60 | | - '''Question 1.1 A: ''' [[BR]] |
61 | | From ''researcher2'', fetch the same data again (from 1902/01/01 to 1902/01/02), and record the fetch times reported by ''client.py''. It prints out the time take to pull each temporary file along with the concatenation and write time. Then fetch 1902/02/03 to 1902/02/04, and record those fetch times. Fetch 1902/02/03 to 1902/02/04 a second time, and record the new times. Which transfer was longest, and which was shortest? Knowing that each ccnd caches data for a short period of time, can you explain this behavior? |
62 | | - '''Question 1.1 B:''' [[BR]] |
63 | | Browse the content caches and interests seen on various hosts in the network by loading their ccnd status page on TCP port 9695 in your browser (see Section 5, Hints, below). Which hosts have seen interests and have content cached, and why? |
| 60 | - '''Question 1.1 A: ''' [[BR]] |
| 61 | From ''researcher2'', fetch the same data again (from 1902/01/01 to 1902/01/02), and record the fetch times reported by ''client.py''. It prints out the time take to pull each temporary file along with the concatenation and write time. Then fetch 1902/02/03 to 1902/02/04, and record those fetch times. Fetch 1902/02/03 to 1902/02/04 a second time, and record the new times. Which transfer was longest, and which was shortest? Knowing that each ccnd caches data for a short period of time, can you explain this behavior? |
| 62 | - '''Question 1.1 B:''' [[BR]] |
| 63 | Browse the content caches and interests seen on various hosts in the network by loading their ccnd status page on TCP port 9695 in your browser (see Section 5, Hints, below). Which hosts have seen interests and have content cached, and why? |
69 | 69 | - '''Task 1.3: Explore traffic patterns''' [[BR]] |
70 | 70 | ''For this task, you will start network monitoring services on your slice and observe the data traffic passing between hosts as you fetch various content.'' [[BR]] |
71 | 71 | Instrumentize your experiment using GEMINI following the instructions here: [http://www.protogeni.net/wiki/GeniTutorial GENIDesktop Tutorial]. [[BR]] |
72 | 72 | Log into the host collaborator1 and use the Atmos client to fetch data from 1902/01/28 to 1902/02/03. Look at the GEMINI data usage, and observe that data is pulled from both datasource1 and datasource2, through router to researcher1 and ultimately to collaborator1. Record or remember the data rates and volumes from this transaction. On the GEMINI web interface (GENIDesktop), show real-time graphs from datasource1, datasource2, router, researcher1 and collaborator1, record the throughput numbers or screenshot the graphs. [[BR]] |
73 | | - '''Question 1.3 A:''' [[BR]] |
74 | | Log into ''collaborator2'' and fetch the same dates. Which hosts transfer data? why? |
75 | | - '''Question 1.3 B''' [[BR]] |
76 | | Now fetch 1902/01/25 to 1902/01/31 from ''researcher2''. How does this transfer differ from the previous two? why? |
| 73 | - '''Question 1.3 A:''' [[BR]] |
| 74 | Log into ''collaborator2'' and fetch the same dates. Which hosts transfer data? why? |
| 75 | - '''Question 1.3 B''' [[BR]] |
| 76 | Now fetch 1902/01/25 to 1902/01/31 from ''researcher2''. How does this transfer differ from the previous two? why? |
95 | | - '''Question 2.1 A''' [[BR]] |
96 | | What general difference do you see in network behavior between these solutions? |
97 | | - '''Question 2.1 B''' [[BR]] |
98 | | Which URI scheme is more efficient in time and network resources if the user only wants a few days of data? What if the user wants a full calendar month of data? [[BR]] |
| 95 | - '''Question 2.1 A''' [[BR]] |
| 96 | What general difference do you see in network behavior between these solutions? |
| 97 | - '''Question 2.1 B''' [[BR]] |
| 98 | Which URI scheme is more efficient in time and network resources if the user only wants a few days of data? What if the user wants a full calendar month of data? [[BR]] |
107 | | - '''Question 3.1 A''': [[BR]] |
108 | | From the host consumer run ''/opt/ccnx-atmos/client.py'' to fetch data from 1902/01/21 through 1902/01/24, and time the total transaction. Within 60 seconds, fetch the same data again, and time it. After 60 seconds (but before 300 seconds have passed), fetch it a third time, and time that. What is the benefit of local caching (the second fetch)? Is there perceptible benefit from server-side caching (the third fetch) when data takes some time to generate? [[BR]] |
| 107 | - '''Question 3.1 A''': [[BR]] |
| 108 | From the host consumer run ''/opt/ccnx-atmos/client.py'' to fetch data from 1902/01/21 through 1902/01/24, and time the total transaction. Within 60 seconds, fetch the same data again, and time it. After 60 seconds (but before 300 seconds have passed), fetch it a third time, and time that. What is the benefit of local caching (the second fetch)? Is there perceptible benefit from server-side caching (the third fetch) when data takes some time to generate? [[BR]] |