Database System Concepts
7th Edition
ISBN: 9780078022159
Author: Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher: McGraw-Hill Education
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Chapter 17, Problem 6PE
Explanation of Solution
Benefits of connectionless protocols over connection-oriented protocols:
- Most of the computer machines have restrictions on the number of concurrent connections they can typically accept.
- Using connectionless protocols, usually, connections are disconnected once a client’s request is fulfilled.
- Thus, other clients can request for open connections...
Explanation of Solution
Drawbacks of connectionless protocols over connection-oriented protocols:
- One of the major drawbacks of the connectionless protocols is that a connection must be reestablished each time a client request is sent...
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Students have asked these similar questions
Design a dynamic programming algorithm for the Coin-change problem described below:
Input: An amount of money C and a set of n possible coin values with an unlimited supply of each
kind of coin.
Output: The smallest number of coins that add up to C exactly, or output that no such set exists.
The algorithm must take O(n C) time. You must also write and explain the recurrence.
Example 1:
Input: C24, Coin values = = [1, 5, 10, 25, 50]
Output: 6 (since 24 = 10+ 10+1+1 +1 + 1)
Example 2:
Input: C = 86, Coin values = [1, 5, 6, 23, 35, 46, 50]
Output: 2 (since 86 = 46+35+5)
Design a dynamic programming algorithm for the Longest Common Subsequence problem de-
scribed below
Input: Two strings x = x1x2 xm and y = Y1Y2... Yn
Output: The length of the longest subsequence that is common to both x and y.
.
The algorithm must take O(m n) time. You must also write and explain the recurrence.
(I want the largest k such that there are 1 ≤ i₁ < ... < ik ≤ m and 1 ≤ j₁ < ... < jk ≤ n such that
Xi₁ Xi2 Xik = Yj1Yj2 ··· Yjk)
Example 1:
Input: x = 'abcdefghijklmnopqrst' and y = 'ygrhnodsh ftw'
Output: 6 ('ghnost' is the longest common subsequence to both strings)
Example 2:
Input: x = 'ahshku' and y = ‘asu'
Output: 3 ('asu' is the longest common subsequence to both strings)
Design a dynamic programming algorithm for the problem described below
Input: A list of numbers A = = [a1,..., an].
Output: A contiguous subsequence of numbers with the maximum sum.
The algorithm must take O(n) time. You must also write and explain the recurrence.
(I am looking for an i ≥ 1 and k ≥ 0 such that a + ai+1 + ···ai+k has the largest possible sum among all
possible values for i and k.)
Example 1:
Input: A[5, 15, -30, 10, -5, 40, 10].
Output: [10, 5, 40, 10]
Example 2:
Input: A = [7, 5, 7, 4, -20, 6, 9, 3, -4, -8, 4]
Output: [6,9,3]
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