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With the rapid growth of the cloud computing marketplace, the issue of pricing resources in the cloud has been the subject of much study in recent years. In this paper, we identify and study a new issue: how to price resources in the cloud so that the customers risk is minimized, while at the same time ensuring that the provider accrues his fair share. We do this by correlating the revenue stream of the customer to the prices charged by the provider. We show that our mechanism is incentive compatible in that it is in the best interest of the customer to provide his true revenue as a function of the resources rented. We next add another restriction to the price function, i.e., that it be linear. This removes the distortion that creeps in when the customer has to pay more money for less resources. Our algorithms for both the schemes mentioned above are efficient.
During the last decade, scheduling the healthcare services (such as staffs and OTs) inside the hospitals have assumed a central role in healthcare. Recently, some works are addressed in the direction of hiring the expert consultants (mainly doctors)
Ridesharing platforms match drivers and riders to trips, using dynamic prices to balance supply and demand. A challenge is to set prices that are appropriately smooth in space and time, so that drivers with the flexibility to decide how to work will
This paper considers prior-independent mechanism design, in which a single mechanism is designed to achieve approximately optimal performance on every prior distribution from a given class. Most results in this literature focus on mechanisms with tru
We consider a robust version of the revenue maximization problem, where a single seller wishes to sell $n$ items to a single unit-demand buyer. In this robust version, the seller knows the buyers marginal value distribution for each item separately,
Cooperative multihop communication can greatly increase network throughput, yet packet forwarding for other nodes involves opportunity and energy cost for relays. Thus one of the pre-requisite problems in the successful implementation of multihop tra