Tzung-Shi Chen

Mobile object tracking in wireless sensor networks

Wireless sensor network is an emerging technology that enables remote monitoring objects and environment. This paper proposes a protocol to track a mobile object in a sensor network dynamically. The previous researches almost focus on how to track object accurately and they do not consider the query for mobile sources. Additionally, they need not report the tracking information to user. The work is concentrated on mobile user how to query target tracks and obtain the target position effectively. The mobile user can obtain the tracking object position without broadcast query. The user is moving and approaching the target when he/she knows the targets position. Wireless sensor networks can assist user to detect target as well as keep the movement information of the target. Sensor nodes establish face structure to track the designated target and keep target tracks. The source follows the tracks to approaching target. To chase the object quick and maintain an accurate tracking route, the sensors cooperate together to shorten the route between target and source dynamically. A source can quickly approach a target along a shortened route. Finally, we compare the proposed scheme with three flooding-based query methods. By the simulation results, the proposed protocol has better performance than that of flooding-based query methods.

The design and implementation of a meaningful learning-based evaluation method for ubiquitous learning

If ubiquitous learning (u-learning) is to be effectively developed and feasibly applied to education, it is necessary to evaluate its effectiveness. Yet to achieve a sound evaluation, a particular paradigm must be employed to fit the problem domain. Toward this end, the authors of this study have adopted a meaningful learning paradigm. Meaningful learning is often regarded as the ultimate learning status for a learner, regardless of the learning environment. Interestingly, several characteristics of u-learning are also linked to attributes of meaningful learning. For example, both u-learning and meaningful learning emphasize the authentic and active of the learning activity. Therefore, it is important to investigate the applicability of a meaningful learning paradigm for evaluating the efficacy of u-learning. The method proposed here evaluates u-learning along both macro and micro aspects, and in an effort to make u-learning more sustainable. By employing a case study, we demonstrate the feasibility of our approach by showing the advantages and disadvantages that are common to both u-learning and meaningful learning. Moreover, we also provide suggestions for instructors and designers so that they can promote the quality of u-learning.

An optimal broadcasting algorithm without message redundancy in star graphs

Based on the V.E. Mendia and D. Sarkars algorithm (1992), we propose an optimal and nonredundant distributed broadcasting algorithm in star graphs. For an n-dimensional star graph, our algorithm takes O(n log/sub 2/ n) time and guarantees that all nodes in the star graph receive the message exactly once. Moreover, broadcasting m packets in a pipeline fashion takes O(m log/sub 2/ n+n log/sub 2/ n) time due to the nonredundant property of our broadcasting algorithm. >

Communication-free data allocation techniques for parallelizing compilers on multicomputers

In distributed memory multicomputers, local memory accesses are much faster than those involving interprocessor communication. For the sake of reducing or even eliminating the interprocessor communication, the array elements in programs must be carefully distributed to local memory of processors for parallel execution. We devote our efforts to the techniques of allocating array elements of nested loops onto multicomputers in a communication-free fashion for parallelizing compilers. We first analyze the pattern of references among all arrays referenced by a nested loop, and then partition the iteration space into blocks without interblock communication. The arrays can be partitioned under the communication-free criteria with nonduplicate or duplicate data. Finally, a heuristic method for mapping the partitioned array elements and iterations onto the fixed-size multicomputers under the consideration of load balancing is proposed. Based on these methods, the nested loops can execute without any communication overhead on the distributed memory multicomputers. Moreover, the performance of the strategies with nonduplicate and duplicate data for matrix multiplication is studied. >

On Data Collection Using Mobile Robot in Wireless Sensor Networks

A novel data-collecting algorithm using a mobile robot to acquire sensed data from a wireless sensor network (WSN) that possesses partitioned/islanded WSNs is proposed in this paper. This algorithm permits the improvement of data-collecting performance by the base station by identifying the locations of partitioned/islanded WSNs and navigating a mobile robot to the desired location. To identify the locations of the partitioned/islanded WSNs, two control approaches, a global- and local-based approach, are proposed. Accordingly, the navigation strategy of the robot can be scheduled based on time and location using three scheduling strategies: time based, location based, and dynamic moving based. With these strategies, the mobile robot can collect the sensed data from the partitioned/islanded WSNs. Therefore, the efficiency of sensed data collected by the base station in partitioned/islanded WSNs is improved. Through simulation under the environment of an ns-2 simulator, the results, from various aspects, show that the collecting strategies proposed can dramatically improve sensed data-collecting performance in partitioned or islanded WSNs.

Mining User Movement Behavior Patterns in a Mobile Service Environment

Mobile service systems offer users useful information ubiquitously via mobile devices. Based on changeable user movement behavior patterns (UMBPs), mobile service systems have the capability of effectively mining a special request from abundant data. In this paper, UMBPs are studied in terms of the problem of mining matching mobile access patterns based on joining the following four kinds of characteristics, U, L, T, and S, where U is the mobile user, L is the movement location, T is the dwell time in the timestamp, and S is the service request. By introducing standard graph-matching algorithms along with the primitives of a database management system, which comprises grouping, sorting, and joining, these joint operations are defined. Moreover, by mining the associated structure via maximum weight bipartite graph matching, a prediction mechanism, based on the model of UMBPs, is utilized to find strong relationships among U , L, T , and S. In addition, a PC-based experimental evaluation under various simulation conditions, using synthetically generated data, is introduced. Finally, performance studies are conducted to show that, in terms of execution efficiency and scalability, the proposed procedures produced excellent performance results.

Efficient path-based multicast in wormhole-routed mesh networks

The capability of multidestination wormhole allows a message to be propagated along any valid path in a wormhole-routed network conforming to the underlying base routing scheme. The multicast on the path-based routing model is highly dependent on the spatial locality of destinations participating in multicasting. In this paper, we propose two proximity grouping schemes for efficient multicast in wormhole-routed mesh networks with multidestination capability by exploiting the spatial locality of the destination set. The first grouping scheme, graph-based proximity grouping, is proposed to group the destinations together with locality to construct several disjoint sub-meshes. This is achieved by modeling the proximity grouping problem to graph partitioning problem. The second one, pattern-based proximity grouping, is proposed by the pattern classification schemes to achieve the goal of the proximity grouping. By simulation results, we show the routing performance gains over the traditional Hamiltonian-path routing scheme.

Geographic convergecast using mobile sink in wireless sensor networks

This paper presents a novel convergecast algorithm called, Virtual Circle Combined Straight Routing (VCCSR), which collects data in a wireless sensor network (WSN) using a mobile sink. Tree-based routing offers the shortest routes to deliver data, and it is a common scheme used by mobile sinks to collect data from sensors. When a mobile sink moves, the routes between the sink and the sensors must be reconstructed dynamically, which wastes a great amount of energy. VCCSR selects a set of cluster heads located near the virtual backbone, and when the sink issues a query in the WSN, a spanning tree is constructed to collect and complete data periodically. With VCCSR, the spanning tree does not need to be reconstructed when the mobile sinks location changes because the algorithm is able to update the location of the mobile sink, which then delivers this information to the cluster heads and adjusts the routing. The goal of the proposed algorithm is to decrease the reconstruction cost and increase the data delivery ratio. In comparing the VCCSR protocol with BFS tree-based protocols in simulation, this paper demonstrates that the spanning tree adjustment process executed by VCCSR does in fact decrease the reconstruction cost and increase the data delivery ratio.

Gathering-Load-Balanced Tree Protocol for Wireless Sensor Networks

Wireless communications and digital electronics have enabled the development of low-power, low-cost, multifunctional sensors. The functionality of sensor network mainly is the measurement collection. The previous proposed protocols mainly focus on broadcasting tree structure, but it may not be efficient in data gathering. In this paper, we propose novel tree architecture that is a dynamic, adjustable, load-balanced tree in sensor networks to decrease the energy utilization and to prolong the lifetime of sensors. A load-balanced tree can share the forwarding loads between non-leaf nodes. Due to the limit of tree topology, we try to adjust forming a tree that has similar amount of children between non-leaf nodes. When the energy of non-leaf node is lower than a designated threshold, the tree structure can be readjusted to prolong the lifetime of tree. In simulation, we compare our protocol with different adjustment phases and an existed protocol. From the result, our protocol can have better performance than others

A dual-Hamiltonian-path-based multicasting strategy for wormhole-routed star graph interconnection networks

Multicast is an important collective communication operation on multicomputer systems, in which the same message is delivered from a source node to an arbitrary number of destination nodes. The star graph interconnection network has been recognized as an attractive alternative to the popular hypercube network. In this paper, we first address a dual-hamiltonian-path-based routing model with two virtual channels based on two hamiltonian paths (HPs) and a network partitioning strategy for wormhole-routed star graph networks. Then, we propose three efficient multicast routing schemes on basis of such a model. All of the three proposed schemes are proved deadlock-free. The first scheme, network-selection-based dual-path routing, selects subnetworks that are constructed either by the first HP or by the second HP for dual-path routing. The second one, optimum dual-path routing, selects subnetworks with optimum routing path for dual-path routing. The third scheme, two-phase optimum dual-path routing, includes two phases, source-to-relay and relay-to-destination. Finally, experimental results are given to show that our proposed three routing schemes outperform the unicast-based, the HP, and the single-HP-based dual-path routing schemes significantly.