A mechanism for pricing and resource allocation in peer-to-peer networks☆

https://doi.org/10.1016/j.elerap.2010.07.004Get rights and content

Abstract

In this study, we design a pricing and allocation mechanism for a peer-to-peer (P2P) network that allows users in a firm to effectively share computing resources. This mechanism allows tasks (incoming jobs) to be allocated to resources (participating peers) in an organization in a decentralized manner. The base case of our P2P mechanism derives the optimal transfer price that maximizes the net value, which is characterized as the difference between the expected gross value of the jobs and the expected delay cost, for the peers in the network. The optimal price for executing any job at a peer location is essentially equal to the marginal delay cost it imposes on all current jobs at that node. With this pricing scheme, no individual user has an incentive to over-utilize shared resources, thereby avoiding the “tragedy of the commons” for the P2P network. Our model builds on the classical Mendelson (1985) study that was one of the first to look at the control and management issues related to a single-server computer system. In this study, we model transfer pricing for a multiple server environment of a P2P network. The original Mendelson (1985) model thus becomes a special single-server case of our general model. Our basic model is extended to incorporate situations where the peers have queue length constraints, which may be used for providing quality of service (QoS) guarantees to users. We then perform numerical computations that illustrate the effects of job arrivals on prices and job allocations at the individual servers. There is an enormous potential for P2P based technologies to help organizations manage their computer resources effectively.

Section snippets

Introduction and problem motivation

Peer-to-peer (P2P) network based technologies allow a distributed community of users to share a variety of digital or computer processing resources. The novelty of P2P networks with respect to traditional client–server networks is that they do not necessarily require centralized or dedicated servers (Krishnan et al. 2003). Every node, or peer, that forms a part of the network may potentially contribute resources to other peers. As a result, P2P networks have many advantages over centralized

Related literature

There has been a substantial literature on computer networks since their introduction in the 1960s. Kleinrock (1964) first reported on communication networks by linking multiple computers that could transfer data. This eventually led to the architecture of the present day Internet (Kleinrock 2002). Most technical studies on computer networks focus on performance analysis issues (Kleinrock, 1976, Tanenbaum, 2003). These include network architecture and topology design for achieving system

Model

Our P2P resource-sharing mechanism models the steady-state behavior of a multiple server system. This abstraction allows us to arrive at insights that are broadly applicable to an actual P2P system. We have a number of assumptions about our model parameters for simplicity. In addition, we are able to capture the relevant characteristics of a decentralized P2P system. This is consistent with existing studies on management of computer networks, including Mendelson (1985) and Mendelson and Wang

Numerical computations

We now perform some numerical computations for our mechanism. They illustrate the effects of job arrivals on prices and load allocations at the individual servers. We consider a simple P2P network structure of three server locations discussed earlier using Fig. 2. The job arrival rates at each of the three neighbor locations, referred to as server 1, 2 and 3, respectively, is simulated using a Poisson process. The mean Poisson arrival rates for the three servers are λ1=3,λ2=4, and λ3=5. The

Discussion and conclusions

In this study, we design a pricing and allocation mechanism for a P2P network that allows users in a firm to effectively share their computing resources. This mechanism allows tasks (incoming jobs) to be allocated to resources (participating peers) in an organization in a decentralized manner. The base case of our P2P mechanism derives the optimal transfer price that maximizes the net value for the peers in the network. The optimal price is equal to the externality cost, which is the expected

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    ☆

    The authors thank the participants of the Workshop on Information Systems and Economics (WISE) 2005, where an earlier, abridged version of the paper was presented, Rob Kaufman, and anonymous referees, for their valuable remarks on this study.

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