1. Distributed Process Management1 Learning Objectives Distributed Scheduling Algorithms Coordinator Elections Orphan Processes

2. Distributed Process Management2 Distributed Scheduling Algorithm Choices Level of scheduling –local scheduling –global scheduling Load distribution goals –load balancing –load sharing ? Study fig. 7.2 p. 153 ?

3. Distributed Process Management3 Scheduling Efficiency Goals Efficiency metrics: –time, execution cost, resource utilization Optimal scheduling is NP-Hard. Sub-optimal scheduling –sub-optimal approximate solutions –sub-optimal heuristic solutions

4. Distributed Process Management4 Processor Binding Time Processor binding time –determines at what point the scheduling algorithm decides when and where a process will execute. Static binding –processor assignment is done once at the link time Dynamic binding –process image is relocatable

5. Distributed Process Management5 Scheduling Algorithm Approaches Usage points –used with centralized server –usage table on the server contains an entry for each computer used in the system –usage points are either charged or credited to a processor charged if a processor requests utilization of remote resources credited if a processor makes itself available to others

6. Distributed Process Management6 Graph Theory Relies on obtaining the minimum cutset for a vertex of a graph. ?See fig. 7.5 p.161. How is the processor assignment created? Basis for evaluating performance: –minimize total execution and communication cost –minimize total interference costs.

7. Distributed Process Management7 Probes Messages are send to members of a system to locate an appropriate processor to schedule a process. –Distributed approach –optimal or suboptimal

8. Distributed Process Management8 Scheduling Queues Local and global scheduling queues. Priority based Hints from the user.

9. Distributed Process Management9 Stochastic Learning Stochastic learning is a heuristic that attempts to find the best solution based on previous actions (learning from experience) Each system state is represented by an automaton vector using workload indicators such as: –one-minute workload averages –amount of free memory –CPU idle time –Length of ready queue

10. Distributed Process Management10 Coordinator Election Used when there is a need for an elected centralized server in a distributed system. Study box 7.3 and fig 7.7 and explain the Bully algorithm

11. Distributed Process Management11 Orphan Processes Orphan process is a child process of a terminated process. Exacerbated in D.S. because of RPCs. Cleanup of orphan processes: –family trees (study fig 7.8 and box 7.4 p 171) –child process allowance (study fig.7.9 p. 173)