

More information

Cross-layer Theoretical Analysis of NC-aided. Cooperative ARQ Protocols in Correlated Shadowed Environments (Extended Version)

Cross-layer Theoretical Analysis of NC-aided. Cooperative ARQ Protocols in Correlated Shadowed Environments (Extended Version) Cross-layer Theoretical Analysis of NC-aided Cooperative ARQ Protocols in Correlated Shadowed Environments (Extended Version) Angelos Antonopoulos, Member, IEEE, Aris S. Lalos, Member, IEEE, arxiv:408.609v

More information

STABILITY OF FINITE-USER SLOTTED ALOHA UNDER PARTIAL INTERFERENCE IN WIRELESS MESH NETWORKS

STABILITY OF FINITE-USER SLOTTED ALOHA UNDER PARTIAL INTERFERENCE IN WIRELESS MESH NETWORKS The 8th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 7) STABILITY OF FINITE-USER SLOTTED ALOHA UNDER PARTIAL INTERFERENCE IN WIRELESS MESH NETWORKS Ka-Hung

More information

Stability analysis of a cognitive multiple access channel with primary QoS constraints

Stability analysis of a cognitive multiple access channel with primary QoS constraints tability analysis of a cognitive multiple access channel with primary o constraints J. Gambini 1,2,O.imeone 1, U. pagnolini 2,.Bar-Ness 1 andungsooim 3 1 CWCR, NJIT, Newark, New Jersey 07102-1982, UA 2

More information

CS276 Homework 1: ns-2

CS276 Homework 1: ns-2 CS276 Homework 1: ns-2 Erik Peterson October 28, 2006 1 Part 1 - Fairness between TCP variants 1.1 Method After learning ns-2, I wrote a script (Listing 3) that runs a simulation of one or two tcp flows

More information

Random Access Game. Medium Access Control Design for Wireless Networks 1. Sandip Chakraborty. Department of Computer Science and Engineering,

Random Access Game. Medium Access Control Design for Wireless Networks 1. Sandip Chakraborty. Department of Computer Science and Engineering, Random Access Game Medium Access Control Design for Wireless Networks 1 Sandip Chakraborty Department of Computer Science and Engineering, INDIAN INSTITUTE OF TECHNOLOGY KHARAGPUR October 22, 2016 1 Chen

More information

cs/ee/ids 143 Communication Networks

cs/ee/ids 143 Communication Networks cs/ee/ids 143 Communication Networks Chapter 4 Transport Text: Walrand & Parakh, 2010 Steven Low CMS, EE, Caltech Agenda Internetworking n Routing across LANs, layer2-layer3 n DHCP n NAT Transport layer

More information

Cooperative HARQ with Poisson Interference and Opportunistic Routing

Cooperative HARQ with Poisson Interference and Opportunistic Routing Cooperative HARQ with Poisson Interference and Opportunistic Routing Amogh Rajanna & Mostafa Kaveh Department of Electrical and Computer Engineering University of Minnesota, Minneapolis, MN USA. Outline

More information

Meta-heuristic Solution for Dynamic Association Control in Virtualized Multi-rate WLANs

Meta-heuristic Solution for Dynamic Association Control in Virtualized Multi-rate WLANs Meta-heuristic Solution for Dynamic Association Control in Virtualized Multi-rate WLANs Dawood Sajjadi, Maryam Tanha, Jianping Pan Department of Computer Science, University of Victoria, BC, Canada November

More information

On the Stability and Optimal Decentralized Throughput of CSMA with Multipacket Reception Capability

On the Stability and Optimal Decentralized Throughput of CSMA with Multipacket Reception Capability On the Stability and Optimal Decentralized Throughput of CSMA with Multipacket Reception Capability Douglas S. Chan Toby Berger Lang Tong School of Electrical & Computer Engineering Cornell University,

More information

communication networks

communication networks Positive matrices associated with synchronised communication networks Abraham Berman Department of Mathematics Robert Shorten Hamilton Institute Douglas Leith Hamilton Instiute The Technion NUI Maynooth

More information

Analysis of Scalable TCP in the presence of Markovian Losses

Analysis of Scalable TCP in the presence of Markovian Losses Analysis of Scalable TCP in the presence of Markovian Losses E Altman K E Avrachenkov A A Kherani BJ Prabhu INRIA Sophia Antipolis 06902 Sophia Antipolis, France Email:altman,kavratchenkov,alam,bprabhu}@sophiainriafr

More information

These are special traffic patterns that create more stress on a switch

These are special traffic patterns that create more stress on a switch Myths about Microbursts What are Microbursts? Microbursts are traffic patterns where traffic arrives in small bursts. While almost all network traffic is bursty to some extent, storage traffic usually

More information

Multimedia Communication Services Traffic Modeling and Streaming

Multimedia Communication Services Traffic Modeling and Streaming Multimedia Communication Services Medium Access Control algorithms Aloha Slotted: performance analysis with finite nodes Università degli Studi di Brescia A.A. 2014/2015 Francesco Gringoli Master of Science

More information

A Stochastic Control Approach for Scheduling Multimedia Transmissions over a Polled Multiaccess Fading Channel

A Stochastic Control Approach for Scheduling Multimedia Transmissions over a Polled Multiaccess Fading Channel A Stochastic Control Approach for Scheduling Multimedia Transmissions over a Polled Multiaccess Fading Channel 1 Munish Goyal, Anurag Kumar and Vinod Sharma Dept. of Electrical Communication Engineering,

More information

Queuing Networks: Burke s Theorem, Kleinrock s Approximation, and Jackson s Theorem. Wade Trappe

Queuing Networks: Burke s Theorem, Kleinrock s Approximation, and Jackson s Theorem. Wade Trappe Queuing Networks: Burke s Theorem, Kleinrock s Approximation, and Jackson s Theorem Wade Trappe Lecture Overview Network of Queues Introduction Queues in Tandem roduct Form Solutions Burke s Theorem What

More information

Multiaccess Problem. How to let distributed users (efficiently) share a single broadcast channel? How to form a queue for distributed users?

Multiaccess Problem. How to let distributed users (efficiently) share a single broadcast channel? How to form a queue for distributed users? Multiaccess Problem How to let distributed users (efficiently) share a single broadcast channel? How to form a queue for distributed users? z The protocols we used to solve this multiaccess problem are

More information

An Admission Control Mechanism for Providing Service Differentiation in Optical Burst-Switching Networks

An Admission Control Mechanism for Providing Service Differentiation in Optical Burst-Switching Networks An Admission Control Mechanism for Providing Service Differentiation in Optical Burst-Switching Networks Igor M. Moraes, Daniel de O. Cunha, Marco D. D. Bicudo, Rafael P. Laufer, and Otto Carlos M. B.

More information

6 Solving Queueing Models

6 Solving Queueing Models 6 Solving Queueing Models 6.1 Introduction In this note we look at the solution of systems of queues, starting with simple isolated queues. The benefits of using predefined, easily classified queues will

More information

On the Throughput-Optimality of CSMA Policies in Multihop Wireless Networks

On the Throughput-Optimality of CSMA Policies in Multihop Wireless Networks Technical Report Computer Networks Research Lab Department of Computer Science University of Toronto CNRL-08-002 August 29th, 2008 On the Throughput-Optimality of CSMA Policies in Multihop Wireless Networks

More information

Performance Analysis of Priority Queueing Schemes in Internet Routers

Performance Analysis of Priority Queueing Schemes in Internet Routers Conference on Information Sciences and Systems, The Johns Hopkins University, March 8, Performance Analysis of Priority Queueing Schemes in Internet Routers Ashvin Lakshmikantha Coordinated Science Lab

More information

TWO PROBLEMS IN NETWORK PROBING

TWO PROBLEMS IN NETWORK PROBING TWO PROBLEMS IN NETWORK PROBING DARRYL VEITCH The University of Melbourne 1 Temporal Loss and Delay Tomography 2 Optimal Probing in Convex Networks Paris Networking 27 Juin 2007 TEMPORAL LOSS AND DELAY

More information

Optimal Physical Carrier Sense for Maximizing Network Capacity in Multi-hop Wireless Networks

Optimal Physical Carrier Sense for Maximizing Network Capacity in Multi-hop Wireless Networks Optimal Physical Carrier Sense for Maximizing Network Capacity in Multi-hop Wireless Networks Kyung-Joon Park, Jihyuk Choi, and Jennifer C. Hou Department of Computer Science University of Illinois at

More information

On the Throughput, Capacity and Stability Regions of Random Multiple Access over Standard Multi-Packet Reception Channels

On the Throughput, Capacity and Stability Regions of Random Multiple Access over Standard Multi-Packet Reception Channels On the Throughput, Capacity and Stability Regions of Random Multiple Access over Standard Multi-Packet Reception Channels Jie Luo, Anthony Ephremides ECE Dept. Univ. of Maryland College Park, MD 20742

More information

A Queueing System with Queue Length Dependent Service Times, with Applications to Cell Discarding in ATM Networks

A Queueing System with Queue Length Dependent Service Times, with Applications to Cell Discarding in ATM Networks A Queueing System with Queue Length Dependent Service Times, with Applications to Cell Discarding in ATM Networks by Doo Il Choi, Charles Knessl and Charles Tier University of Illinois at Chicago 85 South

More information

Signalling Analysis for Adaptive TCD Routing in ISL Networks *

Signalling Analysis for Adaptive TCD Routing in ISL Networks * COST 272 Packet-Oriented Service delivery via Satellite Signalling Analysis for Adaptive TCD Routing in ISL Networks * Ales Svigelj, Mihael Mohorcic, Gorazd Kandus Jozef Stefan Institute, Ljubljana, Slovenia

More information

Timestepped Stochastic Simulation. of WLANs

Timestepped Stochastic Simulation. of WLANs Timestepped Stochastic Simulation 1 of 82.11 WLANs Arunchandar Vasan and A. Udaya Shankar Department of Computer Science and UMIACS University of Maryland College Park, MD 2742 CS-TR-4866 and UMIACS-TR-27-19

More information

Throughput and Fairness Analysis of based Vehicle-to-Infrastructure Data Transfers

Throughput and Fairness Analysis of based Vehicle-to-Infrastructure Data Transfers 211 Eighth IEEE International Conference on Mobile Ad-Hoc and Sensor Systems Throughput and Fairness Analysis of 82.11-based Vehicle-to-Infrastructure Data Transfers Raffaele Bruno, Marco Conti Institute

More information

Modelling the Arrival Process for Packet Audio

Modelling the Arrival Process for Packet Audio Modelling the Arrival Process for Packet Audio Ingemar Kaj and Ian Marsh 2 Dept. of Mathematics, Uppsala University, Sweden ikaj@math.uu.se 2 SICS AB, Stockholm, Sweden ianm@sics.se Abstract. Packets in

More information

On the stability of flow-aware CSMA

On the stability of flow-aware CSMA On the stability of flow-aware CSMA Thomas Bonald, Mathieu Feuillet To cite this version: Thomas Bonald, Mathieu Feuillet. On the stability of flow-aware CSMA. Performance Evaluation, Elsevier, 010, .

More information

A Mathematical Model of the Skype VoIP Congestion Control Algorithm

A Mathematical Model of the Skype VoIP Congestion Control Algorithm A Mathematical Model of the Skype VoIP Congestion Control Algorithm Luca De Cicco, S. Mascolo, V. Palmisano Dipartimento di Elettrotecnica ed Elettronica, Politecnico di Bari 47th IEEE Conference on Decision

More information

Methodology for Computer Science Research Lecture 4: Mathematical Modeling

Methodology for Computer Science Research Lecture 4: Mathematical Modeling Methodology for Computer Science Research Andrey Lukyanenko Department of Computer Science and Engineering Aalto University, School of Science and Technology andrey.lukyanenko@tkk.fi Definitions and Goals

More information

A Virtual Queue Approach to Loss Estimation

A Virtual Queue Approach to Loss Estimation A Virtual Queue Approach to Loss Estimation Guoqiang Hu, Yuming Jiang, Anne Nevin Centre for Quantifiable Quality of Service in Communication Systems Norwegian University of Science and Technology, Norway

More information

Capacity management for packet-switched networks with heterogeneous sources. Linda de Jonge. Master Thesis July 29, 2009.

Capacity management for packet-switched networks with heterogeneous sources. Linda de Jonge. Master Thesis July 29, 2009. Capacity management for packet-switched networks with heterogeneous sources Linda de Jonge Master Thesis July 29, 2009 Supervisors Dr. Frank Roijers Prof. dr. ir. Sem Borst Dr. Andreas Löpker Industrial

More information

Channel Selection in Cognitive Radio Networks with Opportunistic RF Energy Harvesting

Channel Selection in Cognitive Radio Networks with Opportunistic RF Energy Harvesting 1 Channel Selection in Cognitive Radio Networks with Opportunistic RF Energy Harvesting Dusit Niyato 1, Ping Wang 1, and Dong In Kim 2 1 School of Computer Engineering, Nanyang Technological University

More information

Dynamic Power Allocation and Routing for Time Varying Wireless Networks

Dynamic Power Allocation and Routing for Time Varying Wireless Networks Dynamic Power Allocation and Routing for Time Varying Wireless Networks X 14 (t) X 12 (t) 1 3 4 k a P ak () t P a tot X 21 (t) 2 N X 2N (t) X N4 (t) µ ab () rate µ ab µ ab (p, S 3 ) µ ab µ ac () µ ab (p,

More information

Network Traffic Characteristic

Network Traffic Characteristic Network Traffic Characteristic Hojun Lee hlee02@purros.poly.edu 5/24/2002 EL938-Project 1 Outline Motivation What is self-similarity? Behavior of Ethernet traffic Behavior of WAN traffic Behavior of WWW

More information

Performance Analysis of a Network of Event-Based Systems

Performance Analysis of a Network of Event-Based Systems 3568 IEEE TRANSACTIONS ON AUTOMATIC CONTROL, VOL. 61, NO. 11, NOVEMBER 2016 Performance Analysis of a Network of Event-Based Systems Chithrupa Ramesh, Member, IEEE, Henrik Sandberg, Member, IEEE, and Karl

More information

Message Delivery Probability of Two-Hop Relay with Erasure Coding in MANETs

Message Delivery Probability of Two-Hop Relay with Erasure Coding in MANETs 01 7th International ICST Conference on Communications and Networking in China (CHINACOM) Message Delivery Probability of Two-Hop Relay with Erasure Coding in MANETs Jiajia Liu Tohoku University Sendai,

More information

Analysis of random-access MAC schemes

Analysis of random-access MAC schemes Analysis of random-access MA schemes M. Veeraraghavan and Tao i ast updated: Sept. 203. Slotted Aloha [4] First-order analysis: if we assume there are infinite number of nodes, the number of new arrivals

More information

Computer Networks ( Classroom Practice Booklet Solutions)

Computer Networks ( Classroom Practice Booklet Solutions) Computer Networks ( Classroom Practice Booklet Solutions). Concept Of Layering 0. Ans: (b) Sol: Data Link Layer is responsible for decoding bit stream into frames. 0. Ans: (c) Sol: Network Layer has the

More information

An engineering approximation for the mean waiting time in the M/H 2 b /s queue

An engineering approximation for the mean waiting time in the M/H 2 b /s queue An engineering approximation for the mean waiting time in the M/H b /s queue Francisco Barceló Universidad Politécnica de Catalunya c/ Jordi Girona, -3, Barcelona 08034 Email : barcelo@entel.upc.es Abstract

More information

Stability Analysis in a Cognitive Radio System with Cooperative Beamforming

Stability Analysis in a Cognitive Radio System with Cooperative Beamforming Stability Analysis in a Cognitive Radio System with Cooperative Beamforming Mohammed Karmoose 1 Ahmed Sultan 1 Moustafa Youseff 2 1 Electrical Engineering Dept, Alexandria University 2 E-JUST Agenda 1

More information

Integrity-Oriented Content Transmission in Highway Vehicular Ad Hoc Networks

Integrity-Oriented Content Transmission in Highway Vehicular Ad Hoc Networks VANET Analysis Integrity-Oriented Content Transmission in Highway Vehicular Ad Hoc Networks Tom Hao Luan, Xuemin (Sherman) Shen, and Fan Bai BBCR, ECE, University of Waterloo, Waterloo, Ontario, N2L 3G1,

More information

Queues and Queueing Networks

Queues and Queueing Networks Queues and Queueing Networks Sanjay K. Bose Dept. of EEE, IITG Copyright 2015, Sanjay K. Bose 1 Introduction to Queueing Models and Queueing Analysis Copyright 2015, Sanjay K. Bose 2 Model of a Queue Arrivals

More information

Performance Effects of Two-way FAST TCP

Performance Effects of Two-way FAST TCP Performance Effects of Two-way FAST TCP Fei Ge a, Sammy Chan b, Lachlan L. H. Andrew c, Fan Li b, Liansheng Tan a, Moshe Zukerman b a Dept. of Computer Science, Huazhong Normal University, Wuhan, P.R.China

More information

Maximum Sum Rate of Slotted Aloha with Capture

Maximum Sum Rate of Slotted Aloha with Capture Maximum Sum Rate of Slotted Aloha with Capture Yitong Li and Lin Dai, Senior Member, IEEE arxiv:50.03380v3 [cs.it] 7 Dec 205 Abstract The sum rate performance of random-access networks crucially depends

More information