Showing papers by "Wang-Chien Lee published in 2004"

Prediction-based strategies for energy saving in object tracking sensor networks

Abstract: In order to fully realize the potential of sensor networks, energy awareness should be incorporated into every stage of the network design and operation. In this paper, we address the energy management issue in a sensor network killer application - object tracking sensor networks (OTSNs). Based on the fact that the movements of the tracked objects are sometimes predictable, we propose a prediction-based energy saving scheme, called PES, to reduce the energy consumption for object tracking under acceptable conditions. We compare PES against the basic schemes we proposed in the paper to explore the conditions under which PES is most desired. We also test the effect of some parameters related to the system workload, object moving behavior and sensing operations on PES through extensive simulation. Our results show that PES can save significant energy under various conditions.

Dual prediction-based reporting for object tracking sensor networks

Abstract: As one of the wireless sensor network killer applications, object tracking sensor networks (OTSNs) disclose many opportunities for energy-aware system design and implementations. We investigate prediction-based approaches for performing energy efficient reporting in OTSNs. We propose a dual prediction-based reporting mechanism (called DPR), in which both sensor nodes and the base station predict the future movements of the mobile objects. Transmissions of sensor readings are avoided as long as the predictions are consistent with the real object movements. DPR achieves energy efficiency by intelligently trading off multihop/long-range transmissions of sensor readings between sensor nodes and the base station with one-hop/short-range communications of object movement history among neighbor sensor nodes. We explore the impact of several system parameters and moving behavior of tracked objects on DPR performance, and also study two major components of DPR: prediction models and location models through simulations. Our experimental results show that DPR is able to achieve considerable energy savings under various conditions and outperforms existing reporting mechanisms.

Semantic small world: an overlay network for peer-to-peer search

Abstract: For a peer-to-peer (P2P) system holding massive amount of data, efficient semantic based search for resources (such as data or services) is a key determinant to its scalability. This work presents the design of an overlay network, namely semantic small world (SSW), that facilitates efficient semantic based search in P2P systems. SSW is based on three innovative ideas: 1) small world network; 2) semantic clustering; 3) dimension reduction. Peers in SSW are clustered according to the semantics of their local data and self-organized as a small world overlay network. To address the maintenance issue of high dimensional overlay networks, a dynamic dimension reduction method, called adaptive space linearization, is used to construct a one-dimensional SSW that supports operations in the high dimensional semantic space. SSW achieves a very competitive trade-off between the search latencies/traffic and maintenance overheads. Through extensive simulations, we show that SSW is much more scalable to very large network sizes and very large numbers of data objects compared to pSearch, the state-of-the-art semantic-based search technique for P2P systems. In addition, SSW is adaptive to distribution of data and locality of interest; is very resilient to failures; and has good load balancing property.

Performance evaluation of an optimal cache replacement policy for wireless data dissemination

Abstract: Data caching at mobile clients is an important technique for improving the performance of wireless data dissemination systems. However, variable data sizes, data updates, limited client resources, and frequent client disconnections make cache management a challenge. We propose a gain-based cache replacement policy, Min-SAUD, for wireless data dissemination when cache consistency must be enforced before a cached item is used. Min-SAUD considers several factors that affect cache performance, namely, access probability, update frequency, data size, retrieval delay, and cache validation cost. The paper employs stretch as the major performance metric since it accounts for the data service time and, thus, is fair when items have different sizes. We prove that Min-SAUD achieves optimal stretch under some standard assumptions. Moreover, a series of simulation experiments have been conducted to thoroughly evaluate the performance of Min-SAUD under various system configurations. The simulation results show that, in most cases, the Min-SAUD replacement policy substantially outperforms two existing policies, namely, LRU and SAIU.

QFilter: fine-grained run-time XML access control via NFA-based query rewriting

Abstract: At present, most of the state-of-the-art solutions for XML access controls are either (1) document-level access control techniques that are too limited to support fine-grained security enforcement; (2) view-based approaches that are often expensive to create and maintain; or (3) impractical proposals that require substantial security-related support from underlying XML databases. In this paper, we take a different approach that assumes no security support from underlying XML databases and examine three alternative fine-grained XML access control solutions, namely primitive, pre-processing and post-processing approaches. In particular, we advocate a pre-processing method called QFilter that uses Non-deterministic Finite Automata (NFA) to rewrite user's query such that any parts violating access control rules are pruned. We show the construction and execution of a QFilter and demonstrate its superiority to other competing methods.

Spatial queries in wireless broadcast systems

Abstract: Owing to the advent of wireless networking and personal digital devices, information systems in the era of mobile computing are expected to be able to handle a tremendous amount of traffic and service requests from the users. Wireless data broadcast, thanks to its high scalability, is particularly suitable for meeting such a challenge. Indexing techniques have been developed for wireless data broadcast systems in order to conserve the scarce power resources in mobile clients. However, most of the previous studies do not take into account the impact of location information of users. In this paper, we address the issues of supporting spatial queries (including window queries and kNN queries) of location-dependent information via wireless data broadcast. A linear index structure based on the Hilbert curve and corresponding search algorithms are proposed to answer spatial queries on air. Experiments are conducted to evaluate the performance of the proposed indexing technique. Results show that the proposed index and its enhancement outperform existing algorithms significantly.

Exponential index: a parameterized distributed indexing scheme for data on air

Abstract: Wireless data broadcast has received a lot of attention from industries and academia in recent years. Access efficiency and energy conservation are two critical performance concerns in a wireless data broadcast environment. To improve the efficiency of energy consumption on mobile devices, traditional disk-based indexing techniques such as B$^+$-tree have been extended to index broadcast data on a wireless channel. However, existing designs are mostly based on centralized tree structures. Most of these indexing techniques are not flexible in the sense that the trade-off between access efficiency and energy conservation is not adjustable based on application specific requirements. We propose in this paper a novel parameterized index, called the exponential index, which can be tuned to optimize the access latency with the tuning time bounded by a given limit, and vice versa. The proposed index is very efficient because it facilitates replication naturally by sharing links in multiple search trees and thus minimizes storage overhead. Experimental results show that the exponential index not only achieves better performance than the state-of-the-art indexes but also enables great flexibility in trade-offs between access latency and tuning time.

The D-tree: an index structure for planar point queries in location-based wireless services

Abstract: Location-based services (LBSs), considered as a killer application in the wireless data market, provide information based on locations specified in the queries. In this paper, we examine the indexing issue for querying location-dependent data in wireless LBSs; in particular, we focus on an important class of queries, planar point queries. To address the issues of responsiveness, energy consumption, and bandwidth contention in wireless communications, an index has to minimize the search time and maintain a small storage overhead. It is shown that the traditional point-location algorithms and spatial index structures fail to achieve either objective or both. This paper proposes a new index structure, called D-tree, which indexes spatial regions based on the divisions that form the boundaries of the regions. We describe how to construct a binary D-tree index, how to process queries based on the D-tree, and how to page the binary D-tree. Moreover, two parameterized methods for partitioning the original space, called fixed grid assignment (FGA) and adaptive grid assignment (AGA), are proposed to enhance the D-tree. The performance of the D-tree is evaluated using both synthetic and real data sets. Experimental results show that the proposed D-tree outperforms the well-known indexes such as the R/sup */-tree, and that both the FGA and AGA approaches can achieve different performance trade-offs between the index search time and storage overhead by fine-tuning their algorithmic parameters.

Efficient Peer-to-Peer Information Sharing over Mobile Ad Hoc Networks

Abstract: Peer-to-peer systems have gained a lot of attention as information sharing systems for the wide-spread exchange of resources and voluminous information among thousands of users. However, current peer-to-peer information sharing systems work mostly on wired networks. With the growing number of communication-equipped mobile devices that can self-organize into infrastructure-less communication platform, namely mobile ad hoc networks (MANETs), peerto-peer information sharing over MANETs is a promising research area. In this paper, we propose a distributed index structure, Multi-level Peer Index (MPI), that enables efficient peer-to-peer information sharing over MANETs. Preliminary evaluation demonstrates that MPI is scalable, efficient, and adaptive to node mobility.

Performance comparison of cache invalidation strategies for Internet-based mobile ad hoc networks

Abstract: Internet-based mobile ad hoc network (IMANET) combines a mobile ad hoc network (MANET) and the Internet to provide universal information accessibility. Although caching frequently accessed data items in mobile terminals (MTs) improves the communication performance in an IMANET, it brings a critical design issue when data items are updated. We analyze several push and pull-based cache invalidation strategies for IMANETS. A global positioning system (GPS) based connectivity estimation (GPSCE) scheme is first proposed to assess the connectivity of an MT for supporting any cache invalidation mechanism. Then, we propose a pull-based approach, called aggregate cache based on demand (ACOD) scheme, to find the queried data items efficiently. In addition, we modify two push-based cache invalidation strategies, proposed for cellular networks, to work in IMANETs. These are a modified timestamp (MTS) scheme, and an MTS with updated invalidation report (MTS+UIR) scheme. Simulation results indicate that our proposed strategy provides high throughput, low query latency, and low communication overhead, and thus, is a viable approach for implementation in IMANETS.

On semantic caching and query scheduling for mobile nearest-neighbor search

Abstract: Location-based services have received increasing attention in recent years. In this paper, we address the performance issues of mobile nearest-neighbor search, in which the mobile user issues a query to retrieve stationary service objects nearest to him/her. An index based on Voronoi Diagram is used in the server to support such a search, while a semantic cache is proposed to enhance the access efficiency of the service. Cache replacement policies tailored for the proposed semantic cache are examined. Moreover, several query scheduling policies are proposed to address the inter-cell roaming issues in multi-cell environments. Simulations are conducted to evaluate the proposed methods. The result shows that the system performance, in terms of cache hit ratio, query response time, cell-cross number and cell-recross number, is improved significantly.

Energy-Conserving Air Indexes for Nearest Neighbor Search

Abstract: A location-based service (LBS) provides information based on the location information specified in a query. Nearest-neighbor (NN) search is an important class of queries supported in LBSs. This paper studies energy-conserving air indexes for NN search in a wireless broadcast environment. Linear access requirement of wireless broadcast weakens the performance of existing search algorithms designed for traditional spatial database. In this paper, we propose a new energy- conserving index, called grid-partition index, which enables a single linear scan of the index for any NN queries. The idea is to partition the search space for NN queries into grid cells and index all the objects that are potential nearest neighbors of a query point in each grid cell. Three grid partition schemes are proposed for the grid-partition index. Performance of the proposed grid-partition indexes and two representative traditional indexes (enhanced for wireless broadcast) is evaluated using both synthetic and real data. The result shows that the grid-partition index substantially outperforms the traditional indexes.

Energy-conserving air indexes for nearest neighbor search

Abstract: A location-based service (LBS) provides information based on the location information specified in a query. Nearest-neighbor (NN) search is an important class of queries supported in LBSs. This paper studies energy-conserving air indexes for NN search in a wireless broadcast environment. Linear access requirement of wireless broadcast weakens the performance of existing search algorithms designed for traditional spatial database. In this paper, we propose a new energy-conserving index, called grid-partition index, which enables a single linear scan of the index for any NN queries. The idea is to partition the search space for NN queries into grid cells and index all the objects that are potential nearest neighbors of a query point in each grid cell. Three grid partition schemes are proposed for the grid-partition index. Performance of the proposed grid-partition indexes and two representative traditional indexes (enhanced for wireless broadcast) is evaluated using both synthetic and real data. The result shows that the grid-partition index substantially outperforms the traditional indexes.

KPT: a dynamic KNN query processing algorithm for location-aware sensor networks

Abstract: An important type of spatial queries for sensor networks are K Nearest Neighbor (KNN) queries. Currently, research proposals for KNN query processing is based on index structures, which are typically expensive in terms of energy consumption. In addition, they are vulnerable to node failure and are difficult to maintain in dynamic sensor networks. In this paper, we propose KPT, an algorithm for dynamically processing KNN queries in location-aware sensor networks. KPT shows great potential for energy savings and improved query latency. Since the tree infrastructure is constructed only temporarily, KPT is less vulnerable to sensor node failure.

Search continuous nearest neighbors on the air

Abstract: A continuous nearest neighbor (CNN) search retrieves the nearest neighbors corresponding to every point in a given query line segment. It is important for location-based services such as vehicular navigation tools and tourist guides. It is infeasible to answer a CNN search by issuing a traditional nearest neighbor query at every point of the line segment due to the large number of queries generated and the large overhead on bandwidth. Algorithms have been proposed recently to support CNN search in the traditional client-server service model. In this paper, we conduct a pioneering study on CNN search in wireless data broadcast environments. We propose two air indexing techniques, namely, R-tree air index and Hilbert curve air index, and develop algorithms based on these two techniques to search CNNs on the air. A simulation is conducted to compare the proposed air indexing techniques with a naive broadcast approach. The result shows that both of the proposed methods outperform the naive approach significantly. The Hilbert Curve air index is superior for uniform data distributions, while the R-tree air index is a better choice for skewed data distributions.

A Small World Overlay Network for Semantic Based Search in P2P Systems

Abstract: For a peer-to-peer (P2P) system holding massive amount of data, efficient search for resources (such as data or services) is a key determinant to its scalability. This paper presents semantic small world (SSW), an overlay network and index structure for semantic based P2P search. By dynamically clustering peer nodes in a semantic space based on the semantics of their data and organizing the clusters into a small world network, SSW achieves a very competitive trade-off between the search latencies/traffic and maintenance overheads. Preliminary evaluation shows that SSW is much more scalable to very large network sizes and very large numbers of data objects compared to pSearch, the stateof-the-art semantic-based search technique for P2P systems.

A Flexible Framework for Architecting XML Access Control Enforcement Mechanisms

Abstract: Due to the growing interest in XML security, various access control schemes have been proposed recently. However, little effort has been put forth to facilitate a uniform analysis and comparison of these schemes under the same framework. This paper presents a first attempt toward a flexible framework that can capture the design principles and operations of existing XML access control mechanisms. Under this framework, we observe that most existing XML access control mechanisms share the same design principle with slightly different orderings of underlying building blocks (i.e., data, query, and access control rule). Furthermore, according to the framework, we identify four plausible approaches to implement XML access controls, namely built-in, view-based, pre-processing and post-processing. Finally, we compare the actual performance of different approaches.

Data management in location-dependent information services

Abstract: Location-dependent information services (LDISs) answer queries in accordance with the locations the queries are associated with (e.g., the locations from which the queries are issued. The emergence of LDISs is resulted from the convergence of high-speed wireless networks, personal portable devices, and locatining techniques. LDISs have a variety of promising applications, such as local information access (e.g., traffic reports, news, and navigation maps) and nearest neighbor queries (e.g., finding the nearest restaurant), and are expected to become an integral part of our daily life. This seminar will provide background and an overview of research on location-dependent information access in mobile and pervasive environments. In particular, it will discuss the following topic areas:

Scheduling web requests in broadcast environments

Abstract: On-demand broadcast has been supported in the Internet to enhance system scalability. Unfortunately, most of existing on-demand scheduling algorithms did not consider the time constraints associated with web requests. This paper proposes a novel scheduling algorithm, called Slack Inverse Number of requests (SIN), that takes into account the urgency and productivity of serving pending requests. Trace-driven experiments demonstrate that SIN significantly out performs existing algorithms over a wide range of workloads.