Smart data pricing: Using economics to manage network congestion

Soumya Sen, Carlee Joe-Wong, Sangtae Ha, Mung Chiang

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Network operators should not see demand growth as a problem to be solved by penalizing users but as an opportunity to monetize their networks by broadening the revenue base and managing congestion by creating the right economic incentives for users. Two complementary approaches, time-dependent pricing (TDP) and traffic offloading, aim to reduce network congestion by giving users incentives and mechanisms to shift their use to less-congested times or frequencies and networks. To discourage large peak demand, prices should have a temporal component or vary over different times of the day, as in TDP. Only then will users be incentivized to spread their demand over time, improving network resource utilization by reducing the peaks and filling in the valley periods. In addition to considering users' psychological preference for certainty regarding future price points, TDP must accommodate technological and regulatory concerns. With optimized day-ahead time-dependent prices, resource utilization at off-peak hours nearly doubled, indicating TDP can also improve utilization of network capacity by flattening and distributing demand over different times of the day. Economic models and their practical realization in field trials can help ISPs design more effective offloading mechanisms.

Original languageEnglish (US)
Pages (from-to)86-93
Number of pages8
JournalCommunications of the ACM
Volume58
Issue number12
DOIs
StatePublished - Dec 2015

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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