Xiaole Bai

Deploying wireless sensors to achieve both coverage and connectivity

It is well-known that placing disks in the triangular lattice pattern is optimal for achieving full coverage on a plane. With the emergence of wireless sensor networks, however, it is now no longer enough to consider coverage alone when deploying a wireless sensor network; connectivity must also be con-sidered. While moderate loss in coverage can be tolerated by applications of wireless sensor networks, loss in connectivity can be fatal. Moreover, since sensors are subject to unanticipated failures after deployment, it is not enough to have a wireless sensor network just connected, it should be k-connected (for k > 1 ). In this paper, we propose an optimal deployment pattern to achieve both full coverage and 2-connectivity, and prove its optimality for all values of rc/rs, where rc is the communication radius, and rs is the sensing radius. We also prove the optimality of a previously proposed deployment pattern for achieving both full coverage and 1-connectivity, when rc/rs < √3 .Finally, we compare the efficiency of some popular regular deployment patterns such as the square grid and triangular lattice, in terms of the number of sensors needed to provide coverage and connectivity.

Mobile phone based drunk driving detection

Drunk driving, or officially Driving Under the Influence (DUI) of alcohol, is a major cause of traffic accidents throughout the world. In this paper, we propose a highly efficient system aimed at early detection and alert of dangerous vehicle maneuvers typically related to drunk driving. The entire solution requires only a mobile phone placed in vehicle and with accelerometer and orientation sensor. A program installed on the mobile phone computes accelerations based on sensor readings, and compares them with typical drunk driving patterns extracted from real driving tests. Once any evidence of drunk driving is present, the mobile phone will automatically alert the driver or call the police for help well before accident actually happens. We implement the detection system on Android G1 phone and have it tested with different kinds of driving behaviors. The results show that the system achieves high accuracy and energy efficiency.

Complete optimal deployment patterns for full-coverage and k-connectivity (k≤6) wireless sensor networks

In this paper, we propose deployment patterns to achieve full coverage and three-connectivity, and full coverage and five-connectivity under different ratios of sensor communication range (denoted by Rc) over sensing range (denoted by Rs) for wireless sensor networks (WSNs). We also discover that there exists a hexagon-based universally elemental pattern which can generate all known optimal patterns. The previously proposed Voronoi-based approach can not be applied to prove the optimality of the new patterns due to their special features. We propose a new deployment-polygon based methodology, and prove their optimality among regular patterns when Rc/Rs ≥ 1. We conjecture that our patterns are globally optimal to achieve full coverage and three-connectivity, and full coverage and five-connectivity, under all ranges of Rc/Rs. With these new results, the set of optimal patterns to achieve full coverage and k-connectivity (k≤6) is complete, for the first time.

PerFallD: A pervasive fall detection system using mobile phones

Falls are a major health risk that diminish the quality of life among elderly people. With the elderly population surging, especially with aging “baby boomers”, fall detection becomes increasingly important. However, existing commercial products and academic solutions struggle to achieve pervasive fall detection. In this paper, we propose utilizing mobile phones as a platform for pervasive fall detection system development. To our knowledge, we are the first to do so. We design a detection algorithm based on mobile phone platforms. We propose PerFallD, a pervasive fall detection system implemented on mobile phones. We implement a prototype system on the Android G1 phone and conduct experiments to evaluate our system. In particular, we compare PerFallDs performance with that of existing work and a commercial product. Experimental results show that PerFallD achieves strong detection performance and power efficiency.

Mobile phone-based pervasive fall detection

Falls are a major health risk that diminishes the quality of life among the elderly people. The importance of fall detection increases as the elderly population surges, especially with aging “baby boomers”. However, existing commercial products and academic solutions all fall short of pervasive fall detection. In this paper, we propose utilizing mobile phones as a platform for developing pervasive fall detection system. To our knowledge, we are the first to do so. We propose PerFallD, a pervasive fall detection system tailored for mobile phones. We design two different detection algorithms based on the mobile phone platforms for scenarios with and without simple accessories. We implement a prototype system on the Android G1 phone and conduct extensive experiments to evaluate our system. In particular, we compare PerFallD’s performance with that of existing work and a commercial product. The experimental results show that PerFallD achieves superior detection performance and power efficiency.

Deploying Wireless Sensor Networks under Limited Mobility Constraints

In this paper, we study the issue of sensor network deployment using limited mobility sensors. By limited mobility, we mean that the maximum distance that sensors are capable of moving to is limited. Given an initial deployment of limited mobility sensors in a field clustered into multiple regions, our deployment problem is to determine a movement plan for the sensors to minimize the variance in number of sensors among the regions and simultaneously minimize the sensor movements. Our methodology to solve this problem is to transfer the nonlinear variance/movement minimization problem into a linear optimization problem through appropriate weight assignments to regions. In this methodology, the regions are assigned weights corresponding to the number of sensors needed. During sensor movements across regions, larger weight regions are given higher priority compared to smaller weight regions, while simultaneously ensuring a minimum number of sensor movements. Following the above methodology, we propose a set of algorithms to our deployment problem. Our first algorithm is the optimal maximum flow-based (OMF) centralized algorithm. Here, the optimal movement plan for sensors is obtained based on determining the minimum cost maximum weighted flow to the regions in the network. We then propose the simple peak-pit-based distributed (SPP) algorithm that uses local requests and responses for sensor movements. Using extensive simulations, we demonstrate the effectiveness of our algorithms from the perspective of variance minimization, number of sensor movements, and messaging overhead under different initial deployment scenarios.

Mobility Limited Flip-Based Sensor Networks Deployment

An important phase of sensor networks operation is deployment of sensors in the field of interest. Critical goals during sensor networks deployment include coverage, connectivity, load balancing, etc. A class of work has recently appeared, where mobility in sensors is leveraged to meet deployment objectives. In this paper, we study deployment of sensor networks using mobile sensors. The distinguishing feature of our work is that the sensors in our model have limited mobilities. More specifically, the mobility in the sensors we consider is restricted to a flip, where the distance of the flip is bounded. We call such sensors as flip-based sensors. Given an initial deployment of flip-based sensors in a field, our problem is to determine a movement plan for the sensors in order to maximize the sensor network coverage and minimize the number of flips. We propose a minimum-cost maximum-flow-based solution to this problem. We prove that our solution optimizes both the coverage and the number of flips. We also study the sensitivity of coverage and the number of flips to flip distance under different initial deployment distributions of sensors. We observe that increased flip distance achieves better coverage and reduces the number of flips required per unit increase in coverage. However, such improvements are constrained by initial deployment distributions of sensors due to the limitations on sensor mobility

Optimal Deployment Patterns for Full Coverage and

In this paper, we study deployment patterns to achieve full coverage and <i>k</i> -connectivity <i>(k</i> ≤ 6) under different ratios of the sensor communication range (denoted by <i>R</i>_c) to the sensing range (denoted by <i>R</i>_s) for homogeneous wireless sensor networks (WSNs). In particular, we propose new patterns for 3- and 5-connectivity. We also discover that there exists a hexagon-based universally elemental pattern that can generate all known optimal patterns. The previously proposed Voronoi-based approach cannot be applied to prove the optimality of the new patterns due to their special features. We propose a new deployment-polygon-based methodology. We prove the optimality of deployment patterns to achieve 3-connectivity, 4-connectivity, and 5-connectivity for certain ranges of <i>R</i>_c/<i>R</i>_s, respectively, and prove the optimality of deployment patterns to achieve 6-connectivity under all ranges of <i>R</i>_c/<i>R</i>_s.

k

In this paper, we study the problem of constructing full-coverage three dimensional networks with multiple connectivity. We design a set of patterns for full coverage and two representative connectivity requirements, i.e. 14- and 6-connectivity. We prove their optimality under any ratio of the communication range over the sensing range among regular lattice deployment patterns. We also conduct a study on the proposed patterns under practical settings. To our knowledge, our work is the first one that provides deployment patterns with proven optimality that achieve both coverage and connectivity in three dimensional networks.

-Connectivity

Low-connectivity and full-coverage three dimensional Wireless Sensor Networks (WSNs) have many real-world applications. By low connectivity, we mean there are at least <i>k</i> disjoint paths between any two sensor nodes in a WSN, where <i>k</i> ≤ 4. In this paper, we design a set of patterns for these networks. In particular, we design and prove the optimality of <i>1</i>- and <i>2</i>-connectivity patterns under any value of the ratio of communication range <i>r_c</i> over sensing range <i>r_s</i>, among regular lattice deployment patterns. We further propose a set of patterns to achieve <i>3</i>- and <i>4</i>-connectivity patterns and investigate the evolutions among all the proposed low-connectivity patterns. Finally, we study the proposed patterns under several practical settings.