ber of resource types in the buyer request [4]. There are two drawbacks in this approach. Firstly, using a greedy algorithm leads to an outcome that is not Pareto-eﬃcient. Secondly, the allocation mechanism is no longer strategy-proof. Thus, economic eﬃciency is further reduced when users are untruthful [4]. The distributed market framework we propose in this paper uses a strategy-proof pricing mechanism [21]. Although Pareto eﬃciency is not achieved, economic eﬃciency is not aﬀected by the users’ degree of untruthfulness. Several market-based allocation systems for grids, such as Sorma [16] and Nimrod/G [3], use bargaining or negotiation to determine the resource price. The advantage of this approach is that sellers and buyers communicate directly, without a third party mediating an allocation. However, bargaining results in high communication costs. In a large dynamic market, each buyer has to ne- gotiate with all sellers of a resource type in order to maximize his utility. The communication costs further increase when a buyer requires more than one re- source types. Thus, scalability is an issue both when increasing the number of users and the number of resource types in a request. We propose to manage resource information using a peer-to-peer overlay network, where each resource type lookup can be processed in parallel by diﬀerent peers. Cloud computing uses ﬁxed pricing to provide computational resources and services on-demand over the Internet. Although simple to implement, ﬁxed pric- ing is not suitable for a system with multiple providers, or where users are both sellers and buyers of resources [13]. Federated clouds, a topic of recent interest, aims to integrate cloud resources from diﬀerent providers, to increase scalability and reliability [4]. With a large number of providers (sellers) and users (buyers), ﬁxed pricing cannot adapt to the changes in demand and supply. More suitable for federated clouds, dynamic pricing mechanisms such as the one used in the proposed framework sets resource payments according to demand and supply. In PeerMart [10], the authors propose a distributed market for peer-to-peer services built on top of a peer-to-peer overlay. Although resource location in PeerMart and the proposed framework is similar, our framework provides sev- eral key advantages. Firstly, PeerMart does not support multiple resource type allocations. When a user requires several resource types, it has to aggregate resources manually, which is not eﬃcient. Secondly, PeerMart is not strategy- proof. Pricing takes place using a simple double-auction mechanism, where the payment is the mean price between seller price and buyer price. Thus, users are encouraged to submit untruthful prices to increase their utility.

3 Pro posed D ist rib ute d Mark et Arc hit ect ure

We have identiﬁed three major components that constitute the market architec- ture: resource location, the pricing mechanism, and allocation administration. A funda men tal probl em in dealin g with large collec tions of share d resou rces is resource location. As shown in Fig. 2, the resource market receives resource information from sellers in

publish

messages, and query requests from buyers in

lookup