Abstract: With the advance of research in human computation, applications and software systems are increasingly being designed to include the human aspect of computation. We work with Social Compute Units (SCUs) that are computational constructs with people as their core resources. They are collaborative units, and have a cloud-like behavior in the sense that they may be elastically adapted at runtime. Systems that utilize the concept of SCUs bring challenges that are associated with the highly dynamic and unpredictable human-centric behavior. Thus, trust in the human based services that execute tasks is of paramount importance. While there is related work on social trust in the social networking and crowdsourcing areas, trust in highly coordinated team-based systems such as SCUs remains as a significant challenge. Thus, in this paper we provide a trust model that considers merging social trust with performance based trust of human based services into an integrated trust model. We illustrate the models’ application in concrete strategies, such as for elastic management of SCUs and incentives for SCU members.

Citation: Mirela Riveni, Hong-Linh Truong, Schahram Dustdar, “Trust-aware Elastic Social Compute Units”, The 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom-15), Helsinki, Finland, 20-22 August 2015.

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Abstract. Advances in human computation bring the feasibility of utilizing human capabilities as services. On the other hand, we have witnessed emerging collective adaptive systems which are formed from heterogeneous types of compute units to solve complex problems. The recently introduced Social Compute Units (SCUs) present one type of these systems, which have human-based services as their core fundamental compute units. While, there is related work on forming SCUs and optimizing their performance with adaptation techniques, most of it is focused on static structures of SCUs. To provide better runtime performance and exibility management for SCUs, we present an elasticity model for SCUs and mechanisms for their elastic management which allow for certain uctuations in size, structure, performance and quality. We model states of elastic SCUs, present APIs for managing SCUs as well as metrics for controlling their elasticity with which it is possible to tailor their performance parameters at runtime within the customer-set constraints. We illustrate our contribution with an example algorithm.

Keywords: social compute units, elasticity, adaptation, collective adaptive systems

doi: http://link.springer.com/chapter/10.1007%2F978-3-319-07881-6_25

Citation: Mirela Riveni, Hong-Linh Truong, Schahram Dustdar. On the Elasticity of Social Compute Units, Springer-Verlag, 26th International Conference on Advanced Information Systems Engineering (CAiSE 2014), 16-20 June 2014, Thessaloniki, Greece. Accepted.

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