M. Lakshmi

A strategy for mining utility based temporal association rules

Due to the widespread computerization and affordable storage facilities, there exists enormous amount of information in databases belonging to different enterprises. The ultimate intent of this massive data collection is the utilization of this to achieve competitive benefits, by determining formerly unidentified patterns in data that can direct the process of decision making. Data mining, the core step of Knowledge Discovery in Databases (KDD) is the process of applying computational techniques that, under acceptable computational efficiency limitations, produce a particular enumeration of patterns. Data mining tasks can be classified in to two categories. Descriptive mining and Predictive mining. Association Rule mining (ARM), Clustering and sequential pattern mining are some of the descriptive mining. The main advantages of Association rules are simplicity, intuitiveness and freedom from model-based assumptions. In this paper, an extensive survey of Association rule in regard to temporal databases and utilities are done. The proposed algorithm is able to mine temporal association rules based on utilities by adapting the support with relevant to the time periods and utility. An approach of mining UTARM is designed and the efficiency of the method is discussed.

Analysis and prediction of natural disaster using spatial data mining technique

Data mining, also called knowledge-discovery in databases (KDD), is the process of automatically searching large volumes of data for patterns using specific DM technique. Goal of the data mining process is to extract information from a data set and transform it to an user understandable structure. Spatial data mining is the application of data mining methods to spatial data. Goal of Spatial data mining is to find patterns in data with respect to Geography. Data mining offers great potential benefits for GIS ( Geographic Information System) based decision making. Spatial databases mainly store two types of data: raster data (satellite/aerial digital images) and vector data (points, lines, polygons). Need of Spatial database. To store and query data that represents objects defined in a geometric space. To handle more complex structures such as 3D objects, topological coverages, linear networks, etc. Some of its Issues and Challenges are described here: (1) The unique characteristic of spatial datasets requires significant modification of data mining techniques so that they can exploit the rich spatial and temporal relationships and patterns embedded in the datasets. (2) The attributes of neighboring patterns may have significant influence on a pattern and should be considered. (3)Visualization of the spatial patterns, scalability of data mining methods, data structures to represent and efficiently index spatial datasets are also challenging issues. (4) Spatial and temporal relationships like distance, topology, direction, before and after are information bearing. They need to be considered in spatiotemporal data analysis and mining.

UTARM: an efficient algorithm for mining of utility-oriented temporal association rules

Recently, association rule mining has become an area of interest for research in the field of knowledge discovery and several algorithms have been established. Lately, for business development, data mining researchers have enhanced the quality of association rule mining for the mining of association patterns by integrating the influential factors, for instance temporal, value utility and more. Here, we have proposed an efficient algorithm, called UTARM Utility-Based Temporal Association Rule Mining, which combines both temporal time periods and utility for mining of remarkable and helpful association rules. The proposed algorithm can be able to mine utility-oriented temporal association rules by adapting the support with relevant to the time periods and utility. Furthermore, the scan time required for finding the FTU itemsets is considerably reduced. The experimentation is carried out on large data sets and the experimental results ensure that the proposed algorithm effectively discovers the utility-oriented temporal association rules.

An AWG based optical router

Optical packet switching is considered as next generation data transfer technology in conjunction with mature electronics. In the design of optical routers, the main issue is the splitting loss of the devices and control unit complexity. Hence, much research has been done in designing of the simple routers. This exploration leads to generation of AWG based optical routers. In this paper, AWG based optical router is discussed and simulation results are presented in terms of packet loss probability for symmetric and asymmetric switch. It is also shown that in the earlier architecture, due to the unequal power of the buffered and directly transmitted packets, some of the buffered packet may not fully utilize the buffer capacity due to the degraded quality of the packets in the buffer. However, in the modified architecture, the buffer capacity is fully utilized effectively.

Strategic Composition of Semantic Web Services Using SLAKY Composer

Web service composition is the process of aggregation of elementary services to build composite applications. To automate composition several algorithms based on artificial intelligence planning [1], association rule mining [2], petri net [3], case based reasoning [4], genetic algorithm [5][6], neural network [7], etc, have been proposed. However all of these methods select services that only satisfy client’s requirements and behavior [8]. In a real world scenario choosing business service partners for composition on the fly automatically is impractical and often referred to as a toy model [9]. SLAKY System is a new realistic model for selection of business service partners. SLAKY System selects services on the fly considering the vision, time planning, environmental context, user adoption, usage policies, trust management, risk management, market scenario, native intelligence, and competitive profit management of collaborating service partners apart from functionality satisfaction for client’s requirements. In this paper we focus on profit management module. We have proposed SLAKY BWG algorithm for profit management where composition is done in a competitive manner by considering service providers and agent as competitors seeking to maximize their profits by selecting strategic composition as a Non-Zero sum business war game. The execution module executes the compositions as a mixed strategy so that both the agent and service provider gains profit.

A Weighted Particle Swarm Optimization Technique for Optimizing Association Rules

The Process of finding out correlations among the data items in the databases forms the core concept in Association Rule Mining. The Association rule Mining algorithms helps in decision making process. Since it plays a vital role in this area, the rules generated by the algorithms should be of less in number and precise. Association rule algorithms, such as Apriori, scrutinize a long list of transactions in order to decide which items are most commonly purchased together. The challenge of digging out association patterns from data draws upon research in databases, machine learning and optimization to bring advanced intelligent solutions. But even though it provides some robustness, the rules generated from the algorithm may be redundant in some cases. So in order to overcome the problems we need to optimize the rules generated from these algorithms. Here we consider the Utility based Temporal Association Rule Mining method for generating the association rules and the Particle Swam Optimization algorithm is used to optimize the generated rules. The main processes in this proposed approach are calculation of the support and confidence from the input data, the Rule generation, Initialization , updation of the velocity , position of the rules and evaluation of fitness function. This paper attempts to use the PSO technique to optimize the utility based temporal rules by filtering out the redundant rules and thereby reducing the problem space.

A routing optimization algorithm via Fuzzy Logic towards security in wireless ad-hoc networks

An ad hoc network is a collection of wireless mobile hosts forming a temporary network without the aid of any established infrastructure or centralized administration. In this network, it may be necessary for one mobile host to enlist the aid of other hosts in forwarding a packet to its destination, due to the limited range of each mobile hosts wireless transmissions. Mostly work has been concentrated on routing aspect. Security is one of the most important concepts in ad hoc networks. It has been observed that different protocols need different strategies for security. This paper presents new improved secure protocols (FLSL)for routing in ad hoc networks that uses dynamic source routing as well as applying Fuzzy Logic algorithms.

Web Service Selection Using Decision Tree Analysis in a Risky Environment

In real world scenario managerial decisions are made to maximize profit and minimize loss even under circumstances of risk. Web service composition is the process of aggregation of services to create virtual enterprises. During composition the aim of service providers is to offer good service to the client and ensure good return of investment. Software agent composers have several strategies to compose services automatically. However most of the composition algorithms aim at serving good service to the client without considering the corporate metrics and hence regarded as a toy model. To promote web service composition as a feasible business model we have proposed a service provider collaboration stack that considers the service providers metrics during composition. The modules for time planning, profit management, native intelligence and user adoption of SLAKY composition stack have already been implemented. In this paper we focus on selecting services with maximum profit for the composition under environmental metric of risk using decision theory. The software agent uses decision tree analysis to identify the best course of action to be chosen till the end under various possible outcomes as a whole.

Performance analysis of AWG based optical packet switch architecture

In this paper, an optical packet switch architecture which is realized with a very few components is discussed. The main advantage of this architecture is its simple buffering structure. The performance of optical packet switch architecture in terms of packet loss probability and average delay is presented. The obtained results clearly show that the considered architecture provides very low packet loss probability with reasonably low average delay.