With the emergence of utility computing and the continuous search for reducing the cost of running Information Technology (IT) infrastructures, we will soon experience an important change on the way these infrastructures are assembled, configured and managed. In this paper we consider the problem of managing a hybrid high-performance computing infrastructure whose processing elements comprise in-house dedicated machines, a utility computing service provider, and idle machines from a best-effort peer-to-peer grid. This infrastructure supports the execution of both best-effort and real-time applications. Realtime applications use primarily computing power from the inhouse machines and any processing power that can be attained from the best-effort grid. Extra capacity required to meet deadlines is purchased from the utility computing service provider. This extra capacity is reserved for future use through short term contracts which are negotiated with no human intervention. We take a business-driven approach for the management of this hybrid infrastructure and propose heuristics that can be used by a contract planner agent to reduce the cost of running the applications at the same time that guarantees that deadlines are met. In particular, we show that constructing an estimation for the behavior of the grid is essential for making contracts that lead to high efficiency in the use of the hybrid infrastructure.

In this paper we consider a peer-to-peer grid system which provides multiple services to its users. In this system, an incentive mechanism promotes collaboration among peers. It has been shown that the use of a reciprocation mechanism in such a system is able to prevent free riding and, at the same time, promotes the clustering of peers that have mutually profitable interactions. However, when peers are subject to a budget limitation, each peer must select a subset of all services that can possibly be offered. In this work we show that the received utility is strongly dependent of the offered services. The main contributions of this work are a methodology to evaluate the impact of service changes in the obtained utility and how much different sets of offered services impact in the peer's utility. These results indicate that further research is needed, particularly for the development of heuristics to choose the best services to offer.