Sai Ji

Cloud-aided lightweight certificateless authentication protocol with anonymity for wireless body area networks

Abstract With the development of cloud computing and wireless body area networks (WBANs), wearable equipments are able to become new intelligent terminals to provide services for users, which plays an important role to improve the human health-care service. However, The traditional WBANs devices have limited computing and storage capabilities. These restrictions limit the services that WBANs can provide to users. Thus the concept of Cloud-aided WBANs has been proposed to enhance the capabilities of WBANs. In addition, due to the openness of the cloud computing environment, the protection of the users physiological information and privacy remains a major concern. In previous authentication protocols, few of them can protect the users private information in insecure channel. In this paper, we propose a cloud-aided lightweight certificateless authentication protocol with anonymity for wireless body area networks. Our protocol ensures that no one can obtain users real identity except for the network manager in the registration phase. Moreover, in the authentication phase, the network manager cannot know the users real identity. Note that, through the security analysis, we can conclude that our protocol can provide stronger security protection of private information than most of existing schemes in insecure channel.

A Method of Data Recovery Based on Compressive Sensing in Wireless Structural Health Monitoring

In practical structural health monitoring (SHM) process based on wireless sensor network (WSN), data loss often occurs during the data transmission between sensor nodes and the base station, which will affect the structural data analysis and subsequent decision making. In this paper, a method of recovering lost data in WSN based on compressive sensing (CS) is proposed. Compared with the existing methods, it is a simple and stable data recovery method and can obtain lower recovery data error for one-dimensional SHM’s data loss. First, response signal is measured onto the measurement data vector through inner products with random vectors. Note that is the linear projection of and is permitted to be lost in part during the transmission. Next, when the base station receives the incomplete data, the response signal can be reconstructed from the data vector using the CS method. Finally, the test of active structural damage identification on LF-21M aviation antirust aluminum plate is proposed. The response signal gathered from the aluminum plate is used to verify the data recovery ability of the proposed method.

Compressive sampling and data fusion-based structural damage monitoring in wireless sensor network

The Lamb wave phased array structural health monitoring method is effective in structural damage monitoring. In this method, the damage scattering signal can be obtained by comparing the damage structural response signal with health structural response signal, and it can be used for structural damage identification. But in the structural health monitoring based on wireless sensor networks, this method has some inevitable defects in data transmission. A large number of sampling data of damage response signal will cause huge wireless communication burden. To solve this problem, we proposed a phased array image method based on compressive sampling and data fusion for wireless structural damage monitoring. First, compressive sampling signal by compressive sampling method was collected. Then, data fusion for multi-sensor’s damage response signal was implemented in phased array. Finally, the Lamb wave phased array damage identification method based on compressive sampling and data fusion was proposed. Experimental results on carbon composite structure show that the proposed method can largely save network bandwidth and energy. This method can also realize the damage identification accurately on the aviation aluminum plate and keep the detection error within 0.82 mm.

Compressive Sampling Based on Wavelet Analysis for Lamb Wave Signals in Wireless Structural Health Monitoring

In the Wireless Sensor Networks (WSNs) for structural health monitoring (SHM), data compression is often used to reduce the cost of data transfer and storage, because of the large amounts of original data acquired from the monitoring system. Traditionally, we firstly sample the full signal and then compress it. However, the traditional approach for data compression will cause a lot of computing resources and energy loss on sensor nodes. Recently, a new data compression method named compressive sampling (CS) which acquires data in compressed form directly by using special sensors has been presented. In this work, we established a suitability CS approach for lamb wave signals in wireless SHM. For reconstruction of the signal, different wavelet orthogonal bases are examined. The lamb wave data acquired from the SHM system of LF- 21M aviation antirust aluminum plate is used to analyze the data compression ability of CS. Through the experimental demonstration, the application of this method could ensure the accuracy of the data as well as balance the network energy consumption. And it can also reduce the cost of data storage and transmission.

An effective data fusion-based routing algorithm with time synchronization support for vehicular wireless sensor networks

In the field of vehicular wireless sensor networks-based structural health monitoring, the structural damage identification is achieved by two structural features, namely natural frequencies and mode shapes. The kind of data fusion-based routing algorithm in specific applications needs to meet time synchronization requirements and meet certain constraints, such as the single-hop communication between cluster head node and each node in cluster, the overlap between different clusters and so on. To meet the special constraints for data fusion-based routing algorithm in structural health monitoring, this paper proposed a new method based on an improved flooding time synchronization protocol, which is called time synchronization and enhanced greedy algorithm based on D(v) (TSDEGA) routing algorithm. The TSDEGA method can achieve the minimum connected cover by node’s own degree D(v), and it can also meet the structural health monitoring routing constraints. The simulation experiments show that TSDEGA has better energy resistance and longer network lifetime, and it is superior to the traditional greedy algorithms. The proposed algorithm can effectively eliminate interference of outliers and improve the accuracy in order to meet time synchronization requirements in structural health monitoring applications.

S-SurF: An Enhanced Secure Bulk Data Dissemination in Wireless Sensor Networks

Wireless sensor networks (WSNs) have recently gained a lot of attentions as a hot topic of research, with extensive applications being explored. In WSNs, bulk data dissemination protocols are responsible for reprogramming, which have been proposed for efficiency and security. However, few of them can simultaneously achieve both reliability and security. To address this problem, we propose an enhanced protocol entitled Secure Survival of the Fittest (S-SurF) based on SurF [6] in this paper. The proposed protocol is composed of four main phases: packet preprocessing, flooding, negotiation and data verification. Moreover, S-SurF incorporates a time-reliability model to predict the minimum completion time and hence seizes the most opportune moment to transit between flooding and negotiation schemes. In addition, extensive analysis proves the efficiency and security of S-SurF.

Localization Technology in Wireless Sensor Networks Using RSSI and LQI: A Survey

For Wireless Sensor Networks (WSN), low-cost precise localization is the most essential requirement. Localization techniques based on RSSI is cost effective when be in comparison with TDOA, TOA and AOA. Because it doesn’t need any extra power, hardware or bandwidth. In this paper, we simply introduce some related theory and techniques, such as TDOA, TOA and AOA in Wireless Sensor Networks. Localization error can be declined by observing both RSSI and LQI at the same time. We survey a dynamic distance estimation method based on RSSI and LQI, and present a comparison of some algorithms based on the theory. By analyzing the model of radio wave propagation loss and empirical data from real measurement, the method is to use discrete linear lines to approximate the real attenuation of RSSI and LQI.

Exploiting Group Signature to Implement User Authentication in Cloud Computing

Cloud computing is a technology which is developed from the distributed computing. The cloud server provider gathers the redundant storage and computing resource to realize the goal of providing scalable computing resources to consumers. The infrastructures of the cloud computing are virtualized and they can be considered infinite. Therefore, the user side does not need to consider the local storage and computing resource. However, the cloud services are provided by the third party. As a general rule, the user who stores the data in the cloud is not safe. The security of the data is really concerned by the user. In other words, the cloud is interested in the data. We proposed a scheme that can support cloud user’s identity authentication, which is based on the group signature. From the security analysis, our scheme can resist some possible attacks.

A New Mathematics Method for Structural Health Monitoring's Damage Detection Based on WSNs

In the Wireless Sensor Network (WSN) for structural health monitoring (SHM), usually, we transmit the original acquisition data and exchange the large amounts of data between nodes which consume huge energy, occupy a large amount of communication bandwidth. Thus, data compression or data fusion to reduce network traffic and energy loss before transmission is necessary. In this work, we established a suitability compressive sensing (CS) to address some challenges in the Aviation Aluminum Plate Structural Health Monitoring System (AAPSHM) using WSN. Through the experimental demonstration, the application of this method could ensure the accuracy of the data as well as balance the network energy consumption. And it can also reduce the cost of data storage and transmission, improve the efficiency and make a certain contribution to the quality for the AAPSHM.

Application of Analytic Hierarchy Process to Evaluation on Quality of Atmospheric Environment in Nanjing City

Analytic hierarchy process was employed to analyze the atmospheric environmental quality in Nanjing City China. The supervision results of atmospheric pollutants during 2004 and 2014 show that Nanjing atmospheric environmental quality is generally favourable, but the effects of NO2 and PM10 are becoming increasingly serious. It is suggested that to control car exhaust and other sources of pollution including construction dust is vital to improve the quality of atmospheric environment in Nanjing City.