Core based tree multicast (M-CBT) approach in supporting mobility

IP multicasting provides a mechanism for faster handoff support than Mobile IP. Coupled with its location independent addressing, multicasting is a viable alternative to support mobility in the Internet. This paper continues research into using IP multicasting in mobility. Our proposed scheme looks at enabling a mobile node to initiate two way communications with a corresponding node on a shared multicast tree. We use as much of the existing Internet architecture as possible by making the base station a member of the multicast group. The mobile is not directly connected to the tree but goes through the base station to send and receive packets. This paper explains the differences and advantages of our proposed scheme compared with other multicast based mobility schemes and Mobile IP

Performance of a shared tree multicast label filter architecture

This paper defines a new multicast filter algorithm. This algorithm is used to filter packets on a mobile multicast architecture using a multicast shared tree. In a mobile multicast architecture, communications between a corresponding node (source) and the mobile node (receiver) should be private and not be sent to every node (receivers) on the multicast tree. We propose using an algorithm that sets up a label sub-tree on an existing mobile multicast shared tree to filter packets based on these labels. Our proposed label filter architecture is implemented differently to the current MPLS architecture. In this paper, we validate the effectiveness of the label filter in mobile communication compared to the traditional method of creating a new multicast tree by analysing the message and time complexity of the algorithm against the setting up time of a new multicast shared tree

Implementing label filters on a shared tree mobile multicast architecture

This paper describes an architecture that filters packets within a subset of nodes on an existing shared multicast tree. The path connecting the group of nodes that want to communicate privately on the existing tree was given a label. These labels are used to route one-to-one and group communication traffic for selected nodes on a multicast tree. Nodes connected to the tree but are not on this label path do not receive any filtered packets. This filter architecture reduces network resource waste by utilising the existing network resources on the multicast tree like quality of service (QoS). In this paper, we also describe how this architecture can be used for mobile communication when implemented in a shared tree mobile multicast architecture

Mobility and quality of service in wireless multicast infrastructure

This paper defines a new wireless mobility architecture with quality of service (QoS) that uses the fixed network infrastructure for group communication. The mobile core-based tree (M-CBT) architecture uses multicast to provide fast handoff and reduce network utilization costs for group communication. The M-CBT architecture can be coupled with a multicast QoS routing protocol to provide QoS for mobile communication. The Explore Best Path Message (EBPM) protocol is a probe-based dynamic distributed multicast QoS routing protocol that is designed to quickly search the network for an optimal QoS path from a joining node to the multicast tree. This paper illustrates how mobile devices using M-CBT and EBPM can participate in group communications and quickly find a QoS path as theyhandoff to a new network

Prediction of Short-term Traffic Variables using Intelligent Swarm-based Neural Networks

This paper presents an innovative algorithm integrated with particle swarm optimization and artificial neural networks to develop short-term traffic flow predictors, which are intended to provide traffic flow forecasting information for traffic management in order to reduce traffic congestion and improve mobility of transportation. The proposed algorithm aims to address the issues of development of short-term traffic flow predictors which have not been addressed fully in the current literature namely that: a) strongly non-linear characteristics are unavoidable in traffic flow data; b) memory space for implementation of short-term traffic flow predictors is limited; c) specification of model structures for short-term traffic flow predictors which do not involve trial and error methods based on human expertise; d) adaptation to newly-captured, traffic flow data is required. The proposed algorithm was applied to forecast traffic flow conditions on a section of freeway in Western Australia, whose traffic flow information is newly-captured. These results clearly demonstrate the effectiveness of using the proposed algorithm for real-time traffic flow forecasting

Real-time public group collaboration using IP multicast label filters

Internet based enterprise level collaboration tools enable organizations to make decisions faster and more accurately with less effort. However, these tools provide limited real-time group collaboration within and across organizations. Multicast protocols were developed to provide efficient group communication. This paper proposes a novel IP multicast network layer filter architecture that provides efficient and scalable real-time group collaboration between the required entities within an organization. This proposed network architecture uses a label filter mechanism to improve scalability and bandwidth for one-to-many and many-to-many real-time collaboration

Towards DoS attack prevention based on clustering architecture in mobile IP communication

Mobile IP communication, like wired communication and mobile ad hoc networking, is vulnerable to Denial-of-Service (DoS) attacks. In this paper, we propose using a lightweight packet filtering technique in different domains and base stations to reduce/eliminate the threat of DoS attacks on mobile IP networks. The proposed technique will be able to detect and filter out any suspected packets containing spoofed IP address created by DoS attackers. The results of our experiments indicate that our proposed technique can significantly reduce the effect of DoS attacks and improves performance of mobile IP communication

Kinetic Studies on Removal of Fluoride from Drinking Water by using Tamarind Shell and Pipal leaf Powder

Abstract The study aimed to develop adsorbents from leaves of Ficus religiosa (Pipal) and Tamarindus Indica (Tamarind) fruit shell to remove fluoride from drinking water. Batch adsorption experiments were undertaken on natural adsorbents (Tamarindus Indica and Ficus religiosa) developed from locally available trees to assess their suitability to remove fluoride from drinking water. The effect of controlling parameters of adsorption like pH, dose of adsorbent, contact time and initial sorbate concentration on fluoride removal efficiency was studied and optimum values for maximum uptake were found. Tamarind fruit shell exhibited highest fluorine removal efficiency about 85% at pH of 2, initial fluorine concentration of 3 mg/l, contact time of 90 min, adsorbent dosage of 2g/100ml and maintaining temperature of 307 K. The maximum adsorption of fluoride for Pipal leaf powder (79%) was observed at pH 2, the optimum sorbent doses were found to be 2.0 g/l. The equilibrium was achieved in 1.5 and 2 hour, respectively. The obtained data were fitted to Langmuir and Freundlich isotherms

Quantitative Technology Forecasting: a Review of Trend Extrapolation Methods

Quantitative technology forecasting uses quantitative methods to understand and project technological changes. It is a broad field encompassing many different techniques and has been applied to a vast range of technologies. A widely used approach in this field is trend extrapolation. Based on the publications available to us, there has been little or no attempt made to systematically review the empirical evidence on quantitative trend extrapolation techniques. This study attempts to close this gap by conducting a systematic review of technology forecasting literature addressing the application of quantitative trend extrapolation techniques. We identified 25 studies relevant to the objective of this research and classified the techniques used in the studies into different categories, among which growth curves and time series methods were shown to remain popular over the past decade, while newer methods, such as machine learning-based hybrid models, have emerged in recent years. As more effort and evidence are needed to determine if hybrid models are superior to traditional methods, we expect to see a growing trend in the development and application of hybrid models to technology forecasting

Comprehensive analysis of temporal alterations in cellular proteome of bacillus subtilis under curcumin treatment

Curcumin is a natural dietary compound with antimicrobial activity against various gram positive and negative bacteria. This study aims to investigate the proteome level alterations in Bacillus subtilis due to curcumin treatment and identification of its molecular/cellular targets to understand the mechanism of action. We have performed a comprehensive proteomic analysis of B. subtilis AH75 strain at different time intervals of curcumin treatment (20, 60 and 120 min after the drug exposure, three replicates) to compare the protein expression profiles using two complementary quantitative proteomic techniques, 2D-DIGE and iTRAQ. To the best of our knowledge, this is the first comprehensive longitudinal investigation describing the effect of curcumin treatment on B. subtilis proteome. The proteomics analysis revealed several interesting targets such UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1, putative septation protein SpoVG and ATP-dependent Clp protease proteolytic subunit. Further, in silico pathway analysis using DAVID and KOBAS has revealed modulation of pathways related to the fatty acid metabolism and cell wall synthesis, which are crucial for cell viability. Our findings revealed that curcumin treatment lead to inhibition of the cell wall and fatty acid synthesis in addition to differential expression of many crucial proteins involved in modulation of bacterial metabolism. Findings obtained from proteomics analysis were further validated using 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) assay for respiratory activity, resazurin assay for metabolic activity and membrane integrity assay by potassium and inorganic phosphate leakage measurement. The gene expression analysis of selected cell wall biosynthesis enzymes has strengthened the proteomics findings and indicated the major effect of curcumin on cell division