Dr. Alexios Louridas
Channel capacity, nominal & effective
Channel utilization
Delay and jitter
Packet loss and errors
The maximum number of bits that can be transmitted for a unit of time (eg: bits per second)
Depend on bandwidth, CPU processing.
Dependent on overheads of the protocols and algorithms used.
Effective capacity of a channel is always less than the nominal
The smallest value that is larger than 95% of the values in a given sample
The smallest value that is larger than 95% of the values in a given sample
Or rather, the peaks are discarded from consideration
Why is this important in networks?
Gives you an idea of the standard, sustained channel utilization.
ISPs use this measure to bill customers with “larger” connections.
Processor delays
Buffer delays
Transmission delays
Propagation delays
The time required to push all the bits in a packet on the transmission medium in use
For N=Number of bits, S=Size of packet, d=delay
For example, to transmit 1024 bits using Ethernet at (100Mbps):
The time it takes for a signal to travel through a transmission medium, such as a cable, from one point to another.
It is a measure of the time it takes for a signal to travel from the source to the destination, taking into account the speed of the signal in the transmission medium.
Network congestion: When there is too much data being sent over a network
Router or switch problems: not enough buffer size
Bad cabling or weather: Damaged connectors or cables, adverse weather conditions
Latency: packets take too long to travel from the source to the destination
Interference: from other devices or environmental factors
Hardware and Software Failures: Broken cables, network card bugs
principle in queueing theory named after John D.C. Little.
the average number of customers in a stable system is equal to the average arrival rate multiplied by the average time that a customer spends in the system
In a steady state the mean arrival rate (λ) of packets into a system is equal to the mean output rate (throughput) of packets departing the system
The total number of bits, packets, processes, threads (L) in a system is given by:
where W is the mean total time spent in the system processing
Packet arrival rate varies. Jitter measures this variability. Applications have a tolerance level.
Packet arrival
Packet departure
Add Headers
Queue - Buffer
Packet arrival
Packet departure
Add Headers
Queue - Buffer
Packet departure
Packet departure
Packet arrival
Packet departure
Add Headers
Queue - Buffer
Packet arrival
Packet arrival
Packet departure
Packet departure
A mathematical representations of a network system that involves waiting in buffer etc
Assumes that the arrival and service times of packets are fixed and known in advance.
Assumes that the arrival and service times of customers are random variables and can follow a particular probability distribution.
If λ > μ, then your system would start dropping packets in t seconds.
If λ ≤ μ, there shall be no reason for a buffer?
Using Kendall notation
Arrival Distribution / Service Distribution / Number of Servers
M/M/1
M/M/m
G/G/3
M stands for "Markovian", implying a distribution
D stands for Deterministic
G for general
m being a number
User experience: Poor network performance can result in slow response times, lost data, and other issues that can negatively impact user experience.
Business productivity: Slow or unreliable networks can result in lost time and opportunities, while high-performing networks can help organizations work more efficiently and effectively.
Competitive advantage: Network performance can be a key factor in determining an organization's competitiveness.
Cost savings: Network performance can also impact an organization's bottom line by reducing costs associated with network downtime, maintenance, and support.