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Resource Allocation Techniques for Processes

Last Updated : 25 Oct, 2025
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In a multitasking operating system, multiple programs or processes run simultaneously, all competing for system resources like CPU time, memory, I/O devices and files. To ensure smooth execution, the Operating System (OS) acts as a manager - allocating resources to programs when needed and reclaiming them once the programs terminate.

There are two major resource allocation techniques:

1. Resource Partitioning Approach

In the resource partitioning approach, the operating system divides all available resources into fixed partitions before program execution begins. Each resource partition is treated as a bundle of resources, such as:

  • A specific portion of memory (e.g., 1 MB)
  • A fixed number of disk blocks
  • A dedicated I/O device (e.g., printer)

Note: The OS assigns one resource partition to each user program before execution. Once allocated, that program uses only the resources within its assigned partition.

Working

  1. The OS defines several resource partitions at system boot time.
  2. Each partition contains a set of resources.
  3. The Resource Table records all partitions, their components and their allocation status - Allocated or Free.
  4. When a program starts, it is assigned one entire partition.
  5. After the program terminates, its partition is marked Free for reuse.

Example Resource Table

Resource TypeTotalAllocatedFree
Memory (MB)853
Disk Blocks1007525
Printers211

Note: Here, each partition (P1, P2, P3) groups multiple resources. At system boot, this Resource Table is initialized and maintained by the OS.

Advantages of Resource Partitioning

  • Easy to Implement: The OS only needs to assign a partition to each process once.
  • Low Overhead: Since allocation happens only at process startup, management is simple.

Disadvantages of Resource Partitioning

  • Lack of Flexibility: If a program needs more resources than its assigned partition provides, it cannot run - even if other partitions have free resources.
  • Wastage of Resources: When a process uses fewer resources than what its partition holds, the remaining resources go unused.

Example: If a partition contains 2 MB memory but a program only uses 1 MB, the remaining 1 MB remains idle.

2. Pool-Based Approach

Unlike the rigid partitioning approach, the pool-based approach maintains a common pool of resources. Whenever a program requests a resource, the OS dynamically allocates it from the resource pool if available. When the program finishes or releases the resource, it is returned to the pool for reuse.

Working

  1. All resources are kept in a shared pool.
  2. Each resource’s status (free or allocated) is tracked in the Resource Table.
  3. When a process requests a resource: The OS checks its availability in the table. If available, it is allocated to the requesting process.
  4. Once released, the resource’s status is updated back to Free in the table.

Example Resource Table

Resource TypeTotalAllocatedFree
Memory (MB)853
Disk Blocks1007525
Printers211

Note: Whenever a process requests memory or an I/O device, the OS dynamically checks this table to allocate available resources.

Advantages of Pool-Based Approach

  • Efficient Utilization of Resources:
    No resource remains idle unnecessarily. Every available resource can be allocated on demand.
  • Flexibility:
    Any process can get resources as long as they are free, regardless of fixed partitions.

Disadvantages of Pool-Based Approach

  • Higher Overhead: Frequent allocation and deallocation require constant updates to the resource table, increasing system overhead.
  • Complex Management: The OS must handle synchronization, deadlock prevention and fair allocation dynamically.

Comparison - Partitioning vs Pool-Based Approach

CriteriaResource PartitioningPool-Based Approach
Allocation TimeBefore program executionDuring program execution
FlexibilityRigid and staticDynamic and adaptive
Resource UtilizationMay waste unused resourcesEfficient usage of all resources
OverheadLowHigh
Implementation ComplexitySimpleComplex
ScalabilityLimitedScalable
Use CaseEmbedded or static systemsModern multitasking OS

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