Computer Networks
CN Part-1
- What is a Computer Network?
- Goals and Applications of Computer Networking
- Computer Network Components
- Types of Computer Networks
- Network Topology
- Difference between Client Server and Peer to Peer Network
- Layered Architecture in Computer Networks
- Protocol Hierarchy in Computer Networks
- Interfaces and Services in Computer Networks
- Connection Oriented and Connectionless Services
- Service Primitives
- OSI Model
- TCP/IP Model
- Difference between OSI Model and TCP/IP Model
- Encapsulation and Decapsulation in Computer Networks
- Queueing Models in Computer Network
CN Part-2
Queueing Models in Computer Networks
Queueing Model Kya Hota Hai?
Jab network par bahut saare data packets ek server ya router par aate hain, to wo line (queue) mein lag jaate hain. Queueing model help karta hai yeh samajhne mein ki:
-
Packets kitni speed se aa rahe hain (arrival rate)
-
Ek packet ko process karne mein kitna time lagta hai (service rate)
-
System mein kitna delay ho raha hai
-
Kitne servers available hain
-
Kya packet drop hote hain agar jagah nahi hai?
Socho ek ATM par log line mein lag rahe hain — yeh ek queue hai. Har aadmi ek packet ki tarah hai jo wait kar raha hai server (ATM machine) se serve hone ke liye.
Important Terms:
Term | Meaning (Hinglish) |
---|---|
λ (lambda) | Kitne packets per second system mein aa rahe hain (arrival rate) |
μ (mu) | Ek server kitne packets per second serve kar sakta hai (service rate) |
Queue | Wo line jahan packets wait karte hain |
Server | Wo machine ya process jo packet ko handle karta hai |
ρ (rho) | Server ki busy hone ki percentage (utilization) – ρ = λ / μ |
Little’s Theorem – Super Simple Formula
Formula: L = λ × W
Symbol | Meaning |
---|---|
L | System mein average packets |
λ | Packets aane ki speed |
W | Har packet ka system mein rukne ka average time |
Example:
-
5 packets/sec aa rahe hain (λ = 5)
-
Har packet 0.4 sec rukta hai (W = 0.4)
-
To system mein average 5 × 0.4 = 2 packets hamesha hote hain
Common Queueing Models (Kendall’s Notation)
Queueing models ko likhne ka ek format hota hai:
A/S/c
-
A (Arrival) → kaise packets aate hain (M = exponential)
-
S (Service) → server kaise process karta hai (M ya G)
-
c (Servers) → kitne servers hain
M = “Memoryless” yaani exponential distribution (most common),
G = General (koi bhi distribution)
M/M/1 Queue – Sabse Basic Aur Common Model
Feature | Value |
---|---|
Arrival | M (exponential) |
Service | M (exponential) |
Servers | 1 |
Diagram:
Users → [Queue] → (1 Server) → Output
Use Case:
-
Ek router ya printer jahan sabko line mein wait karna padta hai
Example:
-
λ = 4/sec, μ = 5/sec
-
ρ = λ / μ = 4 / 5 = 0.8 → server 80% time busy hai
-
Delay = 1 / (μ – λ) = 1 second average waiting time
Agar ρ 1 se zyada ho gaya, to queue kabhi khatam nahi hogi!
M/M/m Queue – Jab Ek Se Zyada Server Hain
Feature | Value |
---|---|
Servers | m (multiple) |
Diagram:
Users → [Queue] → (Server 1)
(Server 2)
...
(Server m)
Use Case:
-
Call centers (multiple agents)
-
Zomato kitchen jahan ek se zyada chef ho
Example:
-
λ = 12/sec, μ = 4/sec, m = 4 servers
-
Total capacity = 4 × 4 = 16/sec
-
Utilization = 12 / 16 = 0.75 → servers 75% time busy
M/M/∞ Queue – Unlimited Servers, No Waiting
Feature | Value |
---|---|
Servers | ∞ (infinite) |
Diagram:
Users → (Server 1)
(Server 2)
...
(Server ∞)
Use Case:
-
Cloud-based apps jaise Google Search, ChatGPT etc.
-
Har user ko instantly ek server mil jaata hai
Feature:
-
Koi queue nahi hoti, har request instantly serve hoti hai
M/M/m/m Queue – Fixed Servers, No Queue, Request Drop
Feature | Value |
---|---|
Servers | m |
Queue | nahi hai |
Blocking | yes |
Diagram:
Users → (Server 1)
(Server 2)
...
(Server m)
If full → Request dropped
Use Case:
-
Mobile networks jahan limited calling channels hote hain
-
Agar 4 calls chal rahi hain aur 5th aayi → busy tone
Isse Blocking Probability calculate karne ke liye Erlang B formula use hota hai
M/G/1 Queue – Flexible Service Time, 1 Server
Feature | Value |
---|---|
Arrival | M |
Service | G (General) |
Server | 1 |
Use Case:
-
Web server jahan kabhi chhoti file (image) aur kabhi badi file (video) serve hoti hai
-
Service time fix nahi hota
Note:
-
Ye zyada realistic model hai, but complex calculations hoti hain
Full Comparison Table
Model | Arrival | Service | Servers | Queue | Blocking | Use Case |
---|---|---|---|---|---|---|
M/M/1 | M | M | 1 | Yes | No | Printer, single router |
M/M/m | M | M | m | Yes | No | Call centers, load balancing |
M/M/∞ | M | M | ∞ | No | No | Cloud computing |
M/M/m/m | M | M | m | No | Yes | Mobile networks |
M/G/1 | M | General | 1 | Yes | No | Realistic server model |
Summary
Concept | Easy Explanation |
---|---|
Queueing Model | Request ki line aur server ka behavior model |
Little’s Law | L = λ × W – packets, arrival rate, aur delay ka relation |
M/M/1 | Ek server, exponential arrival/service |
M/M/m | Multiple servers |
M/M/∞ | Unlimited servers, zero waiting |
M/M/m/m | Fixed servers, request drop ho sakti hai |
M/G/1 | Flexible service time ke saath ek server |
Real Life Analogy Summary
Model | Real Example |
---|---|
M/M/1 | ATM machine |
M/M/m | Hospital with multiple doctors |
M/M/∞ | Search engine like Google |
M/M/m/m | Phone line with limited seats |
M/G/1 | Xerox shop with small and large jobs |