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In this work, we will illustrate our attempt to exploit log files that are recorded locally on each node in a distributed system or a wired/wireless network. In order to improve the efficiency of retrieving data, we propose the idea of building a global view of the system with a clustered log‐collecting scheme; this would help the monitoring node gain a whole view of the system by building up and maintaining high‐level log files. We also introduce an efficient, tamper‐evident scheme to detect whether a local flow‐net has been deliberately compromised. We provide both simulation results and implementation of the proposed scheme on Emulab, a network testbed. Copyright © 2011 John Wiley & Sons, Ltd.

Date of publication xxxx 00, 0000, date of current v ersion xxxx 00, 0000.

Metaprogramming has shown much promise for improving the quality of software by offering programming language techniques to address issues of modularity, reusability, maintainability, and extensibility. Thus far, the power of metaprogramming has not been explored deeply in the area of high performance computing (HPC). There is a vast body of legacy code written in Fortran running throughout the HPC community. In order to facilitate software maintenance and evolution in HPC systems, we introduce a DSL that can be used to perform source-to-source translation of Fortran programs by providing a higher level of abstraction for specifying program transformations. The underlying transformations are actually carried out through a metaobject protocol (MOP) and a code generator is responsible for translating a SPOT program to the corresponding MOP code. The design focus of the framework is to automate program transformations through techniques of code generation, so that developers only need to specify desired transformations while being oblivious to the details about how the transformations are performed. The paper provides a general motivation for the approach and explains its design and implementation. In addition, this paper presents case studies that illustrate the potential of our approach to improve code modularity, maintainability, and productivity.

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