Big data in the parking lot

Ryan Florin, Syedmeysam Abolghasemi, Aida Ghazi Zadeh, Stephan Olariu

Research output: Contribution to book or proceedingChapterpeer-review

13 Scopus citations

Abstract

One of the significant research challenges in the realm of vehicular clouds is to identify conditions under which these clouds can support big data applications. It is clear that big data applications, with stringent data-processing requirements, cannot be supported by ephemeral vehicular clouds, where the residency time of vehicles in the cloud is too short for supporting virtual machine setup and migration. Similarly, it turns out that vehicular cloud implementations relying on bandwidthconstricted interconnection topologies are not suitable for big data applications. Unfortunately, this is the case of the vast majority of vehicular clouds proposed thus far in the literature that rely on a wireless interconnection fabric. Our main contribution is to identify sufficient conditions under which big data applications can be effectively supported by datacenters built on top of vehicles in a parking lot. This is pioneering work: to the best of our knowledge, this is the first time researchers are looking at evaluating the feasibility of the vehicular cloud concept and its suitability for supporting big data applications. One of our main findings is that (1) if the residency times of the vehicles are sufficiently long and (2) if the interconnection fabric has a sufficient amount of bandwidth, then big data applications can be supported effectively by such datacenters.

Original languageEnglish
Title of host publicationBig Data Management and Processing
PublisherCRC Press
Pages425-449
Number of pages25
ISBN (Electronic)9781498768085
ISBN (Print)9781498768078
DOIs
StatePublished - Jan 1 2017

Scopus Subject Areas

  • General Computer Science
  • General Economics, Econometrics and Finance
  • General Business, Management and Accounting

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