The Problem with Data

Utility Computing requires levels of efficacy and abstraction that are not matched by modern computing clouds. In this paper we argue that the lack of harmonization of data and computation is holding back computing clouds from evolving further into utility clouds. Data gravity is perceived as gravity pull associated with data volume. Data of large volume develop large gravity that pulls computation to it, which contrasts with the computation-centered principle of current computing clouds, where computational resources are centralized and fixed. Based on previous research, eight principles are identified to suggest an infrastructure for a future data-driven utility computing platform. The paper also argues that tuple spaces and functional programming languages together would be a powerful combination to meet the requirements for this next-generation computing utility.