Sensor Cloud: Integrating Wireless Sensor Networks with Cloud Computing

Author(s):  
Rajendra Kumar Dwivedi ◽  
Rakesh Kumar
Author(s):  
Seyed Amin Hosseini Seno ◽  
Fatemeh Banaie

With the advancement of wireless sensor networks (WSN) and the increasing use of sensors in various industrial, environmental and commercial fields, it is difficult to store and process the volume of generated data on local platforms. Cloud computing provides scalable resources to perform analysis of online as well as offline data streams generated by sensor networks. This can help to overcome the weakness of WSN in combining and analyzing heterogeneous and large numbers of sensory data. This chapter presents a comprehensive survey on state-of-the-art results in the context of cloud –enabled large-scale sensor networks. The chapter also discusses the objectives, architecture and design issues of the generic sensor-cloud platform.


2021 ◽  
Author(s):  
Ihsan Ali

<div>Data collection is an essential part of sensor devices, particularly in such technologies Like Internet of Things (IoT), wireless sensor networks (WSN), and sensor cloud (SC). In recent years, various literature had been published in these research areas to propose different models, architectures, and contributions in the domains. Due to the importance of efficient data collection regarding reducing. energy consumption, latency, network lifetime, and general cost, a momentous literature volume has been published to facilitate data collection. Hence, review studies have been conducted on data collection in these domains in isolation. However, a lack of comprehensive review collectively identifies and analyzes the differences and similarities among the data collection proposals in IoT, WSN, and SC. The main objective of this research is to conduct a comprehensive survey to explore the current state, use cases, contributions, performance measures, evaluation measures, and architecture in the IoT, WSN, and SC research domains. The findings indicate that studies on data collection in IoT, WSN, and SC are relatively consistent with stable output in the last five years. Nine novel contributions are found with models, algorithms, and frameworks being the most utilized by the selected studies. In conclusion, key research challenges and future research directions have been identified and discussed.</div>


2021 ◽  
Author(s):  
Ihsan Ali

<div>Data collection is an essential part of sensor devices, particularly in such technologies Like Internet of Things (IoT), wireless sensor networks (WSN), and sensor cloud (SC). In recent years, various literature had been published in these research areas to propose different models, architectures, and contributions in the domains. Due to the importance of efficient data collection regarding reducing. energy consumption, latency, network lifetime, and general cost, a momentous literature volume has been published to facilitate data collection. Hence, review studies have been conducted on data collection in these domains in isolation. However, a lack of comprehensive review collectively identifies and analyzes the differences and similarities among the data collection proposals in IoT, WSN, and SC. The main objective of this research is to conduct a comprehensive survey to explore the current state, use cases, contributions, performance measures, evaluation measures, and architecture in the IoT, WSN, and SC research domains. The findings indicate that studies on data collection in IoT, WSN, and SC are relatively consistent with stable output in the last five years. Nine novel contributions are found with models, algorithms, and frameworks being the most utilized by the selected studies. In conclusion, key research challenges and future research directions have been identified and discussed.</div>


Webology ◽  
2020 ◽  
Vol 17 (2) ◽  
pp. 599-606
Author(s):  
Nagarjuna Valeti ◽  
V. Ceronmani Sharmila

The meaning of cloud computing is providing services by using the internet. From the Cloud Data Centres (CDC) the services are utilized by the cloud users. Presently (Internet of things) IOT playing the key role to improve the performance of the fog computing enabled applications. Migrating the wireless sensor networks with IOT becomes the most powerful and error free application based on the availability of the services, cloud storage, computation and these are transferred efficiently between server and cloud. Health domain is most widely affecting system in cloud computing as well as by using fog computing with IOT. The system causes various failures for providing the service continuously. Enabling the fog computing with the integration of cloud for the medical devices to transmit the patient information to the cloud storage has become the complicated for the IOT sensors continuously. This may cause the data loss and also reduce the performance of the medical device. To improve the continuous services within the cloud server. In this paper, the Fault detection based Connected Dominating Set (FDCDS) which provides the continuous services with the integration of fog computing and IOT devices with wireless sensor networks. Simulation shows the performance of the proposed system.


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