Sensor Cloud Frameworks: State-of-the-Art, Taxonomy, and Research Issues

In recent times, Wireless Sensor Network (WSN) technology has received significant attention owing to its numerous applications in various mission critical services, such as healthcare, military monitoring, public safety systems, and forest monitoring. However, sensor node's low computational power and inadequate advancements in battery design hinder resource-rigorous applications from fully exploiting WSN capabilities. The trend of shifting computations and storage to remote clouds offers the opportunity to integrate WSNs into the cloud to mitigate their limitations. The Sensor Cloud augments WSN capabilities of remote sensing and monitoring while exploiting resource-rich cloud infrastructure. To date, numerous solutions have been proposed to handle the integration concerns of WSNs with the cloud. However, a comprehensive study that covers various Sensor Cloud aspects in terms of architecture, network dynamics, heterogeneity, communication patterns, data management, and security, is still lacking. To fill this gap, state-of-the-art sensor cloud integration frameworks are analyzed in this article. Moreover, a detailed thematic taxonomy is presented to classify existing sensor cloud frameworks while focusing in service oriented and client server architectures. Related features and critical aspects of existing frameworks are inspected through a qualitative analysis based on the parameters selected from the literature and extracted from the taxonomy. Several research opportunities in this research domain are suggested to assist researchers in identifying and designing optimal resource sensor cloud integration frameworks to host emerging applications.