Applying a reconfigurable multi-agent scheduler to product distribution

More intelligent scheduling methods are required for manufacturing scheduling due to the move to more agile systems. Multi-agent methods are one such approach. This paper describes the application of a reconfigurable multi-agent scheduler to the problem of allocating orders to warehouses in a distribution supply chain. This multi-agent system was originally developed for allocation of orders to machines in a highly reconfigurable manufacturing system and this work was aimed at investigating the ease of applying this same scheduler to other problems. It was found that this new application was readily achieved because of the modular structure of the scheduler. This paper shows how the application to the new problem was achieved.

Security in the online e-learning environment

This paper addresses the role of security in the collaborative e-learning environment, and in particular, the social aspects of security and the importance of identity. It represents a case study, completed in Nov 2004, which was conducted to test the sense of security that students experienced whilst using the wiki platform as a means of online collaboration in the tertiary education environment. Wikis, fully editable Web sites, are easily accessible, require no software and allow its contributors (in this case students) to feel a sense of responsibility and ownership. A comparison between two wiki studies will be made whereby one group employed user login and the other maintained anonymity throughout the course of the study. The results consider the democratic participation and evolution of the work requirements over time, which in fact ascertains the nonvalidity of administrative identification.

Finding rule groups to classify high dimensional gene expression datasets

Microarray data provides quantitative information about the transcription profile of cells. To analyze microarray datasets, methodology of machine learning has increasingly attracted bioinformatics researchers. Some approaches of machine learning are widely used to classify and mine biological datasets. However, many gene expression datasets are extremely high dimensionality, traditional machine learning methods can not be applied effectively and efficiently. This paper proposes a robust algorithm to find out rule groups to classify gene expression datasets. Unlike the most classification algorithms, which select dimensions (genes) heuristically to form rules groups to identify classes such as cancerous and normal tissues, our algorithm guarantees finding out best-k dimensions (genes), which are most discriminative to classify samples in different classes, to form rule groups for the classification of expression datasets. Our experiments show that the rule groups obtained by our algorithm have higher accuracy than that of other classification approaches

Supporting disconnected operations in mobile computing

Mobile computing has enabled users to seamlessly access databases even when they are on the move. However, in the absence of readily available high-quality communication, users are often forced to operate disconnected from the network. As a result, software applications have to be redesigned to take advantage of this environment while accommodating the new challenges posed by mobility. In particular, there is a need for replication and synchronization services in order to guarantee availability of data and functionality, (including updates) in disconnected mode. To this end we propose a scalable and highly available data replication and management service. The proposed replication technique is compared with a baseline replication technique and shown to exhibit high availability, fault tolerance and minimal access times of the data and services, which are very important in an environment with low-quality communication links.

Novel data management algorithms in peer-to-peer content distribution networks

The peer-to-peer content distribution network (PCDN) is a hot topic recently, and it has a huge potential for massive data intensive applications on the Internet. One of the challenges in PCDN is routing for data sources and data deliveries. In this paper, we studied a type of network model which is formed by dynamic autonomy area, structured source servers and proxy servers. Based on this network model, we proposed a number of algorithms to address the routing and data delivery issues. According to the highly dynamics of the autonomy area, we established dynamic tree structure proliferation system routing, proxy routing and resource searching algorithms. The simulations results showed that the performance of the proposed network model and the algorithms are stable.

Planar receiver placement for unique emitter localization for indoor applications

This paper investigates two independent approaches to verify the necessary and sufficient condition to guarantee a unique solution for a passive emitter localization system based on time difference of arrival measurements from an
array of sensors.

A multilevel trust management framework

Lack of trust in e-commerce transactions has been identified by researchers as one of the main factors that hamper e-commerce from reaching its full potential. Various trust-related supporting features for online transactions are available to improve trust management. However, most of these existing approaches have insufficient conditions to establish online trust among businesses and customers. There are many relevant factors that influence potential buyers to make decisions. In this paper, we identify several desirable properties of an ideal trust management system that existing trust management systems do not support. A multilevel trust management framework is proposed to improve the support for existing trust management in e-commerce.

Finding motifs in miRNA sequences

Recently, the emergence of non-coding miRNA has attracted biology and computer researchers. miRNA plays an important role in regulation of genes. Finding motifs in RNA is one of important topics. In our work, we attempt to find motifs in mature miRNA from combinations ranging from two to ten nucleotides. Interestingly, we have found several motifs only appear in mature miRNA but not appear in other regions of primary miRNA sequences taken from latest miRNA datasets. The findings of our investigation may help in the building model to predict all possible miRNAs in genomes

Non-quantized minimum free energy in untranslated region exons

In an attempt to improve automated gene prediction in the untranslated region of a gene, we completed an in-depth analysis of the minimum free energy for 8,689 sub-genetic DNA sequences. We expanded Zhang's classification model and classified each sub-genetic sequence into one of 27 possible motifs. We calculated the minimum free energy for each motif to explore statistical features that correlate to biologically relevant sub-genetic sequences. If biologically relevant sub-genetic sequences fall into distinct free energy quanta it may be possible to characterize a motif based on its minimum free energy. Proper characterization of motifs can lead to greater understanding in automated genefinding, gene variability and the role DNA structure plays in gene network regulation.

Our analysis determined: (1) the average free energy value for exons, introns and other biologically relevant sub-genetic sequences, (2) that these subsequences do not exist in distinct energy quanta, (3) that introns exist however in a tightly coupled average minimum free energy quantum compared to all other biologically relevant sub-genetic sequence types, (4) that single exon genes demonstrate a higher stability than exons which span the entire coding sequence as part of a multi-exon gene and (5) that all motif types contain a free energy global minimum at approximately nucleotide position 1,000 before reaching a plateau. These results should be relevant to the biochemist and bioinformatician seeking to understand the relationship between sub-genetic sequences and the information behind them.

Taxonomy and survey of location management systems

In wireless mobile computing, location management is introduced whenever users move from one place to another. In order to track a mobile user, the system must store information about their current location and report new locations to a home base station. Numerous techniques have been proposed to optimally manage the location of mobile hosts in mobile networks. This paper attempts to present a more structured and comprehensive analysis of the current location management techniques architectures and their technology enablers. We discuss some of the principal issues involved in location management and present a taxonomy and survey of location management strategies that have been proposed in the literature over the years for mobile computing systems.

A resource-search and routing algorithm within PCDN autonomy area

This paper studied a new type of network model; it is formed by the dynamic autonomy area, the structured source servers and the proxy servers. The new network model satisfies the dynamics within the autonomy area, where each node undertakes different tasks according to their different abilities, to ensure that each node has the load ability fit its own; it does not need to exchange information via the central servers, so it can carry out the efficient data transmission and routing search. According to the highly dynamics of the autonomy area, we established dynamic tree structure-proliferation system routing and resource-search algorithms and simulated these algorithms. Test results show the performance of the proposed network model and the algorithms are very stable.

A quadtree driven image fusion quality assessment

In this paper a new method to compute saliency of source images is presented. This work is an extension to universal quality index founded by Wang and Bovik and improved by Piella. It defines the saliency according to the change of topology of quadratic tree decomposition between source images and the fused image. The saliency function provides higher weight for the tree nodes that differs more in the fused image in terms topology. Quadratic tree decomposition provides an easy and systematic way to add a saliency factor based on the segmented regions in the images.

Delay control and parallel admission algorithms for real-time anycast flow

An anycast flow is a flow that can be connected to any one of the members in a group of designated (replicated) servers (called anycast group). In this paper, we derive a set of formulas for calculating the end-to-end delay bound for the anycast flows and present novel admission control algorithms for anycast flows with real-time constraints. Given such an anycast group, our algorithms can effectively select the paths for anycast flows' admission and connection based on the least end-to-end delay bounds evaluated. We also present a parallel admission control algorithm that can effectively calculate the available paths with a short delay bound for different destinations in the anycast group so that a best path with the shortest delay bound can be chosen.

Optimal multicast tree routing for cluster computing in hypercube interconnection networks

Cluster computation has been used in the applications that demand performance, reliability, and availability, such as cluster server groups, large-scale scientific computations, distributed databases, distributed media-on-demand servers and search engines etc. In those applications, multicast can play the vital roles for the information dissemination among groups of servers and users. This paper proposes a set of novel efficient fault-tolerant multicast routing algorithms on hypercube interconnection of cluster computers using multicast shared tree approach. We present some new algorithms for selecting an optimal core (root) and constructing the shared tree so as to minimize the average delay for multicast messages. Simulation results indicate that our algorithms are efficient in the senses of short end-to-end average delay, load balance and less resource utilizations over hypercube cluster interconnection networks.

A scalable and robust framework for agent-based heterogeneous database operation

How to operate database efficiently and unfailingly in agent-based heterogeneous data source environment is becoming a big problem. In this paper, we contribute a framework and develop a couple of agent-oriented matchmakers with logical ring organization structure to match task agents' requests with middleware agents of databases. The middleware agent is a wrapper of a specific database and is run on the same server with the database management system. The matchmaker is of the features of proliferation and self-cancellation according to the sensory input from its environment. The ring-based coordination mechanism of matchmakers is designed. Two kinds of matchmakers, namely, host and duplicate, are designed for improving the scalability and robustness of agent-based system. The middleware agents are improved for satisfying the framework. We demonstrate the potentials of the framework by case study and present theoretical and empirical evidence that our approach is scalable and robust.