Power Distribution Management System revisited: Single-thread vs. Multithread Performance

Power Distribution Management System (PDMS) uses very sophisticated algorithms to deliver reliable and efficient functioning of power distribution networks (PDN). PDNs are represented using very large sparse matrices, whose processing is computationally very demanding. Dividing large PDNs into smaller sub-networks results in smaller sparse matrices, and further processing each sub-network in parallel significantly improves the performance of PDMS. Using multithreading to further process each sub-network however degrades PDMS performance. Single-thread processing of sub-network sparse matrices gives much better performance results, mainly due to the structure of these matrices (indefinite and very sparse) and synchronization overhead involved in multi-thread operations. In this paper an overview of PDMS system is presented, and its performance given single-thread and multiple threads is compared. The results have shown that for some applications, single-threaded implementation in multi-process parallel environment gives better performance than multithreaded implementation

Intrusion Detection System using Fuzzy Logic

Intrusion detection plays an important role in today’s computer and communication technology. As such it is very important to design time efficient Intrusion Detection System (IDS) low in both, False Positive Rate (FPR) and False Negative Rate (FNR), but high in attack detection precision. To achieve that, this paper proposes IDS model based on Fuzzy Logic. Proposed model consists of three parts, Input Reduction System (IRS), which uses Principal Component Analysis to reduce the dimensions of the system from 41 to 10, Classification System, which uses Fuzzy C Means to create data clusters based on training data and Pattern Recognition System based on Nearest Neighborhood method, which classifies new-coming data records to their respective clusters. Based on different attack types, the system performance in classification process is different and the best performance is achieved for PROBE attack, with 99.3% success rate, and the best performance in pattern recognition is achieved for U2R with 58.8% of success rate

Multiple Methods for Genome Filtering

Filters are fast algorithms, which help to preprocess DNA sequences in order to reduce the time and complexity of approximate motif search. Multiple filtering methods exist, and this paper classifies the filtering algorithms based on their approach, numerical analysis or digital signal processing, and it briefly reviews both classes of filters. The paper also reflects on filters currently used in popular software for genomic processing

LU Factorization Algorithm with Minimum Degree Ordering in Power Distribution Network Problems

Power systems computations for nowadays common large distributed systems typically involve the usage of very large sparse matrices, whose analysis and verification is very time and memory consuming. When blocked, sparse matrices can be processed much more efficiently, and this made blocked sparse matrices widely used in acquiring solutions for power system problems. The established sparse matrix storage and reordering techniques however do not fully utilize the existing computer architecture, thus search for efficient sparse system solution is ongoing. This paper presents adjustments of well-known LU factorization algorithm suitable for use in power distribution network applications. LU factorization algorithm processes data in blocks and uses minimum degree ordering to accelerate the computations

Intelligent Memory Allocation based on Fuzzy Logic

Based on the Computerized Parkinson’s Law “work expands so as to fill the time available for its completion” (Thimbleby, 1993) it can be deduced that regardless of the size of the memory, there will always be programs to completely fill, or even overload that memory. Thus intelligent/sensible memory allocation process is crucial to system’s performance. However, due to the constant increase of processing power and the growth and spread of distributed systems, such as grid and cloud computing, memory allocation becomes a great challenge in the area of memory management today. Making allocation intelligent, so that the memory fragmentation and response time are reduced would be great, and in this research, this was attempted. The research presents Fuzzy Allocator, memory allocator based on fuzzy inference system. The allocator manages to sort the incoming memory requests according to their size and the size of free memory slot (hole). The output of the fuzzy allocator is the order in which the allocation of memory will be performed on the incoming memory requests. It reorders the incoming memory request queue so that the response time is reduced, and fragmentation is minimized