Xiangmao Chang^{1, 2, *}, Xiaoxiang Xu¹, Deliang Yang³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 193-206, 2020, DOI:10.32604/cmc.2020.08183

Abstract Strip Wireless Sensor Networks (SWSNs) have drawn much attention in many applications such as monitoring rivers, highways and coal mines. Packet delivery in SWSN usually requires a large number of multi-hop transmissions which leads to long transmission latency in low-duty-cycle SWSNs. Several pipeline scheduling schemes have been proposed to reduce latency. However, when communication links are unreliable, pipeline scheduling is prone to failure. In this paper, we propose a pipeline scheduling transmission protocol based on constructive interference. The protocol first divides the whole network into multiple partitions and uses a pipelined mechanism to allocate active time slots for each partition.… More >

Nithya Rekha Sivakumar^{1, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 81-96, 2020, DOI:10.32604/cmc.2020.08851

Abstract In the past few decades, Energy Efficiency (EE) has been a significant challenge in Wireless Sensor Networks (WSNs). WSN requires reduced transmission delay and higher throughput with high quality services, it further pays much attention in increased energy consumption to improve the network lifetime. To collect and transmit data Clustering based routing algorithm is considered as an effective way. Cluster Head (CH) acts as an essential role in network connectivity and perform data transmission and data aggregation, where the energy consumption is superior to non-CH nodes. Conventional clustering approaches attempts to cluster nodes of same size. Moreover, owing to randomly… More >

Xiangmao Chang^{1, 2, *}, Yuan Qiu¹, Shangting Su¹, Deliang Yang³

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 691-703, 2020, DOI:10.32604/cmc.2020.07923

Abstract Wireless sensor networks are increasingly used in sensitive event monitoring. However, various abnormal data generated by sensors greatly decrease the accuracy of the event detection. Although many methods have been proposed to deal with the abnormal data, they generally detect and/or repair all abnormal data without further differentiate. Actually, besides the abnormal data caused by events, it is well known that sensor nodes prone to generate abnormal data due to factors such as sensor hardware drawbacks and random effects of external sources. Dealing with all abnormal data without differentiate will result in false detection or missed detection of the events.… More >

Omid Mahdi Ebadati E.^{1, *}, Farshad Eshghi², Amin Zamani¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 323-349, 2020, DOI:10.32604/cmes.2020.08079

Abstract Transmission pipelines are vulnerable to various accidents and acts of vandalism. Therefore, a reliable monitoring system is needed to secure the transmission pipelines. A wireless sensor network is a wireless network consisting of distributed devices distributed at various distances, which monitors the physical and environmental conditions using sensors. Wireless sensor networks have many uses, including the built-in sensor on the outside of the pipeline or installed to support bridge structures, robotics, healthcare, environmental monitoring, etc. Wireless Sensor networks could be used to monitor the temperature, pressure, leak detection and sabotage of transmission lines. Wireless sensor networks are vulnerable to various… More >

Bing Hu¹, Feng Xiang², Fan Wu³, Jian Liu⁴, Zhe Sun¹, Zhixin Sun^1,*

CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1323-1344, 2019, DOI:10.32604/cmc.2019.06414

Abstract To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively according to the observations. Moreover,… More >

A. Rama Mohan Rao¹, S. Krishna Kumar¹, K. Lakshmi¹

Structural Durability & Health Monitoring, Vol.8, No.3, pp. 271-294, 2012, DOI:10.32604/sdhm.2012.008.271

Abstract Current advancements in structural health monitoring, sensor and sensor network technologies have encouraged using large number of sensor networks in monitoring spatially large civil structures like bridges. Large amount of spatial information obtained from these sensor networks will enhance the reliability in truly assessing the state of the health of the structure. However, if sensors go faulty during operation, the feature extraction techniques embedded into SHM scheme may lead to an erroneous conclusion and often end up with false alarms. Hence it is highly desirable to robustly detect the faulty sensors, isolate and correct the data, if the data at… More >

Qi Wang^1,*, Wei Liu¹, Hualong Yu¹, Shang Zheng¹, Shang Gao¹, Fabrizio Granelli²

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 83-103, 2019, DOI:10.32604/cmes.2019.06897

Abstract The wireless sensor network (WSN) is widely employed in the application scenarios of the Internet of Things (IoT) in recent years. Extending the lifetime of the entire system had become a significant challenge due to the energy-constrained fundamental limits of sensor nodes on the perceptual layer of IoT. The clustering routing structures are currently the most popular solution, which can effectively reduce the energy consumption of the entire network and improve its reliability. This paper introduces an enhanced hybrid intelligential algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) method. The enhanced PSO is deployed to select… More >

Byung-wan Jo¹, Do-keun Kim², Sung-keun Song³, Suk-un Kim⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.1, No.4, pp. 167-172, 2007, DOI:10.3970/icces.2007.001.167

Abstract Wireless sensor networks bring new challenges to Bridge monitoring. To monitor a bridge, behavior, including vibration and displacement, must be measured to analyze the health of the structure based on measured and collected data. The collected data can be used to compute modal properties of the bridge. A bridge is moved by external forces, including wind, seismic activity, and traffic. So it is very hard reliance of safety through a preexistence method which uses Data Logger. Dynamic behavior of a bridge is difficult to measure because of costs and installation methods. In this paper, a new method, using a U-Smart… More >

Haoran Zhu¹, Demin Gao^1,2,*, Shuo Zhang¹

Journal on Internet of Things, Vol.1, No.1, pp. 25-31, 2019, DOI:10.32604/jiot.2019.05897

Abstract Forest fire prediction constitutes a significant component of forest management. Timely and accurate forest fire prediction will greatly reduce property and natural losses. A quick method to estimate forest fire hazard levels through known climatic conditions could make an effective improvement in forest fire prediction. This paper presents a description and analysis of a forest fire prediction methods based on machine learning, which adopts WSN (Wireless Sensor Networks) technology and perceptron algorithms to provide a reliable and rapid detection of potential forest fire. Weather data are gathered by sensors, and then forwarded to the server, where a fire hazard index… More >

Yong Xie¹, Fang Xu², Xiang Li¹, Songsong Zhang¹, Xiaodan Zhang^1,*, Muhammad Israr³

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 903-924, 2019, DOI:10.32604/cmc.2019.05309

Abstract Wireless sensor networks (WSNs) are the major contributors to big data acquisition. The authenticity and integrity of the data are two most important basic requirements for various services based on big data. Data aggregation is a promising method to decrease operation cost for resource-constrained WSNs. However, the process of data acquisitions in WSNs are in open environments, data aggregation is vulnerable to more special security attacks with hiding feature and subjective fraudulence, such as coalition attack. Aimed to provide data authenticity and integrity protection for WSNs, an efficient and secure identity-based aggregate signature scheme (EIAS) is proposed in this paper.… More >