Spontaneous task composition in urban computing environments based on social, spatial, and temporal aspects

  • Authors:
  • Angel Jimenez-Molina;In-Young Ko

  • Affiliations:
  • Department of Computer Science, KAIST, Korea Advanced Institute of Science and Technology, 335 Gwahangno (373-1 Guseong-dong), Yuseong-gu, Daejeon 305-701, Republic of Korea;Department of Computer Science, KAIST, Korea Advanced Institute of Science and Technology, 335 Gwahangno (373-1 Guseong-dong), Yuseong-gu, Daejeon 305-701, Republic of Korea

  • Venue:
  • Engineering Applications of Artificial Intelligence
  • Year:
  • 2011

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Abstract

Ubiquitous and urban computing share the goal of enabling users to access networked services and resources anytime, anywhere. The intermesh of planned and situational activities is a distinguishable characteristic of urban computing environments. This produces a diversity of service requirements that need to be tackled by opportunistically suggesting appropriate services to users or social groups, without having a previous definition of applications in templates or any other descriptions in advance. This paper leverages the approach of task-oriented computing to represent user goals in tasks. A task is composed of unit-tasks: user centric configurations of abstract service coordinations. The focus of this paper is on the provision of a mechanism to cover the spontaneous unit-task composition cycle, based on social, spatial, and temporal aspects. This is realized by identifying the essential semantic elements that describe unit-tasks, UrbComp environments, and social groups. We have extended a unit-task selection mechanism from our previous work. In addition, this paper contributes a set of composability metrics based on social, spatial, and temporal aspects. These metrics concern the measurement of semantic interoperability and potential conflicts between unit-tasks or unit-task composites. These metrics are used to join unit-tasks together in sequences. Experimental results for a real dataset of tasks were obtained. These results show a suitable time-overhead for the unit-task selection mechanism. In addition, a simulation of arrivals at a crowded space was utilized to measure the performance, throughput, and efficacy ratio of the composition mechanism.