1 / 29

MULTI-AGENT BASED SCHEDULING

D. Ouelhadj ASAP (Automated Scheduling Optimisation and Planning) Research Group School of Computer Science and IT University of Nottingham, UK. MULTI-AGENT BASED SCHEDULING. Open Issues in Grid Scheduling, 2003. 1. Introduction 2. Multi-agent systems

siusan
Download Presentation

MULTI-AGENT BASED SCHEDULING

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. D. Ouelhadj ASAP (Automated Scheduling Optimisation and Planning) Research Group School of Computer Science and IT University of Nottingham, UK MULTI-AGENT BASED SCHEDULING Open Issues in Grid Scheduling, 2003

  2. 1. Introduction 2. Multi-agent systems 3. Multi-agent based scheduling 4. Multi-agent systems for integrated and dynamic scheduling of steel production 5. Conclusion Contents Open Issues in Grid Scheduling, 2003

  3. Supervisor level Supervisor level Intermediate levels Resource level Resource level Characteristics of most scheduling systems developed in manufacturing environments:  Centralised or hierarchical.  Tractable.  Stochastic. Introduction Centralised and hierarchical scheduling Open Issues in Grid Scheduling, 2003

  4. Classical scheduling techniques:  Operational research-based techniques: branch and bound, etc.  Artificial intelligence-based techniques: heuristics, meta-heuristics, hyper-heuristics, knowledge-based systems, case-based reasoning, fuzzy logic, etc. Introduction Distributed Scheduling systems using MULTI-AGENTS Open Issues in Grid Scheduling, 2003

  5. Real-life scheduling problems are usually physically or functionally distributed (air traffic control, manufacturing systems, health care, etc.). • Complex systems are beyond direct control. They operate through the cooperation of many interacting subsystems, which may have their independent interest, and modes of operation. • Complexity of real-life scheduling problems dictates a local point of view. When the problems are too extensive to be analysed as a whole, solutions based on local approaches are more efficient. • Centralised structures are difficult to maintain and reconfigure, inflexible, inefficient to satisfy real-world needs, costly in the presence of failures, and the amount of knowledge to manage is very large. Motivations Open Issues in Grid Scheduling, 2003

  6. Need for integration of multiple legacy systems and expertise. • Heterogeneity. Heterogeneous environments may use different data and models, and operate in different modes. • Robustness and reliability against failures. • Scalability and flexibility. • Computational efficiency. Agents can operate asynchronously and in parallel, which can result in increased overall speed. • Clarity of design and reusability. • Costs. It may be much more cost-effective than a centralised system, since it could be composed of simple subsystems of low unit cost. Motivations Open Issues in Grid Scheduling, 2003

  7. autonomy • goal-driven • reactivity and proactivity • social ability •  persistent •  mobility • adaptability • An agent is an intelligent entity that is situated in some environment, and that is capable of flexible and autonomous action in this environment in order to meet its design objectives. By flexible we mean that the system must be responsive, proactive, and social Wooldrige and Jennings (1995). • A Multi-Agent System is a system composed of a population of autonomous agents, which interact with each other to reach common objectives, while simultaneously each agent pursues individual objectivesFerber (1997). Agent communication perception action environment What is a multi-agent system Open Issues in Grid Scheduling, 2003

  8. agent agent Bid Contract Task announcement Task announcement Contract Net Protocol The contract net protocol is a high level protocol for achieving efficient cooperation introduced by Smith (1980) based on a market-like protocol. Cooperation in multi-agent systems Open Issues in Grid Scheduling, 2003

  9.  Local autonomy. An agent has the responsibility for carrying out local scheduling for one or more (functional or physical) components, such as machines and jobs. •  Agents have the ability to observe their environment and to communicate and cooperate with other agents in order to ensure that local scheduling leads to a globally desirable schedule. •  Autonomy allows the agents to respond to local variations, increasing the flexibility of the system. • Concurrency. Negotiation-based decision making instead of totally pre-planned scheduling. • Robustness: fast detection of and recovery from the failures. • Open and dynamic scheduling structures. Announcement of production requirements Resource agent: Local Scheduling Local scheduling Local scheduling Resource agents Multi-agent-based scheduling broken down I am free in that period Open Issues in Grid Scheduling, 2003

  10. Autonomous. • Mediator. Multi-agent-based scheduling architectures Open Issues in Grid Scheduling, 2003

  11. Manufacturing entities Physical or functional agents (resources, parts, tasks, etc) Autonomous architectures Agents representing manufacturing entities (resources, tasks, etc.) have the ability to define their local schedules, react locally to local changes, and cooperate directly with each other to generate the global optimal and robust schedules. Multi-agent-based scheduling architectures Open Issues in Grid Scheduling, 2003

  12. Mediator agent Coordinator for global scheduling Mediator agent Physical or functional agents (resources, parts, tasks, etc) Manufacturing entities Mediator architectures A mediator architecture has a basic structure of autonomous cooperating local agents that are capable of negotiation with each other in order to achieve production targets.That basic structure is extended with mediator agents to coordinate the behaviour of the local agents to generate the global optimal and robust schedules. Multi-agent-based scheduling architectures Open Issues in Grid Scheduling, 2003

  13. A multi-agent system for integrated and dynamic scheduling of steel production Open Issues in Grid Scheduling, 2003

  14. Steel production scheduling Integration: how to integrate the scheduling systems of the continuous caster and the hot strip mill ? Dynamic scheduling: Robustness against failures? Use Of MULTI-AGENT SYSTEMS Open Issues in Grid Scheduling, 2003

  15. ` user User agent HSM Agent SY Agent coils Hot Strip Mill Slabyard CC-3 Agent CC-1 Agent CC-2 Agent Continuous Casters Slabs Ladle Multi-agent architecture proposed Open Issues in Grid Scheduling, 2003

  16. Presence of real-time events On the CC agent: steel with wrong chemical compositions. On the HSM agent: non availability of slabs. Robust predictive-reactive scheduling • first constructs a predictive schedule and then modifies the schedule • in response to real-time events so as to minimise deviation between the performance measure values of the realised and predictive schedule. Dynamic scheduling of the HSM and CC agents Open Issues in Grid Scheduling, 2003

  17. Predictive schedules are generated using tabu search. Robust predictive-reactive schedules are generated using: • Utility, stability, and robustness measures. • Rescheduling strategies: complete rescheduling and schedule repair. Dynamic scheduling of the HSM and CC agents Open Issues in Grid Scheduling, 2003

  18. Utility, stability and robustness measure the effect of real-time events, and are used to select the best rescheduling strategy (schedule repair or complete rescheduling) to react to real-time events. Utility measures the change in the value of the schedule objective function following the schedule revision. Stability measures the deviation from the original predictive schedule caused by schedule revision. Robustness combines the maximisation of utility and the minimisation of stability. Dynamic scheduling of the HSM and CC agents Open Issues in Grid Scheduling, 2003

  19. Schedule repair and complete rescheduling strategies • On the HSM agent • Do-nothing (DON) • Simple Replacement (SR) • Closed Schedule Repair (CSR) • Open Schedule Repair (OSR) • Hybrid Closed Schedule Repair (HCSR) • Hybrid Open Schedule Repair (HOSR) • Partial Reschedule (PR) • Complete Rescheduling (CR) • On the CC agent • Insert- at- end Schedule repair (IESR) • Insert-Heat Schedule Repair (IHSR) • Shift Schedule Repair (SHSR) • Swap Schedule Repair (SWSR) • Hybrid Schedule Repair (HBSR) • Complete Rescheduling (CR) Rescheduling strategies Open Issues in Grid Scheduling, 2003

  20. The negotiation protocol is a two-level bidding mechanism based on the contract net protocol involving negotiation at HSMA-SYA and SYA-CCA(s) levels. At the HSMA-SYA negotiation level, the HSMA requests the supply of slabs from the SYA. At the SYA-CCA (s) negotiation level, the SYA requests the production of slabs not available in the slabyard from the CCA(s). A commitment duration is attached to the the negotiation messages to specify the time windows by which the agents must respond to a given negotiation message. Negotiation protocol for inter-agent cooperation Open Issues in Grid Scheduling, 2003

  21. The negotiation protocol incorporates a decommitment mechanism to allow the agents to decommit by specifying appropriate contract’s alternatives in response to future real-time events. Negotiation protocol for inter-agent cooperation Open Issues in Grid Scheduling, 2003

  22. Steps of the negotiation protocol Announcing Bidding 2. SYA-Announcement for the production of slabs not available in the SY. CC-1 agent CC-1 agent 3. CCA-bid(s) SY agent HSM agent SY agent HSM agent 4. SYA-bid CC-n agent CC-n agent 1.HSMA-announcement for the supply of the slabs for the current turn. Negotiation protocol for inter-agent cooperation 6. Forward of the contract, or renegotiation of the non-satisfied slabs. CC-1 agent Contracting or renegotiating HSM agent SY agent 5. Establishment of a contract, or renegotiation of the non-satisfied slabs. CC-n agent Open Issues in Grid Scheduling, 2003

  23. Prototype developed in simulation • A prototype has been developed in Microsoft Visual C++/MFC. • Cooperation between the agents is done with the exchange of asynchronous messages formatted in XML using MSMQ. Open Issues in Grid Scheduling, 2003

  24. Prototype developed in simulation Open Issues in Grid Scheduling, 2003

  25. Evaluation of the performance of the local and global predictive schedules Open Issues in Grid Scheduling, 2003

  26. Average frequency of schedule repair and complete rescheduling strategies On the HSM agent On the CC agent Open Issues in Grid Scheduling, 2003

  27. Performance of the utility and stability measures On the HSM agent On the CC agent Open Issues in Grid Scheduling, 2003

  28. Conclusion • Dynamic and autonomous distributed scheduling. The dynamic scheduling problem is distributed across a set of agents. • Local autonomy allows the agents to respond to local variations and self-adaptation to real-time events , increasing the robustness and flexibility of the system. • The cooperation protocol allows the agents to cooperate and coordinate their local tasks in order to generate desirable globally predictive and robust schedules. • Dynamic task allocation. Open Issues in Grid Scheduling, 2003

  29. Conclusion • Natural load-balancing as busy agents do not need to bid. • Increased Flexibility. • Robustness against failures. • Heterogeneity. • Open and extensible scheduling architectures: Agents can be introduced and removed dynamically. • Reduced complexity. • Reduced costs. Open Issues in Grid Scheduling, 2003

More Related