Attribute Allocation and Retrieval Scheme for Large-Scale Sensor Networks

Wireless sensor network is an emerging technology that enables remote monitoring of large geographical regions. In this paper, we address the problem of distributing attributes over such a large-scale sensor network so that the cost of data retrieval is minimized. The proposed scheme is a data-centric storage scheme where the attributes are distributed over the network depending on the correlations between them. The problem addressed here is similar to the Allocation Problem of distributed databases. In this paper, we have defined the Allocation Problem in the context of sensor networks and have proposed a scheme for finding a good distribution of attributes to the sensor network. We also propose an architecture for query processing given such a distribution of attributes. We analytically determine the conditions under which the proposed architecture is beneficial and present simulation results to demonstrate the same. To the best of our knowledge, this is the first attempt to determine an allocation of attributes over a sensor network based on the correlations between attributes.     

Why does it pay to be selfish in a MANET?

Routing protocols for a mobile ad hoc network have assumed that all mobile nodes voluntarily participate in forwarding others' packets. This was a reasonable assumption because all MNs in a MANET belonged to a single authority. In the near future, however, a MANET may consist of MNs that belong to many different organizations since numerous civilian applications are expected to crop up. In this situation, some MNs may run independently and purposely decide not to forward packets so as to save their own energy. This could potentially lead to network partitioning and corresponding performance degradation. To minimize such situations in MANETs, many studies have explored the use of both the carrot and the stick approaches by having reputation-based, credit-payment, and game theory schemes. This article summarizes existing schemes, identifies their relative advantages, and projects future directions     

Anthocyanin composition of the red wine Babić affected by maceration treatment

Identification of anthocyanins in the wine made of the Croatian autochthonous grape variety of Babić (Vitis vinifera L.) was carried out and their profile was determined by means of high-performance liquid chromatography with diode array and mass spectrometric detection. Dependence of anthocyanins content and profile on maceration treatment conditions was investigated. Statistically significant differences of anthocyanins concentration in wines Babić produced by various maceration treatments were confirmed by the use of multivariate analysis of variances. The investigation results indicated that the maceration temperature exerts higher influence on anthocyanins concentration than the duration of maceration. In addition, on the basis of anthocyanin composition and using different multivariate statistical analyses, differentiation of wines Babić according to maceration treatments was procured.     

Analysis and Optimization of the Energy Efficiency in the 802.11 DCF

This paper introduces an analytical model to investigate the energy efficiency of the IEEE 802.11 distributed coordinated function (DCF). This model not only accounts for the number of contending nodes, the contention window, but also the packet size, and the channel condition. Based on this model, we identify the tradeoff in choosing optimum parameters to optimize the energy efficiency of DCF in the error-prone environment. The effects of contention window and packet size on the energy efficiency are examined and compared for both DCF basic scheme and DCF with four-way handshaking. The maximum energy efficiency can be obtained by combining both the optimal packet size and optimal contention window. To validate our analysis, we have done extensive simulations in ns-2, and simulation results seem to match well with the presented analytical results. The Ohio Board of Regents Doctoral Enhancements Funds and the National Science Foundation under Grant CCR 0113361 have supported this work. Xiaodong Wang received his B.S. degree in communication engineering from Beijing Information Technical Institute of China in 1995, and his M.S. degree in electric engineering from Beijing University of Aeronautics and Astronautics of China in 1998. He joined China Telecom in 1998 where he worked on communication protocols for telecommunication. From June 2000 to July 2002, he worked on GSM base station software development at Bell-labs China, Beijing, China. Currently he is a Ph.D. student in Computer Engineering at University of Cincinnati. His research activities include wireless MAC protocols, energy saving for wireless sensor networks. He is a student member of the IEEE. Jun Yin received the BS degree in automatic control from Dalian Railway Institute of China in 1997, and the MS degree in flight control from Beijing University of Aeronautics and Astronautics of China in 2001. Since 2001 she has been a Ph.D. student in the OBR Research Center for Distributed and Mobile Computing at the University of Cincinnati. Her research interests include performance evaluation of 802.11 MAC protocol, wireless ad hoc networks and sensor networks. She is a student member of the IEEE. Dharma P.Agrawal IEEE Fellow, 1987; ACM Fellow, 1998; AAAS Fellow, 2003 Dr. Agrawal is the Ohio Board of Regents Distinguished Professor of Computer Science and Computer Engineering in the department of Electrical and Computer Engineering and Computer Science, University of Cincinnati, OH. He has been a faculty member at Wayne State University, (1977–1982) and North Carolina State University (1982–1998). He has been a consultant to the General Dynamics Land Systems Division, Battelle, Inc., and the U. S. Army. He has held visiting appointment at AIRMICS, Atlanta, GA, and the AT&T Advanced Communications Laboratory, Whippany, NJ. He has published a number of papers in the areas of Parallel System Architecture, Multi computer Networks, Routing Techniques, Parallelism Detection and Scheduling Techniques, Reliability of Real-Time Distributed Systems, Modeling of C-MOS Circuits, and Computer Arithmetic. His recent research interest includes energy efficient routing, information retrieval, and secured communication in ad hoc and sensor networks, effective handoff handling and multicasting in integrated wireless networks, interference analysis in piconets and routing in scatternet, use of smart directional antennas (multibeam) for enhanced QoS, Scheduling of periodic real-time applications and automatic load balancing in heterogeneous workstation environment. He has four approved patents and three patent filings in the area of wireless cellular networks.     

Support vector regression for determining the minimum zone sphericity

Several methods have been investigated to determine the deviation of manufactured spherical parts from ideal geometry. One of the most popular is the least squares technique, which is still widely employed in coordinate measuring machines used by industries. The least squares algorithm is optimal under the assumption that the data set is very large and has the inherent disadvantage of overestimating the minimum tolerance zone, resulting sometimes in the rejection of good parts. In addition, it requires that the data be distributed normally. The support vector regression approach alleviates the necessity for these assumptions. While most fitting algorithms in practice today require that the sampled data accurately represent the surface being inspected, support vector regression provides a generalization over the surface. We describe how the concepts of support vector regression can be applied to the determination of tolerance zones of nonlinear surfaces; to demonstrate the unique potential of support vector machine algorithms in the area of coordinate metrology. In specific, we address part quality inspection of spherical geometries.     

A Possible Industrial Solution to Ferment Lignocellulosic Hydrolyzate to Ethanol: Continuous Cultivation with Flocculating Yeast

The cultivation of toxic lignocellulosic hydrolyzates has become a challenging research topic in recent decades. Although several cultivation methods have been proposed, numerous questions have arisen regarding their industrial applications. The current work deals with a solution to this problem which has a good potential application on an industrial scale. A toxic dilute-acid hydrolyzate was continuously cultivated using a high-cell-density flocculating yeast in a single and serial bioreactor which was equipped with a settler to recycle the cells back to the bioreactors. No prior detoxification was necessary to cultivate the hydrolyzates, as the flocks were able to detoxify it in situ. The experiments were successfully carried out at dilution rates up to 0.52 h⁻¹. The cell concentration inside the bioreactors was between 23 and 35 g-DW/L, while the concentration in the effluent of the settlers was 0.32 ± 0.05 g-DW/L. An ethanol yield of 0.42–0.46 g/g-consumed sugar was achieved, and the residual sugar concentration was less than 6% of the initial fermentable sugar (glucose, galactose and mannose) of 35.2 g/L.     

Modulation of silica layer properties by varying the granulometric state of tetraethyl orthosilicate precursor aerosols during combustion chemical vapor deposition (CCVD)

Abstract

For the purpose of silica surface layer modulation, a pneumatic-controlled two-substance atomizer with inertia-based coarse droplet separation was operated at different system pressures for tetraethyl orthosilicate precursor aerosol supply during combustion chemical vapor deposition. A comprehensive testing study was performed to characterize the atomizer’s performance characteristics, initial precursor aerosols at the atomizer’s outlet, transformed aerosols before combustion, combustion aerosols and formed layers. Laser diffraction spectrometry, differential electrical mobility analyses and condensation particle counting were used for aerosol characterization with regard to particle size and particle production quantities. Layers were characterized by scanning electron microscopy, atomic force microscopy, spectral ellipsometry, water contact angle measurements and light transmission concerning geometric properties (thickness, surface structure and roughness) and physical behaviors (i.e., optical behaviors, hydrophobicity). Results show a quasi-linear relationship of the ejection mass flow of the pneumatic-controlled atomizer and geometric layer properties which again show a direct relationship to the physical properties. No correlation was found between the aerosols before combustion and the combustion aerosols since the majority of combustion aerosol particles are synthesized solely from the gas phase based on evaporated precursor material.

Copyright © 2020 American Association for Aerosol Research     

Fault tolerant multiple event detection in a wireless sensor network

With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P$P$) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P$P$ can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10%$10\%$ with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94%$94\%$ and it increases with increase in node density.     

Range-Free Localization Using Expected Hop Progress in Wireless Sensor Networks

Localization algorithm continues to be an important and challenging topic in today's wireless sensor networks (WSNs). In this paper, a novel range-free localization algorithm using expected hop progress (LAEP) to predict the location of any sensor in a WSN is proposed. This algorithm is based on an accurate analysis of hop progress in a WSN with randomly deployed sensors and arbitrary node density. By deriving the expected hop progress from a network model for WSNs in terms of network parameters, the distance between any pair of sensors can be accurately computed. Since the distance estimation is a key issue in localization systems for WSNs, the proposed range-free LAEP achieves better performance and less communication overhead as compared to some existent schemes like DV-Hop and RAW. In addition, we study the effect of anchor placement on the algorithm performance by deriving the corresponding mean position error range. Extensive simulations are performed and the results are observed to be in good agreement with the theoretical analysis.