Cloud Computing for Autonomous Control in Logistics

Logistics processes in a globalised economy are increasingly complex, dynamic, and distributed. These properties pose major challenges for logistics planning and control. Conventional centralised approaches are frequently limited in their efficiency due to the high number of logistics objects and parameters to be considered. As an alternative, the paradigm of autonomous control in logistics delegates decisionmaking to the participating logistics objects themselves. This allows for decreasing the computational effort and coping with dynamics locally. Implementing autonomous logistics with intelligent software agents makes logistics control flexible and scalable with respect to transient demands. In order to meet customer demands, however, also the underlying hardware platform must be scalable. To this end, this paper examines cloud computing as a hardware platform abstraction for autonomous logistics. It discusses and compares different approaches how cloud computing can facilitate logistics control with intelligent software agents.

[1]  王洁,et al.  Cloud computing implementation method and system , 2011 .

[2]  John W. Rittinghouse,et al.  Cloud Computing: Implementation, Management, and Security , 2009 .

[3]  Jan D. Gehrke,et al.  Dynamic Decision Making on Embedded Platforms in Transport Logistics - A Case Study , 2007, LDIC.

[4]  Arne Schuldt,et al.  Multiagent Coordination Enabling Autonomous Logistics , 2011, KI - Künstliche Intelligenz.

[5]  Katja Windt,et al.  Changing Paradigms in Logistics — Understanding the Shift from Conventional Control to Autonomous Cooperation and Control , 2007 .

[6]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.

[7]  Jan D. Gehrke,et al.  Designing a Simulation Middleware for FIPA Multiagent Systems , 2008, 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.

[8]  Sven Werner,et al.  Agent-Based Container Security Systems: An Interdisciplinary Perspective , 2007, GI Jahrestagung.

[9]  Klaus-Dieter Thoben,et al.  A Semantic Mediator for Data Integration in Autonomous Logistics Processes , 2010, I-ESA.

[10]  Klaus-Dieter Thoben,et al.  The Application of the EPCglobal Framework Architecture to Autonomous Control in Logistics , 2009, LDIC.

[11]  Jan Holmström,et al.  Agent-based model for managing composite product information , 2006, Comput. Ind..

[12]  Sriram Khé.  The Box: How the Shipping Container Made the World Smaller and the World Economy Bigger , 2008 .

[13]  Ira Rudowsky,et al.  Intelligent Agents , 2004, Commun. Assoc. Inf. Syst..