Operating System
OS Part-1
OS Part-2
- File Concepts and Access methods
- Free Space Management and Allocation methods
- Directory Systems and Protection
- File Organization, Sharing and Implementation issues
- Disk and Drum Scheduling
- I/O Devices Organisation & I/O Buffering
- I/O Hardware, Kernel I/O subsystem and Transforming I/O Requests to Hardware Operations
- Device Drivers and Path Management
- Device Driver Sub Modules and Procedure
- Device Scheduler and Handler
- Interrupt Service Routine (ISR)
- File System in Linux and Windows
OS Part-3
- Process and Process Control Block(PCB)
- Process Scheduling( Preemptive and Non Preemptive)
- Scheduling Algorithms
- Algorithm Evaluation
- Multiple Processor Scheduling
- Real Time Scheduling
- Operations on Processes
- Threads
- Inter-Process Communication
- Precedence Graphs
- Critical Section Problem
- Semaphores
- Classical Problems of Synchronization
- DeadLock
- Deadlock Prevention and Avoidance
- Deadlock Detection and Recovery
- Process Management in Linux
OS Part-4
- Memory Hierarchy in OS
- Concepts of Memory Management
- MFT and MVT
- Logical and Physical Address Space
- Swapping
- Contiguous and Non Contiguous Memory Allocation
- Paging
- Segmentation
- Paging Combined with Segmentation
- Structure and Implementation of Page Table
- Virtual Memory in OS
- Cache Memory Organization
- Demand Paging
- Page Replacement Algorithms
- Allocation of Frames and Thrashing
- Demand Segmentation
OS Part-5
- Distributed Operating System: Introduction and Types
- Distributed OS: Design Issues
- Distributed OS: File System
- Distributed OS: Remote File Access
- Remote Procedure Call(RPC)
- Remote Method Invocation(RMI)
- Distributed Shared Memory
- Parallel Processing and Concurrent Programming
- Security and Threats Protection in Distributed OS
- Security Design Principles and Authentication in Distributed OS
- Sensor Network and Parallel OS
Sensor Network & Parallel Operating System in OS
Sensor Network in Operating System
What is a Sensor Network?
Sensor Network ek collection hoti hai tiny, wirelessly connected sensor nodes ki, jo environment se data collect karte hain aur ek central system ko send karte hain.
Features of Sensor Networks
Self-organizing: Sensors automatically connect aur communicate karte hain. Scalable: Thousands of sensors ko ek network me add kiya ja sakta hai.
Energy Efficient: Low power consumption ke liye optimized hote hain. Fault Tolerance: Agar ek sensor fail ho jaye, to network adjust kar leta hai.
Architecture of Sensor Network
Diagram: Sensor Network Architecture
Sensor Nodes: Data collect karte hain. Base Station: Data process aur transmit karta hai. Cloud Server: Data store aur analyze hota hai. End User: Processed data ko use karta hai.
Applications of Sensor Networks
Healthcare Monitoring: Wearable sensors heart rate, BP measure karte hain. Smart Agriculture: Sensors temperature, soil moisture detect karte hain. Military Surveillance: Enemy movement detect karne ke liye use hote hain. Smart Cities: Traffic monitoring, pollution detection ke liye use hote hain.
Parallel Operating System
What is a Parallel OS?
Parallel Operating System ek aisa OS hai jo multiple processors ko ek sath kaam karne ki capability deta hai. Ek single task ko multiple processors me divide karke execute karta hai taaki performance improve ho.
Example: Supercomputers me Parallel OS ka use hota hai taaki large-scale scientific computations fast ho sakein.
Architecture of Parallel OS
Diagram: Parallel OS Structure
Process Management: Multiple processors ke liye task scheduling karta hai. Memory Management: Shared Memory ya Distributed Memory ka use hota hai. I/O Management: Data fast access ho taaki performance best rahe.
Types of Parallel OS
Shared Memory Model: Multiple processors ek common memory ka use karte hain. Distributed Memory Model: Har processor ka apna separate memory module hota hai.
Advantages of Parallel OS
Increased Speed: Tasks parallel execute hone se execution fast hoti hai. Better Resource Utilization: Multiple processors ka efficient use hota hai. Scalability: Naye processors easily add kiye ja sakte hain.
Applications of Parallel OS
Scientific Simulations: Climate modeling, space research me use hota hai. Artificial Intelligence: Large-scale machine learning models train karne ke liye. Real-Time Processing: Video rendering, high-speed trading systems me use hota hai.
Conclusion
Sensor Networks environment se data collect karke ek centralized system tak bhejte hain, jo IoT aur monitoring applications ke liye important hai. Parallel OS multiple processors ko efficiently use karke high-speed computing enable karta hai. Dono technologies future computing aur automation ke liye critical hain!