Abstract: We discuss the application of matching in the area of resource discovery and resource allocation in grid computing. We present a formal definition of matchmaking, overview algorithms to evaluate different matchmaking expressions, and develop a matchmaking service for an intelligent grid environment.
Abstract: Market based models are frequently used in the resource
allocation on the computational grid. However, as the size of
the grid grows, it becomes difficult for the customer to negotiate
directly with all the providers. Middle agents are introduced to
mediate between the providers and customers and facilitate the
resource allocation process. The most frequently deployed middle
agents are the matchmakers and the brokers. The matchmaking agent
finds possible candidate providers who can satisfy the requirements
of the consumers, after which the customer directly negotiates with
the candidates. The broker agents are mediating the negotiation with
the providers in real time.
In this paper we present a new type of middle agent, the marketmaker.
Its operation is based on two parallel operations - through
the investment process the marketmaker is acquiring resources and
resource reservations in large quantities, while through the resale process
it sells them to the customers. The operation of the marketmaker
is based on the fact that through its global view of the grid it can
perform a more efficient resource allocation than the one possible in
one-to-one negotiations between the customers and providers.
We present the operation and algorithms governing the operation
of the marketmaker agent, contrasting it with the matchmaker and
broker agents. Through a series of simulations in the task oriented
domain we compare the operation of the three agents types. We find
that the use of marketmaker agent leads to a better performance in the
allocation of large tasks and a significant reduction of the messaging
overhead.