The growing importance of operations such as identification, location sensing, and object tracking has led to increasing interests in contactless Radio Frequency Identification (RFID) systems. Enjoying the low cost of RFID tags, modern RFID systems tend to be deployed for large-scale mobile objects. Both the theoretical and experimental results suggest that when tags are in large numbers, most existing collision arbitration protocols do not satisfy the scalability and time-efficiency requirements of many applications. To address this problem, we propose Adaptively Splitting-based Arbitration Protocol (ASAP), a scheme that provides efficient RFID identification for both small and large deployment of RFID tags, in terms of time and energy cost. Theoretical analysis and simulation evaluation show that the performance of ASAP is better than most existing collision-arbitration solutions and the time efficiency is close to the theoretically optimal values.

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC) sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudonoise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip level. We find that there are notable error patterns corresponding to different cases. We then show that recognizing these patterns enables us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our way can potentially bring benefit to channel coding, routing, and error correction protocol design. Finally, we propose Simple Rule, a simple yet effective method based on the chip error patterns to infer the link condition with an accuracy of over 96 percent in our evaluations.

Counting the number of RFID tags (cardinality) is a fundamental problem for large-scale RFID systems. Not only does it satisfy some real application requirements, it also acts as an important aid for RFID identification. Due to the extremely long processing time, slotted ALOHA-based or tree-based arbitration protocols are often impractical for many applications, because tags are usually attached to moving objects and they may have left the readers interrogation region before being counted. Recently, estimation schemes have been proposed to count the approximate number of tags. Most of them, however, suffer from two scalability problems: time inefficiency and multiple-reading. Without resolving these problems, large-scale RFID systems cannot easily apply the estimation scheme as well as the corresponding identification. In this paper, we present the Lottery Frame (LoF) estimation scheme, which can achieve high accuracy, low latency, and scalability. LoF estimates the tag numbers by utilizing the collision information. We show the significant advantages, e.g., high accuracy, short processing time, and low overhead, of the proposed LoF scheme through analysis and simulations.

Recent years have seen an increasing need of wireless networks in a mobile environment serving for more complex tasks and applications. Mobility becomes an indispensable factor of the system design and has been widely recognized as a general cause of packet loss. Though many works have been done on mobility study, to the best of our knowledge, they are mainly based on simulations or analytical studies that assume idealized link conditions. In this work, we experimentally investigate the nature of the error characteristics of mobility-induced packet losses at "chip-level" in IEEE 802.15.4. We believe this more understanding of mobility-induced packet losses can bring great potential benefits for further study on channel coding, routing and protocol design. Toward this end, we design and implement an efficient algorithm to distinguish mobility-induced packet losses from other packet losses of static environments such as attenuation. Our algorithm is greatly advantaged as it needs no training data even when environment changes. Collecting three corrupted packets is sufficient to obtain a satisfactory performance. This feature makes our design in particular suitable for dynamic and mobile environments, allowing real-time mobility induced loss detection in an online manner. Experiments based on GNU Radio testbed show that our algorithm can provide an accuracy of up to 96%.

The growing importance of operations such as identification, location sensing and object tracking has led to increasing interests in contact less Radio Frequency Identification (RFID) systems. Enjoying the low cost of RFID tags, modern RFID systems tend to be deployed for large-scale mobile objects. Both the theoretical and experimental results suggest that when tags are mobile and with large numbers, two classical MAC layer collision-arbitration protocols, slotted ALOHA and Tree-traversal, do not satisfy the scalability and time-efficiency requirements of many applications. To address this problem, we propose Adaptively Splitting-based Arbitration Protocol (ASAP), a scheme that provides low-latency RFID identification and has stable performance for massive RFID networks. Theoretical analysis and experimental evaluation show that ASAP outperforms most existing collision-arbitration solutions. ASAP is efficient for both small and large deployment of RFID tags, in terms of time and energy cost. Hence it can benefit dynamic and large-scale RFID systems.

IEEE 802.15.4 standard specifies physical layer (PHY) and medium access control (MAC)sublayer protocols for low-rate and low-power communication applications. In this protocol, every 4-bit symbol is encoded into a sequence of 32 chips that are actually transmitted over the air. The 32 chips as a whole is also called a pseudo-noise code (PN-Code). Due to complex channel conditions such as attenuation and interference, the transmitted PN-Code will often be received with some PN-Code chips corrupted. In this paper, we conduct a systematic analysis on these errors occurring at chip-level. We find that there are notable error patterns corresponding to different cases. Recognizing these patterns will enable us to identify the channel condition in great details. We believe that understanding what happened to the transmission in our setup can potentially bring benefit to channel coding, routing and error correction protocol design.

Counting or estimating the number of tags is crucial for large-scale RFID systems. The use of multiple readers was recently proposed to improve the efficiency and effectiveness in reading RFID tags. Due to the long processing time, tag identification based counting schemes are often impractical, especially when tags are attached to moving objects. The existing estimation based schemes, on the other hand, suffer from the multiple-reading problem. To address this issue, we propose the Lottery Frame (LoF) scheme, a replicate-insensitive estimation protocol, that is able to eliminate multiple-readings. We show the high accuracy, short processing time and low overhead of the proposed LoF scheme through analysis and simulations.

Wireless sensor networks have been widely deployed for monitoring environments of interest. The diffusion stimulus (DS) is a very common and important one in real environments, which is characterized by originating at a source spot and continuously spreading outward. DS-based applications are usually time-sensitive and require high accuracy. It is very challenging, however, for sensor networks to monitor a DS when those sensors could usually monitor one point (the sensing range is zero) only. No existing algorithm is effective and energy-efficient for DS monitoring. In this paper, we propose stimulus-based adaptive sleeping (SAS), to tackle this unique challenge. With SAS, each node independently determines its sleep duration based on its local observations on the stimulus. SAS enables sensors near the stimulus boundary to stay alert to accurately capture the stimulus arrival, and those far away from the stimulus to safely sleep longer for energy efficiency.

In March 2004, recognizing the importance of sensor networks, the Chinese Academy of Sciences and the Hong Kong University of Science and Technology launched a joint effort to investigate both fundamental and practical research issues in sensor networks. The goal of this research is to build lightweight optimized sensor systems on a massive scale, namely the BLOSSOMS project. The objective of this research project is to identify research issues at all levels from practical applications down to the design of sensor nodes. This paper reports the status of the project as of April 2005. First, other than making MOTE-compatible sensor nodes, this project has studied the hardware and software co-design and the associated "sensor node on a chip" technology with the aim to make sensor nodes small in size, light in weight, cheap in cost, and low in power consumption. Second, additional toolkits for simulation/emulation and evaluation of sensor networks have been developed to support research at different levels. Third, a number of applications have been investigated and implemented since the launch of this project, and this paper will address two of them. One is an embedded remote health care system based on wireless sensor network technologies to introduce a scalable wireless personal medical network around human's body. The other is a moving object counting system based on an ultrasonic sensor network, which can be used but not limited to crowd estimation and traffic monitoring and coordination.