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Summary :- Distributed Process Scheduling . Prepared BY:- JAYA KALIDINDI. Summary of chapter 5. A System performance model Static process scheduling Dynamic load sharing and balancing Distributed process implementation Real time scheduling. A system performance model[2].

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summary of chapter 5
Summary of chapter 5
  • A System performance model
  • Static process scheduling
  • Dynamic load sharing and balancing
  • Distributed process implementation
  • Real time scheduling
a system performance model 2
A system performance model[2]
  • Depicts the relationship among algorithm, scheduling and architecture to describe the Inter process communication
  • Basically three types of model are there:
  • Precedence process model(DAG)

Directed edges represent the precedence relationship

communication process model
Communication process model
  • In this model processes co-exist and Communicate synchronously.
  • Edges in this model represent the need of communication between the processes
disjoint process model
Disjoint process model:
  • In this processes run independently and completed in finite time.
  • Processes are mapped to the processors to maximize the utilization of processes and minimize the turnaround time of the processes.
speed up
Speed up

N- Number of processes

- Efficiency Loss when implemented on a real machine.

RC-relative concurrency

RP-relative processing requirement

Speed up depends on:

Design and efficiency of the scheduling algorithm.

Architecture of the system

static process scheduling
Static Process Scheduling
  • Is used to find optimal solution to the problem.
  • There are two extreme cases of work assignment.
  • mapping of processes is done before execution of the processes. once process started it stays at the processor until completion of the process. And never preempted.
  • Decentralized and non –Adaptive are the drawbacks of Static process scheduling.
dynamic load sharing and balancing
Dynamic load sharing and Balancing
  • Load balancing can be defined as a technique to distribute work between many computers processes or any other resources to get optimal resource utilization.
  • controller reduces the process idling through load sharing ie,by joining the shortest queue and equalizing queue sizes by load balancing.
  • Further, processes can be allowed to move from longer queue to shorter queue through load Redistribution.
sender initiated algorithm
Sender Initiated Algorithm
  • It is activated by a sender process that wishes to off-load some of its computation by migration of processes from a heavily loaded sender to a lightly loaded receiver.
  • Transfer of process form a sender to reciever requires three basic decisions.
    • Transfer policy:-when does the node become the sender?
    • Selection Policy:-How does the sender choose a process for transfer?
    • Location Policy:-which node should be the target reciever?
receiver initiated algorithm
Receiver initiated Algorithm:-
  • This are the pull models in which receiver can pull a process from others to its site for execution.
  • They are more stable than the sender initiated algorithm.
  • At high system load ,process migrations are few and a sender can be found easily.
  • Receiver initiated algorithms perform better than the sender initiated algorithms
  • Both the algorithms can be combined depending on RT and ST.
distributed process implementation
Distributed process implementation
  • Remote Service:-The message is interpreted as a request for a known service at the remote site
  • Three different software levels:-
    • As remote procedure calls at the language level.
    • As remote commands at the operating system level.
    • As interpretive messages at the application level.
distributed process implementation12
Distributed process Implementation

Depending on how the request messages are interpreted,

there are three main application scenarios:

  • Remote Service
    • The message is interpreted as a request for a known service at the remote site.
  • Remote Execution
      • The messages contain a program to be executed at the remote site.
  • Process Migration
      • The messages represent a process being migrated to a remote site for continuing the execution.
remote execution
Remote Execution
  • The purpose of remote service is to access the remote host unlike remote service remote process maintains the view of originating system.
  • Some Implementation issues:-
    • load sharing algorithms.
    • Location independence.
    • System heterogeneity.
    • Protection and security.
load sharing algorithm
Load-Sharing Algorithm
  • Each process server are responsible to maintain the load information.
  • The list of hosts participating are broadcasted.
    • The selection procedure is by a centralized broker process.
    • Once a remote host is selected-
      • The client process server indicates the resource requirements to the process server at the remote site.
      • If the client is authenticated and its resource requirements can be met, the server grants permission for remote execution.
      • The transfer of code image follows, and the server creates the remote process and the stub.
      • The client initializes the process forked at the remote site.
location independence
Location Independence
  • Process created by remote execution requires coordination to accomplish common task.
  • So it is necessary to support logical views for the processes.
  • Each remote process is represented by an agent process at the originating host.
  • It appears as though the process is running on a single machine.
system heterogeneity
System heterogeneity
  • If remote execution is invoked on heterogeneous host , then it is necessary to re-compile the program.
  • Overhead Issue.
  • Solution:
      • Use canonical machine-independent intermediate language for program execution.
process migration
Process Migration
  • The message represents a process being migrated to the remote site for continuing execution.
    • Process migration facility
    • State and context transfer:-It transfers the computation state information and communication state information
real time scheduling
Real Time Scheduling:-
  • The systems which insures that certain actions are taken within specified time constraints are called real time systems.

Can be classified as:

Static vs dynamic

Premptive vs non-premptive

Global vs Local

rate monotonic
Rate Monotonic
  • It’s easy to implement.
  • Sorts the tasks by the lengths of their periods.
  • It also makes very good priority assignments.
  • Rate monotonic is an optimal priority assignment algorithm.
Deadline Monotonic:-In real time system some tasks need to complete execution a short time after being requested.

Earliest Deadline First:-this is applies dynamic priority scheduling to achieve better CPU utilization .

Real time Synchronization:-A set of tasks that cooperate to achieve a goal will need to share information and resources or other words synchronize with other tasks.



[2]. Randy Chow, Theodore Johnson, “Distributed Operating Systems & Algorithms”, Addison Wesley.(all diagrams)

[3].Dejan S. Milojicic Fred DouglisYves Paindaveine Richard Wheeler Songnian Zhou, “Process Migration” , ACM Computing Surveys (CSUR) Volume 32 ,  Issue 3  (September 2000)

[4]. S. Cheng, J.A. Stankovic and K. Ramamritham, ‘‘Scheduling Algorithms for Hard Real-Time Systems: A Brief Survey’’, page6-7 in Hard Real-Time Systems: Tutorial, IEEE (1988).

[5] .Distributed Process Scheduling. Advanced Operating Systems Louisiana State University Rajgopal Kannan. Issues in Distributed

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