A new fuzzy negotiation protocol for grid resource allocation

In real-life trading, relaxing decisions in the face of trading pressure is common. Similarly, in market-based grid resource allocation problem designing negotiator agents with the flexibility to relax their decision to (quickly) complete a deal in the face of intense Grid Market Pressure (GMP) is essential. To make this idea possible, we design Enhanced Market- and Behavior-driven Negotiation Agents (EMBDNAs) that adopt new fuzzy negotiation protocol. The protocol focuses on both (1) enhancing Rubinstein's sequential alternating offer protocol to handle multiple trading opportunities and market competition and (2) designing two new Fuzzy Grid Market Pressure Determination Systems (FGMPDSs) for both grid resource consumers and grid resource owners to guide negotiator agents in relaxing their bargaining terms under intense GMP to enhance their chance of successfully acquiring/leasing out resources. Implementing the idea in an agent-based testbed, an experiment for evaluating and comparing EMBDNA against EMDA (Enhanced Market-Driven Agent) and our previous work in name MBDNA (Market- and Behavior-driven Negotiation Agent) were carried out through stochastic simulations. While EMDA relaxes its bargaining term in the face of intense GMP by considering just two relaxation factors the MBDNA uses the same negotiation strategy as EMBDNA but does not relax its bargaining term in the face of intense GMP. The results show that adopting the new fuzzy negotiation protocol, EMBDNAs outperform MBDNAs and EMDAs.

[1]  Kwang Mong Sim,et al.  Evolving Fuzzy Rules for Relaxed-Criteria Negotiation , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[2]  Richard Wolski,et al.  Analyzing Market-Based Resource Allocation Strategies for the Computational Grid , 2001, Int. J. High Perform. Comput. Appl..

[3]  Nicholas R. Jennings,et al.  Brain Meets Brawn: Why Grid and Agents Need Each Other , 2004, Towards the Learning Grid.

[4]  Ayman M. Wasfy,et al.  Two-Party Negotiation Modeling: An Integrated Fuzzy Logic Approach , 1998 .

[5]  Chuntian Cheng,et al.  Utility-driven solution for optimal resource allocation in computational grid , 2009, Comput. Lang. Syst. Struct..

[6]  E. Mansfield,et al.  Microeconomics: Theory and Applications , 1976 .

[7]  Chunlin Li,et al.  Utility driven dynamic resource allocation using competitive markets in computational grid , 2005, Adv. Eng. Softw..

[8]  Kwang Mong Sim,et al.  Agents that react to changing market situations , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Lakhmi C. Jain,et al.  Network and information security: A computational intelligence approach: Special Issue of Journal of Network and Computer Applications , 2007, J. Netw. Comput. Appl..

[10]  Kwang Mong Sim,et al.  Grid Commerce, Market-Driven G-Negotiation, and Grid Resource Management , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[11]  Ivan Marsá-Maestre,et al.  Effective bidding and deal identification for negotiations in highly nonlinear scenarios , 2009, AAMAS.

[12]  Kwang Mong Sim,et al.  Toward market-driven agents for electronic auction , 2001, IEEE Trans. Syst. Man Cybern. Part A.

[13]  T. Ross Fuzzy Logic with Engineering Applications , 1994 .

[14]  V. V. Srinivas,et al.  Intelligent Agent Based Resource Sharing in Grid Computing , 2011 .

[15]  J. Plank,et al.  Grid Resource Allocation and Control Using Computational Economies , 2003 .

[16]  Robert Libby,et al.  Retraction: Capital Market Pressure, Disclosure Frequency-Induced Earnings/Cash Flow Conflict, and Managerial Myopia , 2005 .

[17]  Sajal K. Das,et al.  A pricing strategy for job allocation in mobile grids using a non-cooperative bargaining theory framework , 2005, J. Parallel Distributed Comput..

[18]  George F. Luger,et al.  Artificial intelligence - structures and strategies for complex problem solving (2. ed.) , 1993 .

[19]  Ladislau Bölöni,et al.  A macroeconomic model for resource allocation in large-scale distributed systems , 2008, J. Parallel Distributed Comput..

[20]  Fu Wei,et al.  A negotiation model based on fuzzy multiple criteria decision making method , 2004, The Fourth International Conference onComputer and Information Technology, 2004. CIT '04..

[21]  Kwang Mong Sim,et al.  Equilibria, prudent Compromises,and the "Waiting" game , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[22]  Rajendran Parthiban,et al.  A survey of economic models in grid computing , 2011, Future Gener. Comput. Syst..

[23]  V. Lesser,et al.  Automated negotiation for complex multi-agent resource allocation , 2010 .

[24]  Koen V. Hindriks,et al.  Eliminating Interdependencies Between Issues for Multi-issue Negotiation , 2006, CIA.

[25]  Nicholas R. Jennings,et al.  Using similarity criteria to make issue trade-offs in automated negotiations , 2002, Artif. Intell..

[26]  Nicholas R. Jennings,et al.  A fuzzy constraint based model for bilateral, multi-issue negotiations in semi-competitive environments , 2003, Artif. Intell..

[27]  Nicholas R. Jennings,et al.  An agenda-based framework for multi-issue negotiation , 2004, Artif. Intell..

[28]  Nicholas R. Jennings,et al.  Successful negotiation strategies: an evolutionary approach , 2001 .

[29]  Gregory E. Kersten,et al.  Are All E-Commerce Negotiations Auctions? , 2000, COOP.

[30]  Zsolt Németh,et al.  Performance evaluation on grids: directions, issues, and open problems , 2004, 12th Euromicro Conference on Parallel, Distributed and Network-Based Processing, 2004. Proceedings..

[31]  Rajkumar Buyya,et al.  Economic-based Distributed Resource Management and Scheduling for Grid Computing , 2002, ArXiv.

[32]  Michael N. Huhns,et al.  Multiagent systems and societies of agents , 1999 .

[33]  F. Lang,et al.  Developing dynamic strategies for multi-issue automated contracting in the agent based commercial grid , 2005, CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005..

[34]  Ryszard Kowalczyk,et al.  FeNAs: a fuzzy e-negotiation agents system , 2000, Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520).

[35]  Liu Xing,et al.  A Grid Resource Allocation Method Based on Iterative Combinatorial Auctions , 2009, 2009 International Conference on Information Technology and Computer Science.

[36]  Li Zhang,et al.  Tycoon: An implementation of a distributed, market-based resource allocation system , 2004, Multiagent Grid Syst..

[37]  Serena Pastore,et al.  The service discovery methods issue: A web services UDDI specification framework integrated in a grid environment , 2008, J. Netw. Comput. Appl..

[38]  N. R. Jennings,et al.  To appear in: Int Journal of Group Decision and Negotiation GDN2000 Keynote Paper Automated Negotiation: Prospects, Methods and Challenges , 2022 .

[39]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[40]  Remigiusz Smolinski,et al.  Fundamentals of International Negotiation , 2006 .

[41]  Kwang Mong Sim,et al.  Flexible negotiation agent with relaxed decision rules , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[42]  Chunlin Li,et al.  Resource scheduling with conflicting objectives in grid environments: Model and evaluation , 2009, J. Netw. Comput. Appl..

[43]  Hamid Beigy,et al.  Market_based grid resource allocation using new negotiation model , 2013, J. Netw. Comput. Appl..

[44]  K. Robert Lai,et al.  Fuzzy Constraint-Based Agent Negotiation , 2005, Journal of Computer Science and Technology.

[45]  Sajal K. Das,et al.  A game theory based pricing strategy for job allocation in mobile grids , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[46]  Ryszard Kowalczyk,et al.  On Fuzzy e-Negotiation Agents: autonomous negotiation with incomplete and imprecise information , 2000, Proceedings 11th International Workshop on Database and Expert Systems Applications.

[47]  J. Archibald,et al.  Guest Editorial Special Issue on Game-Theoretic Analysis and Stochastic Simulation of Negotiation Agents , 2006 .

[48]  Nicholas R. Jennings,et al.  Negotiation decision functions for autonomous agents , 1998, Robotics Auton. Syst..

[49]  Sarit Kraus,et al.  Strategic Negotiation in Multiagent Environments , 2001, Intelligent robots and autonomous agents.

[50]  Layuan Li,et al.  Competitive proportional resource allocation policy for computational grid , 2004, Future Gener. Comput. Syst..

[51]  Nicholas R. Jennings,et al.  STRATUM: A METHODOLOGY FOR DESIGNING HEURISTIC AGENT NEGOTIATION STRATEGIES , 2007, Appl. Artif. Intell..

[52]  Ajith Abraham,et al.  An auction method for resource allocation in computational grids , 2009 .

[53]  Graciela Piedras,et al.  5.4.3 The Global Information Infrastructure, the Global Information Society, is it a reality? , 1998 .

[54]  A. Rubinstein,et al.  Bargaining and Markets , 1991 .

[55]  Kwang Mong Sim,et al.  A Market–Driven Model for Designing Negotiation Agents , 2002, Comput. Intell..

[56]  Nicholas R. Jennings,et al.  Managing commitments in multiple concurrent negotiations , 2005, Electron. Commer. Res. Appl..

[57]  Katia Sycara,et al.  Bilateral negotiation decisions with uncertain dynamic outside options , 2004 .

[58]  Chunyan Miao,et al.  Fuzzy cognitive maps for dynamic grid service negotiation , 2006, Multiagent Grid Syst..

[59]  David Abramson,et al.  Economic models for resource management and scheduling in Grid computing , 2002, Concurr. Comput. Pract. Exp..

[60]  Rajkumar Buyya,et al.  Compute Power Market: towards a market-oriented grid , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[61]  A. Rubinstein Perfect Equilibrium in a Bargaining Model , 1982 .

[62]  Xiaojun Shen,et al.  A Fuzzy Logic Based Intelligent Negotiation Agent (FINA) in Ecommerce , 2006, 2006 Canadian Conference on Electrical and Computer Engineering.

[63]  Yan Feng,et al.  A Fuzzy Negotiation Model of e-Commerce and Its Implementation , 2006, 2006 Technology Management for the Global Future - PICMET 2006 Conference.

[64]  Kwang Mong Sim,et al.  Negotiation Agents that Make Prudent Compromises and are Slightly Flexible in Reaching Consensus , 2004, Comput. Intell..

[65]  Eduardo Alonso Fernández,et al.  Rules of encounter: designing conventions for automated negotiation among computers , 1995 .

[66]  Julita Vassileva,et al.  Non-Monotonic-Offers Bargaining Protocol , 2004, Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems, 2004. AAMAS 2004..

[67]  Ryszard Kowalczyk,et al.  Fuzzy e-negotiation agents , 2002, Soft Comput..

[68]  Kwang Mong Sim,et al.  Grid Resource Negotiation: Survey and New Directions , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[69]  Nicholas R. Jennings,et al.  Determining successful negotiation strategies: an evolutionary approach , 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

[70]  Saad Haj Bakry,et al.  Grid computing: a STOPE view , 2007, Int. J. Netw. Manag..