II. Read each problem carefully and present an algorithm with the required running-time to solve each problem. 1. In class we discussed that directed acyclic graphs (DAG) can be used to represent dependency/precedence relations. One example is modeling task dependency where tasks are represented as vertices and edges represents direct dependencies between tasks, e.g., if task Ti requires task I, then there is an edge from vertex i to vertex j. Arranging tasks with respect to their dependencies can easily be done by performing topological sort to the DAG.
II. Read each problem carefully and present an algorithm with the required running-time to solve each problem. 1. In class we discussed that directed acyclic graphs (DAG) can be used to represent dependency/precedence relations. One example is modeling task dependency where tasks are represented as vertices and edges represents direct dependencies between tasks, e.g., if task Ti requires task I, then there is an edge from vertex i to vertex j. Arranging tasks with respect to their dependencies can easily be done by performing topological sort to the DAG.
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Transcribed Image Text:II. Read each problem carefully and present an algorithm with the required running-time to solve each
problem.
1. In class we discussed that directed acyclic graphs (DAG) can be used to represent
dependency/precedence relations. One example is modeling task dependency where tasks are
represented as vertices and edges represents direct dependencies between tasks, e.g., if task T
requires task T, then there is an edge from vertex i to vertex j. Arranging tasks with respect to their
dependencies can easily be done by performing topological sort to the DAG.
b. Describe an algorithm that runs in O(n + m) time that given a task T₁, outputs the minimum
possible position of tasks T, in any topological order.
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