New Method of Measuring TCP Performance of IP Network using Bio-computing

The measurement of performance of Internet Protocol IP network can be done by Transmission Control Protocol TCP because it guarantees send data from one end of the connection actually gets to the other end and in the same order it was send, otherwise an error is reported. There are several methods to measure the performance of TCP among these methods genetic algorithms, neural network, data mining etc, all these methods have weakness and can't reach to correct measure of TCP performance. This paper proposed a new method of measuring TCP performance for real time IP network using Biocomputing, especially molecular calculation because it provides wisdom results and it can exploit all facilities of phylogentic analysis. Applying the new method at real time on Biological Kurdish Messenger BIOKM model designed to measure the TCP performance in two types of protocols File Transfer Protocol FTP and Internet Relay Chat Daemon IRCD. This application gives very close result of TCP performance comparing with TCP performance which obtains from Little's law using same model (BIOKM), i.e. the different percentage of utilization (Busy or traffic industry) and the idle time which are obtained from a new method base on Bio-computing comparing with Little's law was (nearly) 0.13%. KEYWORDS Bio-computing, TCP performance, Phylogenetic tree, Hybridized Model (Normalized), FTP, IRCDComment: 17 Pages,10 Figures,5 Table

Cloud based testing of business applications and web services

This paper deals with testing of applications based on the principles of cloud computing. It is aimed to describe options of testing business software in clouds (cloud testing). It identifies the needs for cloud testing tools including multi-layer testing; service level agreement (SLA) based testing, large scale simulation, and on-demand test environment. In a cloud-based model, ICT services are distributed and accessed over networks such as intranet or internet, which offer large data centers deliver on demand, resources as a service, eliminating the need for investments in specific hardware, software, or on data center infrastructure. Businesses can apply those new technologies in the contest of intellectual capital management to lower the cost and increase competitiveness and also earnings. Based on comparison of the testing tools and techniques, the paper further investigates future trend of cloud based testing tools research and development. It is also important to say that this comparison and classification of testing tools describes a new area and it has not yet been done

Iso-energy-efficiency: An approach to power-constrained parallel computation

Future large scale high performance supercomputer systems require high energy efficiency to achieve exaflops computational power and beyond. Despite the need to understand energy efficiency in high-performance systems, there are few techniques to evaluate energy efficiency at scale. In this paper, we propose a system-level iso-energy-efficiency model to analyze, evaluate and predict energy-performance of data intensive parallel applications with various execution patterns running on large scale power-aware clusters. Our analytical model can help users explore the effects of machine and application dependent characteristics on system energy efficiency and isolate efficient ways to scale system parameters (e.g. processor count, CPU power/frequency, workload size and network bandwidth) to balance energy use and performance. We derive our iso-energy-efficiency model and apply it to the NAS Parallel Benchmarks on two power-aware clusters. Our results indicate that the model accurately predicts total system energy consumption within 5% error on average for parallel applications with various execution and communication patterns. We demonstrate effective use of the model for various application contexts and in scalability decision-making

An Extensible Timing Infrastructure for Adaptive Large-scale Applications

Real-time access to accurate and reliable timing information is necessary to profile scientific applications, and crucial as simulations become increasingly complex, adaptive, and large-scale. The Cactus Framework provides flexible and extensible capabilities for timing information through a well designed infrastructure and timing API. Applications built with Cactus automatically gain access to built-in timers, such as gettimeofday and getrusage, system-specific hardware clocks, and high-level interfaces such as PAPI. We describe the Cactus timer interface, its motivation, and its implementation. We then demonstrate how this timing information can be used by an example scientific application to profile itself, and to dynamically adapt itself to a changing environment at run time

Measuring in-plane deflections and strains through visual sensing techniques for civil infrastructure applications

Maintaining the integrity and safety of civil infrastructures such as bridges, dams, tunnels and high-rise buildings is an essential task for civil engineers. Collapse or damage of these civil infrastructures may lead to a tremendous amount of injuries and casualties. To alleviate this situation, a real-time surveillance method enabled by visual sensing techniques is proposed in this thesis. The advances of applying visual sensing techniques, for instance, are allowing practical deployment for large extended systems in a more cost-effective way. Also, the image or video data can be easily used for long-term condition assessments.;The proposed method entails applying visual sensing techniques to measure in-plane deflections and strains of structural members for civil infrastructure applications. In specific, it employs visual sensors (digital/industrial cameras) to capture and record a series of continuous image frames of the targets. Then automated feature detection and matching algorithms are applied to detect and match object features in the consecutive image frames. Based on the location information of the detected features, the in-plane object displacement can be accurately calculated through keeping tracking those features in the continuous image frames. Next, an optimized interpolation procedure is conducted to obtain dense displacement field for the object. And the strains can be consequently recovered from the displacement field through computing its derivatives.;In this research, firstly, the work of evaluating the optimum feature detection and matching algorithm is reported, which is the key task to achieve accurate surveillance. A series of experiments were conducted to compare the three algorithms: DIC (Digital Image Correlation), SIFT (Scale Invariant Feature Transform), and SURF (Speeded-Up Robust Features). The experimental result indicated that the DIC algorithm reveals superiority among the three algorithms and holds the most potential for measuring in-plane deflections and strains of civil infrastructures. To further validate our method, we employed high-speed industrial camera (Manta G223B) to capture a series of continuous image frames of deformed real-world scenarios. The DIC algorithm was adopted for the feature detection and matching process. As the output, the displacement and strains were calculated and then compared with the ground truth in order to evaluate the accuracy performance of the method. Colored strain maps were generated by using different colors to reflect different strain levels in an intuitive way. The experimental result indicated that our method can achieve highly accurate measuring performance of computing in-plane displacements and strains for civil infrastructure applications. The proposed method has several advantages when compared to pre-existing methods (such as sensor networks). It can generate accurate full-field deflections and strains of the target. Besides, the cost-effective equipment and much more convenient set-up procedures will enable engineers to operate periodically and apply for different scales of civil infrastructure applications