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Maximizing utility by optimal capacity division in P2P networks

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Abstract

In most wireless networks, users/peers are connected to backbone networks using access links. The access link capacity is divided into upload and download capacity, and these capacities are used for upload and download of data, respectively. A peer can modify this division of link capacity between upload and download. A peer will allocate its entire link capacity for download to maximize utility. But incentive mechanism forces them to allocate some portion of capacity for upload. This paper investigates how to optimally divide link capacity so that peers receive maximum utility in a P2P network. We model this scenario as a game and determine capacity partitioning of peers during the Nash equilibrium NE. We also prove the social optimality of NE. As this portioning maximizes individual as well as social benefit, so NE is an optimal state of capacity partition. Using simulation, we verify that NE is an optimal state. BitTorrent network and a distributed algorithm for dividing access capacities are simulated, and partition providing maximum utility is compared with NE. This work provides a generalized expression and the mathematical proof for capacity partitioning at which peers receive maximum utility.

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Notes

  1. A round starts with each peer sending requests to other peers, and after that, all the serving peers allocate their resources to the requesters. A round ends after every peer has received the resources.

  2. For partition 18-0 in Fig. 3 the incentive level of peers is zero as they allocate zero capacity for upload. But they can receive some utility/resources because of the random unchoke policy of BitTorrent.

  3. During the first round \(\Delta =\frac{C_i}{10}\). For subsequent rounds, the size of \(\Delta \) depends on the difference in utility received in the last two rounds, such that \(\Delta \) value decreases if the difference is low; otherwise, it increases (refer [12] for details about \(\Delta \) calculation).

  4. For some initial rounds, newcomers are provided a fixed incentive level independent of their contribution. It is assumed that newcomers have no data to share. This strategy allows them to receive resources from the network, which can be later shared with other peers [4]

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No funds, grants, or other support was received for the publication of this article. Further, authors have no competing interests to declare that are relevant to the content of this paper.

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  1. Department of Electronics and Communication Engineering, National Institute of Technology, Delhi, India

    Nitin Singha & Mahesh K. Singh

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  1. Nitin Singha
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  2. Mahesh K. Singh
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Dr. Nitin and Dr. Mahesh have contributed to writing the manuscript. Dr. Nitin has also performed simulations, so he is the corresponding author.

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Correspondence to Nitin Singha.

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Singha, N., Singh, M.K. Maximizing utility by optimal capacity division in P2P networks. Cluster Comput 27, 1159–1168 (2024). https://doi.org/10.1007/s10586-023-03996-x

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