Math Problem Statement
Solve
Solution
The problem involves scheduling tasks on two processors for a directed acyclic graph (DAG), where each task has a given processing time (in parentheses) and dependencies represented by directed edges.
Let’s go through it step-by-step.
Step 1: Identify Task Durations and Dependencies
From the graph:
- Tasks with durations:
- : 1 hour
- : 1 hour
- : 2 hours
- : 1 hour
- : 1 hour
- : 5 hours
- : 2 hours
- : 4 hours
- : 5 hours
- Dependencies (from the arrows):
Step 2: Schedule Tasks on Two Processors
Criteria:
- Respect dependencies.
- Minimize overall completion time.
- Use no more than 15 hours.
Possible Schedule
We’ll aim to balance the load across two processors and sequence tasks based on dependencies. Here’s one feasible schedule:
Processor 1 | Processor 2 | Time Interval |
---|---|---|
0 - 1 | ||
1 - 3 | ||
3 - 8 | ||
3 - 5 | ||
8 - 13 | ||
End | End | 13 |
Explanation:
- 0-1 hours: Processor 1 handles , and Processor 2 handles (independent tasks).
- 1-3 hours: (depends on ) is assigned to Processor 1, and (independent) to Processor 2.
- 3-8 hours: (depends on and ) is on Processor 1, and (depends on ) is on Processor 2.
- 3-5 hours: (depends on ) starts on Processor 1.
- 8-13 hours: (depends on and ) on Processor 1, and (depends on ) on Processor 2.
- End: Both processors complete by hour 13.
Step 3: Optimal Completion Time
Using the above schedule, the total time is 13 hours, which is within the 15-hour limit.
Step 4: Bound on Optimal Finishing Time
For part (b), using the critical path (longest path through the task graph):
- Critical Path: with total time hours.
- Lower Bound on Optimal Time: 8 hours (time to complete the critical path).
The schedule achieves a completion time of 13 hours, which is close to optimal given dependencies and processor constraints.
Would you like further details on each step or have any specific questions?
Related Questions
- How would the schedule change if there was an additional processor?
- How would different task durations affect the optimal schedule?
- What happens if one of the dependencies is removed?
- Could tasks and be scheduled on the same processor initially?
- How do different scheduling algorithms, like Earliest Start Time, affect the outcome?
Tip
When dealing with scheduling problems, visualize dependencies and critical paths to identify constraints quickly.
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Math Problem Analysis
Mathematical Concepts
Scheduling
Graph Theory
Critical Path Analysis
Formulas
Total time = sum of task durations on the critical path
Processor scheduling algorithms
Theorems
Critical Path Theorem
Greedy Scheduling Algorithm
Suitable Grade Level
College-level Discrete Mathematics or Operations Research
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