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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 distributed process scheduling l.jpg

Summary :- Distributed Process Scheduling

Prepared BY:-


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Summary of chapter 5

  • A System performance model

  • Static process scheduling

  • Dynamic load sharing and balancing

  • Distributed process implementation

  • Real time scheduling

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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

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Communication process model

  • In this model processes co-exist and Communicate synchronously.

  • Edges in this model represent the need of communication between the processes

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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.

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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

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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.

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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.

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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?

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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.

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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.

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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.

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    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.

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    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.

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    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.

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    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.

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    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

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    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

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    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.

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    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.

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    [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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