CPU timing
The CPU temporalization It refers to the process through which an operating system manages the allocation and distribution of the processing time processing time (CPU) between multiple processes or threads in execution. This concept is fundamental in operating systems architecture, since it allows optimizing system performance, guarantee equity in access to resources and improve the response of applications. In this article, The different temporalization algorithms will be explored, Its characteristics, and the impact they have on the performance of operating systems.
History and evolution of temporalization
CPU time management has evolved significantly from the first operating systems. In the beginning, The systems were predominantly batch processing, where tasks were executed sequentially. As the need for interactivity and multitasking grew, New temporalization methods were developed.
Shared time systems
Shared time systems arose in the decade of 1960, allowing several users to interact with a single machine simultaneously. This approach required a more sophisticated management of CPU time, since each user should have a quick response experience. Planning algorithms such as Round Robin and Shortest Job First were introduced (SJF) To facilitate this management.
Processes and threads
With the arrival of processes and thread architecture, Temporalization became even more complex. Modern operating systems need to manage both complete processes and threads within these processes. Each thread can have different priorities and time requirements, which complicates the efficient assignment of CPU time.
Temporalization algorithms
There are several temporalization algorithms that operating systems use to manage the CPU time allocation. Each has its advantages and disadvantages, And your choice can significantly impact system performance.
1. Round Robin (RR)
Robin Round algorithm is one of the simplest and most widely used. Works by assigning each process a fixed time interval, known as "quantum". If a process does not end within your quantum, It is placed at the end of the tail and the next process in the tail receives the CPU time.
Advantages:
- Simplicity: Easy to implement and understand.
- Equity: All processes have the same opportunity to access the CPU.
Disadvantages:
- Time waste: If the quantum is too small, There is a high overhead of context change.
- Non -optimal for long -term processes: Can lead to low efficiency if there are many short and long processes.
2. Shortest Job First (SJF)
The SJF algorithm assigns the CPU to the shortest execution time. This approach minimizes the average waiting time of processes in the tail.
Advantages:
- Efficiency: Reduces the average waiting time.
- Ideal for predictable work: It works well when the execution times are known and constant.
Disadvantages:
- Difficulty: It can be difficult to implement in dynamic systems.
- Injustice: Long -lasting processes can be constantly delayed, What is known as "Starvation".
3. Priority
The priority algorithm assigns the CPU to the process with the highest priority. Priorities can be static (fixed) The Dinamic (change during execution).
Advantages:
- Flexibility: Allows the system to manage critical tasks more effectively.
- Adaptability: Priorities can be adjusted according to system load.
Disadvantages:
- Starvation: Low priority processes may be indefinitely postponed.
- Complexity: Maintaining a priority system requires careful management.
4. Multilevel Feedback Queue (MLFQ)
The Multilevel feedback algorithm that combines multiple queues with different priorities. A process can move between queues based on its behavior and execution time.
Advantages:
- Adaptability: It adapts well to different types of workloads.
- Swinging: Improve equity and reduce waiting time for short processes.
Disadvantages:
- Complexity: Its implementation can be complicated.
- Setting: Requires careful configuration to function properly.
Context Switching
The Context change It is the process by which an operating system keeps the status of a process in execution and loads the status of another process. This process is critical of temporalization, since it allows multitasking.
Context change process
- State saved: The system keeps the CPU records and the current process information in its data structure.
- Selection of the next process: The following process to be executed according to the chosen temporalization algorithm is selected.
- State load: The records and context of the new process are restored.
- Run: The CPU begins to execute the new process.
Context change costs
Context change, although necessary, It has an associated cost that can reduce the general efficiency of the system. This cost includes:
- Weather: The time that is lost during the change of context itself, which can be significant if it occurs frequently.
- Resources: The use of memory and other system resources to store the states of the processes.
Modern operating systems implement techniques to minimize context change, such as the optimization of the quantum in Round Robin or the process grouping.
Planning in modern operating systems
Planning in modern operating systems, like Windows 10, Linux O MacOS, has evolved to efficiently handle CPU temporalization. Each operating system has its own set of algorithms and programming strategies.
Windows
In Windows, A planning algorithm based on priorities with several levels is used. Each process receives a priority that influences its access to the CPU. Windows also implements real -time planning for critical tasks, ensuring that these have immediate access to system resources.
Linux
Linux uses a completely different planning approach based on Completely Fair Scheduler algorithm (CFS). This algorithm uses a "shared time" approach, where a CPU time proportional to the priority of each process is assigned, ensuring that all processes receive their fair part of CPU time.
macOS
Macos combines shared time planning elements and real time, allowing critical processes to have priority. What's more, Use priorities -based planning algorithm, similar to Windows, But with specific optimizations for efficient multitasking.
Impact of temporary performance
The way in which CPU temporalization is managed can have a significant impact on the general performance of a system. Some of the most notable effects include:
Latency and response
Latency refers to the time that passes from the moment an appeal is requested until. The choice of a temporalization algorithm can affect this latency. For example, An algorithm like Round Robin can offer more predictable response times for interactive applications compared to SJF.
Use of the CPU
The use of the CPU refers to the percentage of time that the CPU is effectively processing tasks. INEFICIENT ALGORITMOS can lead to a low use of the CPU, since time can be wasted in context change processes or waiting for low priority processes.
Equity in the allocation of resources
Equity is an essential aspect in resource management. Temporalization algorithms must ensure that all processes have the opportunity to access the CPU. The lack of equity can lead to inefficient performance and user frustration.
Conclution
CPU temporalization is a critical aspect in the management of modern operating systems, affecting the efficiency and performance of applications. With a variety of planning algorithms available, each with its advantages and disadvantages, It is essential that system developers and administrators understand how to select and configure the appropriate algorithm for their specific needs. As technology progresses and operating systems evolve, CPU temporalization will continue to be a key research and development area to improve user efficiency and experience.
