Localization through Map Stitching in Wireless Sensor Networks

Node localization is an essential problem in ad hoc wireless sensor networks. Map stitching is a type of localization algorithm that has received a great deal of attention recently. In this algorithm, the network is divided into small overlapping sub-regions, each of which creates a local map. Then, the local maps are stitched together to form a single global map. In this paper, we first propose a new technique for map-to-map stitching that exploits every available distances between two maps. Next, we propose a few anchor-free localization algorithms based on our stitching technique. We experimentally studied the performance of our algorithms under various settings. The results show that our method achieves a significant performance improvement upon the existing method.     

A survey of Flash Translation Layer

Recently, flash memory is widely adopted in embedded applications as it has several strong points, including its non-volatility, fast access speed, shock resistance, and low power consumption. However, due to its hardware characteristics, specifically its “erase-before-write” feature, it requires a software layer known as FTL (Flash Translation Layer). This paper surveys the state-of-the-art FTL software for flash memory. It defines the problems, addresses algorithms to solve them, and discusses related research issues. In addition, the paper provides performance results based on our implementation of each FTL algorithm.     

The Effects of Stitching Orders in Patch-and-Stitch WSN Localization Algorithms

A "patch-and-stitch” localization algorithm divides the network into small overlapping subregions. Typically, each subregion consists of a node and all or some of its neighbors. For each subregion, the algorithm builds a local map, called a patch, which is actually an embedding of the nodes it spans in a relative coordinate system. Finally, the algorithm stitches those patches to form a single global map. In a patch-and-stitch algorithm, the stitching order makes an influence on both the performance and the complexity of the algorithm. In this paper, we present a formal framework to deal with stitching orders in patch-and-stitch localization algorithms. In our framework, the stitching order is determined by a stitching scheme and the stitching scheme consists of a stitching policy and a potential function. The potential function is to predict how well a patch will be stitched if patches are stitched according to a given partial order. The stitching policy is a mechanism that determines the stitching order based on the predictions by the potential function. We present various stitching schemes and evaluate them through simulations. In addition, we apply the patch-and-stitch strategy into the anchor-based localization and propose a clustering-based localization algorithm. A potential function is used to partition the network into clusters each of which is centered at an anchor node. For each cluster, a cluster map is constructed via the anchor-free localization algorithm. Then, those cluster maps are combined to form a single global map. We propose a stitching technique for combining those cluster maps and analyze the performance of the algorithm by simulations.     

Index set: A practical indexing scheme for object database systems

Efficient indexing in a class hierarchy is essential for the achievement of high performance in query evaluation for object database management systems. In this paper, we present a practical indexing scheme, index set, which provides good index configuration for any real database environment. The proposed scheme considers the distribution of key values, as well as query patterns such as query weight on each class. The index set can easily be applied to any database system, since it uses the well-known B⁺-tree structure. We develop a cost model and, through experiments, demonstrate the performance of the proposed scheme over various class hierarchies.