Math Problem Statement

Solve

A scheduling problem is modeled by a directed acyclic graph (DAG) with tasks T1 to T9, each having a specific processing time. The objective is to find a schedule for two processors that completes all tasks within 15 hours, respecting dependencies. Additionally, calculate bounds on the optimal finishing time.

Solution

The problem involves scheduling tasks on two processors for a directed acyclic graph (DAG), where each task TiT_i 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:
    • T1T1: 1 hour
    • T2T2: 1 hour
    • T3T3: 2 hours
    • T4T4: 1 hour
    • T5T5: 1 hour
    • T6T6: 5 hours
    • T7T7: 2 hours
    • T8T8: 4 hours
    • T9T9: 5 hours
  • Dependencies (from the arrows):
    • T1T4,T5T1 \rightarrow T4, T5
    • T2T5T2 \rightarrow T5
    • T3T6T3 \rightarrow T6
    • T4T7T4 \rightarrow T7
    • T5T8T5 \rightarrow T8
    • T6T9T6 \rightarrow T9
    • T7T8T7 \rightarrow T8
    • T8,T9EndT8, T9 \rightarrow \text{End}

Step 2: Schedule Tasks on Two Processors

Criteria:

  1. Respect dependencies.
  2. Minimize overall completion time.
  3. 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 1Processor 2Time Interval
T1T1T2T20 - 1
T4T4T3T31 - 3
T5T5T6T63 - 8
T7T73 - 5
T8T8T9T98 - 13
EndEnd13

Explanation:

  • 0-1 hours: Processor 1 handles T1T1, and Processor 2 handles T2T2 (independent tasks).
  • 1-3 hours: T4T4 (depends on T1T1) is assigned to Processor 1, and T3T3 (independent) to Processor 2.
  • 3-8 hours: T5T5 (depends on T1T1 and T2T2) is on Processor 1, and T6T6 (depends on T3T3) is on Processor 2.
  • 3-5 hours: T7T7 (depends on T4T4) starts on Processor 1.
  • 8-13 hours: T8T8 (depends on T5T5 and T7T7) on Processor 1, and T9T9 (depends on T6T6) 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: T1T4T7T8EndT1 \rightarrow T4 \rightarrow T7 \rightarrow T8 \rightarrow \text{End} with total time 1+1+2+4=81 + 1 + 2 + 4 = 8 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

  1. How would the schedule change if there was an additional processor?
  2. How would different task durations affect the optimal schedule?
  3. What happens if one of the dependencies is removed?
  4. Could tasks T1T1 and T2T2 be scheduled on the same processor initially?
  5. 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.

Ask a new question for Free

By Image

Drop file here or Click Here to upload

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