TechNews digests: Jan - Nov 2005

TechNews is a technology, news and analysis service aimed at anyone in the education sector keen to stay informed about technology developments, trends and issues. TechNews focuses on emerging technologies and other technology news. TechNews service : digests september 2004 till May 2010 Analysis pieces and News combined publish every 2 to 3 month

Building a scalable global data processing pipeline for large astronomical photometric datasets

Astronomical photometry is the science of measuring the flux of a celestial object. Since its introduction, the CCD has been the principle method of measuring flux to calculate the apparent magnitude of an object. Each CCD image taken must go through a process of cleaning and calibration prior to its use. As the number of research telescopes increases the overall computing resources required for image processing also increases. Existing processing techniques are primarily sequential in nature, requiring increasingly powerful servers, faster disks and faster networks to process data. Existing High Performance Computing solutions involving high capacity data centres are complex in design and expensive to maintain, while providing resources primarily to high profile science projects. This research describes three distributed pipeline architectures, a virtualised cloud based IRAF, the Astronomical Compute Node (ACN), a private cloud based pipeline, and NIMBUS, a globally distributed system. The ACN pipeline processed data at a rate of 4 Terabytes per day demonstrating data compression and upload to a central cloud storage service at a rate faster than data generation. The primary contribution of this research is NIMBUS, which is rapidly scalable, resilient to failure and capable of processing CCD image data at a rate of hundreds of Terabytes per day. This pipeline is implemented using a decentralised web queue to control the compression of data, uploading of data to distributed web servers, and creating web messages to identify the location of the data. Using distributed web queue messages, images are downloaded by computing resources distributed around the globe. Rigorous experimental evidence is presented verifying the horizontal scalability of the system which has demonstrated a processing rate of 192 Terabytes per day with clear indications that higher processing rates are possible.Comment: PhD Thesis, Dublin Institute of Technolog

Evaluation of security vulnerabilities of popular computer and server operating systems under cyber attacks

Nowadays many operating systems are including security features in order to prevent network attacks, and since one of the roles of the OS is to manage the resources as efficient as possible. It is imperative to investigate the protection that is provided. Therefore, the scientific significance of this thesis was to evaluate, what type of built-in defense mechanisms that different OS’s had in place in order to mitigate these network attacks. In this thesis, we considered the security of the following globally deployed computer OS’s: Microsoft’s Windows 7, Apple’s OS X Lion, and Ubuntu 13.10. Furthermore, we also tested four server OS’s: Microsoft’s Server 2008 and 2012, Apple’s OS X Lion Server, and Ubuntu Server 12.04, and their performance under DoS attacks. Our experimental results show that the OS’s that were evaluated were found to have inadequate security protection and showed different degree of effectiveness in handling different DDoS attacks

Sandboxed, Online Debugging of Production Bugs for SOA Systems

Short time-to-bug localization is extremely important for any 24x7 service-oriented application. To this end, we introduce a new debugging paradigm called live debugging. There are two goals that any live debugging infrastructure must meet: Firstly, it must offer real-time insight for bug diagnosis and localization, which is paramount when errors happen in user-facing applications. Secondly, live debugging should not impact user-facing performance for normal events. In large distributed applications, bugs which impact only a small percentage of users are common. In such scenarios, debugging a small part of the application should not impact the entire system. With the above-stated goals in mind, this thesis presents a framework called Parikshan, which leverages user-space containers (OpenVZ) to launch application instances for the express purpose of live debugging. Parikshan is driven by a live-cloning process, which generates a replica (called debug container) of production services, cloned from a production container which continues to provide the real output to the user. The debug container provides a sandbox environment, for safe execution of monitoring/debugging done by the users without any perturbation to the execution environment. As a part of this framework, we have designed customized-network proxies, which replicate inputs from clients to both the production and test-container, as well safely discard all outputs. Together the network duplicator, and the debug container ensure both compute and network isolation of the debugging environment. We believe that this piece of work provides the first of its kind practical real-time debugging of large multi-tier and cloud applications, without requiring any application downtime, and minimal performance impact