http://www.eecs.ucf.edu/~dcm/Teaching/COT4810-Spring2011/Literature/SensorNetworksSurvey.pdf

Wireless sensor networks: a survey

http://www.csun.edu/~andrzej/COMP529-S05/papers/Mesh%20Networks%20Survey.pdf

Wireless mesh networks: a survey

In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.

/pdf/energy-conservation-in-wireless-sensor-networks-a-survey-1bl7d2obnm.pdf

Energy conservation in wireless sensor networks: A survey

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

Energy harvesting generators are attractive as inexhaustible replacements for batteries in low-power wireless electronic devices and have received increasing research interest in recent years. Ambient motion is one of the main sources of energy for harvesting, and a wide range of motion-powered energy harvesters have been proposed or demonstrated, particularly at the microscale. This paper reviews the principles and state-of-art in motion-driven miniature energy harvesters and discusses trends, suitable applications, and possible future developments.

/pdf/energy-harvesting-from-human-and-machine-motion-for-wireless-3lsf4oudvo.pdf

Energy Harvesting From Human and Machine Motion for Wireless Electronic Devices

The AERPAW project is an ambitious project, funded by the PAWR program of the US NSF, to create a remote accessible research platform for a research facility with some distinct features that makes its operational model unique, and possibly non-obvious to computing researchers more familiar with computing and networking testbeds. AERPAW is primarily a platform of physical resources - specifically the RF environment, and the airspace. Experimenters can explore them through radio transceivers and Unmanned Aerial Vehicles, both under the Experimenter's programmatic control. The entire workflow of the remote Experimenter is through the mediation of virtual computing environments, but AERPAW Operators have to ensure that the Experimenter's programming controls the physical resources precisely as intended by the Experimenter, while also satisfying safety and compliance goals. To this end, the AERPAW platform adopts multiple distinct, and quite different, execution environments. This in turn gives something of a different color to the well-understood problems of resource allocation, scheduling, and access control. In this paper, we articulate lessons we have learned, and the challenges and considerations we have come to appreciate, in designing a resource control framework for such a physico-cyber facility.

The AERPAW Control Framework - Considerations for Resource Control and Orchestration for a Computing-supported Physical Research Platform

In this paper, we report experimental results in collecting and processing 5G NR I/Q samples in the 3.7 GHz C-band by using a software-defined radio (SDR)-mounted helikite. We use MATLAB's 5G toolbox to post-process the collected data, to obtain the synchronization signal block (SSB) from the I/Q samples, and then go through the cell search, synchronization procedures, and reference signal received power (RSRP) and reference signal received quality (RSRQ) calculation. We plot these performance metrics for various physical cell identities as a function of the helikite's altitude. Furthermore, building on our experience with the collected and post-processed data, we discuss potential vulnerabilities and challenges for the 5G NR systems to surveillance, spectrum coexistence with existing services, jammina attacks, and post-quantum era attacks.

SDR-Based 5G NR C-Band I/Q Monitoring and Surveillance in Urban Area Using a Helikite

Recently, unmanned aerial vehicles (UAVs) have been receiving significant attention due to their wide range of potential application areas. To support UAV use cases with beyond visual line of sight (BVLOS) and autonomous flights, cellular networks can serve as ground connectivity points, and they can provide remote control and payload communication for UAV links. However, there are limited data sets to study the coverage of cellular technologies for UAV flights at different altitudes and develop machine learning (ML) techniques for improving UAV communication and navigation. In this article, we present raw LTE I/Q sample data sets from physical field experiments in the Lake Wheeler farm area of the NSF AERPAW experimentation platform. We fly a UAV that carries a software-defined radio (SDR) at altitudes ranging from 30~m to 110~m and collect raw I/Q samples from an SDR-based LTE base station on the ground operating at 3.51 GHz. We adopt a standard metadata format for reproducing the results from the collected data sets. The post-processing of raw I/Q samples using MATLAB's 4G LTE toolbox is described and various representative results are provided. In the end, we discuss the possible ways that our provided data set, post-processing sample code, and sample experiment code for collecting I/Q measurements and vehicle control can be used by other ML researchers in the future.

LTE I/Q Data Set for UAV Propagation Modeling, Communication, and Navigation Research

The deployment at scale of Unmanned Aerial Systems have become increasingly imminent in the last few years, even as concerns regarding the dependability and predictability of their command and control channels remain fully to be addressed. The intersection of ground-to-air wireless communications, aerial networking, and trajectory control has become a research area of sharp interest. The validation of such research, beyond the theoretical/simulation stage, requires a facility that is both realistic, and admits of potentially risky or unsafe operation, while in the end guaranteeing personnel and equipment safety. The AERPAW project is an ambitious project, funded by the PAWR program of the US NSF, to create a remote accessible research platform for a research facility to enable such validation. To enable remote usage of such a testbed, yet provide the researcher with complete experimental freedom, the AERPAW facility includes a combination of architectural mechanisms that balance freedom of experimentation with regulatory compliance and safety. In this paper, we articulate the challenges and considerations of designing such mechanisms, and present the architectural features of AERPAW that attempt to realize these lofty goals.

Automating Operator Oversight in an Autonomous, Regulated, Safety-Critical Research Facility

Extensive use of unmanned aerial vehicles (UAVs) is expected to raise privacy and security concerns among individuals and communities. In this context, the detection and localization of UAVs will be critical for maintaining safe and secure airspace in the future. In this work, Keysight N6854A radio frequency (RF) sensors are used to detect and locate a UAV by passively monitoring the signals emitted from the UAV. First, the Keysight sensor detects the UAV by comparing the received RF signature with various other UAVs' RF signatures in the Keysight database using an envelope detection algorithm. Afterward, time difference of arrival (TDoA) based localization is performed by a central controller using the sensor data, and the drone is localized with some error. To mitigate the localization error, implementation of an extended Kalman filter~(EKF) is proposed in this study. The performance of the proposed approach is evaluated on a realistic experimental dataset. EKF requires basic assumptions on the type of motion throughout the trajectory, i.e., the movement of the object is assumed to fit some motion model~(MM) such as constant velocity (CV), constant acceleration (CA), and constant turn (CT). In the experiments, an arbitrary trajectory is followed, therefore it is not feasible to fit the whole trajectory into a single MM. Consequently, the trajectory is segmented into sub-parts and a different MM is assumed in each segment while building the EKF model. Simulation results demonstrate an improvement in error statistics when EKF is used if the MM assumption aligns with the real motion.

Mihail L. Sichitiu

Papers

The AERPAW Control Framework - Considerations for Resource Control and Orchestration for a Computing-supported Physical Research Platform

SDR-Based 5G NR C-Band I/Q Monitoring and Surveillance in Urban Area Using a Helikite

LTE I/Q Data Set for UAV Propagation Modeling, Communication, and Navigation Research

Automating Operator Oversight in an Autonomous, Regulated, Safety-Critical Research Facility

Experimental Study of Outdoor UAV Localization and Tracking using Passive RF Sensing