Abstract
Internet of Things is a promising paradigm that integrates a plethora of heterogeneous computational devices, incorporating the crowd, frameworks, additional system elements, and infrastructure. Information sensing, modeling, retrieval, and distribution perform an emerging role in the Internet of Things network. Dew computing is a challenging research issue, which needs to demonstrate its impact on the sensor data in the domain of parallel and distributed computing. We have presented a dew-cloud computing-based music crowdsourcing framework in this paper, to address the dew computing effectiveness in the context of the Internet of Things. The crowdsourcing paradigms are efficient to collect and analyze billions of information efficiently with a diminutive cost. In this promising paradigm, participated sound sensing devices sense acoustic information from the environment; transmit the sensor data to fog computing devices through dew repository, and eventually, cloud data center stores the processed data for providing aggregated musical information and relevant services to the end-users. This paper presents a Dew-Cloud based music crowdsourcing framework in the ambiance of the Internet of Things. We have illustrated a semantic mathematical background for the proposed crowdsourcing-based Internet of Music Things architecture in the dew-cloud computing framework. We have also discussed the system performance metrics, in terms of information transmission time, service latency, and energy dissipation in this endeavor. We have additionally illustrated a comparative analysis between the proposed paradigm and the conventional cloud computing schema in terms of data transmission time and overall system energy dissipation. The goal of this paper is to conceptualize, how the end-users can be benefitted from data analytics through data sensing, computing, and distributed scenario using a dew-cloud computational framework in the Internet of Things environment.
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