From Computer Science Wiki
Resource Management[1]


Definition of policies[edit]

In the context of computing and operating systems, policies refer to a set of rules, principles, or guidelines that determine how specific tasks or operations are performed. Policies help manage various aspects of a system, such as resource allocation, scheduling, security, and access control. They provide a framework for making decisions and taking actions in a consistent and predictable manner, ensuring the efficient and orderly functioning of the system.

Types of policies[edit]

Preemptive vs. non-preemptive scheduling[edit]

Preemptive and non-preemptive scheduling are two types of scheduling approaches used in operating systems to manage the execution of processes or tasks. They differ primarily in how they handle the allocation and reallocation of the CPU to processes. Preemptive scheduling: In preemptive scheduling, the operating system has the ability to interrupt a running process and reallocate the CPU to another process. This typically occurs when a higher-priority process enters the ready queue or when the currently executing process has exhausted its allocated time quantum in time-sharing systems.

Preemptive scheduling allows for better responsiveness, as it can quickly allocate resources to high-priority or time-sensitive tasks. However, it also introduces the overhead of context switching, which is the process of saving the state of the preempted process and restoring the state of the new process that takes over the CPU.

Real-time vs. best-effort scheduling[edit]

Real-time and best-effort scheduling are two different approaches used in operating systems and other computing environments to manage the execution of processes or tasks. They differ primarily in their objectives and the requirements they impose on the system. Real-time scheduling: Real-time scheduling is used in systems where processes or tasks have strict timing constraints and deadlines that must be met. In real-time systems, the primary objective is to ensure that processes complete their execution within specified deadlines to avoid any negative consequences, such as system failure, data loss, or reduced performance.

Real-time scheduling algorithms focus on guaranteeing deterministic and predictable behavior, ensuring that high-priority and time-sensitive tasks receive the necessary resources in a timely manner. There are two main types of real-time scheduling:

  1. Hard real-time scheduling: Missing a deadline in a hard real-time system can lead to catastrophic consequences, such as system failure or loss of life. Examples of hard real-time systems include flight control systems, medical equipment, and nuclear power plant control systems.
  2. Soft real-time scheduling: In soft real-time systems, missing a deadline may cause degraded performance but does not lead to system failure or severe consequences. Examples of soft real-time systems include multimedia applications, video games, and communication systems.
  3. Best-effort scheduling: Best-effort scheduling, also known as general-purpose scheduling, is used in systems where there are no strict timing constraints or deadlines for processes. The primary objective of best-effort scheduling is to optimize system performance, throughput, and responsiveness while maintaining a fair allocation of resources among all processes.

Best-effort scheduling algorithms focus on balancing factors such as process priority, execution time, and waiting time to ensure efficient resource utilization and provide a good user experience. Examples of best-effort scheduling algorithms include First-Come, First-Served (FCFS), Shortest Job Next (SJN), Priority Scheduling, and Round Robin.

In summary, real-time scheduling is used in systems with strict timing constraints and deadlines, while best-effort scheduling is used in general-purpose systems where the focus is on optimizing system performance, throughput, and responsiveness. The choice of scheduling approach depends on the specific requirements and objectives of the system in question.

Time-sharing vs. batch processing[edit]

Time-sharing and batch processing are two different approaches used in computing systems for managing the execution of tasks and utilizing system resources. Time-sharing: Time-sharing, also known as multitasking or interactive processing, is a method that allows multiple users or processes to share a single computing system's resources concurrently. In time-sharing systems, the CPU and other system resources are allocated to each user or process for a small time slice or time quantum, making it appear as if each user has their own dedicated system.

The main goals of time-sharing systems are to provide fast response times, support multiple users or processes simultaneously, and optimize resource utilization. Time-sharing systems often employ preemptive scheduling algorithms, such as Round Robin, to manage resource allocation and ensure that each process gets a fair share of the CPU time.

Time-sharing systems are commonly used in environments where users interact with the system in real-time, such as online applications, desktop operating systems, and multi-user systems.

Batch processing: Batch processing is a method in which a series of tasks or jobs are executed sequentially without any user interaction. In batch processing systems, tasks are grouped together in a batch, and the system processes the entire batch at once, often during periods of low system demand or scheduled maintenance windows. Batch processing is designed to optimize throughput, processing large volumes of data or tasks efficiently and with minimal intervention. Batch processing systems usually employ non-preemptive scheduling algorithms, such as First-Come, First-Served (FCFS) or Shortest Job Next (SJN), to manage the execution of tasks. Batch processing is commonly used in environments where tasks can be executed without real-time user interaction or immediate response, such as data processing, report generation, and system maintenance tasks.

In summary, time-sharing systems focus on providing fast response times and supporting multiple users or processes concurrently, while batch processing systems prioritize throughput and efficiency for large volumes of tasks without real-time user interaction. The choice between time-sharing and batch processing depends on the specific requirements and objectives of the computing environment.

Importance of policies in resource management[edit]

Policies play a crucial role in resource management within computing systems, such as operating systems, by providing a consistent and systematic framework for making decisions and taking actions. The importance of policies in resource management can be highlighted through several key aspects:

  1. Efficient resource allocation: Policies define how resources, such as CPU time, memory, and I/O devices, are allocated to processes or tasks. By establishing a set of rules for resource allocation, policies help ensure that resources are used efficiently and optimally, maximizing system performance and throughput.
  2. Fairness: Policies help maintain fairness in resource allocation among different processes or users. By enforcing rules that prevent resource monopolization and ensuring that all processes have a fair chance to access resources, policies can help prevent issues such as starvation and provide a better user experience.
  3. Responsiveness: In interactive systems, policies are crucial for maintaining system responsiveness. By prioritizing processes based on factors such as importance, time constraints, or resource requirements, policies can ensure that critical and time-sensitive tasks receive the necessary resources promptly.
  4. Predictability: Policies provide a systematic approach to resource management, enabling consistent and predictable system behavior. This predictability is essential in many computing environments, such as real-time systems, where meeting strict timing constraints and deadlines is crucial.
  5. Security and access control: Policies also play an essential role in maintaining system security and controlling access to resources. By defining rules for user authentication, authorization, and access control, policies help protect system resources from unauthorized access and ensure that users have the appropriate permissions for their tasks.
  6. Adaptability and scalability: Policies provide a flexible framework for managing resources that can be adapted to different computing environments and scaled to accommodate changing requirements. By allowing for adjustments in resource allocation and scheduling, policies can help maintain optimal system performance and user experience under varying workloads and conditions.

In summary, policies are vital in resource management as they provide a structured and systematic approach for allocating resources, maintaining fairness and responsiveness, ensuring security and access control, and adapting to changing requirements. By implementing effective policies, computing systems can achieve optimal performance, user satisfaction, and overall system stability.


  • Outline OS resource management techniques: scheduling, policies, multitasking, virtual memory, paging, interrupt, polling.