These non-technical papers on SDP research are accessible to non-experts and aim to provide readers with a general introduction to the field. Many of them survey relevant papers published at various points in the past 20 years, while others are position or tutorial papers that debate different viewpoints or explain different SDP research methods.
S. Sen, C. Joe-Wong, S. Ha and M. Chiang IEEE Communications Magazine, 50(11): 91—99, 2012
The tremendous growth in demand for broadband data is forcing ISPs to use pricing as a congestion management tool. This changing landscape of Internet access pricing is evidenced by the elimination of flat rate data plans in favor of usage-based pricing by major wired and wireless operators in the US and Europe. But simple usage-based fees suffer from the problem of imposing costs on all users, irrespective of the network congestion level at a given time. To effectively reduce network congestion, appropriate incentives must be provided to users who are willing to time-shift their data demand from peak to off-peak periods. These pricing incentives can either be static (e.g., two-period daytime/ nighttime prices) or computed dynamically (e.g., day-ahead pricing, real-time pricing). Data plans that offer such incentives to consumers fall under the category of time-dependent pricing (TDP). Many ISPs across the world are currently exploring various forms of TDP to manage their traffic growth. This article first outlines the sources of today’s challenges, and then discusses current trends from regulatory and technological perspectives. Finally, we review representative pricing proposals for incentivizing the time-shifting of data.
M.-J. Sheng, C. Joe-Wong, S. Ha, F. M. F. Wong and S. Sen Proceedings of the 2nd IEEE International Workshop on Smart Data Pricing (SDP), 2013
Rapid increases in the demand for broadband data are increasingly causing a growth in costs for communication service providers (CSPs). Yet under the current pricing plans, CSPs’ revenue has not kept pace with these costs. Thus, many CSPs are considering Smart Data Pricing (SDP) as a way to reduce cost or increase revenue. Before offering such novel data plans, however, CSPs must conduct trials of the specific data plans proposed. Due to the complexity of necessary changes in network equipment and a need to carefully design the trial in order to understand customer behavior, planning such trials is not only a critical precursor to SDP deployment, but also a nontrivial undertaking in itself. This paper discusses general principles of trial design and proposes two methods for estimating their effectiveness. We first give an introduction to the goals of SDP research and review three possible SDP approaches. We then discuss the importance of pre-trial participant surveys and some technical considerations of implementing the trial infrastructure for a particular SDP algorithm. Finally, we show how the CSP may extrapolate from the trial results to estimate the SDP trial’s benefits, in terms of changes in traffic patterns and a reduction in spectrum requirements. We conclude with some remarks about future work.
S. Sen, C. Joe-Wong, S. Ha and M. Chiang Recent Advances in Networking, eds. H. Haddadi and O. Bonaventure, volume 1, ACM SIGCOMM eBook, August 2013
Advances in Internet technologies have resulted in an unprecedented growth in demand for data. In particular, demand in the mobile Internet sector is doubling every year. Given the limited wireless spectrum availability, the rate of growth in the supply of wireless capacity (per dollar of investment) is unlikely to match the rate of growth in demand in the long run. Internet Service Providers (ISPs) are therefore turning to new pricing and penalty schemes in an effort to manage the demand on their network, while also matching their prices to cost. But changes in pricing and accounting mechanisms, if not done carefully, can have significant consequences for the entire network ecosystem. Multiple stakeholders in this ecosystem, including operators, consumers, regulators, content providers, hardware and software developers, and architects of network technologies, have all been tackling these issues of charging and allocating limited network resources.