Detecting the Direction of Motion in a Binary Sensor Network

We examine the problem of detecting the direction of motion in a binary sensor network; in such a network each sensor’s value is supplied reliably in a single bit of information: whether the moving object is approaching towards or moving away from the sensor. We demonstrate that the geometric properties of the network itself can be exploited for the detection of movement direction, from a single instance of sensor reading only. Moreover the estimation is performed in a distributed processing fashion, with only a minimal data collection at situation-dependent leading sensors and features a low computational burden on each sensor. In addition, different detection instances drain the resources of different groups of sensors, of a small size compared to the size of the whole network. Our experiments demonstrate high accuracy that increases with sensor density and/or sensing range, while the responsiveness of the detection model is practically instantaneous.published_or_final_versio

Connecting Soil to the Cloud: A Wireless Underground Sensor Network Testbed

In this demo, a novel underground communication system and an online underground sensor network testbed is demonstrated. The underground communication system, developed in the Cyber-physical Networking (CPN) Laboratory at the University of Nebraska-Lincoln, includes an underground antenna that is tailored to mitigate the adverse effects of soil on underground communication. An online connection is established with the CPN underground sensor network testbed that is located at Clay Center, Nebraska. The underground sensor network testbed consists of a network of underground communication systems equipped with soil moisture sensors and a mobile data harvesting unit equipped with cellular communication capabilities. Real-time soil moisture data delivery from Nebraska to Korea is demonstrated

Connecting Soil to the Cloud: A Wireless Underground Sensor Network Testbed

In this demo, a novel underground communication system and an online underground sensor network testbed is demonstrated. The underground communication system, developed in the Cyber-physical Networking (CPN) Laboratory at the University of Nebraska-Lincoln, includes an underground antenna that is tailored to mitigate the adverse effects of soil on underground communication. An online connection is established with the CPN underground sensor network testbed that is located at Clay Center, Nebraska. The underground sensor network testbed consists of a network of underground communication systems equipped with soil moisture sensors and a mobile data harvesting unit equipped with cellular communication capabilities. Real-time soil moisture data delivery from Nebraska to Korea is demonstrated

E-SAP: Efficient-Strong Authentication Protocol for Healthcare Applications Using Wireless Medical Sensor Networks

A wireless medical sensor network (WMSN) can sense humans’ physiological signs without sacrificing patient comfort and transmit patient vital signs to health professionals’ hand-held devices. The patient physiological data are highly sensitive and WMSNs are extremely vulnerable to many attacks. Therefore, it must be ensured that patients’ medical signs are not exposed to unauthorized users. Consequently, strong user authentication is the main concern for the success and large scale deployment of WMSNs. In this regard, this paper presents an efficient, strong authentication protocol, named E-SAP, for healthcare application using WMSNs. The proposed E-SAP includes: (1) a two-factor (i.e., password and smartcard) professional authentication; (2) mutual authentication between the professional and the medical sensor; (3) symmetric encryption/decryption for providing message confidentiality; (4) establishment of a secure session key at the end of authentication; and (5) professionals can change their password. Further, the proposed protocol requires three message exchanges between the professional, medical sensor node and gateway node, and achieves efficiency (i.e., low computation and communication cost). Through the formal analysis, security analysis and performance analysis, we demonstrate that E-SAP is more secure against many practical attacks, and allows a tradeoff between the security and the performance cost for healthcare application using WMSNs

MORA: an Energy-Aware Slack Reclamation Scheme for Scheduling Sporadic Real-Time Tasks upon Multiprocessor Platforms

In this paper, we address the global and preemptive energy-aware scheduling problem of sporadic constrained-deadline tasks on DVFS-identical multiprocessor platforms. We propose an online slack reclamation scheme which profits from the discrepancy between the worst- and actual-case execution time of the tasks by slowing down the speed of the processors in order to save energy. Our algorithm called MORA takes into account the application-specific consumption profile of the tasks. We demonstrate that MORA does not jeopardize the system schedulability and we show by performing simulations that it can save up to 32% of energy (in average) compared to execution without using any energy-aware algorithm.Comment: 11 page

Cryptanalysis of and Improvement on Biometric-based User Authentication Scheme for C/S System

Password-based authentication schemes are convenient, but vulnerable to simple dictionary attacks. Cryptographic secret keys are safe, but difficult to memorize. More recently, biometric information has been used for authentication schemes. Das proposed a biometric-based authentication scheme, but it has various vulnerabilities. Jiping et al. improved Das’s scheme, but some vulnerabilities remain. In this paper, we analyze the cryptanalysis of Jiping et al.’s authentication scheme and propose the security enhanced biometric-based user authentication scheme for the C/S System

Smart Learning Environment: Paradigm Shift for Online Learning

Online learning has always been influenced by advanced technology. The role of online learning is expected not only for delivering contents to massive learners anywhere and anytime but also for promoting successful learning for the learners. Consequently, this emerged role has introduced the concept of smart learning environment. More specifically, smart learning environment is developed to promote personalized learning for learners. Personalized learning focuses on individual learner and provides appropriate feedback individually. Currently, the advances of modern technologies and intelligence data analytics have brought the idea of smart learning environment into realization. Machine learning techniques are generally applied to analyze real-time dynamic learner behavior and provide the appropriate response to the right learner. In this chapter, the evolution of online learning environment from different points of technological overviews is first introduced. Next, the concepts of personalized learning and smart learning environment are explained. Then, the essential components of smart learning environment are presented including learner classification and intervention feedback. Learner classification is to understand different learners. Intervention feedback is to provide an individual response appropriately. Additionally, some machine learning techniques widely used in smart learning environment in order to perform smart classification and response are briefly explained

A Novel Design of an Automatic Lighting Control System for a Wireless Sensor Network with Increased Sensor Lifetime and Reduced Sensor Numbers

Wireless sensor networks (WSN) are currently being applied to energy conservation applications such as light control. We propose a design for such a system called a Lighting Automatic Control System (LACS). The LACS system contains a centralized or distributed architecture determined by application requirements and space usage. The system optimizes the calculations and communications for lighting intensity, incorporates user illumination requirements according to their activities and performs adjustments based on external lighting effects in external sensor and external sensor-less architectures. Methods are proposed for reducing the number of sensors required and increasing the lifetime of those used, for considerably reduced energy consumption. Additionally we suggest methods for improving uniformity of illuminance distribution on a workplane’s surface, which improves user satisfaction. Finally simulation results are presented to verify the effectiveness of our design

Harvesting-aware energy management for environmental monitoring WSN

Wireless sensor networks can be used to collect data in remote locations, especially when energy harvesting is used to extend the lifetime of individual nodes. However, in order to use the collected energy most effectively, its consumption must be managed. In this work, forecasts of diurnal solar energies were made based on measurements of atmospheric pressure. These forecasts were used as part of an adaptive duty cycling scheme for node level energy management. This management was realized with a fuzzy logic controller that has been tuned using differential evolution. Controllers were created using one and two days of energy forecasts, then simulated in software. These controllers outperformed a human-created reference controller by taking more measurements while using less reserve energy during the simulated period. The energy forecasts were comparable to other available methods, while the method of tuning the fuzzy controller improved overall node performance. The combination of the two is a promising method of energy management.Web of Science105art. no. 60

Adaptive Square-Shaped Trajectory-Based Service Location Protocol in Wireless Sensor Networks

In this paper we propose an adaptive square-shaped trajectory (ASST)-based service location method to ensure load scalability in wireless sensor networks. This first establishes a square-shaped trajectory over the nodes that surround a target point computed by the hash function and any user can access it, using the hash. Both the width and the size of the trajectory are dynamically adjustable, depending on the number of queries made to the service information on the trajectory. The number of sensor nodes on the trajectory varies in proportion to the changing trajectory shape, allowing high loads to be distributed around the hot spot area