An Off-the-Shelf Scheme for Dependable Grid Systems Using Virtualization

Recently, grid computing has been widely focused on the science, industry, and business fields, which are required a vast amount of computing. Grid computing is to provide the environment that many nodes (i.e., many computers) are connected with each other through a local/global network and it is available for many users. In the environment, to achieve data processing among nodes for any applications, each node executes mutual authentication by using certificates which published from the Certificate Authority (for short, CA). However, if a failure or fault has occurred in the CA, any new certificates cannot be published from the CA. As a result, a new node cannot participate in the gird environment. In this paper, an off-the-shelf scheme for dependable grid systems using virtualization techniques is proposed and its implementation is verified. The proposed approach using the virtualization techniques is to restart an application, e.g., the CA, if it has failed. The system can tolerate a failure or fault if it has occurred in the CA. Since the proposed scheme is implemented at the application level easily, the cost of its implementation by the system builder hardly takes compared it with other methods. Simulation results show that the CA in the system can recover from its failure or fault.

A New Scheduling Algorithm Based on Traffic Classification Using Imprecise Computation

Wireless channels are characterized by more serious bursty and location-dependent errors. Many packet scheduling algorithms have been proposed for wireless networks to guarantee fairness and delay bounds. However, most existing schemes do not consider the difference of traffic natures among packet flows. This will cause the delay-weight coupling problem. In particular, serious queuing delays may be incurred for real-time flows. In this paper, it is proposed a scheduling algorithm that takes traffic types of flows into consideration when scheduling packets and also it is provided scheduling flexibility by trading off video quality to meet the playback deadline.

Intelligent Audio Watermarking using Genetic Algorithm in DWT Domain

In this paper, an innovative watermarking scheme for audio signal based on genetic algorithms (GA) in the discrete wavelet transforms is proposed. It is robust against watermarking attacks, which are commonly employed in literature. In addition, the watermarked image quality is also considered. We employ GA for the optimal localization and intensity of watermark. The watermark detection process can be performed without using the original audio signal. The experimental results demonstrate that watermark is inaudible and robust to many digital signal processing, such as cropping, low pass filter, additive noise.

Approaches and Schemes for Storing DTD-Independent XML Data in Relational Databases

The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method's query answering.

Addressing Security Concerns of Data Exchange in AODV Protocol

The Ad Hoc on demand distance vector (AODV) routing protocol is designed for mobile ad hoc networks (MANETs). AODV offers quick adaptation to dynamic link conditions; it is characterized by low memory overhead and low network utilization. The security issues related to the protocol remain challenging for the wireless network designers. Numerous schemes have been proposed for establishing secure communication between end users, these schemes identify that the secure operation of AODV is a bi tier task (routing and secure exchange of information at separate levels). Our endeavor in this paper would focus on achieving the routing and secure data exchange in a single step. This will facilitate the user nodes to perform routing, mutual authentications, generation and secure exchange of session key in one step thus ensuring confidentiality, integrity and authentication of data exchange in a more suitable way.

Hybrid TOA/AOA Schemes for Mobile Location in Cellular Communication Systems

Wireless location is to determine the mobile station (MS) location in a wireless cellular communications system. When fewer base stations (BSs) may be available for location purposes or the measurements with large errors in non-line-of-sight (NLOS) environments, it is necessary to integrate all available heterogeneous measurements to achieve high location accuracy. This paper illustrates a hybrid proposed schemes that combine time of arrival (TOA) at three BSs and angle of arrival (AOA) information at the serving BS to give a location estimate of the MS. The proposed schemes mitigate the NLOS effect simply by the weighted sum of the intersections between three TOA circles and the AOA line without requiring a priori information about the NLOS error. Simulation results show that the proposed methods can achieve better accuracy when compare with Taylor series algorithm (TSA) and the hybrid lines of position algorithm (HLOP).

Energy Efficient and Reliable Geographic Routing in Wireless Sensor Networks

The wireless link can be unreliable in realistic wireless sensor networks (WSNs). Energy efficient and reliable data forwarding is important because each node has limited resources. Therefore, we must suggest an optimal solution that considers using the information of the node-s characteristics. Previous routing protocols were unsuited to realistic asymmetric WSNs. In this paper, we propose a Protocol that considers Both sides of Link-quality and Energy (PBLE), an optimal routing protocol that balances modified link-quality, distance and energy. Additionally, we propose a node scheduling method. PBLE achieves a longer lifetime than previous routing protocols and is more energy-efficient. PBLE uses energy, local information and both sides of PRR in a 1-hop distance. We explain how to send data packets to the destination node using the node's information. Simulation shows PBLE improves delivery rate and network lifetime compared to previous schemes. Moreover, we show the improvement in various WSN environments.

Using the V-Sphere Code for the Passive Scalar in the Wake of a Bluff Body

The objective of this research was to find the diffusion properties of vehicles on the road by using the V-Sphere Code. The diffusion coefficient and the size of the height of the wake were estimated with the LES option and the third order MUSCL scheme. We evaluated the code with the changes in the moments of Reynolds Stress along the mean streamline. The results show that at the leading part of a bluff body the LES has some advantages over the RNS since the changes in the strain rates are larger for the leading part. We estimated that the diffusion coefficient with the computed Reynolds stress (non-dimensional) was about 0.96 times the mean velocity.

Transmitter Design for LMS-MIMO-MCCDMA Systems with Pilot Channel Estimates and Zero Forcing Equalizer

We propose a downlink multiple-input multipleoutput (MIMO) multi-carrier code division multiple access (MCCDMA) system with adaptive beamforming algorithm for smart antennas. The algorithm used in this paper is based on the Least Mean Square (LMS), with pilot channel estimation (PCE) and the zero forcing equalizer (ZFE) in the receiver, requiring reference signal and no knowledge channel. MC-CDMA is studied in a multiple antenna context in order to efficiently exploit robustness against multipath effects and multi-user flexibility of MC-CDMA and channel diversity offered by MIMO systems for radio mobile channels. Computer simulations, considering multi-path Rayleigh Fading Channel, interference inter symbol and interference are presented to verify the performance. Simulation results show that the scheme achieves good performance in a multi-user system.

Application of Smooth Ergodic Hidden Markov Model in Text to Speech Systems

In developing a text-to-speech system, it is well known that the accuracy of information extracted from a text is crucial to produce high quality synthesized speech. In this paper, a new scheme for converting text into its equivalent phonetic spelling is introduced and developed. This method is applicable to many applications in text to speech converting systems and has many advantages over other methods. The proposed method can also complement the other methods with a purpose of improving their performance. The proposed method is a probabilistic model and is based on Smooth Ergodic Hidden Markov Model. This model can be considered as an extension to HMM. The proposed method is applied to Persian language and its accuracy in converting text to speech phonetics is evaluated using simulations.

Finite Element Modeling of Rotating Mixing of Toothpaste

The objective of this research is to examine the shear thinning behaviour of mixing flow of non-Newtonian fluid like toothpaste in the dissolution container with rotating stirrer. The problem under investigation is related to the chemical industry. Mixing of fluid is performed in a cylindrical container with rotating stirrer, where stirrer is eccentrically placed on the lid of the container. For the simulation purpose the associated motion of the fluid is considered as revolving of the container, with stick stirrer. For numerical prediction, a time-stepping finite element algorithm in a cylindrical polar coordinate system is adopted based on semi-implicit Taylor-Galerkin/pressure-correction scheme. Numerical solutions are obtained for non-Newtonian fluids employing power law model. Variations with power law index have been analysed, with respect to the flow structure and pressure drop.

Unsteady Laminar Boundary Layer Forced Flow in the Region of the Stagnation Point on a Stretching Flat Sheet

This paper analyses the unsteady, two-dimensional stagnation point flow of an incompressible viscous fluid over a flat sheet when the flow is started impulsively from rest and at the same time, the sheet is suddenly stretched in its own plane with a velocity proportional to the distance from the stagnation point. The partial differential equations governing the laminar boundary layer forced convection flow are non-dimensionalised using semi-similar transformations and then solved numerically using an implicit finitedifference scheme known as the Keller-box method. Results pertaining to the flow and heat transfer characteristics are computed for all dimensionless time, uniformly valid in the whole spatial region without any numerical difficulties. Analytical solutions are also obtained for both small and large times, respectively representing the initial unsteady and final steady state flow and heat transfer. Numerical results indicate that the velocity ratio parameter is found to have a significant effect on skin friction and heat transfer rate at the surface. Furthermore, it is exposed that there is a smooth transition from the initial unsteady state flow (small time solution) to the final steady state (large time solution).

Enhanced-Delivery Overlay Multicasting Scheme by Optimizing Bandwidth and Latency Discrepancy Ratios

With optimized bandwidth and latency discrepancy ratios, Node Gain Scores (NGSs) are determined and used as a basis for shaping the max-heap overlay. The NGSs - determined as the respective bandwidth-latency-products - govern the construction of max-heap-form overlays. Each NGS is earned as a synergy of discrepancy ratio of the bandwidth requested with respect to the estimated available bandwidth, and latency discrepancy ratio between the nodes and the source node. The tree leads to enhanceddelivery overlay multicasting – increasing packet delivery which could, otherwise, be hindered by induced packet loss occurring in other schemes not considering the synergy of these parameters on placing the nodes on the overlays. The NGS is a function of four main parameters – estimated available bandwidth, Ba; individual node's requested bandwidth, Br; proposed node latency to its prospective parent (Lp); and suggested best latency as advised by source node (Lb). Bandwidth discrepancy ratio (BDR) and latency discrepancy ratio (LDR) carry weights of α and (1,000 - α ) , respectively, with arbitrary chosen α ranging between 0 and 1,000 to ensure that the NGS values, used as node IDs, maintain a good possibility of uniqueness and balance between the most critical factor between the BDR and the LDR. A max-heap-form tree is constructed with assumption that all nodes possess NGS less than the source node. To maintain a sense of load balance, children of each level's siblings are evenly distributed such that a node can not accept a second child, and so on, until all its siblings able to do so, have already acquired the same number of children. That is so logically done from left to right in a conceptual overlay tree. The records of the pair-wise approximate available bandwidths as measured by a pathChirp scheme at individual nodes are maintained. Evaluation measures as compared to other schemes – Bandwidth Aware multicaSt architecturE (BASE), Tree Building Control Protocol (TBCP), and Host Multicast Tree Protocol (HMTP) - have been conducted. This new scheme generally performs better in terms of trade-off between packet delivery ratio; link stress; control overhead; and end-to-end delays.

Complexity of Operation and Maintenance in Irrigation Network Management-A Case of the Dez Scheme in the Greater Dezful, Iran

Food and fibre production in arid and semi-arid regions has emerged as one of the major challenges for various socio-economic and political reasons such as the food security and self-sufficiency. Productive use of the renewable water resources has risen on top ofthe decision-making agenda. For this reason, efficient operation and maintenance of modern irrigation and drainage schemes become part and parcel and indispensible reality in agricultural policy making arena. The aim of this paper is to investigate the complexity of operating and maintaining such schemes, mainly focussing on challenges which enhance and opportunities that impedsustainable food and fibre production. The methodology involved using secondary data complemented byroutine observations and stakeholders views on issues that influence the O&M in the Dez command area. The SPSS program was used as an analytical framework for data analysis and interpretation.Results indicate poor application efficiency in most croplands, much of which is attributed to deficient operation of conveyance and distribution canals. These in turn, are reportedly linked to inadequate maintenance of the pumping stations and hydraulic structures like turnouts,flumes and other control systems particularly in the secondary and tertiary canals. Results show that the aforementioned deficiencies have been the major impediment to establishing regular flow toward the farm gates which subsequently undermine application efficiency and tillage operationsat farm level. Results further show that accumulative impact of such deficiencies has been the major causes of poorcrop yield and quality that deem production system in these croplands uneconomic. Results further show that the present state might undermine the sustainability of agricultural system in the command area. The overall conclusion being that present water management is unlikely to be responsive to challenges that the sector faces. And in the absence of coherent measures to shift the status quo situation in favour of more productive resource use, it would be hard to fulfil the objectives of the National Economic and Socio-cultural Development Plans.

Load Balancing in Heterogeneous P2P Systems using Mobile Agents

Use of the Internet and the World-Wide-Web (WWW) has become widespread in recent years and mobile agent technology has proliferated at an equally rapid rate. In this scenario load balancing becomes important for P2P systems. Beside P2P systems can be highly heterogeneous, i.e., they may consists of peers that range from old desktops to powerful servers connected to internet through high-bandwidth lines. There are various loads balancing policies came into picture. Primitive one is Message Passing Interface (MPI). Its wide availability and portability make it an attractive choice; however the communication requirements are sometimes inefficient when implementing the primitives provided by MPI. In this scenario we use the concept of mobile agent because Mobile agent (MA) based approach have the merits of high flexibility, efficiency, low network traffic, less communication latency as well as highly asynchronous. In this study we present decentralized load balancing scheme using mobile agent technology in which when a node is overloaded, task migrates to less utilized nodes so as to share the workload. However, the decision of which nodes receive migrating task is made in real-time by defining certain load balancing policies. These policies are executed on PMADE (A Platform for Mobile Agent Distribution and Execution) in decentralized manner using JuxtaNet and various load balancing metrics are discussed.

Learning Classifier Systems Approach for Automated Discovery of Crisp and Fuzzy Hierarchical Production Rules

This research presents a system for post processing of data that takes mined flat rules as input and discovers crisp as well as fuzzy hierarchical structures using Learning Classifier System approach. Learning Classifier System (LCS) is basically a machine learning technique that combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. Crisp description for a concept usually cannot represent human knowledge completely and practically. In the proposed Learning Classifier System initial population is constructed as a random collection of HPR–trees (related production rules) and crisp / fuzzy hierarchies are evolved. A fuzzy subsumption relation is suggested for the proposed system and based on Subsumption Matrix (SM), a suitable fitness function is proposed. Suitable genetic operators are proposed for the chosen chromosome representation method. For implementing reinforcement a suitable reward and punishment scheme is also proposed. Experimental results are presented to demonstrate the performance of the proposed system.

Enhanced QoS Mechanisms for IEEE 802.11e Wireless Networks

The quality-of-service (QoS) support for wireless LANs has been a hot research topic during the past few years. In this paper, two QoS provisioning mechanisms are proposed for the employment in 802.11e EDCA MAC scheme. First, the proposed call admission control mechanism can not only guarantee the QoS for the higher priority existing connections but also provide the minimum reserved bandwidth for traffic flows with lower priority. In addition, the adaptive contention window adjustment mechanism can adjust the maximum and minimum contention window size dynamically according to the existing connection number of each AC. The collision probability as well as the packet delay will thus be reduced effectively. Performance results via simulations have revealed the enhanced QoS property achieved by employing these two mechanisms.

Stabilization of the Bernoulli-Euler Plate Equation: Numerical Analysis

The aim of this paper is to study the internal stabilization of the Bernoulli-Euler equation numerically. For this, we consider a square plate subjected to a feedback/damping force distributed only in a subdomain. An algorithm for obtaining an approximate solution to this problem was proposed and implemented. The numerical method used was the Finite Difference Method. Numerical simulations were performed and showed the behavior of the solution, confirming the theoretical results that have already been proved in the literature. In addition, we studied the validation of the numerical scheme proposed, followed by an analysis of the numerical error; and we conducted a study on the decay of the energy associated.

Comparison between Turbo Code and Convolutional Product Code (CPC) for Mobile WiMAX

Mobile WiMAX is a broadband wireless solution that enables convergence of mobile and fixed broadband networks through a common wide area broadband radio access technology and flexible network architecture. It adopts Orthogonal Frequency Division Multiple Access (OFDMA) for improved multi-path performance in Non-Line-Of-Sight (NLOS) environments. Scalable OFDMA (SOFDMA) is introduced in the IEEE 802e[1]. WIMAX system uses one of different types of channel coding but The mandatory channel coding scheme is based on binary nonrecursive Convolutional Coding (CC). There are other several optional channel coding schemes such as block turbo codes, convolutional turbo codes, and low density parity check (LDPC). In this paper a comparison between the performance of WIMAX using turbo code and using convolutional product code (CPC) [2] is made. Also a combination between them had been done. The CPC gives good results at different SNR values compared to both the turbo system, and the combination between them. For example, at BER equal to 10-2 for 128 subcarriers, the amount of improvement in SNR equals approximately 3 dB higher than turbo code and equals approximately 2dB higher than the combination respectively. Several results are obtained at different modulating schemes (16QAM and 64QAM) and different numbers of sub-carriers (128 and 512).

A Hybrid Scheme for on-Line Diagnostic Decision Making Using Optimal Data Representation and Filtering Technique

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.