Wei-Mei Chen

Localization of Wireless Sensor Networks Using a Moving Beacon with a Directional Antenna

Wireless sensor networking is a current topic of research areas and widely used in a variety of applications. The localization of sensor nodes is a fundamental problem in wireless sensor networks. Many localization approaches have been presented and can be implemented using some powerful nodes with GPS devices. In this paper, we introduce a distributed localization scheme, called Rectangle Overlapping Approach (ROA), using a moving beacon with a GPS and a directional antenna. The positions can be computed by simple operations according to the current state of the moving beacon, including the rotation angle and the position. Simulation results show that the proposed scheme is very efficient and the node positions can be determined accurately after the beacon operates along straight-line traverse routes.

Probabilistic Analysis of the (1 + 1)-Evolutionary Algorithm

We give a detailed analysis of the optimization time of the -Evolutionary Algorithm under two simple fitness functions (OneMax and LeadingOnes). The problem has been approached in the evolutionary algorithm literature in various ways and with different degrees of rigor. Our asymptotic approximations for the mean and the variance represent the strongest of their kind. The approach we develop is based on an asymptotic resolution of the underlying recurrences and can also be extended to characterize the corresponding limiting distributions. While most of our approximations can be derived by simple heuristic calculations based on the idea of matched asymptotics, the rigorous justifications are challenging and require a delicate error analysis.

Energy-aware data center networks

With developing on cloud computing, data center networks have received great attention recently. In order to support high availability and bandwidth, data center networks are usually designed based on peak traffic. Unfortunately, peak traffic does not happen all the time. This causes unnecessary energy wastage and leads to low network utilization. We aim to minimize the power usage of data center networks by consolidating traffic flows and turning off unnecessary network devices. To support high availability, a requirement of two node-disjoint paths between the source and destination of each traffic flow is considered. We formulate the problem in mathematical format by integer linear programming (ILP). Due to its high computational complexity, we further propose a heuristic approach for practical use. The experimental results show that the heuristic approach reduces the power consumption by 15 to 35% in average while improving the availability by about 15% with significant improvement on computation time.

Task scheduling for grid computing systems using a genetic algorithm

A grid computing environment is a parallel and distributed system that brings together various computing capacities to solve large computational problems. Task scheduling is a critical issue for grid computing; in task scheduling, tasks are mapped onto system processors with the aim of achieving good performance in terms of minimizing the overall execution time. In previous studies, there have been several approaches to solving the task-scheduling problem by genetic algorithms, which is a random search technique that is inspired by natural biological evolution. This study presents a genetic algorithm for solving the problem of task scheduling with two main ideas: a new initialization strategy to generate the first population and new genetic operators based on task–processor assignments to preserve the good characteristics of the found solutions. Our proposed algorithm is implemented and evaluated using a set of well-known applications in our specifically defined system environment. The experimental results show that the proposed algorithm outperforms other popular algorithms in a variety of scenarios with several parameter settings.

A study of QoS guarantee and fairness based on cross-layer channel state in Worldwide Interoperability for Microwave Access

Because the bandwidth usage of wireless transmission is limited, one of the major research topics in this field is to improve system throughput by supporting multiple users with limited bandwidth resources. Although there are several studies on cross-layer designs for improving system throughput, previous research on quality-of-service guarantee and fairness are relatively rare. This study proposes a cross-layer subcarrier permutation (CLSP) mechanism that uses cross-layer strategies to select suboptimal subcarriers. Service flows simulations in the IEEE 802.16e system indicate that CLSP achieved a lower delay time and a long-term fairness among multiple users. Experimental results further show that the throughput of CLSP is 28 percent higher than that of the partial usage of subchannels model using the orthogonal frequency division multiple access technique. Copyright

Maxima-finding algorithms for multidimensional samples: A two-phase approach

Simple, two-phase algorithms are devised for finding the maxima of multidimensional point samples, one of the very first problems studied in computational geometry. The algorithms are easily coded and modified for practical needs. The expected complexity of some measures related to the performance of the algorithms is analyzed. We also compare the efficiency of the algorithms with a few major ones used in practice, and apply our algorithms to find the maximal layers and the longest common subsequences of multiple sequences.

Generalized Diameters of the Mesh of Trees

Abstract The mesh of trees, which owns two favorable properties, small diameter and large bisection, is known as the fastest network when considered in terms of speed. In this paper we show that the wide diameter, fault diameter and Rabin number, which are three generalizations of diameter, of a two-dimensional 2n×2n mesh of trees are equal to 5n + 1.

RSSI-based localization for wireless sensor networks with a mobile beacon

Localization is one of the fundamental issues in wireless sensor networks. Many approaches including range-based and range-free categories have been proposed to determine sensor node locations. The range-based algorithms often achieve higher accuracy, but they are easier to be interfered and an additional hardware is required. In this paper, we present a fast and simple localization scheme for wireless sensor networks, which is computed by simple operations with the specific approximate RSSI value on an accelerative signal attenuation model. Simulation results show that our scheme is very efficient and that the node positions can be determined accurately.

An intelligent target localization in wireless sensor networks

Recently, wireless sensor networks (WSNs) has been widely recognized as a promising technology in latest development in green buildings communications. Localization is one of the fundamental issues in wireless sensor networks. The accuracy of estimated positions can be significantly helpful to use in an intelligent e-applications. In this paper, we propose a fast and efficient localization scheme based on RSSI model for wireless sensor networks. The node locations are computed by performing simple geometric calculations that rely on the broadcasting information from a mobile beacon equipped with GPS. Simulation results show the node positions can be determined accurately and our proposed scheme outperforms previous well known localization schemes.

Upper Bounds for Dynamic Memory Allocation

In this paper, we study the upper bounds of memory storage for two different allocators. In the first case, we consider a general allocator that can allocate memory blocks anywhere in the available heap space. In the second case, a more economical allocator constrained by the address-ordered first-fit allocation policy is considered. We derive the upper bound of memory usage for all allocators and present a systematic approach to search for allocation/deallocation patterns that might lead to the largest fragmentation. These results are beneficial in embedded systems where memory usage must be reduced and predictable because of lack of swapping facility. They are also useful in other types of computing systems.