Weizhen Mao

Counting RFID Tags Efficiently and Anonymously

Radio Frequency IDentification (RFID) technology has attracted much attention due to its variety of applications, e.g., inventory control and object tracking. One important problem in RFID systems is how to quickly estimate the number of distinct tags without reading each tag individually. This problem plays a crucial role in many real-time monitoring and privacy-preserving applications. In this paper, we present an efficient and anonymous scheme for tag population estimation. This scheme leverages the position of the first reply from a group of tags in a frame. Results from mathematical analysis and extensive simulation demonstrate that our scheme outperforms other protocols proposed in the previous work.

Outlier detection in sensor networks

Outlier detection has many important applications in sensor networks, e.g., abnormal event detection, animal behavior change, etc. It is a difficult problem since global information about data distributions must be known to identify outliers. In this paper, we use a histogram-based method for outlier detection to reduce communication cost. Rather than collecting all the data in one location for centralized processing, we propose collecting hints (in the form of a histogram) about the data distribution, and using the hints to filter out unnecessary data and identify potential outliers. We show that this method can be used for detecting outliers in terms of two different definitions. Our simulation results show that the histogram method can dramatically reduce the communication cost.

Data storage placement in sensor networks

Data storage has become a important issue in sensor networks as a large amount of collected data need to be archived for future information retrieval. This paper introduces storage nodes to store the data collected from the sensors in their proximities. The storage nodes alleviate the heavy load of transmitting all the data to a central place for archiving and reduce the communicatio cost induced by the network query. This paper considers the storage node placement problem aiming to minimize the total energy cost for gathering data to the storage nodes and replying queries. We examine deterministic placement of storage odes and present optimal algorithms based on dy amic programming. Further, we give stochastic analysis for random deployment and conduct simulatio evaluatio for both deterministic and random placements of storage nodes.

Finding popular categories for RFID tags

As RFID tags are increasingly attached to everyday items, it quickly becomes impractical to collect data from every tag in order to extract useful information. In this paper, we consider the problem of identifying popular categories of RFID tags out of a large collection of tags, without reading all the tag data. We propose two algorithms based on the idea of group testing, which allows us to efficiently derive popular categories of tags. We evaluate our solutions using both theoretical analysis and simulation.

Efficient Continuous Scanning in RFID Systems

RFID is an emerging technology with many potential applications such as inventory management for supply chain. In practice, these applications often need a series of continuous scanning operations to accomplish a task. For example, if one wants to scan all the products with RFID tags in a large warehouse, given a limited reading range of an RFID reader, multiple scanning operations have to be launched at different locations to cover the whole warehouse. Usually, this series of scanning operations are not completely independent as some RFID tags can be read by multiple processes. Simply scanning all the tags in the reading range during each process is inefficient because it collects a lot of redundant data and consumes a long time. In this paper, we develop efficient schemes for continuous scanning operations defined in both spatial and temporal domains. Our basic idea is to fully utilize the information gathered in the previous scanning operations to reduce the scanning time of the succeeding ones. We illustrate in the evaluation that our algorithms dramatically reduce the total scanning time when compared with other solutions.

An Approximation Algorithm for Data Storage Placement in Sensor Networks

Data storage has become an important issue in sensor networks as a large amount of collected data needs to be archived for future information retrieval. This paper proposes to introduce storage nodes that can store data collected from the sensors in their proximities. The storage nodes alleviate the heavy load of transmitting all the data to a central place for archiving and reduce the communication cost induced by the network query. This paper considers the storage node placement problem to minimize the total power consumption for data funneling to the storage nodes and data query. We formulate it as an integer linear programming problem and present an approximation algorithm based on a rounding technique. Our simulation shows that our approximation algorithm performs well in practice.

A look-ahead heuristic for scheduling jobs with release dates on a single machine

Abstract The paper explores how limited look-ahead improves the performance of on-line heuristics. In particular, we consider the NP-complete single machine scheduling of independent jobs with release dates to minimize the total completion time. We present an on-line with look-ahead algorithm which foresees the next in-coming job. We study its worst-case behavior and prove that it outperforms most on-line and off-line heuristics.

BodyT2: Throughput and time delay performance assurance for heterogeneous BSNs

Body sensor networks (BSNs) have been developed for a set of performance-critical applications, including smart healthcare, assisted living, emergency response, athletic performance evaluation, and interactive controls. Many of these applications require stringent performance assurance in terms of communication throughput and bounded time delay. While solutions exist in literature for providing joint throughput and time delay assurance by proposing specific MAC protocols or extensions, we provide this joint assurance in a novel radio-agnostic manner. In our approach, the underlying MAC and PHY layers can be heterogeneous and their details do not need to be known to upper layers like the resource management. Such a radio-agnostic performance assurance is critical because a range of radio platforms are adopted for practical body sensor usage. Our approach is based on a group-polling scheme that is essential for radio-agnostic BSN design. Through theoretical analysis, we prove that with the group-polling scheme, achieving joint throughput and time delay assurance is an NP-hard problem. For practical system deployment, we propose the BodyT2 framework that assures throughput and time delay performance in a heterogeneous BSN. Through both TelosB mote lab tests and real body experiments in an Android phone-centric BSN, we demonstrate that BodyT2 achieves superior performance over existing solutions.

Efficient subtorus processor allocation in a multi-dimensional torus

Processor allocation in a mesh or torus connected multicomputer system with up to three dimensions is a hard problem that has received some research attention in the past decade. With the recent deployment of multicomputer systems with a torus topology of dimensions higher than three, which are used to solve complex problems arising in scientific computing, it becomes imminent to study the problem of allocating processors of the configuration of a torus in a multi-dimensional torus connected system. In this paper, we first define the concept of a semitorus. We present two partition schemes, the Equal Partition (EP) and the Non-Equal Partition (NEP), that partition a multi-dimensional semitorus into a set of sub-semitori. We then propose two processor allocation algorithms based on these partition schemes. We evaluate our algorithms by incorporating them in commonly used FCFS and backfilling scheduling policies and conducting simulation using workload traces from the Parallel Workloads Archive. Specifically, our simulation experiments compare four algorithm combinations, FCFS/EP, FCFS/NEP, backfilling/EP, and backfilling/NEP, for two existing multi-dimensional torus connected systems. The simulation results show that our algorithms (especially the backfilling/NEP combination) are capable of producing schedules with system utilization and mean job bounded slowdowns comparable to those in a fully connected multicomputer

Achieving efficiency and fairness for association control in vehicular networks

Deploying city-wide 802.11 access points has made possible internet access in a vehicle, nevertheless it is challenging to maintain client performance at vehicular speed especially when multiple mobile users exist. This paper considers the association control problem for vehicular networks in drive-thru Internet scenarios. In particular, we aim to improve the overall throughput and fairness for all users. We design efficient algorithms to achieve the objectives through several techniques including approximation. Our simulation results confirm the performance of our algorithms.