IBM Research © 2013 IBM Corporation Leveraging Attention Scarcity to Improve the Overall User Experience of Cloud Services Marco Netto, Marcos Assunção and Silvia Bianchi
© Copyright IBM Corporation 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 ** The Communications Market Report: United Kingdom, Ofcom, Aug *** Five insights into consumers’ online video viewing and buying habits, Accenture Point of View, No. 2 Jul
© Copyright IBM Corporation 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? *
© Copyright IBM Corporation 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 ? ?
© Copyright IBM Corporation 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|
© Copyright IBM Corporation 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
© Copyright IBM Corporation 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
© Copyright IBM Corporation 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
© Copyright IBM Corporation 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 *
© Copyright IBM Corporation Overall User Patience Multi-task users Single-task users
© Copyright IBM Corporation User Experience (Scenario 3) Standard strategy PaP strategy
© Copyright IBM Corporation User Experience (Scenario 2) Standard strategy PaP strategy
© Copyright IBM Corporation 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 *
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