Managing Cancellations and No-Shows of Reservations with Overbooking to Increase Resource Revenue

Advance reservation allows users to request available nodes in the future, whereas economy provides an incentive for resource owners to be part of the Grid, and encourages users to utilize resources optimally and effectively. In this paper, we use overbooking models from Revenue Management to manage cancellations and no-shows of reservations in a Grid system. Without overbooking, the resource owners are faced with a prospect of loss of income and lower system utilization. Thus, the models aim to find an ideal limit that exceeds the maximum capacity, without incurring greater compensation cost. Moreover, we introduce several novel strategies for selecting which bookings to deny, based on compensation cost and user class level, namely Lottery, Denied Cost First (DCF), and Lower Class DCF. The result shows that by overbooking reservations, a resource gains an extra 6-9% in the total net revenue.

[1]  W. Lieberman.  The Theory and Practice of Revenue Management , 2005 .

[2]  Klara Nahrstedt,et al.  A distributed resource management architecture that supports advance reservations and co-allocation , 1999, 1999 Seventh International Workshop on Quality of Service. IWQoS'99. (Cat. No.98EX354).

[3]  Jeffrey I. McGill,et al.  Revenue Management: Research Overview and Prospects , 1999, Transp. Sci..

[4]  Ali Afzal,et al.  Workflow Enactment in ICENI , 2004 .

[5]  Changjia Chen,et al.  A redundant overbooking reservation algorithm for OBS/OPS networks , 2007, Comput. Networks.

[6]  Rajkumar Buyya,et al.  GarQ: An efficient scheduling data structure for advance reservations of grid resources , 2009, Int. J. Parallel Emergent Distributed Syst..

[7]  Rajkumar Buyya,et al.  On incorporating differentiated levels of network service into GridSim , 2007, Future Gener. Comput. Syst..

[8]  R. Phillips,et al.  Pricing and Revenue Optimization , 2005 .

[9]  Ivan Janciak,et al.  UK e-Science All Hands Meeting , 2009 .

[10]  Michael Menth,et al.  Experience-Based Admission Control with Type-Specific Overbooking , 2006, IPOM.

[11]  David Abramson,et al.  The Grid Economy , 2005, Proceedings of the IEEE.

[12]  Barry C. Smith,et al.  Yield Management at American Airlines , 1992 .

[13]  Michael Muskulus,et al.  Analysis and modeling of job arrivals in a production grid , 2007, PERV.

[14]  Prashant J. Shenoy,et al.  Resource overbooking and application profiling in shared hosting platforms , 2002, OSDI '02.

[15]  Ian T. Foster,et al.  The anatomy of the grid: enabling scalable virtual organizations , 2001, Proceedings First IEEE/ACM International Symposium on Cluster Computing and the Grid.

[16]  Joseph Coughlan,et al.  Airline overbooking in the multi-class case , 1999, J. Oper. Res. Soc..

[17]  Rajkumar Buyya,et al.  Using Revenue Management to Determine Pricing of Reservations , 2007, Third IEEE International Conference on e-Science and Grid Computing (e-Science 2007).

[18]  H. R. Thompson,et al.  Statistical Problems in Airline Reservation Control , 1961 .

[19]  M. Geraghty,et al.  Revenue Management Saves National Car Rental , 1997 .

[20]  Rajkumar Buyya,et al.  On incorporating an on-line strip packing algorithm into elastic Grid reservation-based systems , 2007, 2007 International Conference on Parallel and Distributed Systems.

[21]  UrgaonkarBhuvan,et al.  Resource overbooking and application profiling in shared hosting platforms , 2002 .

[22]  George C. Hadjinicola,et al.  The overbooking problem in hotels with multiple tour‐operators , 1997 .