Sensor-cloud Integration Research Articles

A Green-IoT Healthcare and Agriculture Application

In the fields of agriculture and healthcare, the usage of two very common prominent and emerging technical knowledge, Cloud Computing i.e., CC in short and the Internet of Things or IoT in short, is currently a trending topic. Motivated by a desire to create a more ecological world, the authors in the paper examines a number of technological aspects and concerns related to eco-friendly CC and IoT, and expands on the argument by examining the fall of electric power intake of the two listed techniques when used together either in farm or health related work. It will be addressed in the paper - the idea of the ecological ICTs (Information and Communications Technologies) and its past that are responsible for empowering Green-IoT. Eco-friendly or green computing is introduced initially, followed by a discussion of current research on the discussed two very fast developing knowledges in farming and medical care. Furthermore, this article adds by proposing a sensorcloud integration paradigm for Green-IoT Healthcare and Agriculture Application (GHAA). Finally, the benefits, difficulties, and future research prospects for green application design are listed. Our study seeks to expand the green area and contribute to a more sustainable future.

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.

An Efficient On-Demand Latency Guaranteed Interactive Model for Sensor-Cloud

Motivated by the Internet-of-Things (IoT) cloudification as the trend to implement IoT applications, an efficient design for interactions between sensors and cloud is necessary. In this paper, we propose an efficient interactive model that is designed for the sensor-cloud integration to enable the sensor-cloud to simultaneously provide sensing services on-demand to multiple applications with various latency requirements. In the proposed model, complicated functions are offloaded to the cloud, and only the light-weight processes are executed at resource constrained sensor nodes. We design an aggregation mechanism for the sensor-cloud to aggregate the application requests so that the workloads that are required for sensors are minimized, thereby saving energy. The latency of sensing packets from sensor-to-cloud is controlled by the sensor-cloud based feedback control theory. Based on the feedback from the sensor-cloud, physical sensor nodes optimize their scheduling accordingly to save energy while maintaining the latency of all sensing flows routed through them satisfied the requirements of applications. Extensive experimental and analysis results show that the proposed model effectively controls the latency of sensing flows with a low signaling overhead and a high energy efficiency compared with the state-of-the-art scheme.

WITHDRAWN: Towards sensor-cloud integration: A survey of enabling technologies and architectures

WITHDRAWN: Towards sensor-cloud integration: A survey of enabling technologies and architectures