West Virginia University Institute of Technology

This paper promotes the concept of smart and connected communities SCC, which is evolving from the concept of smart cities. SCC are envisioned to address synergistically the needs of remembering the past (preservation and revitalization), the needs of living in the present (livability), and the needs of planning for the future (attainability). Therefore, the vision of SCC is to improve livability, preservation, revitalization, and attainability of a community. The goal of building SCC for a community is to live in the present, plan for the future, and remember the past. We argue that Internet of Things (IoT) has the potential to provide a ubiquitous network of connected devices and smart sensors for SCC, and big data analytics has the potential to enable the move from IoT to real-time control desired for SCC. We highlight mobile crowdsensing and cyber-physical cloud computing as two most important IoT technologies in promoting SCC. As a case study, we present TreSight, which integrates IoT and big data analytics for smart tourism and sustainable cultural heritage in the city of Trento, Italy.

Shotgun proteomics experiments are dependent upon database search engines to identify peptides from tandem mass spectra. Many of these algorithms score potential identifications by evaluating the number of fragment ions matched between each peptide sequence and an observed spectrum. These systems, however, generally do not distinguish between matching an intense peak and matching a minor peak. We have developed a statistical model to score peptide matches that is based upon the multivariate hypergeometric distribution. This scorer, part of the "MyriMatch" database search engine, places greater emphasis on matching intense peaks. The probability that the best match for each spectrum has occurred by random chance can be employed to separate correct matches from random ones. We evaluated this software on data sets from three different laboratories employing three different ion trap instruments. Employing a novel system for testing discrimination, we demonstrate that stratifying peaks into multiple intensity classes improves the discrimination of scoring. We compare MyriMatch results to those of Sequest and X!Tandem, revealing that it is capable of higher discrimination than either of these algorithms. When minimal peak filtering is employed, performance plummets for a scoring model that does not stratify matched peaks by intensity. On the other hand, we find that MyriMatch discrimination improves as more peaks are retained in each spectrum. MyriMatch also scales well to tandem mass spectra from high-resolution mass analyzers. These findings may indicate limitations for existing database search scorers that count matched peaks without differentiating them by intensity. This software and source code is available under Mozilla Public License at this URL: http://www.mc.vanderbilt.edu/msrc/bioinformatics/.

Vehicular ad hoc networks (VANETs) have the potential to transform the way people travel through the creation of a safe interoperable wireless communications network that includes cars, buses, traffic signals, cell phones, and other devices. However, VANETs are vulnerable to security threats due to increasing reliance on communication, computing, and control technologies. The unique security and privacy challenges posed by VANETs include integrity (data trust), confidentiality, nonrepudiation, access control, real-time operational constraints/demands, availability, and privacy protection. The trustworthiness of VANETs could be improved by addressing holistically both data trust, which is defined as the assessment of whether or not and to what extent the reported traffic data are trustworthy, and node trust, which is defined as how trustworthy the nodes in VANETs are. In this paper, an attack-resistant trust management scheme (ART) is proposed for VANETs that is able to detect and cope with malicious attacks and also evaluate the trustworthiness of both data and mobile nodes in VANETs. Specially, data trust is evaluated based on the data sensed and collected from multiple vehicles; node trust is assessed in two dimensions, i.e., functional trust and recommendation trust, which indicate how likely a node can fulfill its functionality and how trustworthy the recommendations from a node for other nodes will be, respectively. The effectiveness and efficiency of the proposed ART scheme is validated through extensive experiments. The proposed trust management theme is applicable to a wide range of VANET applications to improve traffic safety, mobility, and environmental protection with enhanced trustworthiness.

The term big data occurs more frequently now than ever before. A large number of fields and subjects, ranging from everyday life to traditional research fields (i.e., geography and transportation, biology and chemistry, medicine and rehabilitation), involve big data problems. The popularizing of various types of network has diversified types, issues, and solutions for big data more than ever before. In this paper, we review recent research in data types, storage models, privacy, data security, analysis methods, and applications related to network big data. Finally, we summarize the challenges and development of big data to predict current and future trends.

Existing static grid resource scheduling algorithms, which are limited to minimizing the makespan, cannot meet the needs of resource scheduling required by cloud computing. Current cloud infrastructure solutions provide operational support at the level of resource infrastructure only. When hardware resources form the virtual resource pool, virtual machines are deployed for use transparently. Considering the competing characteristics of multi-tenant environments in cloud computing, this paper proposes a cloud resource allocation model based on an imperfect information Stackelberg game (CSAM-IISG) using a hidden Markov model (HMM) in a cloud computing environment. CSAM-IISG was shown to increase the profit of both the resource supplier and the applicant. Firstly, we used the HMM to predict the service provider's current bid using the historical resources based on demand. Through predicting the bid dynamically, an imperfect information Stackelberg game (IISG) was established. The IISG motivates service providers to choose the optimal bidding strategy according to the overall utility, achieving maximum profits. Based on the unit prices of different types of resources, a resource allocation model is proposed to guarantee optimal gains for the infrastructure supplier. The proposed resource allocation model can support synchronous allocation for both multi-service providers and various resources. The simulation results demonstrated that the predicted price was close to the actual transaction price, which was lower than the actual value in the game model. The proposed model was shown to increase the profits of service providers and infrastructure suppliers simultaneously.

The problem of defining critical flow condition associated with the initial instability of bed material particle has been studied in relation to existing concepts. The data has been collected and analysed to indicate that a distinct condition for the beginning of movement doe not exist. The bed load transport in the proximity of so called critical shear stress is governed by certain well defined law. For all practical purpose, a limiting bed shear stress for a bed material can be defined below which the bed load transport is of no practical importance.

Wireless sensor networks (WSNs) have witnessed rapid advancement in medical applications from real-time telemonitoring and computer-assisted rehabilitation to emergency response systems. In this paper, we present the state-of-the-art research from the ubiquity perspective, and discuss the insights as well as vision of future directions in WSN-based healthcare systems. First, we propose a novel tiered architecture that can be generally applied to WSN-based healthcare systems. Then, we analyze the IEEE 802 series standards in the access layer on their capabilities in setting up WSNs for healthcare. We also explore some of the up-to-date work in the application layer, mostly on the smartphone platforms. Furthermore, in order to develop and integrate effective ubiquitous sensing for healthcare (USH), we highlight four important design goals (i.e., proactiveness, transparency, awareness, and trustworthiness) that should be taken into account in future systems.

Face identification and resolution technology is crucial to ensure the identity consistency of humans in physical space and cyber space. In the current Internet of Things (IoT) and big data situation, the increase of applications based on face identification and resolution raises the demands of computation, communication, and storage capabilities. Therefore, we have proposed the fog computing-based face identification and resolution framework to improve processing capacity and save the bandwidth. However, there are some security and privacy issues brought by the properties of fog computing-based framework. In this paper, we propose a security and privacy preservation scheme to solve the above issues. We give an outline of the fog computing-based face identification and resolution framework, and summarize the security and privacy issues. Then the authentication and session key agreement scheme, data encryption scheme, and data integrity checking scheme are proposed to solve the issues of confidentiality, integrity, and availability in the processes of face identification and face resolution. Finally, we implement a prototype system to evaluate the influence of security scheme on system performance. Meanwhile, we also evaluate and analyze the security properties of proposed scheme from the viewpoint of logical formal proof and the confidentiality, integrity, and availability (CIA) properties of information security. The results indicate that the proposed scheme can effectively meet the requirements for security and privacy preservation.

Many researches show that the power consumption of network devices of ICT is nearly 10% of total global consumption. While the redundant deployment of network equipment makes the network utilization is relatively low, which leads to a very low energy efficiency of networks. With the dynamic and high quality demands of users, how to improve network energy efficiency becomes a focus under the premise of ensuring network performance and customer service quality. For this reason, we propose an energy consumption model based on link loads, and use the network’s bit energy consumption parameter to measure the network energy efficiency. This paper is to minimize the network’s bit energy consumption parameter, and then we propose the energy-efficient minimum criticality routing algorithm, which includes energy efficiency routing and load balancing. To further improve network energy efficiency, this paper proposes an energy-efficient multi-constraint rerouting (E2MR2) algorithm. E2MR2 uses the energy consumption model to set up the link weight for maximum energy efficiency and exploits rerouting strategy to ensure network QoS and maximum delay constraints. The simulation uses synthetic traffic data in the real network topology to analyze the performance of our method. Simulation results that our approach is feasible and promising.

A composite sorbent (GAC-QPVP) was prepared by coating poly(4-vinylpyridine) onto a granular activated carbon, followed by cross-linking and quaternization processes. The sorbent was characterized by scanning electron microscopy, point of zero charge measurement, and BET analysis. Batch experiments with variable pH, ionic strength, and concentrations of Cr(VI), sorbent, and competing anions were conducted to evaluate the selective sorption of Cr(VI) from aqueous solutions. The results showed that Cr(VI) sorption rates could be described by a reversible second-order kinetics, and equilibrium uptake of Cr(VI) increased with decreasing pH, decreasing ionic strength, and increasing sorbent concentration. The estimated maximum equilibrium uptake of chromium was 53.7 mg/g at pH = 2.25, 30.7 mg/g at pH = 3.65, and 18.9 mg/g at pH = 6.03, much higher than the maximum capacity of PVP-coated silica gel, an adsorbent for Cr examined previously. When compared with the untreated granular activated carbon, sorption onto GAC-QPVP resulted in much less Cr(VI) reduction and subsequent release of Cr(III). The effect of phosphate, sulfate, and nitrate was minor on the selective sorption of Cr(VI). An ion exchange model that was linked with aqueous speciation chemistry described Cr(VI) sorption reasonably well as a function of pH, ionic strength, and Cr(VI) concentration. Model simulations suggested that sorbed Cr(VI) was partially reduced to Cr(III) on the sorbent when pH was less than 4. The presence of Cr(III) on the sorbent was confirmed by the X-ray photoelectron spectroscopic analysis. Overall, the study has demonstrated that GAC-QPVP can effectively remove Cr(VI) from aqueous solutions under a wide range of experimental conditions, without significant Cr(III) release associated with the virgin GAC treatment.

One of the emerging networking standards that gap between the physical world and the cyber one is the Internet of Things. In the Internet of Things, smart objects communicate with each other, data are gathered and certain requests of users are satisfied by different queried data. The development of energy efficient schemes for the IoT is a challenging issue as the IoT becomes more complex due to its large scale the current techniques of wireless sensor networks cannot be applied directly to the IoT. To achieve the green networked IoT, this paper addresses energy efficiency issues by proposing a novel deployment scheme. This scheme, introduces: (1) a hierarchical network design; (2) a model for the energy efficient IoT; (3) a minimum energy consumption transmission algorithm to implement the optimal model. The simulation results show that the new scheme is more energy efficient and flexible than traditional WSN schemes and consequently it can be implemented for efficient communication in the IoT.

The Internet of Things (IoT) depicts a bright future, where any devices having sensorial and computing capabilities can interact with each other. Among all existing technologies, the techniques for the fifth generation (5G) systems are the main driving force for the actualization of IoT concept. However, due to the heterogeneous environment in 5G networks and the broadcast nature of radio propagation, the security assurance against eavesdropping is a vital yet challenging task. In this paper, we focus on the transmission design for secure relay communications in IoT networks, where the communication is exposed to eavesdroppers with unknown number and locations. The randomize-and-forward relay strategy specially designed for secure multi-hop communications is employed in our transmission protocol. First, we consider a single-antenna scenario, where all the devices in the network are equipped with the single antenna. We derive the expression for the secrecy outage probability of the two-hop transmission. Following this, a secrecy-rate-maximization problem subject to a secrecy-outage-probability constraint is formulated. The optimal power allocation and codeword rate design are obtained. Furthermore, we generalize the above analyses to a more generic scenario, where the relay and eavesdroppers are equipped with multiple antennas. Numerical results show that the proper use of relay transmission can enhance the secrecy throughput and extend the secure coverage range.

Recently, named data networking (NDN) has been proposed as a promising architecture for future Internet technologies. NDN is an extension to the content-centric network (CCN) and is expected to support various applications in vehicular communications [vehicular NDN (VNDN)]. VNDN basically relies on naming the content rather than using end-to-end device names. In VNDN, a vehicle broadcasts an “Interest” packet for the required “content,” regardless of end-to-end connectivity with servers or other vehicles and known as a “consumer.” In response, a vehicle with the content replies to the Interest packet with a “Data” packet and named as a “provider.” However, the simple VNDN architecture faces several challenges such as consumer/provider mobility and Interest/Data packet(s) forwarding. In VNDN, for the most part, the Data packet is sent along the reverse path of the related Interest packet. However, there is no extensive simulated reference available in the literature to support this argument. In this paper, therefore, we first analyze the propagation behavior of Interest and Data packets in the vehicular ad hoc network (VANET) environment through extensive simulations. Second, we propose the “CODIE” scheme to control the Data flooding/broadcast storm in the naïve VNDN. The main idea is to allow the consumer vehicle to start hop counter in Interest packet. Upon receiving this Interest by any potential provider, a data dissemination limit (DDL) value stores the number of hops and a data packet needs to travel back. Simulation results show that CODIE forwards fewer copies of data packets processed (CDPP) while achieving similar interest satisfaction rate (ISR), as compared with the naïve VNDN. In addition, we also found that CODIE also minimizes the overall interest satisfaction delay (ISD), respectively.

(1971). A Stochastic Model Of Bed Load Transport. Journal of Hydraulic Research: Vol. 9, No. 4, pp. 527-554.

The realization of the Internet of Things greatly depends on the information communication among physical terminal devices and informationalized platforms, such as smart sensors, embedded systems and intelligent networks. Playing an important role in information acquisition, sensors for stereo capture have gained extensive attention in various fields. In this paper, we concentrate on promoting such sensors in an intelligent system with self-assessment capability to deal with the distortion and impairment in long-distance shooting applications. The core design is the establishment of the objective evaluation criteria that can reliably predict shooting quality with different camera configurations. Two types of stereo capture systems-toed-in camera configuration and parallel camera configuration-are taken into consideration respectively. The experimental results show that the proposed evaluation criteria can effectively predict the visual perception of stereo capture quality for long-distance shooting.

With the rapid development of computer science, problems with digital products piracy and copyright dispute become more serious; therefore, it is an urgent task to find solutions for these problems. In this study, the authors’ develop a digital watermarking algorithm based on a fractal encoding method and the discrete cosine transform (DCT). The proposed method combines fractal encoding method and DCT method for double encryptions to improve traditional DCT method. The image is encoded by fractal encoding as the first encryption, and then encoded parameters are used in DCT method as the second encryption. First, the fractal encoding method is adopted to encode a private image with private scales. Encoding parameters are applied as digital watermarking. Then, digital watermarking is added to the original image to reversibly using DCT, which means the authors can extract the private image from the carrier image with private encoding scales. Finally, attacking experiments are carried out on the carrier image by using several attacking methods. Experimental results show that the presented method has higher performance characteristics such as robustness and peak signal to noise ratio than classical methods.

Ubiquity of mobile devices with rich sensory capabilities has given rise to the mobile crowd-sensing (MCS) concept, in which a central authority (the platform) and its participants (mobile users) work collaboratively to acquire sensory data over a wide geographic area. Recent research in MCS highlights the following facts: 1) a utility metric can be defined for both the platform and the users, quantifying the value received by either side; 2) incentivizing the users to participate is a non-trivial challenge; 3) correctness and truthfulness of the acquired data must be verified, because the users might provide incorrect or inaccurate data, whether due to malicious intent or malfunctioning devices; and 4) an intricate relationship exists among platform utility, user utility, user reputation, and data trustworthiness, suggesting a co-quantification of these inter-related metrics. In this paper, we study two existing approaches that quantify crowd-sensed data trustworthiness, based on statistical and vote-based user reputation scores. We introduce a new metric - collaborative reputation scores - to expand this definition. Our simulation results show that collaborative reputation scores can provide an effective alternative to the previously proposed metrics and are able to extend crowd sensing to applications that are driven by a centralized as well as decentralized control.

Energy consumption is one of the constraints in wireless sensor networks (WSNs). The routing protocols are the hot areas to address quality-of-service (QoS) related issues, viz., energy consumption, network lifetime, network scalability, and packet overhead. The key issue in WSN is that these networks suffer from the packet overhead, which is the root cause of more energy consumption and degrade the QoS in sensor networks. In WSN, there are several routing protocols, which are used to enhance the performance of the network. Out of those protocols, dynamic source routing (DSR) protocol is more suitable in terms of small energy density, but sometimes when the mode of a node changes from active to sleep, the efficiency decreases as the data packets need to wait at the initial point, where the packet has been sent and this increases the waiting time and end-to-end delay of the packets, which leads to increase in energy consumption. Our problem is to identify the dead nodes and to choose another suitable path so that the data transmission becomes smoother and less energy gets conserved. In order to resolve these issues, we propose directional transmission-based energy aware routing protocol named PDORP. The proposed protocol PDORP has the characteristics of both power efficient gathering sensor information system and DSR routing protocols. In addition, hybridization of genetic algorithm and bacterial foraging optimization is applied to proposed routing protocol to identify energy efficient optimal paths. The performance analysis, comparison through a hybridization approach of the proposed routing protocol, gives better result comprising less bit error rate, less delay, less energy consumption, and better throughput, which leads to better QoS and prolong the lifetime of the network. Moreover, the computation model is adopted to evaluate and compare the performance of the both routing protocols using soft computing techniques.

Smart city sensing calls for crowdsensing via mobile devices that are equipped with various built-in sensors. As incentivizing users to participate in distributed sensing is still an open research issue, the trustworthiness of crowdsensed data is expected to be a grand challenge if this cloud-inspired recruitment of sensing services is to be adopted. Recent research proposes reputation-based user recruitment models for crowdsensing; however, there is no standard way of identifying adversaries in smart city crowdsensing. This paper adopts previously proposed vote-based approaches, and presents a thorough performance study of vote-based trustworthiness with trusted entities that are basically a subset of the participating smartphone users. Those entities are called trustworthy anchors of the crowdsensing system. Thus, an anchor user is fully trustworthy and is fully capable of voting for the trustworthiness of other users, who participate in sensing of the same set of phenomena. Besides the anchors, the reputations of regular users are determined based on vote-based (distributed) reputation. We present a detailed performance study of the anchor-based trustworthiness assurance in smart city crowdsensing through simulations, and compare it with the purely vote-based trustworthiness approach without anchors, and a reputation-unaware crowdsensing approach, where user reputations are discarded. Through simulation findings, we aim at providing specifications regarding the impact of anchor and adversary populations on crowdsensing and user utilities under various environmental settings. We show that significant improvement can be achieved in terms of usefulness and trustworthiness of the crowdsensed data if the size of the anchor population is set properly.

Carbon monoxide (CO) burns or explodes at over-standard concentration. Hence, in this paper, a Wifi-based, real-time monitoring of a CO system is proposed for application in the construction industry, in which a sensor measuring node is designed by low-frequency modulation method to acquire CO concentration reliably, and a digital filtering method is adopted for noise filtering. According to the triangulation, the Wifi network is constructed to transmit information and determine the position of nodes. The measured data are displayed on a computer or smart phone by a graphical interface. The experiment shows that the monitoring system obtains excellent accuracy and stability in long-term continuous monitoring.