E. K. Park

OntoKhoj: a semantic web portal for ontology searching, ranking and classification

The goal of the next generation Web is to build virtual communities, wherein software agents and people can work in cooperation by sharing knowledge. To achieve this goal, the emerging Semantic Web community has proposed ontologies to express knowledge in a machine understandable way. The process of building and maintaining ontologies, which is known as Ontology Engineering, presents unique challenges. These challenges are related to lack of trustworthy and authoritative knowledge sources and absence of a centralized repository to locate ontologies to be reused. In this paper, we propose a Semantic Web portal, called OntoKhoj that is designed to simplify the Ontology Engineering process. The methodology in developing OntoKhoj is based on algorithms used for searching, aggregating, ranking and classifying ontologies in Semantic Web. The proposed OntoKhoj would 1) allow agents and ontology engineers to retrieve trustworthy, authoritative knowledge, and 2) expedite the process of ontology engineering through extensive reuse of ontologies. We have implemented the OntoKhoj portal and further validated our system on the real ontological data in the Semantic Web.

Using domain knowledge in knowledge discovery

With the explosive growth of the size of databases, many knowledge discovery applications deal with large quantities of data. There is an urgent need to develop methodologies which will allow the applications to focus search to a potentially interesting and relevant portion of the data, which can reduce the computational complexity of the knowledge discovery process and improve the interestingness of discovered knowledge. Previous work on semantic query optimization, which is an approach to take advantage of domain knowledge for query optimization, has demonstrated that significant cost reduction can be achieved by reformulating a query into a less expensive yet equivalent query which produces the same answer as the original one. In this paper, we introduce a method to utilize three types of domain knowledge in reducing the cost of finding a potentially interesting and relevant portion of the data while improving the quality of discovered knowledge. In addition, we propose a method to select relevant domain knowledge without an exhaustive search of all domain knowledge. The contribution of this paper is that we lay out a general framework for using domain knowledge in the knowledge discovery process effectively by providing guidelines.

An Algorithm for Traffic Grooming in WDM Optical Mesh Networks with Multiple Objectives

Abstract This paper studies a traffic grooming in wavelength-division multiplexing (WDM) mesh networks for the SONET/SDH streams requested between node pairs. The traffic could be groomed at the access node before converting to an optical signal carried in the all-optical network. We design a virtual topology with a given physical topology to satisfy multiple objectives and constraints. The grooming problem of a static demand is considered as an optimization problem. The traditional algorithms found in the literatures mostly focus on a single objective either to maximize the performance or to minimize the cost. We propose a multi-objective evolutionary algorithm to solve a grooming problem that optimizes multiple objectives all together at the same time. In this paper we consider the optimization of three objectives: maximize the traffic throughput, minimize the number of transceivers, and minimize the average propagation delay or average hop counts. The simulation results show that our approach is superior to an existing heuristic approaches in an acceptable running time.

Performance of an enhanced GSM protocol supporting non-repudiation of service

In this article, we analyze an authentication protocol, compatible with Global System for Mobile (GSM) communication, that employs an additional one way function to establish trust between a Mobile Unit and Visiting Location Register for the purpose of non-repudiation of service. The security of this protocol is discussed and a traffic analysis is performed indicating that the protocols message overhead during call origination is tolerable under various cell densities and traversal rates. The message penalty for use of the additional one way function is under 15% of total control traffic at vehicular speeds with an origination rate of 5.6 calls per handset per hour. The penalty for pedestrian traffic and high origination rate is about 23% of total control traffic. Therefore, the enhanced protocol appears undesirable for pedestrian networks unless the potential for fraud is great. However, the more modest overhead associated with vehicular traffic is acceptable when billing accuracy and service settlement is required between Personal Communications Networks.

Hybrid Optical Wireless Networks

This paper describes a dynamic reconfiguration algorithm for a hybrid fiber wireless network, which takes advantage of dynamic reconfiguration in WDM based optical networks to provide bandwidth on the fly. The WDM technique for optical networks allows network operators to extend the existing capacity of passive optical networks manifolds. However presently, WDM networks were used mostly in long haul backbone networks and recently have been put to use in metropolitan networks (MAN). But till now not much work has been done on use of WDM networks in MAN. We use wireless technology to solve the Last mile problem of WDM networks. Wireless networks on the other hand are always constrained by need of bandwidth and we use WDM based optical networks to provide that. So both network technologies complement each other. Our proposed approach allows providing bandwidth on demand. It also allows for service differentiation by service providers, and sharing of infrastructure by several service providers.

A genetic algorithm for traffic grooming in all-optical mesh networks

Rapid advances in the world of high-speed optical network and high-speed electronic routing has led to consideration of advanced models such as genetic algorithms (GAs). GAs have proved to be a practical and robust optimization and search tool for network design. However, a GA is not generally employed in traffic grooming over mesh networks. In this paper, we propose a new GA model to handle the traffic grooming problem in an all-optical WDM mesh network. The new model extends classical GAs with heuristic approach to support network cost optimization for combining multiple traffic streams into a single lightpath. In addition, to support our new GA model, we have developed a set of new investigation including position-based bit matrix encoding, genetic heuristic operators, and fitness evaluation function using the clustering method. The experimental results show that our GA model is superior to traditional heuristic approaches for the 5, 6 and 14-node benchmark networks.

A token based distributed k mutual exclusion algorithm

The authors present an algorithm for solving the k mutual exclusion problem in a distributed system. The algorithm is token based, whereby a token is passed among sites. Only sites that either receive the token with a nonzero semaphore or receive the token with a zero semaphore and later receive a release message from a previous site are allowed to enter their critical sections. Attached to the token is a queue which lists the sites scheduled to receive the token and a general semaphore. In all cases except extremely light token request traffic, the number of messages per critical section execution can be expressed as a small constant. This constant approaches three in an extremely heavy token request environment.<<ETX>>

An algorithm for traffic grooming in WDM optical mesh networks with multiple objectives

This paper studies a traffic grooming in wavelength-division multiplexing (WDM) mesh networks for the SONET/SDH streams requested between node pairs. The traffic could be groomed at the access node before converting to an optical signal carried in the all-optical network. We design a virtual topology with a given physical topology to satisfy multiple objectives and constraints. The grooming problem of a static demand is considered as an optimization problem. The algorithms found in the literatures focus on a single objective either to maximize the performance or to minimize the cost. We propose a multiobjective evolutionary algorithm to solve a grooming problem that optimizes multiple objectives all together at the same time. In this paper we consider the optimization of three objectives: maximize the traffic throughput, minimize the number of transceivers, and minimize the average propagation delay or average hop counts. The simulation results show that our approach is superior to an existing heuristic approaches for the 6-node benchmark network in an acceptable running time.

Using RTT Variability for Adaptive Cross-Layer Approach to Multimedia Delivery in Heterogeneous Networks

A holistic approach should be made for a wider adoption of a cross-layer approach. A cross-layer design on a wireless network assumed with a certain network condition, for instance, can have a limited usage in heterogeneous environments with diverse access network technologies and time varying network performance. The first step toward a cross-layer approach is an automatic detection of the underlying access network type, so that appropriate schemes can be applied without manual configurations. To address the issue, we investigate the characteristics of round-trip time (RTT) on wireless and wired networks. We conduct extensive experiments from diverse network environments and perform quantitative analyses on RTT variability. We show that RTT variability on a wireless network exhibits greatly larger mean, standard deviation, and min-to-high percentiles at least 10 ms bigger than those of wired networks due to the MAC layer retransmissions. We also find that the impact of packet size on wireless channel is particularly significant. Thus through a simple set of testing, one can accurately classify whether or not there has been a wireless network involved. We then propose effective adaptive cross-layer schemes for multimedia delivery over error-prone links. They include limiting the MAC layer retransmissions, controlling the application layer forward error correction (FEC) level, and selecting an optimal packet size. We conduct an analysis on the interplay of those adaptive parameters given a network condition. It enables us to find optimal cross-layer adaptive parameters when they are used concurrently.

Ontology-driven peer profiling in peer-to-peer enabled semantic web

Peer-to-peer (P2P) systems and Semantic Web are two novel technologies that face a lot of shortcomings if considered as isolated paradigms. We present an approach that utilizes ontologies to set up a peer profile containing all the data, necessary for peer-to-peer interoperability. Using this profile can help eliminate some major issues persistent in current P2P networks, such as security, resource aggregation, group management. We also consider applications of peer profiling for Semantic Web built on P2P networks, such as an improved semantic search for resources, not explicitly published on the Web, but available in a P2P system. We develop the ontology-based peer profile in RDF format and demonstrate its manifold benefits for peer communication and knowledge discovery in both P2P networks and Semantic Web.