Kai Bu

Unknown Tag Identification in Large RFID Systems: An Efficient and Complete Solution

Radio-Frequency Identification (RFID) technology brings revolutionary changes to many fields like retail industry. One important research issue in large RFID systems is the identification of unknown tags, i.e., tags that just entered the system but have not been interrogated by reader(s) covering them yet. Unknown tag identification plays a critical role in automatic inventory management and misplaced tag discovery, but it is far from thoroughly investigated. Existing solutions either trivially interrogate all the tags in the system and thus are highly time inefficient due to re-identification of already identified tags, or use probabilistic approaches that cannot guarantee complete identification of all the unknown tags. In this paper, we propose a series of protocols that can identify all of the unknown tags with high time efficiency. We develop several novel techniques to quickly deactivate already identified tags and prevent them from replying during the interrogation of unknown tags, which avoids re-identification of these tags and consequently improves time efficiency. To our knowledge, our protocols are the first non-trivial solutions that guarantee complete identification of all the unknown tags. We illustrate the effectiveness of our protocols through both rigorous theoretical analysis and extensive simulations. Simulation results show that our protocols can save up to 70 percent time when compared with the best existing solutions.

Efficient Distributed Query Processing in Large RFID-enabled Supply Chains

Radio Frequency Identification (RFID) has dramatically streamlined supply chain management by automatically monitoring and tracking commodities. Considering the proliferation of RFID data volume, distributed storage is more applicable and scalable than centralized storage for distributed query processing. Traditional distributed RFID data storage requires each distribution center to locally store raw RFID data, leading to data redundancy, storage and query inefficiency. In this paper, we design an efficient distributed storage model by leveraging Bloom filters to save storage space and improve query efficiency. Meanwhile, we establish corresponding query processing schemes to locally support existence queries and path queries, which are two kinds of most popular queries in the supply chain management. A local query can be completed with constant time complexity regardless of data volume. Experiments demonstrate that our storage model outperforms the traditional one in terms of both space and time efficiency.

Efficient Misplaced-Tag Pinpointing in Large RFID Systems

Radio-Frequency Identification (RFID) technology brings many innovative applications. Of great importance to RFID applications in production economics is misplaced-tag pinpointing (MTP), because misplacement errors fail optimal inventory placement and thus significantly decrease profit. The existing MTP solution [1], originally proposed from a data-processing perspective, collects and processes a large amount of data. It suffers from time inefficiency (and energy-inefficiency as well if active tags are in use). The problem of finding efficient solutions for the MTP problem from the communication protocol design perspective has never been investigated before. In this paper, we propose a series of protocols toward efficient MTP solutions in large RFID systems. The proposed protocols detect misplaced tags using reader positions instead of tag positions to guarantee the efficiency and scalability as system scale grows, because RFID readers are much fewer than tags. Considering applications that employ active tags, we further propose a solution requiring responses from only a subset of tags in favor of energy saving. We also design a distributed protocol that enables each reader to independently detect misplaced tags. We then investigate how to apply the proposed protocols in scenarios with tag mobility. To evaluate the proposed protocols, we analyze their optimal performances to demonstrate their efficiency potential and also conduct extensive simulation experiments. The results show that the proposed protocols can significantly increase the time efficiency and the energy efficiency by over 70 percent on average when compared with the best existing work.

Complete and fast unknown tag identification in large RFID systems

The RFID technology greatly improves efficiency of many applications including inventory control, object tracking, and supply chain management. In such applications, it is common that new objects are added into the system or existing objects are misplaced in wrong regions. When this happens, fast and complete identification of such tags is very important. We name this problem unknown tag identification, as these tags appear to be unknown by the reader(s) currently covering them. In this paper, we propose a series of protocols to identify unknown tags completely and fast. In these protocols, we develop several novel techniques to efficiently resolve collisions caused by known tags when identifying unknown tags, which greatly improve the time efficiency. To our knowledge, this is the first work that completely identify all the unknown tags with deterministic approaches. Simulation results show the superior performance of the proposed protocols: Compared with a baseline method which collects IDs of all the tags in the system, our best protocol reduces the execution time by 63% in average and by 85% at most.

ENDA: embracing network inconsistency for dynamic application offloading in mobile cloud computing

Mobile Cloud Computing (MCC) enables smartphones to offload compute-intensive codes and data to clouds or cloudlets for energy conservation. Thus, MCC liberates smartphones from battery shortage and embraces more versatile mobile applications. Most pioneering MCC research work requires a consistent network performance for offloading. However, such consistency is challenged by frequent mobile user movements and unstable network quality, thereby resulting in a suboptimal offloading decision. To embrace network inconsistency, we propose ENDA, a three-tier architecture that leverages user track prediction, realtime network performance and server loads to optimize offloading decisions. On cloud tier, we first design a greedy searching algorithm to predict user track using historical user traces stored in database servers. We then design a cloud-enabled Wi-Fi access point (AP) selection scheme to find the most energy efficient AP for smartphone offloading. We evaluate the performance of ENDA through simulations under a real-world scenario. The results demonstrate that ENDA can generate offloading decisions with optimized energy efficiency, desirable response time, and potential adaptability to a variety of scenarios. ENDA outperforms existing offloading techniques that do not consider user mobility and server workload balance management.

Unreconciled Collisions Uncover Cloning Attacks in Anonymous RFID Systems

Cloning attacks threaten radio-frequency identification (RFID) applications but are hard to prevent. Existing cloning attack detection methods are enslaved to the knowledge of tag identifiers (IDs). Tag IDs, however, should be protected to enable and secure privacy-sensitive applications in anonymous RFID systems. In a first step, this paper tackles cloning attack detection in anonymous RFID systems without requiring tag IDs as a priori. To this end, we leverage unreconciled collisions to uncover cloning attacks. An unreconciled collision is probably due to responses from multiple tags with the same ID, exactly the evidence of cloning attacks. This insight inspires GREAT, our pioneer protocol for cloning attack detection in anonymous RFID systems. We evaluate the performance of GREAT through theoretical analysis and extensive simulations. The results show that GREAT can detect cloning attacks in anonymous RFID systems fairly fast with required accuracy. For example, when only six out of 50,000 tags are cloned, GREAT can detect the cloning attack in 75.5 s with a probability of at least 0.99.

Efficient pinpointing of misplaced tags in large RFID systems

The Radio-Frequency Identification (RFID) technology has stimulated many innovative applications. Misplaced-tag pinpointing (MTP) is important to RFID applications in production economics because optimal inventory placement can significantly increase profit. Previous research from the database perspective needs to process a large amount of data which is time-consuming to collect (and energy-consuming if active tags are used). How to efficiently address the MTP problem from the protocol design perspective however has not been investigated. In this paper, we propose a series of protocols toward efficient MTP solution in large RFID systems. The proposed protocols detect misplaced tags based on reader positions instead of tag positions to guarantee the efficiency and scalability as system scale grows, because the number of readers is much smaller than that of tags. Considering applications to employ more and more popular active tags, we further propose a solution requiring responses from only partial tags in favor of energy saving. We analyze the optimal performances of proposed protocols to demonstrate their efficiency potential and conduct extensive simulation experiments to evaluate their performance under various scenarios. The results show that the proposed protocols can significantly increase the time efficiency and the energy efficiency by over 70% on average when compared with the state of the art.

Flexible and Time-Efficient Tag Scanning with Handheld Readers

Tag scanning is an important issue to dynamically manage tag IDs in radio frequency identification (RFID) systems. Different from tag identification that collects IDs of all the tags, tag scanning first verifies whether or not a responding tag has already been identified and retrieves its ID when the answer is yes, and collects the tags ID only when it is unidentified. In this paper, we present the first study on spot scanning with a handheld reader, which aims to scan tags in the readers interrogation range at an arbitrarily specified position in the system. Existing studies mainly focus on continuous scanning, and they are highly time inefficient in performing spot scanning. The inefficiency stems from the small overlap between tag populations in different spot scanning operations, in which case existing solutions cannot efficiently recognize unidentified tags. We develop a novel technique called LOCK to efficiently recognize unidentified tags even when the overlapped tags are few. LOCK does not simply use a tags reply slot index but also compact short responses from tags to efficiently distinguish unidentified tags from identified ones. The valuable compact short responses are firstly investigated, which are the keys for efficient tag identification in the paper. Based on LOCK, three tag scanning protocols are proposed to solve the spot scanning problem. Simulation results show that, for spot scanning, our best protocol reduces per tag scanning time by up to 70 percent when compared with the state-of-the-art solution. Moreover, the proposed protocols can also be employed to perform continuous scanning with better time efficiency than the best existing solutions.

Compiling minimum incremental update for modular SDN languages

Measurement results show that updating rules on switches poses major latency overhead during the course of the policy update. However, current SDN policy compilers do not handle policy updates well and generate large amount of redundant rule updates, most of which modify only the priority field. Our analysis shows that the lack of knowledge on the rule dependency and the consecutively distributed priority numbers are the fundamental problems behind the redundancy. In this paper, we propose to tackle the problems through 1) an extended policy compiler that builds rule dependency along with the compilation, and 2) an online optimization algorithm that maintains a scattered priority distribution. Our preliminary evaluation demonstrates that our proposed patch can eliminate nearly all the priority updates.

Is every flow on the right track?: Inspect SDN forwarding with RuleScope

Software-Defined Networking (SDN) promises un-precedentedly flexible network management but it is susceptible to forwarding faults. Such faults originate from data-plane rules with missing faults and priority faults. Yet existing fault detection ignores priority faults because they are not discovered on commercial switches until recently. In this paper, we present RuleScope, a more comprehensive solution for inspecting SDN forwarding. RuleScope offers a series of accurate and efficient algorithms for detecting and troubleshooting rule faults. They inspect forwarding behavior using customized probe packets to exercise data-plane rules. The detection algorithm exposes not only missing faults but also priority faults. Beyond simply detecting rule faults, the troubleshooting algorithms uncover actual data-plane flow tables. They help track real-time forwarding status and benefit reliable network monitoring. We explore various techniques for enhancing algorithm efficiency without sacrificing inspection accuracy. Experiments with our prototype on the Ryu SDN controller and Pica8 P-3297 switch show that RuleScope achieves accurate and efficient forwarding inspection with limited bandwidth and packet-switching overhead.