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We present two resource-allocation mechanisms for on-demand computing services in parallel and distributed systems, where users pay for their actual usage of the computational resources. We specialize our solution for allocation of grid resources which is a challenging issue due to the dynamic behavior of the system. The problem is studied from the seller's(More)
This paper introduces an efficient bidding strategy for budget-constrained buyers in repeated auctions with entry fees. We present a general algorithm that is applicable to distributed resource allocation. The game is modeled on an economically reasonable assumption [1] according to which any player can participate in an auction after paying for information(More)
We analyze rational strategies of users in a dynamic grid market. We consider efficient usage of the shared resources in modeling users' preference relations, an objective that prevents congestion and consequently the collapse of the grid system. A repeated auction-based allocation protocol is presented for sharing the computational grid resources. We(More)
As a new means for data acquisition and fusion, mobile ad hoc sensor networks has been the focus of many researchers during the previous years. To enhance both the quality of service (QoS) and the network's robustness, the concept of mobility were introduced which gives the designer the capability of using various topologies to perform a certain task. This(More)
In this paper, we present a strategic bidding framework for repeated auctions with monitoring and entry fees. We motivate and formally define the desired properties of our framework and present a recursive bidding algorithm, according to which buyers learn to avoid submitting bids in stages where they have a relatively low chance of winning the auctioned(More)
<?Pub Dtl?>The evolution of the mobile handset in support of fourth-generation and beyond technology requirements continues to introduce significant challenges. Tunable systems promise improvements in performance and flexibility with the significant potential to relax limitations currently imposed on traditional RF components and systems. This paper(More)
Game theory deals with decision-making processes involving two or more parties with partly or completely conflicting interests. The players involved in the game usually make their decisions under conditions of risk or uncertainty. In this paper, an idea of nondeterministic payoffs is proposed and optimization is done in a more realistic fuzzy environment,(More)
A game is a decision making situation in which each player attempts to act in such a way that the game's circumstances get close to what desirable for him. To reach this goal, a player needs to have a suitable estimation of the other players' decisions. In this paper, we propose a fuzzy approach by which a player can attain an estimation of the other(More)