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4. In number 3, suppose that each boxes must be coming from the Warehouse and the transport delivery service must need to back-and-port to pick-up each box. What is the distance travelled by the transport delivery service? 5. Evaluate the methods used in number 3 and number 4 method of delivery. If the function x2 is considered as the dominant term for each method used. 6. What will happen to the term 2x + 5 of the original function x2 + 2x + 5 when compared to the dominant term which is x2. Show a simple analysis for this function. 7. Generating sequences of random-like numbers in a specific range. Xi+1 = aXi +c Mod m where, X, is the sequence of pseudo-random numbers m, (> 0) the modulus a, (0, m) the multiplier G (0, m) the increment Xo, (0, m) – Initial value of sequence known as seed m, a, c, and XO should be chosen appropriately to get a period almost equal to m. For a = 1, it will be the additive congruence method. For c = 0, it will be the multiplicative congruence method. Approach: E Choose the seed value X0, Modulus parameter m, Multiplier term a, and increment term c. E Initialize the required amount of random numbers to generate (say, an integer variable noofRandomNums). E Define a storage to keep the generated random numbers (here, vector is considered) of Size noOfRandomNums. E Initialize the Oth index of the vector with the seed value. O For rest of the indexes follow the Linear Congruential Method to generate the random numbers. randomNumsli) = (randomNums[i – 1] * a) + c) % m

4. In number 3, suppose that each boxes must be coming from the Warehouse and the transport delivery service must need to back-and-port to pick-up each box. What is the distance travelled by the transport delivery service? 5. Evaluate the methods used in number 3 and number 4 method of delivery. If the function x2 is considered as the dominant term for each method used. 6. What will happen to the term 2x + 5 of the original function x2 + 2x + 5 when compared to the dominant term which is x2. Show a simple analysis for this function. 7. Generating sequences of random-like numbers in a specific range. Xi+1 = aXi +c Mod m where, X, is the sequence of pseudo-random numbers m, (> 0) the modulus a, (0, m) the multiplier G (0, m) the increment Xo, (0, m) – Initial value of sequence known as seed m, a, c, and XO should be chosen appropriately to get a period almost equal to m. For a = 1, it will be the additive congruence method. For c = 0, it will be the multiplicative congruence method. Approach: E Choose the seed value X0, Modulus parameter m, Multiplier term a, and increment term c. E Initialize the required amount of random numbers to generate (say, an integer variable noofRandomNums). E Define a storage to keep the generated random numbers (here, vector is considered) of Size noOfRandomNums. E Initialize the Oth index of the vector with the seed value. O For rest of the indexes follow the Linear Congruential Method to generate the random numbers. randomNumsli) = (randomNums[i – 1] * a) + c) % m

Computer Networking: A Top-Down Approach (7th Edition)
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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4. In number 3, suppose that each boxes must be coming from the Warehouse and the transport delivery service must need to back-and-port to pick-up each box. What is the distance travelled by the transport delivery service? 5. Evaluate the methods used in number 3 and number 4 method of delivery. If the function x2 is considered as the dominant term for each method used. 6. What will happen to the term 2x + 5 of the original function x2 2x + 5 when compared to the dominant term which is x2. Show a simple analysis for this function. 7. Generating sequences of random-like numbers in a specific range. Xi+1 = aXi + c Mod m where, X, is the sequence of pseudo-random numbers m, (> 0) the modulus a, (0, m) the multiplier ç (0, m) the increment xo, [0, m) – Initial value of sequence known as seed m, a, c, and XO should be chosen appropriately to get a period almost equal to m. For a = 1, it will be the additive congruence method. For c= 0, it will be the multiplicative congruence method. Approach: B Choose the seed value X0, Modulus parameter m, Multiplier term a, and increment term c. E Initialize the required amount of random numbers to generate (say, an integer variable noofRandomNums). B Define a storage to keep the generated random numbers (here, vector is considered) of size noofRandomNums. E Initialize the Oth index of the vector with the seed value. E For rest of the indexes follow the Linear Congruential Method to generate the random numbers. randomNumsli) = ((randomNumsli – 1] * a) + c) % m
Transcribed Image Text:4. In number 3, suppose that each boxes must be coming from the Warehouse and the transport delivery service must need to back-and-port to pick-up each box. What is the distance travelled by the transport delivery service? 5. Evaluate the methods used in number 3 and number 4 method of delivery. If the function x2 is considered as the dominant term for each method used. 6. What will happen to the term 2x + 5 of the original function x2 2x + 5 when compared to the dominant term which is x2. Show a simple analysis for this function. 7. Generating sequences of random-like numbers in a specific range. Xi+1 = aXi + c Mod m where, X, is the sequence of pseudo-random numbers m, (> 0) the modulus a, (0, m) the multiplier ç (0, m) the increment xo, [0, m) – Initial value of sequence known as seed m, a, c, and XO should be chosen appropriately to get a period almost equal to m. For a = 1, it will be the additive congruence method. For c= 0, it will be the multiplicative congruence method. Approach: B Choose the seed value X0, Modulus parameter m, Multiplier term a, and increment term c. E Initialize the required amount of random numbers to generate (say, an integer variable noofRandomNums). B Define a storage to keep the generated random numbers (here, vector is considered) of size noofRandomNums. E Initialize the Oth index of the vector with the seed value. E For rest of the indexes follow the Linear Congruential Method to generate the random numbers. randomNumsli) = ((randomNumsli – 1] * a) + c) % m
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