%0 Conference Paper %1 met19ITC31 %A Mete, Akshay %A Manjunath, D. %A Nair, Jayakrishnan %A Prabhu, Balakrishna %B 31th International Teletraffic Congress (ITC 31) %C Budapest, Hungary %D 2019 %K itc itc31 %T Partial Server Pooling in Redundancy Systems %U https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc31/met19ITC31.pdf?inline=true %X We develop a partial sharing model for providers described as a multi server system. This is a generalisation of the full pooling that have been studied in the literature. Partial sharing allows providers to possibly pool a fraction of their resources when full pooling is not beneficial to them. Two M/M/N queues with redundant service models are considered. Copies of an arriving job are placed in the queues of servers that can serve the job. Partial sharing models for cancel-on-complete and cancel-on-start redundancy models are developed. For cancel-on-complete, it is shown that the Pareto efficient region is the full pooling configuration. For a cancel-on-start policy, we conjecture that the Pareto frontier is always non-empty and is such that at least one of the two providers is sharing all of its resources. For this system, using bargaining theory the sharing configuration that the providers may use is determined. Mean response time and probability of waiting are the performance metrics considered.

@inproceedings{met19ITC31, abstract = {We develop a partial sharing model for providers described as a multi server system. This is a generalisation of the full pooling that have been studied in the literature. Partial sharing allows providers to possibly pool a fraction of their resources when full pooling is not beneficial to them. Two M/M/N queues with redundant service models are considered. Copies of an arriving job are placed in the queues of servers that can serve the job. Partial sharing models for cancel-on-complete and cancel-on-start redundancy models are developed. For cancel-on-complete, it is shown that the Pareto efficient region is the full pooling configuration. For a cancel-on-start policy, we conjecture that the Pareto frontier is always non-empty and is such that at least one of the two providers is sharing all of its resources. For this system, using bargaining theory the sharing configuration that the providers may use is determined. Mean response time and probability of waiting are the performance metrics considered.}, added-at = {2020-04-29T15:29:04.000+0200}, address = {Budapest, Hungary}, author = {Mete, Akshay and Manjunath, D. and Nair, Jayakrishnan and Prabhu, Balakrishna}, biburl = {https://www.bibsonomy.org/bibtex/22630e71f30ee30cd3ece5a2e4c038e33/itc}, booktitle = {31th International Teletraffic Congress (ITC 31)}, interhash = {d93b2dc4ef82a4957f1992a82e5303ec}, intrahash = {2630e71f30ee30cd3ece5a2e4c038e33}, keywords = {itc itc31}, timestamp = {2020-04-30T18:18:45.000+0200}, title = {Partial Server Pooling in Redundancy Systems}, url = {https://gitlab2.informatik.uni-wuerzburg.de/itc-conference/itc-conference-public/-/raw/master/itc31/met19ITC31.pdf?inline=true}, year = 2019 }