1 research outputs found
Detecting and Handling Flash-Crowd Events on Cloud Environments
Cloud computing is a highly scalable computing paradigm where resources are
delivered to users on demand via Internet. There are several areas that can
benefit from cloud computing and one in special is gaining much attention: the
flash-crowd handling. Flash-crowd events happen when servers are unable to
handle the volume of requests for a specific content (or a set of contents)
that actually reach it, thus causing some requests to be denied. For the
handling of flash-crowd events in Web applications, clouds can offer elastic
computing and storage capacity during these events in order to process all
requests. However, it is important that flash-crowd events are quickly detected
and the amount of resources to be instantiated during flash crowds is correctly
estimated. In this paper, a new mechanism for detection of flash crowds based
on concepts of entropy and total correlation is proposed. Moreover, the
Flash-Crowd Handling Problem (FCHP) is precisely defined and formulated as an
integer programming problem. A new algorithm for solving it, named FCHP-ILS, is
also proposed. With FCHP-ILS the Web provider is able to replicate contents in
the available resources and define the types and amount of resources to
instantiate in the cloud during a flash-crowd event. Finally we present a case
study, based on a synthetic dataset representing flash-crowd events in small
scenarios aiming at comparing the proposed approach with de facto standard
Amazon's Auto Scaling mechanism.Comment: Submitted to the ACM Transactions on the Web (TWEB