8057684
A Scalable Parallel Algorithm for Global Optimization Based on Seed-Growth Techniques
Global optimization requires huge computations for complex objective functions. Conventional global optimization based on stochastic and probability algorithms can not guarantee an actual global optimum with finite searching iteration. A numerical implementation of the scalable parallel Seed-Growth (SG) algorithm is introduced for global optimization of two-dimensional multi-extremal functions. The proposed parallel SG algorithm is characterized by a parallel phase that exploits the local optimum neighborhood features of the objective function assigned to each processor. The seeds are located at the optimum and inner neighborhood points. Seeds grow towards nearby grids and attach flags to them until reaching the boundary points in each dimension. When all grids in the subspace assigned to each CPU have been searched, the local optimum neighborhood boundaries are determined. As the definition domain is completely divided into different subdomains, the global optimal solution of each CPU is found. A coordination phase follows which, by a synchronous interaction scheme, optimizes the partial results obtained by the parallel phase. The actual global optimum in the total definition space can be determined. Numerical examples demonstrate the high efficiency, global searching ability, robustness and stability of this method.
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.
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.
18703573
Ant colony optimization for routing and load-balancing: survey and new directions
Although an ant is a simple creature, collectively a colony of ants performs useful tasks such as finding the shortest path to a food source and sharing this information with other ants by depositing pheromone. In the field of ant colony optimization (ACO), models of collective intelligence of ants are transformed into useful optimization techniques that find applications in computer networking. In this survey, the problem-solving paradigm of ACO is explicated and compared to traditional routing algorithms along the issues of routing information, routing overhead and adaptivity. The contributions of this survey include 1) providing a comparison and critique of the state-of-the-art approaches for mitigating stagnation (a major problem in many ACO algorithms), 2) surveying and comparing three major research in applying ACO in routing and load-balancing, and 3) discussing new directions and identifying open problems. The approaches for mitigating stagnation discussed include: evaporation, aging, pheromone smoothing and limiting, privileged pheromone laying and pheromone-heuristic control. The survey on ACO in routing/load-balancing includes comparison and critique of ant-based control and its ramifications, AntNet and its extensions, as well as ASGA and SynthECA. Discussions on new directions include an ongoing work of the authors in applying multiple ant colony optimization in load-balancing.
31072695
Making XML document markup international
In name and in practice, the World-Wide Web (hereafter Web) is used around the World beyond English-speaking areas. This creates a tremendous need to internationalize standard terminology used in the technologies that make the Web possible. Existing efforts on XML internationalization (i18n) and localization (i10n) have focused on the content of XML documents instead of the terms used in markup (annotations) such as elements and attributes. The SGML standard ISO 8879 supports the use of Unicode (ISO 10646) throughout a document, including markups. However, most elements and attributes of XML documents are still defined in English, thereby limiting their use among non-English speakers. This paper presents an XSLT-based method that can completely localize the markup of XML documents into different natural languages. We also describe how the proposed technique can be applied to translation problems in programming (e.g. C and Java) or documentation (e.g. LATEX or other formatting languages) so that a program or a document can be converted to and from an XML format.
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.