Only b Suppose there are memory partitions of 455 KB, 305 KB, 355 KB and 655 KB. These partitions arein order. Use first fit, best fit, and worst fit algorithms to allocate processes of parameters 420 KB,520 KB, 225 KB, and 355 KB, and solve the following:a. Represent the allocations with the help of a figure or table.b. Which algorithms of the three make the most efficient use of memory?

Answered: a. Represent the allocations with the…

a. Represent the allocations with the help of a figure or table. b. Which algorithms of the three make the most efficient use of memory?

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

See similar textbooks

Similar questions

Consider a satellite moving around the earth along the equator and recording some data (air-pressure, temperature, height etc.) for scientific investigation. The data thus obtained is stored in a database where the key to each data entry is the longitude of the point. We require this data to be sorted, but each of the n data entries might have been misplaced by no more than k positions from the correct sorted order (k is a predefined constant, depending on the speed of the satellite). Design a worst-case time and space efficient algorithm for sorting such a dataset.
Job scheduling: Consider the problem of scheduling n jobs of known durations t1, t2, . . . , tn for execution by a single processor. The jobs can be executed in any order, one job at a time. You want to find a schedule that minimizes the total time spent by all the jobs in the system. (The time spent by one job in the system is the sum of the time spent by this job in waiting plus the time spent on its execution.) Design a greedy algorithm for this problem. Does the greedy algorithm always yield an optimal solution? (Hint: You may get a clue from Prim’s Algorithm)
Answer the following questions about Monte Carlo problems and pseudo-random number generators (PRNGs). Pick the best answer for each item. A PRNG will always eventually repeat itself - this is called A method of creating PRNG for parallel applications is for each task to take only every Pth random number (P is the number of processors). A PRNG that has only one work of state is A matrix whose diagonal elements sre an order of magnitude higher than the rest We want to be able to rerun with the exact same random numbers - we care about The theory behind Monte Carlo methods Reproducibility [Choose ] [Choose] Linear Congruential Reproducibility Diagonally Dominant Leapfrog Method Uniform distribution cycles Lagged Fibonaci Mean Value Theorem Sequence Splitting Method Manager Worker Method Uncorrelated [Choose] [Choose]
Consider the following functions as time complexities of some algorithms. (a) First write the worst-case runtime of each algorithm in Big-O notation. (b) Then arrange functions from low to high (Consider their Big-O notations as you arrange them; as n grows, the function that grows slower should come sooner than the one that grows faster). (c) Arbitrary, select TWO of arrangements in part (b) and for each one of them justify why you have chosen such an ordering for the corresponding function. Provide formal proof. For example if fl<=f2<= f3<= f4<=f5 you may choose to formally justify why (1) fl<=f2 and why (2) f4<=f5 . fI(n)=n², f2(n)=210 nlogn, f3(n)=3", f4(n)=n, f5(n)=1, f6(n)=5*logn, f7(n)= n", f8(n)=4 n*n, f9(n)=2log(n³)
use the Process object of the multiprocessing module to make Python implement row-partitioning for parallel matrix multiplication. Each of the three processes receives its row and matrix B from the master process and multiplies them to create the row of the output matrix C. The input matrices A and B are tiny 33 matrices. The associated row of matrixC from a worker is then sent to the master. For this algorithm, we must take the following into account: The data of the parent process is entirely present in the process when it is launched using the Process module, but any changes it makes are not reflected in the parent process.We must utilise the Manager object of the multiprocessing module and declare C as an array to be shared from this object in order to distribute the product matrix C amongst the processes. Each worker process multiplies and records the outcome in the corresponding row entry of matrix C.
use the Process object of the multiprocessing module to make Python implement row-partitioning for parallel matrix multiplication. Each of the three processes receives its row and matrix B from the master process and multiplies them to create the row of the output matrix C. The input matrices A and B are tiny 33 matrices. A worker then sends its related row of matrixC to the master. For this algorithm, we must take the following into account: The data of the parent process is entirely present in the process when it is launched using the Process module, but any changes it makes are not reflected in the parent process. In order to have the product matrix C shared between the processes, we need to use the Manager object of the multiprocessing module and define C as an array to be shared from this object. Each worker process performs multiplication and stores the result in its row entry of matrix C.
Job scheduling Consider the problem of scheduling n jobs of known durations t1,t2,. . .,tn for execution by a single processor. The jobs can be executed in any order, one job at a time. You want to find a schedule that minimizes the total time spent by all the jobs in the system. (The time spent by one job in the system is the sum of the time spent by this job in waiting plus the time spent on its execution.) Design a greedy algorithm for this problem. Does the greedy algorithm always yield an optimal solution?
You will analyze three algorithms to solve the maximum contiguous subsequence sum problem, and then evaluate the performance of instructor-supplied implementations of those three algorithms. You will compare your theoretical results to your actual results in a written report. What is the maximum contiguous subsequence sum problem? Given a sequence of integers A1, A2, ..., An (where the integers may be positive or negative), find a subsequence Aj, ... , Ak that has the maximum value of all possible subsequences. The maximum contiguous subsequence sum is defined to be zero if all of the integers in the sequence are negative. Consider the sequence shown below. A1: -2 A2: 11 A3: -4 A4: 13 A5: -5 A6: 2 The maximum contiguous subsequence sum is 20, representing the contiguous subsequence in positions 2, 3, and 4 (i.e. 11 + (-4) + 13 = 20). The sum of the values in all other contiguous subsequences is less than or equal to 20. Consider a second sequence, shown below. A1: 1…
Observe the following two Sequential Search and Binary Search algorithms in the image. Perform a comparative analysis of the Sequential Search and Binary Search algorithms in terms of the number of basic operations executed by the two algorithms. A. Calculate and analyze the time complexity T(n) and the efficiency class of the two search algorithms in the worst case. B. Write an example case by writing down the elements for different data sizes, for example n=4, 8, ... Please specify the elements of table A and the data you are looking for, x. Write an illustration of the comparison process for every n to confirm the complexity of the algorithm in point a). C. Describe your opinion regarding the comparative analysis of the efficiency of the two algorithms! Please solve subparts A,B,C in 60 minutes ASAP can u get thank u
L6M]: SO1-HVCLO8 Given five memory partitions of 200KB, 500KB, 300KB, 400KB, 600KB (in order), 1. how would the first-fit, best-fit, and worst-fit algorithms place processes of 312 KB, 417 KB, 136 KB, and 326 KB (in order)? 2. Which algorithm makes the most efficient use of memory? L First fit 200KB 500KB 300KB 400KB 600KB
Question 17. Sorting a data set is an important sub-problem in data science. Given the size n of a data set, which statements are correct? a) Bubble Sort has worst-case run-time complexity O(n).b) Bubble Sort has worst-case run-time complexity O(n log N).c) Bubble Sort has worst-case run-time complexity O(n2).d) Merge Sort has worst-case run-time complexity O(n).e) Merge Sort has worst-case run-time complexity O(n log N).f) Merge Sort has worst-case run-time complexity O(n2).g) Quick Sort has worst-case run-time complexity O(n).h) Quick Sort has worst-case run-time complexity O(n log N).i) Quick Sort has worst-case run-time complexity O(n2).
The search algorithm developed will be used for users to search the catalog for all items matching the search keyword(s), and there are a total of 15000 items in the catalog. During development, three different algorithms were created. • Algorithm A runs in constant time, with a maximum runtime of 1.10 seconds and returns all matching results. ● Algorithm B runs in logarithmic time, with a maximum runtime of 0.3 seconds, and returns only the first result. ● Algorithm C runs in linear time, with a maximum runtime of 1.50 seconds and returns all matching results. Which algorithm would be the least suitable for the requirements stated? In your answer, justify your choice by explaining why you picked that algorithm, and why you did not pick the other two algorithms.OND OND OND DAD