1037558
PhoenixG: a unified management framework for industrial information grid
The industrial information grid is a special kind of system, the users of which exclusively own geographically distributed computing resources for business service, and try to maintain the lowest total cost of ownership while guaranteeing quality of service. In this paper, we classify the industrial information grid as an extension to grid problem; develop a unified management framework for new management paradigm, which supports the distribution of administration labor and collaboration of system administrator at different locations; propose a self-organizing algorithm, which supports the initial establishment, daily management and exception processing of industrial information grid. Finally, we evaluate the performance of system management, and analyze the management overhead with this new management paradigm.
15192522
A layered design methodology of cluster system stack
The application range of cluster has expanded beyond scientific computing, but the present cluster system software fails to provide a flexible architecture to promote code reuse and facilitate building cluster system software for different computing contexts, most of which are developed from scratch case by case, or integrated or packaged with ldquothe best practicerdquo. In this paper, we have proposed a layered design methodology to build cluster system stack with different layers concentrating on different functions, and developed common sets of core service as reusing framework for different computing context. Following this methodology, we have built Phoenix-a complete cluster system stack for both scientific and business computing, which is verified and deployed on Dawning 4000 A super computer for scientific computing and other cluster systems for business computing. The qualitative evaluation and our practices show the design methodology of Phoenix has advantages over other methodologies.
2643198
Easy and reliable cluster management: the self-management experience of Fire Phoenix
High-Performance clusters are rapidly becoming an important computing platform for both scientific and business applications. To fulfil the new demands and challenges, cluster system software is inevitably complex. Even for experienced administrators, the management of a cluster system is an exhausting job. This paper introduces Fire Phoenix, a scalable and self-managing cluster system software that supports both scientific and commercial applications. With the self-configuring and self-healing features, much of the machine configuration and error recovery can be done automatically. Our design has been proven effective in the operations of the Dawning 4000A supercomputer, which is the biggest cluster system in China
14894173
Gingko: correlating causal paths in distributed systems
Many large-scale systems are distributed systems of multiple communicating components. Finding causal paths of message traces between components throughout these systems is important to uncover runtime behaviors and identify the root cause of failures, but this "art" often hides in the heads of developers or domain experts. Our goal is to design tools and algorithms to help developers record this art into logs and help the modestly-skilled users and system administrators master it to make better use and management of distributed systems. In this paper, we present a methodology that automatically builds the causal paths of message traces by 1) an agreement with programmers on the style and content of logs produced by operational distributed systems they develop and 2) a correlation algorithm to build message causal paths with the clues from these logs. To validate this mechanism, we have implemented Gingko, a prototype providing a tool chain for users to gain better comprehensions of distributed systems and to debug them efficiently when errors happen.
11038275
Exploiting idle register classes for fast spill destination
On today's microprocessors, there often exist several different types of registers, e.g. general purpose registers and floating point registers. A given program may use one type of registers much more frequently than other types. This creates an opportunity to employ the infrequently used registers as spill destinations for the more frequently used register types. In this paper, we present a code optimization method named idle register exploitation (IRE) to exploit such opportunities. We developed a model, called the IRE model, or IREM, to determine the static performance gains of IRE versus spilling to the stack. On a microprocessor with fast data paths between different types of registers, we find that IRE method speeds up the execution of the SPECint benchmark suite from 1.7% to 10%. In contrast, on microprocessors with less efficient data transfer paths, the performance gain is limited. In some cases, performance may even suffer degradation. This result argues strongly for the adoption of fast data paths between different types of registers for the purpose of reducing register spills, which is important in view of the increased significance of memory bottlenecks on future microprocessors.
14795008
The design methodology of Phoenix cluster system software stack
Though many research groups have explored the design methodology of cluster system software stack, few works discuss what constitutes a good one. In this paper, we choose four criteria throughout the lifecycle of cluster system software stack to evaluate its design methodology, including code reusability, evolveability, adaptability and manageability. According to the four criteria, we have proposed a management service-based layered design methodology and built a complete cluster system software stack for both scientific and business computing. Our practices and evaluations show our design methodology has advantages over others in terms of the proposed criteria.
1170919
A Hybrid Method for Constructing Semi-structural Process in Knowledge-Intensive Information System
Recent research on processes in information system has revealed that processes in prevalent fields present to be semi-Structural. It seems to be structural at the process layer, but in the enacting time, executive situation might change due to various reasons. To solve that, in this paper, we illustrate how the flexibility of construction processes can be handled using a hybrid method. At structural layer, we construct the process in imperative way, whereas at the lower level, we decompose tasks into fine-grained operations, and declaratively perceive operation sequence. Moreover, we propose a prototype tool for constructing and enacting semi-Structural business processes.
18306747
Visualizing simulation and testbed of wireless sensor networks with NetTopo
In this paper, we present an integrated framework called NetTopo for providing both simulation and visualization functions to assist the investigation of algorithms in WSNs. NetTopo provides a common virtual WSN for the purpose of interaction between sensor devices and simulated virtual nodes. Two case studies are described to prove the effectiveness of NetTopo.
17514115
Low-complexity adaptive step size constrained constant modulus sg-based algorithms for blind adaptive beamforming
In this paper, two low-complexity adaptive step size algorithms are investigated for blind adaptive beamforming. Both of them are used in a stochastic gradient (SG) algorithm, which employs the constrained constant modulus (CCM) criterion as the design approach. A brief analysis is given for illustrating their properties. Simulations are performed to compare the performances of the novel algorithms with other well-known methods. Results indicate that the proposed algorithms achieve superior performance, better convergence behavior and lower computational complexity in both stationary and non-stationary environments.
14688887
Data Compression Algorithm Based on Hierarchical Cluster Model for Sensor Networks
A new distributed algorithm of data compression based on hierarchical cluster model for sensor networks is proposed, in which, the whole sensor network is mapped into a kind of hierarchical clusters model firstly, and then different wavelet transform models are used to commit data compression in inner and super clusters respectively. Theoretical analyses and simulation results show that, the above new methods have good performance of approximation, and can compress data and reduce the amount of data efficiently.
15406626
A Lightweight Sensor Network Management System Design
In this paper, we propose a lightweight and transparent management framework for TinyOS sensor networks, called L-SNMS, which minimizes the overhead of management functions, including memory usage overhead, network traffic overhead, and integration overhead. We accomplish this by making L-SNMS virtually transparent to other applications hence requiring minimal integration. The proposed L-SNMS framework has been successfully tested on various sensor node platforms, including TelosB, MICAz and IMote2.