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.
[1] X. Bai, H. Yu, Y. Ji, and D. C. Marinescu. Resource matching and a
matchmaking service for an intelligent grid. International Journal of
Computational Intelligence, 1(3):197-205, 2004.
[2] R. J. Bayardo, Jr., W. Bohrer, R. Brice, A. Cichocki, J. Fowler,
A. Helal, V. Kashyap, T. Ksiezyk, G. Martin, M. Nodine, M. Rashid,
M. Rusinkiewicz, R. Shea, C. Unnikrishnan, A. Unruh, and D. Woelk.
InfoSleuth: Agent-based semantic integration of information in open
and dynamic environments. In Proceedings of the ACM SIGMOD
International Conference on Management of Data, volume 26,2, pages
195-206, New York, 13-15 1997. ACM Press.
[3] L. Bölöni, R. Hao, K. Jun, and D. C. Marinescu. An object-oriented
approach for semantic understanding of messages in a distributed object
system. In Proceedings of the International Conference on Software Engineering
Applied to Networking and Parallel/ Distributed Computing,
Rheims, France, May 2000.
[4] L. Bölöni and D. C. Marinescu. An object-oriented framework for
building collaborative network agents. In H. Teodorescu, D. Mlynek,
A. Kandel, and H.-J. Zimmerman, editors, Intelligent Systems and
Interfaces, International Series in Intelligent Technologies, chapter 3,
pages 31-64. Kluwer Publising House, 2000.
[5] L. Bölöni and D. Turgut. YAES - a modular simulator for mobile networks.
In Proceedings of the 8-th ACM/IEEE International Symposium
on Modeling, Analysis and Simulation of Wireless and Mobile Systems
MSWIM 2005, pages 169-173, October 2005.
[6] R. Buyya, D. Abramson, and J. Giddy. Economy driven resource
management architecture for computational power grids. In Proceedings
of the International Conference on Parallel and Distributed Processing
Techniques and Applications (PDPTA2000), 2000.
[7] R. Buyya, D. Abramson, and J. Giddy. A case for economy grid
architecture for service-oriented grid computing. In Proceedings of
the 10th IEEE International Heterogeneous Computing Workshop (HCW
2001), page 83, April 2001.
[8] R. Buyya, J. Giddy, and D. Abramson. An evaluation of economybased
resource trading and scheduling on computational power grids
for parameter sweep applications. In Proceedings of the 2 nd International
Workshop on Active Middleware Services (AMS 2000). Kluwer
Academic Press, August 2000.
[9] M. Klusch and K. P. Sycara. Brokering and matchmaking for coordination
of agent societies: A survey. In Coordination of Internet Agents:
Models, Technologies, and Applications, pages 197-224. Springer, 2001.
[10] D. Kuokka and L. Harada. Matchmaking for information agents. In
IJCAI (1), pages 672-678, 1995.
[11] L. W. McKnight and J. Boroumand. Pricing internet services: Approaches
and challenges. IEEE Computer, 33(2):128-129, 2000.
[12] N. Nisan, S. London, O. Regev, and N. Camiel. Globally distributed
computation over the internet - the POPCORN project. In ICDCS -98:
Proceedings of the The 18th International Conference on Distributed
Computing Systems, page 592, Washington, DC, USA, 1998. IEEE
Computer Society.
[13] M. Paolucci, N. Srinivasan, K. P. Sycara, and T. Nishimura. Towards
a semantic choreography of web services: From WSDL to DAML-S.
In Proceedings of the First International Conference on Web Services
(ICWS-03), pages 22-26, 2003.
[14] T. Payne, R. Singh, and K. Sycara. Facilitating message exchange
through middle agents. In The First International Joint Conference on
Autonomous Agents and Multi-Agent Systems, 2002.
[15] R. Raman, M. Livny, and M. H. Solomon. Matchmaking: Distributed
resource management for high throughput computing. In Proceedings
of the Seventh IEEE International Symposium on High Performance
Distributed Computing, pages 140-146, 1998.
[16] N. Singh. A common Lisp API and facilitator for ABSI: version
2.0.3. Technical Report Logic-93-4, Logic Group, Computer Science
Department, Stanford University, 1993.
[17] K. Sycara, J. Lu, and M. Klusch. Interoperability among heterogeneous
software agents on the internet. Technical Report CMU-RI-TR-98-22,
Carnegie Mellon University, PA (USA), 1998.
[18] K. P. Sycara, S. Widoff, M. Klusch, and J. Lu. Larks: Dynamic
matchmaking among heterogeneous software agents in cyberspace.
Autonomous Agents and Multi-Agent Systems, 5(2):173-203, 2002.
[19] C. A. Waldspurger, T. Hogg, B. A. Huberman, J. O. Kephart, and
W. S. Stornetta. Spawn: A distributed computational economy. Software
Engineering, 18(2):103-117, 1992.
[20] H. C. Wong and K. P. Sycara. A taxonomy of middle-agents for the
internet. In ICMAS, pages 465-466, 2000.
[21] Mojo Nation. URL http://www.mojonation.net/.
[22] F. Zeuthen. Problems of Monopoly and Economic Warfare. Routledge
and Sons, 1930.
[23] CONDOR. URL http://www.cs.wisc.edu/condor/.
[24] SETI@home. URL http://setiathome.ssl.berkeley.edu/.
[1] X. Bai, H. Yu, Y. Ji, and D. C. Marinescu. Resource matching and a
matchmaking service for an intelligent grid. International Journal of
Computational Intelligence, 1(3):197-205, 2004.
[2] R. J. Bayardo, Jr., W. Bohrer, R. Brice, A. Cichocki, J. Fowler,
A. Helal, V. Kashyap, T. Ksiezyk, G. Martin, M. Nodine, M. Rashid,
M. Rusinkiewicz, R. Shea, C. Unnikrishnan, A. Unruh, and D. Woelk.
InfoSleuth: Agent-based semantic integration of information in open
and dynamic environments. In Proceedings of the ACM SIGMOD
International Conference on Management of Data, volume 26,2, pages
195-206, New York, 13-15 1997. ACM Press.
[3] L. Bölöni, R. Hao, K. Jun, and D. C. Marinescu. An object-oriented
approach for semantic understanding of messages in a distributed object
system. In Proceedings of the International Conference on Software Engineering
Applied to Networking and Parallel/ Distributed Computing,
Rheims, France, May 2000.
[4] L. Bölöni and D. C. Marinescu. An object-oriented framework for
building collaborative network agents. In H. Teodorescu, D. Mlynek,
A. Kandel, and H.-J. Zimmerman, editors, Intelligent Systems and
Interfaces, International Series in Intelligent Technologies, chapter 3,
pages 31-64. Kluwer Publising House, 2000.
[5] L. Bölöni and D. Turgut. YAES - a modular simulator for mobile networks.
In Proceedings of the 8-th ACM/IEEE International Symposium
on Modeling, Analysis and Simulation of Wireless and Mobile Systems
MSWIM 2005, pages 169-173, October 2005.
[6] R. Buyya, D. Abramson, and J. Giddy. Economy driven resource
management architecture for computational power grids. In Proceedings
of the International Conference on Parallel and Distributed Processing
Techniques and Applications (PDPTA2000), 2000.
[7] R. Buyya, D. Abramson, and J. Giddy. A case for economy grid
architecture for service-oriented grid computing. In Proceedings of
the 10th IEEE International Heterogeneous Computing Workshop (HCW
2001), page 83, April 2001.
[8] R. Buyya, J. Giddy, and D. Abramson. An evaluation of economybased
resource trading and scheduling on computational power grids
for parameter sweep applications. In Proceedings of the 2 nd International
Workshop on Active Middleware Services (AMS 2000). Kluwer
Academic Press, August 2000.
[9] M. Klusch and K. P. Sycara. Brokering and matchmaking for coordination
of agent societies: A survey. In Coordination of Internet Agents:
Models, Technologies, and Applications, pages 197-224. Springer, 2001.
[10] D. Kuokka and L. Harada. Matchmaking for information agents. In
IJCAI (1), pages 672-678, 1995.
[11] L. W. McKnight and J. Boroumand. Pricing internet services: Approaches
and challenges. IEEE Computer, 33(2):128-129, 2000.
[12] N. Nisan, S. London, O. Regev, and N. Camiel. Globally distributed
computation over the internet - the POPCORN project. In ICDCS -98:
Proceedings of the The 18th International Conference on Distributed
Computing Systems, page 592, Washington, DC, USA, 1998. IEEE
Computer Society.
[13] M. Paolucci, N. Srinivasan, K. P. Sycara, and T. Nishimura. Towards
a semantic choreography of web services: From WSDL to DAML-S.
In Proceedings of the First International Conference on Web Services
(ICWS-03), pages 22-26, 2003.
[14] T. Payne, R. Singh, and K. Sycara. Facilitating message exchange
through middle agents. In The First International Joint Conference on
Autonomous Agents and Multi-Agent Systems, 2002.
[15] R. Raman, M. Livny, and M. H. Solomon. Matchmaking: Distributed
resource management for high throughput computing. In Proceedings
of the Seventh IEEE International Symposium on High Performance
Distributed Computing, pages 140-146, 1998.
[16] N. Singh. A common Lisp API and facilitator for ABSI: version
2.0.3. Technical Report Logic-93-4, Logic Group, Computer Science
Department, Stanford University, 1993.
[17] K. Sycara, J. Lu, and M. Klusch. Interoperability among heterogeneous
software agents on the internet. Technical Report CMU-RI-TR-98-22,
Carnegie Mellon University, PA (USA), 1998.
[18] K. P. Sycara, S. Widoff, M. Klusch, and J. Lu. Larks: Dynamic
matchmaking among heterogeneous software agents in cyberspace.
Autonomous Agents and Multi-Agent Systems, 5(2):173-203, 2002.
[19] C. A. Waldspurger, T. Hogg, B. A. Huberman, J. O. Kephart, and
W. S. Stornetta. Spawn: A distributed computational economy. Software
Engineering, 18(2):103-117, 1992.
[20] H. C. Wong and K. P. Sycara. A taxonomy of middle-agents for the
internet. In ICMAS, pages 465-466, 2000.
[21] Mojo Nation. URL http://www.mojonation.net/.
[22] F. Zeuthen. Problems of Monopoly and Economic Warfare. Routledge
and Sons, 1930.
[23] CONDOR. URL http://www.cs.wisc.edu/condor/.
[24] SETI@home. URL http://setiathome.ssl.berkeley.edu/.
@article{"International Journal of Information, Control and Computer Sciences:50753", author = "Xin Bai and Kresimir Sivoncik and Damla Turgut and Ladislau Bölöni", title = "Grid Coordination with Marketmaker Agents", 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.", keywords = "grid computing, autonomous agents, market-basedgrid", volume = "1", number = "10", pages = "2959-8", }
