Suppose that we run the sliding window algorithm with SWS 5 and RWS = 3, and no out-of-order arrivals. (a) Find the smallest value for MaxSeqNum. You may assume that it suffices to find the smallest MaxSeqNum such that if DATA[MaxSeqNum] is in the receive window, then DATA[0] can no longer arrive. (b) Give an example showing that MaxSeqNum – 1 is not sufficient. (c) State a general rule for the minimum MaxSeqNum in terms of SWS and RWS.

Suppose that we run the sliding window algorithm with SWS 5 and RWS = 3, and no out-of-order arrivals. (a) Find the smallest value for MaxSeqNum. You may assume that it suffices to find the smallest MaxSeqNum such that if DATA[MaxSeqNum] is in the receive window, then DATA[0] can no longer arrive. (b) Give an example showing that MaxSeqNum – 1 is not sufficient. (c) State a general rule for the minimum MaxSeqNum in terms of SWS and RWS.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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2.
Suppose that we run the sliding window algorithm with SWS = 5 and RWS = 3, and no out-of-order arrivals. (a) Find the smallest value for MaxSeqNum. You may assume that it suffices to find the smallest MaxSeqNum such that if DATA[MaxSeqNum] is in the receive window, then DATA[0] can no longer arrive. (b) Give an example showing that MaxSeqNum - 1 is not sufficient. (c) State a general rule for the minimum MaxSeqNum in terms of SWS and RWS.
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Suppose that we run the sliding window algorithm with SWS = 5 and RWS = 3, and no out-of-order arrivals. (a) Find the smallest value for MaxSeqNum. You may assume that it suffices to find the smallest MaxSeqNum such that if DATA[MaxSeqNum] is in the receive window, then DATA[0] can no longer arrive. (b) Give an example showing that MaxSeqNum - 1 is not sufficient. (c) State a general rule for the minimum MaxSeqNum in terms of SWS and RWS.
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Suppose that we run the sliding window algorithm with SWS = 5 and RWS = 3, and no out-of-order arrivals. (a) Find the smallest value for MaxSeqNum. You may assume that it suffices to find the smallest MaxSeqNum such that if DATA[MaxSeqNum] is in the receive window, then DATA[0] can no longer arrive. (b) Give an example showing that MaxSeqNum - 1 is not sufficient. (c) State a general rule for the minimum MaxSeqNum in terms of SWS and RWS.
Apply the k-means algorithm on the following dataset (x, y): (-1,- 0.75), (-1, – 1), (-0.75, - 1.0), (-0.25, – 0.25), (0.25,0.25), (0.75,1.0), (1.0,1.0), (1.0,0.75) and create two clusters. Let the initial cluster prototypes be located at (0.0,0.0) and (0.75,0.75) respectively.
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