206624051
A Comparative Study of ANT-Based Optimization for Dynamic Routing
An ANT is a mobile agent that is capable of solving various kinds of routing and congestion problems in computer networking by continuously modifying routing tables in respond to congestion. In a distributed problem solving paradigm, a society of ANTs (each contributing some information) collaborate to solve a larger problem. In recent years, Ant-based algorithms were used to solve classical routing problems such as: Travelling Salesman Problem, Vehicle Routing Problem, Quadratic Assignment Problem, connection-oriented/connectionless routing, sequential ordering, graph coloring and shortest common supersequence. By introducing the general idea of Ant-based algorithms with a focus on Ant Colony Optimization (ACO) and their mathematical models, this paper brings together a collection of ACO algorithms discussed their features, strength and weaknesses.
2764182
Multiple ant-colony optimization for network routing
An ANT is a mobile agent that is capable of solving various kinds of routing and congestion problems in computer networking by continuously modifying routing tables in response to congestion. In a distributed problem solving paradigm, a society of ANTs (each contributing some information) collaborate to solve a larger problem. In recent years, ant-based algorithms were used to solve classical routing problems such as: traveling salesman problem, vehicle routing problem, quadratic assignment problem, connection-oriented/connectionless routing, sequential ordering, graph coloring and shortest common supersequence. This paper introduces the general idea of Ant-based algorithms with a focus on ant colony optimization (ACO), and their features, strengths, weaknesses and applications in network routing. The contribution of this paper is the proposal of a multiple ant-colony optimization (MACO) approach for network routing.
2820577
Localizing XML Documents through XSLT
Existing efforts on XML internationalization and localization have been focusing on the contents of XML documents instead of on the meta presentations such as tags and attributes. Although XML standard allows the use of unicode throughout a document including the meta level presentations, most tags and attributes of XML documents are still defined in English, which makes it difficult for native people to use. This paper presents a pure XSLT stylesheet to completely translate and localize XML documents into different natural languages. Furthermore, we also describe how this technique can be applied to translation problems in programming (e.g. C and Java) or documentation (e.g. LaTeX) languages when the program or the document can be converted to and from XML documents.
5687277
A self-adaptive scheduling algorithm of on-demand broadcasts
In mobile wireless systems data on air can be accessed by a large number of mobile users. Many of these applications such as wireless internets and traffic information systems are pull-based, that is, they respond to on-demand user requests. In this paper, we study the scheduling problems of on-demand broadcast environments. Traditionally, the response time of the requests has been used as a performance measure. In this paper we consider the performance as the average cost of request composed of three kinds of costs—access time cost, tuning time cost, and cost of handling failure request. Our main contribution is a self-adaptive scheduling algorithm named LDFC, which computes the delay cost of data item as the priority for broadcast. It performs well compared with some previous algorithms in this context.
45543536
Dynamic File Allocation in Storage Area Networks with Neural Network Prediction
Disk arrays are widely used in Storage Area Networks (SANs) to achieve mass storage capacity and high level I/O parallelism. Data partitioning and distribution among the disks is a promising approach to minimize the file access time and balance the I/O workload. But disk I/O parallelism by itself does not guarantee the optimal performance of an application. The disk access rates fluctuate with time because of access pattern variations, which leads to a workload imbalance. The user access pattern prediction is of great importance to dynamic data reorganization between hot and cool disks. Data migration occurs according to current and future disk allocation states and access frequencies. The objective of this paper is to develop a neural network based disk allocation trend prediction method and optimize the disks’ file capacity to their balanced level. A Levenberg-Marquardt neural network was adopted to predict the disk access frequencies with the I/O track. History. Data reorganization on disk arrays was optimized to provide a good workload balance. The simulation results proved that the proposed method performs well.
18180354
Study of coordinative gene expression at the biological process level
MOTIVATION
Cellular processes are not isolated groups of events. Nevertheless, in most microarray analyses, they tend to be treated as standalone units. To shed light on how various parts of the interlocked biological processes are coordinated at the transcription level, there is a need to study the between-unit expressional relationship directly.


RESULTS
We approach this issue by constructing an index of correlation function to convey the global pattern of coexpression between genes from one process and genes from the entire genome. Processes with similar signatures are then identified and projected to a process-to-process association graph. This top-down method allows for detailed gene-level analysis between linked processes to follow up. Using the cell-cycle gene-expression profiles for Saccharomyces cerevisiae, we report well-organized networks of biological processes that would be difficult to find otherwise. Using another dataset, we report a sharply different network structure featuring cellular responses under environmental stress.


SUPPLEMENTARY INFORMATION
http://kiefer.stat.ucla.edu/lap2/download/KL_supplement.pdf.
12847164
Storage Virtualization System with Load Balancing for SAN
Logical Volume Manager (LVM) has been a key subsystem for online disk storage management. Additional layer is created in the kernel to present a logical view of physical storage devices. Many transparent functions can be implemented between the logical and physical layers, such as merging several physical disks into a larger logical device, resizing logical devices without stopping the system. In a logical volume group, files can be striped into several physical disks so as to achieve high I/O performance. But data I/O parallelism by itself does not guarantee the optimal performance of an application since higher data throughput does not necessarily result in better application performance. This paper studied the dynamic load balancing and data redistribution algorithms in the storage virtualization layer when the load becomes imbalanced across the disks due to access pattern fluctuation. An extension of the heuristic load balancing method was proposed to the storage virtualization subsystem of Tsinghua-Mass Storage Network System (TH-MSNS). Logical volume I/O request status is monitored and the physical disks are sorted according to the access number of Logical Extents (LE) per time unit. The I/O operations on a LE of the hottest disk are transparently migrated to other disks. The preliminary performance simulations under a WWW server file access workload give satisfactory results by the promising cooling algorithm in storage virtualization systems.