Bala Srinivasan

Dynamic self-organizing maps with controlled growth for knowledge discovery

The growing self-organizing map (GSOM) has been presented as an extended version of the self-organizing map (SOM), which has significant advantages for knowledge discovery applications. In this paper, the GSOM algorithm is presented in detail and the effect of a spread factor, which can be used to measure and control the spread of the GSOM, is investigated. The spread factor is independent of the dimensionality of the data and as such can be used as a controlling measure for generating maps with different dimensionality, which can then be compared and analyzed with better accuracy. The spread factor is also presented as a method of achieving hierarchical clustering of a data set with the GSOM. Such hierarchical clustering allows the data analyst to identify significant and interesting clusters at a higher level of the hierarchy, and as such continue with finer clustering of only the interesting clusters. Therefore, only a small map is created in the beginning with a low spread factor, which can be generated for even a very large data set. Further analysis is conducted on selected sections of the data and as such of smaller volume. Therefore, this method facilitates the analysis of even very large data sets.

Voronoi-Based Continuous

Digital ecosystems are formed by “digital organisms” in complex, dynamic, and interrelated ecosystems and utilize multiple technologies to provide cost-efficient digital services and value-creating activities. A distributed wireless mobile network that serves as the underlying infrastructure to digital ecosystems provides important applications to the digital ecosystems, two of which are mobile navigation and continuous mobile information services. Most information and query services in a mobile environment are continuous mobile query processing or continuous k nearest neighbor (CKNN), which finds the locations where interest points or interest objects change while mobile users are moving. These locations are known as “split nodes.” All of the existing works on CKNN divide the query path into segments, which is a segment of road separated by two intersections, and then, the process to find split nodes is applied to each segment. Since there are many segments (due to many intersections, obviously), processing each segment is naturally inefficient. In this paper, we propose an alternative solution to overcome this problem. We use the Voronoi diagram for CKNN [called Voronoi CKNN (VCKNN)]. Our proposed approach does not need to divide the query path into segments, hence improving the overall query processing performance. Our experiment verified the applicability of the VCKNN approach to solve CKNN queries.

k

Recently, making Internet credit-card payment is widely accepted. Several payment protocols have been proposed to secure the credit-card payment on fixed networks. However, these protocols do not apply well to wireless networks due to the limitations of wireless devices and wireless networks themselves. In this paper, we propose a simple and powerful credit-card payment protocol for wireless networks. We implement a secure cryptographic technique that works well under this protocol. We show that our proposed protocol is more suitable for applying to wireless networks than SET and iKP in that client’s computation is reduced. The protocol also satisfies all security properties provided by both SET and iKP. Moreover, it offers the ability to resolve disputes and recover from failures which are normally occurred in wireless environment. Furthermore, client’s credit-card information is not required to be sent in the protocol. It results in the security enhancement of the system.

Nearest Neighbor Search in Mobile Navigation

With the wide availability of mobile devices (smart phones, iPhones, etc.), mobile location-based queries are increasingly in demand. One of the most frequent queries is range search which returns objects of interest within a pre-defined area. Most of the existing methods are based on the road network expansion method - expanding all nodes (intersections and objects) and computing the distance of each node to the query point. Since road networks are extremely complex, node expansion approaches are inefficient. In this paper, we propose a method, Voronoi Range Search (VRS) based on the Voronoi diagram, to process range search queries efficiently and accurately by partitioning the road networks to some special polygons. Then we further propose Voronoi Continuous Range (VCR) to satisfy the requirement for continuous range search queries (moving queries) based on VRS. Our empirical experiments show that VRS and VCR surpass all their rivals for both static and moving queries.

Lightweight Mobile Credit-Card Payment Protocol

Range search query processing has become one of the most important technologies in spatial and mobile databases. Most literature focuses on static range search extended from one point on both Euclidean distance and actual network distance, but there are only a few methods which can properly solve the problem for moving users, such as searching objects of interest on a road within a certain range. Although there are some techniques, which address continuous search, most approaches are absorbed in the KNN (k nearest neighbour) queries which are a different research area. In this paper, we propose two new methods to process continuous range search query in mobile computing. One is constructed using R-tree index based on Euclidean distance, and the other addresses the requirement on actual network distance.

Voronoi-based range and continuous range query processing in mobile databases

In a decentralised system like P2P where each individual peers are considerably autonomous, the notion of mutual trust between peers is critical. In addition, when the environment is subject to inherent resource constraints, any efficiency efforts are essentially needed. In light of these two issues, we propose a novel trustworthy-based efficient broadcast scheme in a resource-constrained P2P environment. The trustworthiness is associated with the peer@?s reputation. A peer holds a personalised view of reputation towards other peers in four categories namely SpEed, Correctness, qUality, and Risk-freE (SeCuRE). The value of each category constitutes a fraction of the reliability of individual peer. Another factor that contributes to the reliability of a peer is the peer@?s credibility concerning trustworthiness in providing recommendation about other peers. Our trust management scheme is applied in conjunction with our trust model in order to detect malicious and collaborative-based malicious peers. Knowledge of trustworthiness among peers is used in our proposed broadcast model named trustworthy-based estafet multi-point relays (TEMPR). This model is designed to minimise the communication overhead between peers while considering the trustworthiness of the peers such that only trustworthy peer may relay messages to other peers. With our approach, each peer is able to disseminate messages in the most efficient and reliable manner.

Continuous Range Search Query Processing in Mobile Navigation

In this article we propose an infrastructure that allows mobile users to securely share and search for their real-time video data. Specifically, the proposed infrastructure takes the advantages of the cloud platform and 5G technology to achieve its goals, where mobile users (connected with some external video taking device) can share their real-time video with their friends or families through the cloud while any other user with no permission cannot get any information about the video. More importantly, the infrastructure security is guaranteed even if the cloud server is hacked. In addition, our infrastructure also allows secure searching within the users own video data. We believe our solution is practical to be deployed in the existing telecommunication platforms.

Trustworthy-based efficient data broadcast model for P2P interaction in resource-constrained wireless environments

The increase number of mobile users in wireless environment affects query access time substantially. To minimise the query access time, one possible way is to employ data broadcasting strategy. In this paper, we propose cost models for both query access time over broadcast channel and on-demand channel. We examine the cost models to find optimum number of broadcast items in a channel while utilising query access time over on-demand channel as a threshold point. The optimum number indicates a point to split the broadcast cycle and allocate the data items in the new channel or else the on-demand channel outperforms the broadcast channel. The cost model involves several factors that dynamically change the optimum number of broadcast items like request arrival rate, service rate, size of data item, size of request, and bandwidth. Simulation model is developed to verify the performance of the cost model. This paper focuses on request that returns a single data item.

Secure sharing and searching for real-time video data in mobile cloud

Due to the universality and importance of range search queries processing in mobile and spatial databases as well as in geographic information system (GIS), numerous approaches on range search algorithms have been proposed in recent years. But ordinary range search queries focus only on a specific type of point objects. For queries which require to retrieve objects of interest locating in a particular region, ordinary range search could not get the expected results. In addition, most existing range search methods need to perform a searching on each road segments within the pre-defined range, which decreases the performance of range search. In this paper, we design a weighted network Voronoi diagram and propose a high-performance multilevel range search query processing that retrieves a set of objects locating in some specified region within the searching range. The experimental results show that our proposed algorithm runs very efficiently and outperforms its main competitor.

Optimal Broadcast Channel for Data Dissemination in Mobile Database Environment

Data broadcasting strategy is known as a scalable way to disseminate information to mobile users. However, with a very large set of broadcast items, the query access time of mobile clients raise accordingly, due to high waiting time for mobile clients to find their data of interest. One possible solution is to split the database information into several broadcast channels. In this paper, we introduce taxonomy of index dissemination for multibroadcast channel based on B* tree structure. We consider three indexing schemes namely: (i) nonreplicated indexing scheme (NRI), (ii) partially-replicated indexing scheme (PRI), and (iii) fully-replicated indexing scheme (FRI). Simulation model is developed to find out the access time performance of each scheme.