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Give-and-take based peer-to-peer content distribution networks

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Abstract

Content Distribution Networks (CDNs) are widely used to distribute data to large number of users. Traditionally, content is being replicated among a number of surrogate servers, leading to high operational costs. In this context, Peer-to-Peer (P2P) CDNs have emerged as a viable alternative. An issue of concern in P2P networks is that of free riders, i.e., selfish peers who download files and leave without uploading anything in return. Free riding must be discouraged. In this paper, we propose a criterion, the Give-and-Take (G&T) criterion, that disallows free riders. Incorporating the G&T criterion in our model, we study a problem that arises naturally when a new peer enters the system: viz., the problem of downloading a ‘universe’ of segments, scattered among other peers, at low cost. We analyse this \(\mathcal {N}\mathcal {P}-\)hard problem, and characterize the optimal download cost under the G&T criterion. We propose an optimal algorithm, and provide a sub-optimal algorithm that is nearly optimal, but runs much more quickly; this provides an attractive balance between running time and performance. Finally, we compare the performance of our algorithms with that of a few existing P2P downloading strategies in use. We also study the computation time for prescribing the strategy for initial segment and peer selection for the newly arrived peer for various existing and proposed algorithms, and quantify cost–computation time trade-offs.

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Notes

  1. X c denotes the complement of set X.

  2. Peer 0’s augmented set will always be considered for exchange. Hence, the order of peers in which exchanges are carried out by peer 0 also matters.

  3. We note that all minimum cost set cover solutions are considered in arriving at Γ∗,e.

  4. For solving set cover problem, we write the same as binary integer program. We use bintprog function of the Optimization toolbox, MATLAB 2013b for evaluating the solution. Bintprog uses the branch and bound method for solving binary integer program.

  5. The complexity for Algorithm 1 and Algorithm 2 is O(n2m) and O(2m) respectively.

    Figure 6
    figure 6

    Trade-off between computation time and cost for 50 randomly generated datasets with 300 segments and 200 peers. Cost against the time taken for running each algorithm on each of data point is plotted.

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AGGARWAL, S., KURI, J. & SAHA, C. Give-and-take based peer-to-peer content distribution networks. Sadhana 39, 843–858 (2014). https://doi.org/10.1007/s12046-014-0266-1

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