Canfeng Chen

Bio: Canfeng Chen is an academic researcher from Nokia. The author has contributed to research in topics: Wireless sensor network & Key distribution in wireless sensor networks. The author has an hindex of 22, co-authored 68 publications receiving 1548 citations. Previous affiliations of Canfeng Chen include Beijing University of Posts and Telecommunications.

Accelerometer Based Transportation Mode Recognition on Mobile Phones

Abstract: Recognizing the transportation modes of people’s daily living is an important research issue in the pervasive computing. Prior research in this field mainly uses Global Positioning System (GPS), Global System for Mobile Communications (GSM) or their combination with accelerometer to recognize transportation modes, such as walking, driving, etc. In this paper, we will introduce transportation mode recognition on mobile phones only using embedded accelerometer. In order to deal with uncertainty of position and orientation of mobile phone, acceleration synthesization based method and acceleration decomposition based method are introduced. Performance comparison indicates that acceleration synthesization based method outperforms acceleration decomposition based method. We will discuss the factors affect the recognition accuracy of acceleration decomposition based method and present potential improvements.

HUMS: An Autonomous Moving Strategy for Mobile Sinks in Data-Gathering Sensor Networks

Abstract: Sink mobility has attracted much research interest in recent years because it can improve network performance such as energy efficiency and throughput. An energy-unconscious moving strategy is potentially harmful to the balance of the energy consumption among sensor nodes so as to aggravate the hotspot problem of sensor networks. In this paper, we propose an autonomous moving strategy for the mobile sinks in data-gathering applications. In our solution, a mobile sink approaches the nodes with high residual energy to force them to forward data for other nodes and tries to avoid passing by the nodes with low energy. We performed simulation experiments to compare our solution with other three data-gathering schemes. The simulation results show that our strategy cannot only extend network lifetime notably but also provides scalability and topology adaptability.

Modeling Neighbor Discovery in Bluetooth Low Energy Networks

Abstract: In this letter, an analytical model is proposed for 3-channel-based neighbor discovery in Bluetooth Low Energy (BLE) networks. The model can be used to determine some important performance metrics, such as average latency or average energy consumption during the course of discovering neighbors. Since intermittent connections are frequently encountered in practical scenarios of BLE, the modeling results can provide a beneficial guidance to customize advertising or scanning behavior towards user desired performance.

Designing Energy-Efficient Wireless Sensor Networks with Mobile Sinks

Abstract: Mobile enable Wireless Sensor Network (mWSN) has been proposed to realize large-scale information gathering via networking wireless sensors and mobile sinks. Some fundamental design parameters in mWSN have been investigated in this article, such as cluster size, sink velocity, transmission range, and packet length. Our contributions include: 1) We propose to use multihop forwarding to form a cluster around the expected position of a mobile sink, in order to guarantee packet delay and minimize energy consumption. 2) Sink velocity should be carefully chosen, in order to make a compromise between sink-sensor meeting delay and message delivery delay. 3) Large transmission range and short packet length are both of benefit to lower the outage probability of packet transmission. Extensive simulations have been designed to evaluate the performance of mWSN in terms of packet delay, energy consumption and outage probability.

Energy Analysis of Device Discovery for Bluetooth Low Energy

Abstract: Bluetooth Low Energy (BLE) is drawing more and more attention due to its recent appearance in consumer electronic products. As a low-power wireless solution, BLE provides attractive energy performance that makes it particularly suitable for portable, battery-driven electronic devices. Although there are some prior arts focusing on BLE energy performance, it still lacks a thorough study on the important aspect of device discovery. Such energy cost, introduced by intermittent scanning or connection setup, could seriously affect the battery endurance ability of the devices. In this paper, we present quantitative analysis on the neighbor discovery energy for BLE. The modeling results that built upon measurement of CC2541 Mini-Development Kit have been validated quite accurate via extensive experiments. In addition, several interesting conclusions are found while investigating the achieved energy model, which may provide precious guidelines to the design of energy-efficient applications for BLE.

Context Aware Computing for The Internet of Things: A Survey

Abstract: As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.

Privacy in the digital age: a review of information privacy research in information systems

Abstract: Information privacy refers to the desire of individuals to control or have some influence over data about themselves. Advances in information technology have raised concerns about information privacy and its impacts, and have motivated Information Systems researchers to explore information privacy issues, including technical solutions to address these concerns. In this paper, we inform researchers about the current state of information privacy research in IS through a critical analysis of the IS literature that considers information privacy as a key construct. The review of the literature reveals that information privacy is a multilevel concept, but rarely studied as such. We also find that information privacy research has been heavily reliant on studentbased and USA-centric samples, which results in findings of limited generalizability. Information privacy research focuses on explaining and predicting theoretical contributions, with few studies in journal articles focusing on design and action contributions. We recommend that future research should consider different levels of analysis as well as multilevel effects of information privacy. We illustrate this with a multilevel framework for information privacy concerns. We call for research on information privacy to use a broader diversity of sampling populations, and for more design and action information privacy research to be published in journal articles that can result in IT artifacts for protection or control of information privacy.

Accelerometer-based transportation mode detection on smartphones

Abstract: We present novel accelerometer-based techniques for accurate and fine-grained detection of transportation modes on smartphones. The primary contributions of our work are an improved algorithm for estimating the gravity component of accelerometer measurements, a novel set of accelerometer features that are able to capture key characteristics of vehicular movement patterns, and a hierarchical decomposition of the detection task. We evaluate our approach using over 150 hours of transportation data, which has been collected from 4 different countries and 16 individuals. Results of the evaluation demonstrate that our approach is able to improve transportation mode detection by over 20% compared to current accelerometer-based systems, while at the same time improving generalization and robustness of the detection. The main performance improvements are obtained for motorised transportation modalities, which currently represent the main challenge for smartphone-based transportation mode detection.

Incentives for Mobile Crowd Sensing: A Survey

Abstract: Recent years have witnessed the fast proliferation of mobile devices (e.g., smartphones and wearable devices) in people's lives. In addition, these devices possess powerful computation and communication capabilities and are equipped with various built-in functional sensors. The large quantity and advanced functionalities of mobile devices have created a new interface between human beings and environments. Many mobile crowd sensing applications have thus been designed which recruit normal users to contribute their resources for sensing tasks. To guarantee good performance of such applications, it's essential to recruit sufficient participants. Thus, how to effectively and efficiently motivate normal users draws growing attention in the research community. This paper surveys diverse strategies that are proposed in the literature to provide incentives for stimulating users to participate in mobile crowd sensing applications. The incentives are divided into three categories: entertainment, service, and money. Entertainment means that sensing tasks are turned into playable games to attract participants. Incentives of service exchanging are inspired by the principle of mutual benefits. Monetary incentives give participants payments for their contributions. We describe literature works of each type comprehensively and summarize them in a compact form. Further challenges and promising future directions concerning incentive mechanism design are also discussed.

Convergence of MANET and WSN in IoT Urban Scenarios

Abstract: Ubiquitous smart environments, equipped with low-cost and easy-deployable wireless sensor networks (WSNs) and widespread mobile ad hoc networks (MANETs), are opening brand new opportunities in wide-scale urban monitoring. Indeed, MANET and WSN convergence paves the way for the development of brand new Internet of Things (IoT) communication platforms with a high potential for a wide range of applications in different domains. Urban data collection, i.e., the harvesting of monitoring data sensed by a large number of collaborating sensors, is a challenging task because of many open technical issues, from typical WSN limitations (bandwidth, energy, delivery time, etc.) to the lack of widespread WSN data collection standards, needed for practical deployment in existing and upcoming IoT scenarios. In particular, effective collection is crucial for classes of smart city services that require a timely delivery of urgent data such as environmental monitoring, homeland security, and city surveillance. After surveying the existing WSN interoperability efforts for urban sensing, this paper proposes an original solution to integrate and opportunistically exploit MANET overlays, impromptu, and collaboratively formed over WSNs, to boost urban data harvesting in IoT. Overlays are used to dynamically differentiate and fasten the delivery of urgent sensed data over low-latency MANET paths by integrating with latest emergent standards/specifications for WSN data collection. The reported experimental results show the feasibility and effectiveness (e.g., limited coordination overhead) of the proposed solution.