The crowd in the cloud: moving beyond traditional boundaries for large scale experiences in the cloud Adam Roughton 1 John Downs 1,2 Beryl Plimmer 1 Ian Warren 1 1 Department of Computer Science University of Auckland, New Zealand Email: arou012@aucklanduni.ac.nz {beryl|ian-w}@cs.auckland.ac.nz 2 Department of Information Systems University of Melbourne, Australia Email: j.downs@pgrad.unimelb.edu.au Abstract In this paper we propose a taxonomy for crowd based interaction paradigms, and categorise the literature according to this taxonomy. The conventional defini- tion of crowds needs to be reconsidered in the light of advances in communication technology such as smart phones and cloud based infrastructures. We have ex- tended the definition to encompass virtual dispersed crowds by considering the core components of crowd based activities. We found that much of the exist- ing work offers simplistic reactive control in exchange for economical, highly synchronous, co-operative ac- tivities. We argue that the same co-operative compo- nent and economy can be obtained with rich reflective control. By combining the cloud, smart phones, and tools, this gap can be exploited to create a new class of rich, thought provoking, economical, crowd com- puting. Keywords: Crowd computer interaction, crowd com- puting, crowd and the cloud, collective behaviour 1 Introduction Humans are an inherently community-based species; we associate with nations, societies, and clubs. Our interaction with society at large is often at times of shared activity: events like the Olympics are able to engage the passions of entire nations. There exists little technology that attempts to engage communi- ties in crowd activity. Work in the emerging field of crowd computer interaction attempts to address this shortcoming. Crowd computer interaction first came to promi- nence in 1991 during the SIGGRAPH Electronic The- atre show with the deployment of Cinematrix Interac- tive Entertainment System (Carpenter, 1993). Each audience member was given a double sided paddle with a green face on one side and a red one on the other; cameras tracked the paddles in real-time allow- ing for collaborative audience activities. In this way the audience was able to collectively control a single paddle in a game of pong, vote on an issue, or move through a maze (Maynes-Aminzade et al., 2002; Bre- gler et al., 2005). The system was invented to get around the expense and the required preparedness of wiring seats with controllers, or the need to hand out expensive wireless controllers to audience members Copyright c 2011, Australian Computer Society, Inc. This pa- per appeared at the 12th Australasian User Interface Confer- ence (AUIC2011), Perth, Australia, January 2011. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 117, Christof Lutteroth and Haifeng Shen, Ed. Reproduc- tion for academic, not-for profit purposes permitted provided this text is included. (Carpenter, 1993). Much of the subsequent work in this area has built on this foundation of throwaway sensors deployed to a co-located crowd (or in some work no controller at all) and a large shared screen for feedback. Crowds present a unique problem space for the deployment of technology. This is because of the or- ganisation and composition of individuals within the crowd, and the sheer scale presented by the possible numbers of participants. The organisational struc- ture of the crowd takes on a looser form than groups (Turner and Killian, 1972): crowds are far more ad- hoc in their nature, and in most cases there is no clear leadership. Crowd membership is not as stringently regulated as groups with participation often open to anyone who is able to take part. The relaxed form of membership and the large number of people leads to a collection of many different cultures and iden- tities. Within the larger crowd aggregate are many small sub-crowds and groups with their own idiosyn- crasies and traditons (Reicher, 2002). Behaviours ap- propriate to the traditions of one sub-crowd may not be appropriate for another. How the crowd works as a whole to work around these differences, or how it might attenuate or exaggerate issues remains a new area of inquiry for technology solutions deployed into this arena. In this paper we considered how two new technolo- gies, smart phones and cloud computing, can change crowd participation. The recent proliferation of smart phones equipped with accelerometers, compasses, microphones, and gyroscopes eliminates the need to build, develop, or distribute sensors. This paired with the rich inter- faces provided by the devices opens up the possibil- ity of richer crowd experiences. Application market- places have provided the ability to quickly distribute applications to client phones, eliminating the original problem of sensor deployment cost. Cloud computing provides the second piece of the puzzle: the cloud computing paradigm reduces entry barriers with reduced infrastructure costs and quick access to computing power and storage (Greengard, 2010). The potential benefits of cloud computing to crowd computing are vast. By their very nature, crowd applications benefit from the elasticity offered by the cloud (Owens, 2010): the ability to scale up a modest infrastructure for short durations at a very modest cost fits the typical crowd application scenario beautifully. The combination of smart phones and cloud com- puting opens the possibility for rich, economical crowd computer interaction without the need for co- location. This paper first proposes a new definition of crowds for the purpose of crowd computer applica-