https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

Position information of individual nodes is useful in implementing functions such as routing and querying in ad-hoc networks. Deriving position information by using the capability of the nodes to measure time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA) and signal strength have been used to localize nodes relative to a frame of reference. The nodes in an ad-hoc network can have multiple capabilities and exploiting one or more of the capabilities can improve the quality of positioning. In this paper, we show how AOA capability of the nodes can be used to derive position information. We propose a method for all nodes to determine their orientation and position in an ad-hoc network where only a fraction of the nodes have positioning capabilities, under the assumption that each node has the AOA capability.

/pdf/ad-hoc-positioning-system-aps-using-aoa-a9nzx3n736.pdf

Ad hoc positioning system (APS) using AOA

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」

An emerging category of devices at the edge of the Internet are consumer-centric mobile sensing and computing devices, such as smartphones, music players, and in-vehicle sensors. These devices will fuel the evolution of the Internet of Things as they feed sensor data to the Internet at a societal scale. In this article, we examine a category of applications that we term mobile crowdsensing, where individuals with sensing and computing devices collectively share data and extract information to measure and map phenomena of common interest. We present a brief overview of existing mobile crowdsensing applications, explain their unique characteristics, illustrate various research challenges, and discuss possible solutions. Finally, we argue the need for a unified architecture and envision the requirements it must satisfy.

Mobile crowdsensing: current state and future challenges

The invention provides a method and system for creating an innovative file system that separates its directory presentation from its data store. The method and system include processing, division, distribution, managing, synchronizing, and reassembling of file system objects that does not delay the presentation of the content to the user, but also uses a reduced amount of storage space. The invention includes the ability to manage and control the integrity of the files distributed across the network, and the ability to serve and reconstruct files in real time using a Virtual File Control System.

Method and system for managing distributed content and related metadata

CarTel is a mobile sensor computing system designed to collect, process, deliver, and visualize data from sensors located on mobile units such as automobiles. A CarTel node is a mobile embedded computer coupled to a set of sensors. Each node gathers and processes sensor readings locally before delivering them to a central portal, where the data is stored in a database for further analysis and visualization. In the automotive context, a variety of on-board and external sensors collect data as users drive.CarTel provides a simple query-oriented programming interface, handles large amounts of heterogeneous data from sensors, and handles intermittent and variable network connectivity. CarTel nodes rely primarily on opportunistic wireless (e.g., Wi-Fi, Bluetooth) connectivity to the Internet, or to "data mules" such as other CarTel nodes, mobile phone flash memories, or USB keys-to communicate with the portal. CarTel applications run on the portal, using a delay-tolerant continuous query processor, ICEDB, to specify how the mobile nodes should summarize, filter, and dynamically prioritize data. The portal and the mobile nodes use a delay-tolerant network stack, CafNet, to communicat.CarTel has been deployed on six cars, running on a small scale in Boston and Seattle for over a year. It has been used to analyze commute times, analyze metropolitan Wi-Fi deployments, and for automotive diagnostics.

/pdf/cartel-a-distributed-mobile-sensor-computing-system-3495ux11p8.pdf

CarTel: a distributed mobile sensor computing system

The ability to determine the orientation of a device is of fundamental importance in context aware and location-dependent mobile computing. By analogy to a traditional compass, knowledge of orientation through the Cricket compass attached to a mobile device enhances various applications, including efficient way-finding and navigation, directional service discovery, and “augmented-reality” displays. Our compass infrastructure enhances the spatial inference capability of the Cric ketindoor location system [20], and enables new pervasive computing applications.Using fixed active beacons and carefully placed passive ultrasonic sensors, we show how to estimate the orientation of a mobile device to within a few degrees, using precise, sub-centimeter differences in distance estimates from a beacon to each sensor on the compass. Then, given a set of fixed, active position beacons whose locations are known, we describe an algorithm that combines several carrier arrival times to produce a robust estimate of the rigid orientation of the mobile compass.The hardware of the Cricket compass is small enough to be integrated with a handheld mobile device. It includes five passive ultrasonic receivers, each 0.8cm in diameter, arrayed in a “V” shape a few centimeters across. Cricket beacons deployed throughout a building broadcast coupled 418MHz RF packet data and a 40KHz ultrasound carrier, which are processed by the compass software to obtain differential distance and position estimates. Our experimental results show that our prototype implementation can determine compass orientation to within 3 degrees when the true angle lies between ±30 degrees, and to within 5 degrees when the true angle lies between ±40 degrees, with respect to a fixed beacon.

http://www.ai.mit.edu/projects/oxygen/oxygen-book2001/Section2-Network21/N21-09.pdf

The cricket compass for context-aware mobile applications

The impressive penetration of 802.11-based wireless networks in many metropolitan areas around the world offers, for the first time, the opportunity of a "grassroots" wireless Internet service provided by users who "open up" their 802.11 (Wi-Fi) access points in a controlled manner to mobile clients. While there are many business, legal, and policy issues to be ironed out for this vision to become reality, we are concerned in this paper with an important technical question surrounding such a system: can such an unplanned network service provide reasonable performance to network clients moving in cars at vehicular speeds.To answer this question, we present the results of a measurement study carried out over 290 "drive hours" over a few cars under typical driving conditions, in and around the Boston metropolitan area (some of our data also comes from a car in Seattle). With a simple caching optimization to speed-up IP address acquisition, we find that for our driving patterns the median duration of link-layer connectivity at vehicular speeds is 13 seconds, the median connection upload bandwidth is 30 KBytes/s, and that the mean duration between successful associations to APs is 75 seconds. We also find that connections are equally probable across a range of urban speeds (up to 60 km/hour in our measurements). Our end-to-end TCP upload experiments had a median throughput of about 30 KBytes/s, which is consistent with typical uplink speeds of home broadband links in the US. The median TCP connection is capable of uploading about 216 KBytes of data.Our high-level conclusion is that grassroots Wi-Fi networks are viable for a variety of applications, particularly ones that can tolerate intermittent connectivity. We discuss how our measurement results can improve transport protocols in such networks.

/pdf/a-measurement-study-of-vehicular-internet-access-using-in-3jbmhut8qo.pdf

A measurement study of vehicular internet access using in situ Wi-Fi networks

This paper describes the Multi-Radio Diversity (MRD) wireless system, which uses path diversity to improve loss resilience in wireless local area networks WLANs). MRD coordinates wireless receptions among multiple radios to improve loss resilience in the face of path-dependent frame corruption over the radio. MRD incorporates two techniques to recover from bit errors and lower the loss rates observed by higher layers, without consuming much extra bandwidth. The first technique is frame combining in which multiple, possibly erroneous, copies of a given frame are combined together in an attempt to recover the frame without retransmission. The second technique is a low-overhead retransmission scheme called request-for-acknowledgment (RFA), which operates above the link layer and below the network layer to attempt to recover from frame combining failures. We present an analysis that determines how the parameters for these algorithms should be chosen.We have designed and implemented MRD as a fully functional WLAN infrastructure based on 802.11a. In our testbed, we measured throughput gains up to 2.3 - over single radio communication schemes employing 802.11's autorate adaptation scheme.

/pdf/improving-loss-resilience-with-multi-radio-diversity-in-3si899uy7m.pdf

Improving loss resilience with multi-radio diversity in wireless networks

Carrier sense is a fundamental part of most wireless networking stacks in wireless local area- and sensor networks. As increasing numbers of users and more demanding applications push wireless networks to their capacity limits, the efficacy of the carrier sense mechanism becomes a key factor in determining wireless network capacity.We describe how carrier sense works, point out its limitations, and advocate an experimental approach to studying carrier sense. We describe our current testbed setup, and then present preliminary experimental results from both a 60-node sensor network deployment and a small-scale 802.11 deployment. Our preliminary results evaluate how well carrier sense works and expose its limitations.

/pdf/understanding-the-real-world-performance-of-carrier-sense-54sp31ca01.pdf

Allen Miu

Papers

CarTel: a distributed mobile sensor computing system

The cricket compass for context-aware mobile applications

A measurement study of vehicular internet access using in situ Wi-Fi networks

Improving loss resilience with multi-radio diversity in wireless networks

Understanding the real-world performance of carrier sense