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In P 2 P systems, user cooperation is a key element to achieve good system performance. In this problem, we will study how incentive schemes

In P2P systems, user cooperation is a key element to achieve good system performance. In this
problem, we will study how incentive schemes improve system performance. Lets consider a P2P
file sharing system. Assume there is one seed, who has the complete file of interest, in the system
at the beginning with service rate s. Leechers, who want to download the file, arrive the system
in accordance with a Poisson process of rate \lambda , and denote by l the service rate of leechers.
Further, assume resource is fair shared by all leechers. That is if there are K leechers in the
system, the seed will provide each leecher a service rate s
K . Finally, assume the file download
time of a leecher is exponential distributed with mean 1
a if the leecher receives an aggregate
service rate a.
(i) If the system doesnt adapt any incentive scheme, leechers will not provide service to system
(to other leechers) and they will leave the system as soon as they finish their downloads.
Model this system as a CTMC by defining states and sketch the corresponding state transition diagram.
(ii) Now we enforce an incentive scheme so that leechers will provide a portion, say \alpha , of their
service rates to the system (fair shared by all other leechers) but they still leave the system
after they download the file. Model this system as a CTMC by defining states and sketch
the corresponding state transition diagram.
(iii) Find the stability condition of the two systems (with and without incentive scheme).
(iv) Let s =15,l =10,\alpha =0.2. Assume now there are 5 leechers in the system. Compute
the expected time until all leechers finish their downloads for both systems.
(v) Comment how incentive schemes improve system performance in terms of system stability
and file download delay.
(iv) Now we adapt a good incentive scheme so that leechers not only provide a portion of their
service rates to the system but also stay in the system (become seeds) for an exponential
time with mean 1
\beta after they download the file. Model this system as a CTMC by defining
states and sketch the corresponding state transition diagram.
(Hint: Now the number of seeds in the system is not fixed. You need to define states that
incorporate seed dynamics.)
3. Consider the following Markov Chain (MC), whose transition diagram is shown in Figure 1. For
state 3...8, each state will jump to any of its neighbors with equal probability. (Note that state
3s neighbors are 4 and 8. You cannot go from state 3 to state 1.)

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