Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/4268
Title: | Sharing the cost of backbone networks: cui bono? | Authors: | Gyarmati, Laszlo Stanojevic, Rade Sirivianos, Michael |
metadata.dc.contributor.other: | Σιριβιανός, Μιχάλης | Major Field of Science: | Engineering and Technology | Field Category: | Computer and Information Sciences | Keywords: | Fairness;Cost allocation;Internet;Real property | Issue Date: | 2012 | Source: | IMC '12 Proceedings of the 2012 Internet Measurement Conference, Boston, Massachusetts, USA, November 14- 16, 2012, pp. 509-522 | Conference: | ACM SIGCOMM Internet Measurement Conference | Abstract: | We study the problem of how to share the cost of a backbone network among its customers. A variety of empirical cost-sharing policies are used in practice by backbone network operators but very little ever reaches the research literature about their properties. Motivated by this, we present a systematic study of such policies focusing on the discrepancies between their cost allocations. We aim at quantifying how the selection of a particular policy biases an operator's understanding of cost generation. We identify F-discrepancies due to the specific function used to map traffic into cost (e.g., volume vs. peak rate vs. 95-percentile) and M-discrepancies, which have to do with where traffic is metered (per device vs. ingress metering). We also identify L-discrepancies relating to the liability of individual customers for triggered upgrades and consequent costs (full vs. proportional), and finally, TCO-discrepancies emanating from the fact that the cost of carrying a bit is not uniform across the network (old vs. new equipment, high vs. low energy or real estate costs, etc.). Using extensive traffic, routing, and cost data from a tier-1 network we show that F-discrepancies are large when looking at individual links but cancel out when considering network-wide cost-sharing. Metering at ingress points is convenient but leads to large M-discrepancies, while TCO-discrepancies are huge. Finally, L-discrepancies are intriguing and esoteric but understanding them is central to determining the cost a customer inflicts on the network | URI: | https://hdl.handle.net/20.500.14279/4268 | ISBN: | 978-1-4503-1705-4 | DOI: | 10.1145/2398776.2398830 | Rights: | © ACM 2012 | Type: | Book Chapter | Affiliation : | Cyprus University of Technology Terveystalo Turku |
Appears in Collections: | Κεφάλαια βιβλίων/Book chapters |
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