Pricing and resource allocation in caching services with multiple levels of quality of service

被引:32
|
作者
Hosanagar, K [1 ]
Krishnan, R
Chuang, J
Choudhary, V
机构
[1] Univ Penn, Wharton Sch, Philadelphia, PA 19104 USA
[2] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
[3] Univ Calif Berkeley, Berkeley, CA 94720 USA
[4] Univ Calif Irvine, Irvine, CA USA
关键词
Web caching; content delivery pricing; capacity allocation; quality of service (QoS);
D O I
10.1287/mnsc.1050.0420
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Network caches are the storage centers in the supply chain for content delivery-the digital equivalent of warehouses. Operated by access networks and other operators, they provide benefits to content publishers in the forms of bandwidth cost reduction, response time improvement, and handling of flash crowds. Yet, caching has not been fully embraced by publishers, because its use can interfere with site personalization strategies and/or collection of visitor information for business intelligence purposes. While recent work has focused on technological solutions to these issues, this paper provides the first study of the managerial issues related to the design and provisioning of incentive-compatible caching services. Starting with a single class of caching service, we find conditions under which the profit-maximizing cache operator should offer the service for free. This occurs when the access networks' bandwidth costs are high and a large fraction of content publishers value personalization and business intelligence. Some publishers will still opt out of the service, i.e., cache bust, as observed in practice. We next derive the conditions under which the profit-maximizing cache operator should provision two vertically differentiated service classes, namely, premium and best effort. Interestingly, caching service differentiation is different from traditional vertical differentiation models, in that the premium and best-effort market segments do not abut. Thus, optimal prices for the two service classes can be set independently and cannibalization does not occur. It is possible for the cache operator to continue to offer the best-effort service for free while charging for the premium service. Furthermore, consumers are better off because more content is cached and delivered faster to them. Finally, we find that declining bandwidth costs will put negative pressure on cache operator profits, unless consumer adoption of broadband connectivity and the availability of multimedia content provide the necessary increase in traffic volume for the caches.
引用
下载
收藏
页码:1844 / 1859
页数:16
相关论文
共 50 条
  • [21] Satisfaction-driven services caching and resource allocation for UAV mobile edge computing
    Li, Wei
    Guo, Yan
    He, Ming
    Yuan, Hao
    Lai, Xuebin
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2024, 45 (19):
  • [22] RAaaS: Resource Allocation as a Service in multiple cloud providers
    Vieira, Cristiano Costa Argemon
    Bittencourt, Luiz Fernando
    Genez, Thiago Augusto Lopes
    Peixoto, Maycon Leone M.
    Madeira, Edmundo Roberto Mauro
    JOURNAL OF NETWORK AND COMPUTER APPLICATIONS, 2024, 221
  • [23] Service components-Based resource allocation in services cloud
    Gao, F., 1600, Asian Network for Scientific Information (12):
  • [24] Generalized quality-of-service routing with resource allocation
    Bashandy, AR
    Chong, EKP
    Ghafoor, A
    IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2005, 23 (02) : 450 - 463
  • [25] Pricing and resource provisioning for delivering E-content on-demand with multiple levels-of-service
    Jagannathan, S
    Almeroth, KC
    FROM QOS PROVISIONING TO QOS CHARGING, PROCEEDINGS, 2002, 2511 : 325 - 336
  • [26] Optimal Resource Allocation and Quality of Service Prediction in Cloud
    Baldoss, Priya
    Thangavel, Gnanasekaran
    CMC-COMPUTERS MATERIALS & CONTINUA, 2021, 67 (01): : 253 - 265
  • [27] Joint Service Caching and Computing Resource Allocation for Edge Computing-Enabled Networks
    Kim, Mingun
    Cho, Hewon
    Cui, Ying
    Lee, Jemin
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2023, 22 (12) : 9029 - 9044
  • [28] Joint Service Caching, Computation Offloading and Resource Allocation in Mobile Edge Computing Systems
    Zhang, Guanglin
    Zhang, Shun
    Zhang, Wenqian
    Shen, Zhirong
    Wang, Lin
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2021, 20 (08) : 5288 - 5300
  • [29] Resource allocation to improve service quality perceptions in multistage service systems
    Soteriou, AC
    Hadjinicola, GC
    PRODUCTION AND OPERATIONS MANAGEMENT, 1999, 8 (03) : 221 - 239
  • [30] Usage-based dynamic pricing of Web services for optimizing resource allocation
    Lin Z.
    Ramanathan S.
    Zhao H.
    Information Systems and e-Business Management, 2005, 3 (3) : 221 - 242