Insurable Storage Services: Creating a Marketplace for Long-Term Document Archival

  • Rahul Simha
  • K. Gopinath
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3993)


Digital storage is a key element not only of computing systems, but is now considered an essential component of the infrastructure of any modern organization. This need has co-evolved with the technology that has grown rapidly in recent years to provide low-cost high-capacity storage. At the same time, the storage needs of users have now become more sophisticated and diverse. Some users require very long-term preservation; others need high security; and still others ask for highly-reliable, distributed storage solutions. These needs pose a problem for solution providers in that no single solution seems to meet all needs. Similarly, users must construct services out of disk systems on their own. This paper proposes a way to streamline the marketplace through insurable storage services, a combination of two ideas. The first is to define different categories of storage service; the assumption here is that a refined categorization will better identify particular user needs. The second, and more substantive idea, is to treat digital documents as insurable property. The insurance of storage will provide economic incentives for both producers (storage service providers) and consumers (individuals, organizations) to jointly create a marketplace that provides a diversity of differentially-priced services. For example, insurers can help assess the durability of storage solutions and provide consumers with a quantitative valuation (“It’ll cost you $x per GB to ensure that your documents last 100 years”). Similarly, storage service providers will have incentives to maintain multiple geographically distributed copies, and to continually move the copies onto emerging technologies (“You’ll need to store more copies if you want a higher reliability rating”).


Trust Management Storage Service Local Disk Digital Document Proprietary Format 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Rahul Simha
    • 1
  • K. Gopinath
    • 2
  1. 1.Department of Computer ScienceThe George Washington UniversityWashington DCUSA
  2. 2.Department of Computer Science and AutomationIndian Institute of ScienceBangaloreIndia

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