X. Bai, K. Sivoncik, D. Turgut, and L. Bölöni

Grid coordination with marketmaker agents


Cite as:

X. Bai, K. Sivoncik, D. Turgut, and L. Bölöni. Grid coordination with marketmaker agents. International Journal of Computational Intelligence, 3(2):153–160, 2006.

Download:

Download 

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 \em investment process the marketmaker is acquiring resources and resource reservations in large quantities, while through the \em 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.

BibTeX:

@article{Bai-2006-IJCI,
   author = "X. Bai and K. Sivoncik and D. Turgut and L. B{\"o}l{\"o}ni",
   title = "Grid coordination with marketmaker agents",
   journal = "International Journal of Computational Intelligence",
   year = "2006",
   volume = "3",
   number = "2",
   pages = "153-160",
   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 {\em investment
     process} the marketmaker is acquiring resources and resource reservations
     in large quantities, while through the {\em 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.
   }
}

Generated by bib2html.pl (written by Patrick Riley, Lotzi Boloni ) on Fri Oct 06, 2017 18:15:24