scholarly journals Fault Detection based Connected Dominating Set (FDCDS) in Fog Computing

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.

Sensors ◽  
2019 ◽  
Vol 19 (10) ◽  
pp. 2378 ◽  
Author(s):  
Dennis Lisiecki ◽  
Peilin Zhang ◽  
Oliver Theel

Wireless sensor networks (WSNs) play a significant role in a large number of applications, e.g., healthcare and industry. A WSN typically consists of a large number of sensor nodes which rely on limited power sources in many applications. Therefore, improving the energy efficiency of WSNs becomes a crucial topic in the research community. As a fundamental service in WSNs, network flooding offers the advantages that information can be distributed fast and reliably throughout an entire network. However, network flooding suffers from low energy efficiency due to the large number of redundant transmissions in the network. In this work, we exploit connected dominating sets (CDS) to enhance the energy efficiency of network flooding by reducing the number of transmissions. For this purpose, we propose a connected dominating set-based flooding protocol (CONE). CONE inhibits nodes that are not in the CDS from rebroadcasting packets during the flooding process. Furthermore, we evaluate the performance of CONE in both simulations and a real-world testbed, and then we compare CONE to a baseline protocol. Experimental results show that CONE improves the end-to-end reliability and reduces the duty cycle of network flooding in the simulations. Additionally, CONE reduces the average energy consumption in the FlockLab testbed by 15%.


2013 ◽  
Vol 13 (2) ◽  
pp. 121 ◽  
Author(s):  
Najla Al Nabhan ◽  
Mznah Al Rodhaan ◽  
Abdullah Al Dhelaan ◽  
Xiuzhen Cheng

2018 ◽  
Vol 14 (1) ◽  
pp. 155014771875563 ◽  
Author(s):  
Gulshan Kumar ◽  
Mritunjay Kumar Rai ◽  
Rahul Saha ◽  
Hye-jin Kim

Localization is one of the key concepts in wireless sensor networks. Different techniques and measures to calculate the location of unknown nodes were introduced in recent past. But the issue of nodes’ mobility requires more attention. The algorithms introduced earlier to support mobility lack the utilization of the anchor nodes’ privileges. Therefore, in this article, an improved DV-Hop localization algorithm is introduced that supports the mobility of anchor nodes as well as unknown nodes. Coordination of anchor nodes creates a minimum connected dominating set that works as a backbone in the proposed algorithm. The focus of the research paper is to locate unknown nodes with the help of anchor nodes by utilizing the network resources efficiently. The simulated results in network simulator-2 and the statistical analysis of the data provide a clear impression that our novel algorithm improves the error rate and the time consumption.


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