1. IBM Research © 2013 IBM Corporation Leveraging Attention Scarcity to Improve the Overall User Experience of Cloud Services Marco Netto, Marcos Assunção and Silvia Bianchi

2. © Copyright IBM Corporation 2013 2 Background  Large volumes of data are produced every day  Increasing use of mobile devices *  Around 700 million smartphones shipped a year  1.5 billion mobile broadband subscriptions by end 2013  Cloud-computing as a platform to support user services  Multiple devices and media multi-tasking  53% of UK adults media multi-task while watching TV **  Users expect other devices to augment content shown on TV *** * The State of Broadband 2013: Universilizing Broadband, Broadband Commission, Sep. 2013. ** The Communications Market Report: United Kingdom, Ofcom, Aug. 2013. *** Five insights into consumers’ online video viewing and buying habits, Accenture Point of View, No. 2 Jul. 2013.

3. © Copyright IBM Corporation 2013 3 Motivation  Applications, information and media are abundant, attention is scarce  Cloud is elastic, but resources are limited  Current devices can provide more honest signals on user behaviour and their profiles *  When do users actually consume the results of their requests? http://www.drawbrid.ge http://www.flurry.com/ http://www.velti.com *

4. © Copyright IBM Corporation 2013 4 Illustrative Scenario and Research Question  User switches across multiple applications  Can these signals on service consumption be used to differentiate the processing of requests, optimise the use of Cloud resources, and deliver better user experience? Game App Active Apps ? ?

5. © Copyright IBM Corporation 2013 5 Problem Description  Consider two service requests, req 1 and req 2, made by two distinct users  User patience d i = tc i – rt i where d < 0 means user is angry  User experience ue is modelled using principles from prospect theory, where d < 0 translates into worse ue than under |d|

6. © Copyright IBM Corporation 2013 6  Goals of the present work:  Minimising the distance between consumption time and response time  Investigate the impact on overall user experience  Outline:  Adaptive QoS architecture  Request prioritisation strategy  Experimental evaluation

7. © Copyright IBM Corporation 2013 7 Adaptive QoS Architecture User Device Cloud App1 Cloud App2 Local App Sensors QoS Setup Assistant Cloud Service Provider IT Infrastructure Service 1 Service 2 Service n QoS Setup Service

8. © Copyright IBM Corporation 2013 8 QoS Setup Service  Determines the user context  Monitors how users interact with a service  Patience-aware Prioritisation (PaP): 1. Obtains the expected time before consumption and average response time 2. Determines the user’s patience 3. Prioritises users who have less patience 4. To avoid starvation, a user’s patience decreases as her requests waits to be served

9. © Copyright IBM Corporation 2013 9 Experimental Setup  Built-in-house discrete event simulator  One service able to handle 100 requests at a time  Two categories of users, namely multi-task and single task  tc’s of single-task and multi-task users are 2 and 10 seconds respectively  Requests have fixed processing length  Evaluation under three workload scenarios, comparing PaP against a FCFS (standard) policy * C. Cardonha, M. Assuncao, M. Netto, R. Cunha, C. Queiroz, Patience-aware Scheduling for Cloud Services: Freeing Users from the Chains of Boredom, ICSOC 2013. *

10. © Copyright IBM Corporation 2013 10 Overall User Patience Multi-task users Single-task users

11. © Copyright IBM Corporation 2013 11 User Experience (Scenario 3) Standard strategy PaP strategy

12. © Copyright IBM Corporation 2013 12 User Experience (Scenario 2) Standard strategy PaP strategy

13. © Copyright IBM Corporation 2013 13 Final Remarks  Important to understand how users consume results of Cloud services and to optimise the utilisation or resources or enhance user experience  An architecture for leveraging more honest signals  A simple strategy to prioritise user requests *  Possible to improve user experience without heavily impact on users who multi-task  Proposed strategy is suitable to peak load conditions C. Cardonha, M. Assuncao, M. Netto, R. Cunha, C. Queiroz, Patience- aware Scheduling for Cloud Services: Freeing Users from the Chains of Boredom, ICSOC 2013. *

14. © Copyright IBM Corporation 2013 14 Thank you for your attention!