Loop Scheduling for Heterogeneous Computing Environment Based on Performance Prediction

Dear SCPE Reader, We present a selection of papers which are extensions of papers presented at the 7-th International Symposium on Parallel and Distributed Computing, 1–5 July 2008, in Krakow, Poland. The motivation for publishing the selection in the SCPE Journal was, on the one hand, to present the flavour of the research reported at the conference and on the other hand to present some of the most relevant topics currently focused on the research on parallel and distributed computing in general. The selection contains only 6 papers out of about 60 presented at the conference, and thus, is far from covering all relevant topics represented at the ISPDC 2008. This is because not all of the invited authors were patient enough to accept a fairly long paper publishing process. Nevertheless, we hope that the presented papers will bring you closer to the research covered by the ISPDC conferences and will encourage you to participate in future ISPDC editions. The first paper ``The Impact of Workload Variability on Load Balancing Algorithms'' is by Marta Beltran and Antonio Guzman from King Juan Carlos University in Spain. It concerns an important topic of load balancing in cluster systems, namely adaptativity of the load balancing algorithms to changes of the workload in the system. Adequate accounting for additional load in the hosting system is of great relevance for correct optimization effects. The paper presents a thorough formal analysis of the workload variability metrics and their influence on the quality of load balancing algorithms. Four basic activities appearing in load balancing algorithms are identified, and based on them some algorithmic solutions are proposed to correctly deal with workload variability in system load balancing. The problem of dynamic load balancing algorithms robustness has been discussed. Two different robustness metrics sensitive to the applied type of opimization: local task-oriented or a global one enable selecting task remote execution or migration as load balancing operations. The proposed approach is illustrated with experiments. The second paper ``Model-Driven Engineering and Formal Validation of High-Performance Embedded Systems'' is by Abdoulaye Gamatie, Eric Rutten, Huafeng Yu, Pierre Boulet, Jean-Luc Dekeyser, from University of Lille and INRIA in France. The paper is concerned with a very advanced methodology of designing correct parallel embedded systems for intensive data-parallel computing. In their previous research, the authors of the paper designed the GASPARD embedded system design framework. It is based on the hardware/software co-design approach through model-driven engineering. The framework is based on an UML-like model specification language in which hardware and software elements are modelled using a component approach with special mechanisms for repetitive structures. This paper tries to combine the modelling framework of GASPARD with the mechanisms of synchronous languages to achieve design verifiability provided for such languages. The paper shows how GASPARD models can be translated into synchronous models based on data flow equations in order to formally check their correctness. The proposed approach is illustrated with an example of a video processing system. The third paper ``Relations Between Several Parallel Computational Models'' is by Stephan Bruda and Yuanqiao Zhang from Bishop’s University in Canada. The paper is concerned with theoretical aspects of shared memory systems described by the parallel random access machine PRAM model and aims in studying performance properties of different types of PRAM systems. The attention is focussed on analysing the computational power of two more sophisticated PRAM models (Combining CRCW and Broadcast Selective Reduction), which include data reduction in case of concurrent writes. The paper shows that these two models have equivalent computational power, which is a new result comparing the existing literature. The performance of both models applied to reconfigurable multiple bus machines was studied as a possible architectural solution for current VLSI processor implementations. It was shown that in such systems under reasonable assumptions concurrent-write does not enhance performance comparing the exclusive-write model. Another result important for the VLSI technology is that the Combining CRCW PRAM model (in which data of concurrent writes are arthmetically or logically combined before write) and the exclusive-write on directed reconfigurable busses perform in equivalent way under strong real-time requirements. The fourth paper ``Experiences with Mesh-Like Computations Using Prediction Binary Trees'' is by Gennaro Cordasco, Biagio Cosenza, Rosario de Chiara, Ugo Erra and Vittorio Scarano from the University ``degli Studi'' of Salerno and the University ``degli Studi della Biasilicata'' of Potenza in Italy. The paper concerns optimization methods for mesh-like computations in clusters of processors. The computations are perfomed assuming a phase-like program execution control using a tiling approach which reduces inter-processor communication. A temporal coherence is also assumed, which means that task sizes provide similar execution times in consecutive phases. Temporary coherent computations are structured in a Prediction Binary Tree, in which leaves represent computing tiles to be mapped to processors. A phase-by-phase semi-static load balancing is introduced to the scheduling algorithm. The scheduling algorithm is equipped with a predictor, which estimates the computation time of next phase tiles based on previous execution times and modifies the tiles to achieve balanced execution in phases. For this, two heuristics are used to leverage on data locality in processors. The proposed approach is illustrated by the example of interactive rendering with Parallel Ray Tracing algorithm. The fifth paper ``The Influence of the IBM pSeries Servers Virtualization Mechanism on Dynamic Resource Allocation in AIX 5L'' is by Maciej Mlynski from ASpartner Limited in Poland. The paper concerns a very up-to-date problem of system virtualization and presents the results of research carried on IBM pSeries servers. IBM is strongly developing the virtualization technique especially on IBM pSeries servers enabling an improved and flexible sharing of system resources between applications. The paper investigates novel facilities for dynamic resource management such as micro-partitioning and partition load manager. They enable dynamic creation of workload logical partitions of system resources and their dynamic mangement. It includes run-time resource re-alocation between logical partitions including setting of sharing specifications as well as run-time adding/removing/setting parameters of resources in the system. It remains an open question how to properly tune parameters of the operating system using the provided virtualization facilities to obtain the best efficiency for a given application program. The paper presents the results of experiments which study the effects of tuning the disk subsystem parameters under the IBM AIX 5L operating system with the use of the provided virtualization facilities on the resulting application execution performance. The results show that even small deterioration in the resource pool status requires an immediate adaptation of the operating system parameters to maintain the required performance. The sixth paper ``HeteroPBLAS: A Set of Parallel Basic Linear Algebra Subprograms Optimized for Heterogeneous Computational Clusters'' is by Ravi Reddy, Alexey Lastovetsky and Pedro Alonso from University College Dublin in Ireland and Polytechnic University of Valencia in Spain. The paper concerns the methodology for parallelization of linear algebra computations for execution in heterogeneous cluster environments. The design of the HeteroPBLAS library (Parallel Basic Linear Algebra Subprograms) for heterogeneous computational clusters is presented. The main contribution of the paper is the automation of the parallelization and optimization of the PBLAS, which is done by means of a special user interface and the underlying set of functions. An important element is here a performance model that is based on program code instrumentation, which determines parameters of the application and the executive heterogeneous platform relevant for execution performance of parallel code. The parameter values specified for or returned by execution of the performance model functions are next used for generation and optimal mapping of the parallel code of the library subroutines. The proposed approach is illustrated by experimental results of execution of optimized HeteroPBLAS programs on homogeneous and heterogeneous computing clusters. Marek Tudruj

Heterogeneous Distributed Computing (HDC) system consists of Workstations (WSs) and Personal Computers (PCs). In HDC system, each WS/PC may have different processor and performance. In order to take advantage of this diversity of processing power of a system, an effective task partitioning, scheduling, and load balancing are needed to get the optimum performance. This paper examines the effectiveness of task partitioning and scheduling strategies for image (raytracing) processing application on HDC system. The static and dynamic/Run-time Task Scheduling (RTS) strategies are shown inadequate for balancing the load of HDC system. Two adaptive tasks scheduling strategies are proposed for HDC image computing system. These adaptive strategies are: i) Master Initiate Sub-task size (MIS) strategy (based on centralized resources management approach), and ii) Worker Initiated Sub-task size (WIS) strategy (based on semi-decentralized resources management approach). The measured results show that the adaptive (MIS & WIS) strategies dramatically improve the performance of HDC raytracing system and remedy the defects of static and RTS strategies. Performances of the all investigated strategies are evaluated on manager/master and workers model of HDC system. In performance comparisons of MIS and WIS strategies, the WIS strategy shows a slightly better speedup and scalability over MIS strategy.

Intelligent Internet Computing (IIC) is emerging rapidly including grid, cluster computing, and peer-topeer computing to provide computing and communication services any time and anywhere. IIC foresees the integration of communicating and computational devices and applications in our heterogeneous computing environments. In this paper, we focus on the task allocation, which is a typical problem in the area of high performance computing and has been extensively studied in the past. Efficient task allocation is critical for achieving secure and high performance in a heterogeneous computing (HC) environment. In addition, the problem of allocating these tasks to the machines of a HC environment has been shown, in general, to be NP-complete, requiring the development of heuristic techniques. Therefore, a task allocation algorithm based on discrete particle swarm optimization (PSO) algorithm in the HC environment is proposed in this paper. Firstly, a new structure of cluster system is designed, and a mathematical model is built for dynamic server alliance according to practical tasks and situations of servers. Then an efficient discrete PSO with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm's ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results compared with other algorithms show that this proposed algorithm produces better results in terms of both quality of solution and convergence speed.

We propose a unifying framework based on configuration linear programs and randomized rounding, for different energy optimization problems in the dynamic speed-scaling setting. We apply our framework to various scheduling and routing problems in heterogeneous computing and networking environments. We first consider the energy minimization problem of scheduling a set of jobs on a set of parallel speed-scalable processors in a fully heterogeneous setting. For both the preemptive-non-migratory and the preemptive-migratory variants, our approach allows us to obtain solutions of almost the same quality as for the homogeneous environment. By exploiting the result for the preemptive-non-migratory variant, we are able to improve the best known approximation ratio for the single processor non-preemptive problem. Furthermore, we show that our approach allows to obtain a constant-factor approximation algorithm for the power-aware preemptive job shop scheduling problem. Finally, we consider the min-power routing problem where we are given a network modeled by an undirected graph and a set of uniform demands that have to be routed on integral routes from their sources to their destinations so that the energy consumption is minimized. We improve the best known approximation ratio for this problem.

Cloud computing has become buzzword in computer industry as it provides scalable, reliable and economical services to the users. For better performance of cloud computing it is crucial that an efficient task scheduling algorithm is in place. Scheduling algorithms allocates the resources to the user’s task i.e. it provides mapping between resources and tasks. Scheduling in cloud is NP-hard problem because of large solution space available. Meta-heuristic algorithms have become the most famous scheduling approaches as they provide near optimal solution in short span of time. This paper surveys the various approaches for cloudlet scheduling. It also classifies the various approaches based on the objectives considered for optimization.

Heterogeneous distributed computing has traditionally been a problematic undertaking which increases in complexity as heterogeneity increases. This paper presents results obtained using DOGMA--a Java based system which simplifies parallel computing on heterogeneous computers. The performance of Java just-in-time compilers currently approaches C++ for many applications, making Java a serious contender for parallel application development. DOGMA provides support for dedicated clusters as well as idle workstations through the use of a web based browse-in feature or the DOGMA screen saver. DOGMA supports parallel programming in both a traditional message passing form and a novel object-oriented approach. This research provides a unified environment for developing high performance parallel applications on heterogeneous systems.

In this thesis, the role of location-specific microstructural features in the fatigue performance of the safety-critical aerospace components made of Nickel (Ni)-base superalloys and linear friction welded (LFW) Titanium (Ti) alloys has been studied using crystal plasticity finite element (CPFE) simulations, energy dispersive X-ray diffraction (EDD), backscatter electron (BSE) images and digital image correlation (DIC).<br>In order to develop a microstructure-sensitive fatigue life prediction framework, first, it is essential to build trust in the quantitative prediction from CPFE analysis by quantifying uncertainties in the mechanical response from CPFE simulations. Second, it is necessary to construct a unified fatigue life prediction metric, applicable to multiple material systems; and a calibration strategy of the unified fatigue life model parameter accounting for uncertainties originating from CPFE simulations and inherent in the experimental calibration dataset. To achieve the first task, a genetic algorithm framework is used to obtain the statistical distributions of the crystal plasticity (CP) parameters. Subsequently, these distributions are used in a first-order, second-moment method to compute the mean and the standard deviation for the stress along the loading direction (σ_load), plastic strain accumulation (PSA), and stored plastic strain energy density (SPSED). The results suggest that an ~10% variability in σ_load and 20%-25% variability in the PSA and SPSED values may exist due to the uncertainty in the CP parameter estimation. Further, the contribution of a specific CP parameter to the overall uncertainty is path-dependent and varies based on the load step under consideration. To accomplish the second goal, in this thesis, it is postulated that a critical value of the SPSED is associated with fatigue failure in metals and independent of the applied load. Unlike the classical approach of estimating the (homogenized) SPSED as the cumulative area enclosed within the macroscopic stress-strain hysteresis loops, CPFE simulations are used to compute the (local) SPSED at each material point within polycrystalline aggregates of 718Plus, an additively manufactured Ni-base superalloy. A Bayesian inference method is utilized to calibrate the critical SPSED, which is subsequently used to predict fatigue lives at nine different strain ranges, including strain ratios of 0.05 and -1, using nine statistically equivalent microstructures. For each strain range, the predicted lives from all simulated microstructures follow a log-normal distribution; for a given strain ratio, the predicted scatter is seen to be increasing with decreasing strain amplitude and are indicative of the scatter observed in the fatigue experiments. Further, the log-normal mean lives at each strain range are in good agreement with the experimental evidence. Since the critical SPSED captures the experimental data with reasonable accuracy across various loading regimes, it is hypothesized to be a material property and sufficient to predict the fatigue life.<br>Inclusions are unavoidable in Ni-base superalloys, which lead to two competing failure modes, namely inclusion- and matrix-driven failures. Each factor related to the inclusion, which may contribute to crack initiation, is isolated and systematically investigated within RR1000, a powder metallurgy produced Ni-base superalloy, using CPFE simulations. Specifically, the role of the inclusion stiffness, loading regime, loading direction, a debonded region in the inclusion-matrix interface, microstructural variability around the inclusion, inclusion size, dissimilar coefficient of thermal expansion (CTE), temperature, residual stress, and distance of the inclusion from the free surface are studied in the emergence of two failure modes. The CPFE analysis indicates that the emergence of a failure mode is an outcome of the complex interaction between the aforementioned factors. However, the possibility of a higher probability of failure due to inclusions is observed with increasing temperature, if the CTE of the inclusion is higher than the matrix, and vice versa. Any overall correlation between the inclusion size and its propensity for damage is not found, based on inclusion that is of the order of the mean grain size. Further, the CPFE simulations indicate that the surface inclusions are more damaging than the interior inclusions for similar surrounding microstructures. These observations are utilized to instantiate twenty realistic statistically equivalent microstructures of RR1000 – ten containing inclusions and remaining ten without inclusions. Using CPFE simulations with these microstructures at four different temperatures and three strain ranges for each temperature, the critical SPSED is calibrated as a function of temperature for RR1000. The results suggest that critical SPSED decreases almost linearly with increasing temperature and is appropriate to predict the realistic emergence of the competing failure modes as a function of applied strain range and temperature.<br>LFW process leads to the development of significant residual stress in the components, and the role of residual stress in the fatigue performance of materials cannot be overstated. Hence, to ensure fatigue performance of the LFW Ti alloys, residual strains in LFW of similar (Ti-6Al-4V welded to Ti-6Al-4V or Ti64-Ti64) and dissimilar (Ti-6Al-4V welded to Ti-5Al-5V-5Mo-3Cr or Ti64-Ti5553) Ti alloys have been characterized using EDD. For each type of LFW, one sample is chosen in the as-welded (AW) condition and another sample is selected after a post-weld heat treatment (HT). Residual strains have been separately studied in the alpha and beta phases of the material, and five components (three axial and two shear) have been reported in each case. In-plane axial components of the residual strains show a smooth and symmetric behavior about the weld center for the Ti64-Ti64 LFW samples in the AW condition, whereas these components in the Ti64-Ti5553 LFW sample show a symmetric trend with jump discontinuities. Such jump discontinuities, observed in both the AW and HT conditions of the Ti64-Ti5553 samples, suggest different strain-free lattice parameters in the weld region and the parent material. In contrast, the results from the Ti64-Ti64 LFW samples in both AW and HT conditions suggest nearly uniform strain-free lattice parameters throughout the weld region. The observed trends in the in-plane axial residual strain components have been rationalized by the corresponding microstructural changes and variations across the weld region via BSE images. <br>In the literature, fatigue crack initiation in the LFW Ti-6Al-4V specimens does not usually take place in the seemingly weakest location, i.e., the weld region. From the BSE images, Ti-6Al-4V microstructure, at a distance from the weld-center, which is typically associated with crack initiation in the literature, are identified in both AW and HT samples and found to be identical, specifically, equiaxed alpha grains with beta phases present at the alpha grain boundaries and triple points. Hence, subsequent fatigue performance in LFW Ti-6Al-4V is analyzed considering the equiaxed alpha microstructure.<br>The LFW components made of Ti-6Al-4V are often designed for high cycle fatigue performance under high mean stress or high R ratios. In engineering practice, mean stress corrections are employed to assess the fatigue performance of a material or structure; albeit this is problematic for Ti-6Al-4V, which experiences anomalous behavior at high R ratios. To address this problem, high cycle fatigue analyses are performed on two Ti-6Al-4V specimens with equiaxed alpha microstructures at a high R ratio. In one specimen, two micro-textured regions (MTRs) having their c-axes near-parallel and perpendicular to the loading direction are identified. High-resolution DIC is performed in the MTRs to study grain-level strain localization. In the other specimen, DIC is performed on a larger area, and crack initiation is observed in a random-textured region. To accompany the experiments, CPFE simulations are performed to investigate the mechanistic aspects of crack initiation, and the relative activity of different families of slip systems as a function of R ratio. A critical soft-hard-soft grain combination is associated with crack initiation indicating possible dwell effect at high R ratios, which could be attributed to the high-applied mean stress and high creep sensitivity of Ti-6Al-4V at room temperature. Further, simulations indicated more heterogeneous deformation, specifically the activation of multiple families of slip systems with fewer grains being plasticized, at higher R ratios. Such behavior is exacerbated within MTRs, especially the MTR composed of grains with their c-axes near parallel to the loading direction. These features of micro-plasticity make the high R ratio regime more vulnerable to fatigue damage accumulation and justify the anomalous mean stress behavior experienced by Ti-6Al-4V at high R ratios.<br>

Reconfigurable computing (RC) is rapidly emerging as a promising technology for the future of high-performance and embedded computing, enabling systems with the computational density and power of custom-logic hardware and the versatility of software-driven hardware in an optimal mix. Novel methods for rapid virtual prototyping, performance prediction, and evaluation are of critical importance in the engineering of complex reconfigurable systems and applications. These techniques can yield insightful tradeoff analyses while saving valuable time and resources for researchers and engineers alike. The research described herein provides a methodology for mapping arbitrary applications to targeted reconfigurable platforms in a simulation environment called RCSE. By splitting the process into two domains, the application and simulation domains, characterization of each element can occur independently and in parallel, leading to fast and accurate performance prediction results for large and complex systems. This article presents the design of a novel framework for system-level simulative performance prediction of RC systems and applications. The article also presents a set of case studies analyzing two applications, Hyperspectral Imaging (HSI) and Molecular Dynamics (MD), across three disparate RC platforms within the simulation framework. The validation results using each of these applications and systems show that our framework can quickly obtain performance prediction results with reasonable accuracy on a variety of platforms. Finally, a set of simulative case studies are presented to illustrate the various capabilities of the framework to quickly obtain a wide range of performance prediction results and power consumption estimates.

As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm are proposed in this paper to optimize the native scheduling strategy of Spark. In this new strategy, the static level of nodes is calculated, the dynamic factors such as the length of running tasks, and CPU usage of work nodes are considered comprehensively. And through a series of comparative experiments in alienation cluster, the new strategy costs less running time and lower CPU usage rate than the original Spark strategy, which verifies that the new schedule strategy is more effective one.

This special issue is based on a collection of selected papers presented at the Fifth International Conference on Advanced Computing held in Chennai (Madras), India in December 97. The International Conference on Advanced Computing is organized annually in India by the Advanced Computing Society (ACS) which is a premier professional society set up in India to cater to the broad interests in the area of Advanced Computing. One of the significant activities of the Society is to organize regular Meetings/Conferences/Symposia. The Conferences are held annually in India during December. Out of the shortlisted papers presented at the Conference held in Chennai (Madras) during December 97, the following six papers were finally selected after a second round of detailed review of the papers. The first paper On designing and implementing collaborative system using Java-RMI by Rajeev R. Raje, Snehasis Mukhopadhyay, Michael Boyles and Nila Patel describe the use of Java-RMI in designing a collaborative information classifier. The principles of RMI, the details of the prototype, and some preliminary results are presented. The paper primarily concentrates on web-based computing paradigms. In the second paper A framework for performance-based program partitioning , Ram Subramanian and Santosh Pande present an efficient and accurate performance model based program-partitioning approach for parallel architectures. The interactions between computation and communication are captured through behavioral edges . The approach yields significant performance improvement. The third paper DDSCHED: a distributed dynamic real-time scheduling algorithm by Anup K. Bhattacharjee, K. Ravindranath, R. Mall and A. Pal presents a dynamic soft real-time scheduling algorithm for distributed systems. The algorithm is based on a local scheduler and a distributed scheduling scheme. The algorithm takes care of the network delays assuming that the communication protocol is CSMA/CD. In the fourth paper Generic operational decomposition for concurrent systems semantics and reflection , Annie Marcoux, Christine Maurel, Frederic Migeon and Patrick Salle discuss about the reflection in concurrent languages, particularly in actor-based languages. The main objective of the paper is to extend concurrent systems to reflection. The authors present a modular and dynamic description of entity operational management, and extend the decomposition to obtain reflective entities. The fifth paper Parallel programming using visual patterns by A. S. M. Sajeev proposes a two level approach to parallel programming within the context of a visual environment. The first level is the specification of patterns encapsulating process communation and synchronization, and the second level is the use of patterns for parallel programming. The approach encourages reuse of patterns. In the sixth paper An application framework for dynamic distributed software architectures , G. R. Ribeiro-Justo and P. R. F. Cunha present an object-oriented application framework for developing evolving (reconfigurable) software architectures for distributed systems. The application framework is called C++CL. Such a requirement is encountered in banking, industrial control and telecommunications applications. We are extremely thankful to the following reviewers who have helped us in reviewing the papers submitted for this special issue: Lawrence Jenkins N. Mohan Ram Nishit Narang Rajeev Shorey Sameer Adhikari K. Balaji K. Rajan Sumit Kasera Subhrajyothi Bhar Pankaj Sethi Ravindranath Kokku Guest Editors: L. M. Patnaik, Ravi Mittal and K. M. Mehta

The usage of voice over IP (VoIP) traffic in IEEE 802.11 wireless networks is expected to increase in the near future due to widely deployed 802.11 wireless networks and VoIP services on fixed lines. However, the quality of service (QoS) of VoIP traffic in wireless networks is still unsatisfactory. In this thesis, I identify several sources for the QoS problems of VoIP traffic in IEEE 802.11 wireless networks and propose solutions for these problems. The QoS problems discussed can be divided into three categories, namely, user mobility, VoIP capacity, and call admission control. User mobility causes network disruptions during handoffs. In order to reduce the handoff time between Access Points (APs), I propose a new handoff algorithm, Selective Scanning and Caching, which finds available APs by scanning a minimum number of channels and furthermore allows clients to perform handoffs without scanning, by caching AP information. I also describe a new architecture for the client and server side for seamless IP layer handoffs, which are caused when mobile clients change the subnet due to layer 2 handoffs. I also present two methods to improve VoIP capacity for 802.11 networks, Adaptive Priority Control (APC) and Dynamic Point Coordination Function (DPCF). APC is a new packet scheduling algorithm at the AP and improves the capacity by balancing the uplink and downlink delay of VoIP traffic, and DPCF uses a polling based protocol and minimizes the bandwidth wasted from unnecessary polling, using a dynamic polling list. Additionally, I estimated the capacity for VoIP traffic in IEEE 802.11 wireless networks via theoretical analysis, simulations, and experiments in a wireless test-bed and show how to avoid mistakes in the measurements and comparisons. Finally, to protect the QoS for existing VoIP calls while maximizing the channel utilization, I propose a novel admission control algorithm called QP-CAT (Queue size Prediction using Computation of Additional Transmission), which accurately predicts the impact of new voice calls by virtually transmitting virtual new VoIP traffic.

Since the grid system is implemented on a network framework with heterogeneous remote resources, it is a hazardous environment. The possibility of failure occurrence on the grid resources are not negligible and should be considered. On the other hand, the reliability is a major criterion for the safety-critical and real time applications. This paper focuses on dependability aspects of grid scheduling strategies such as reliability and availability by using various forms of redundancy (e.g. hardware, software, and data). A hybrid method including fault masking and fault tolerance is used in this paper to improve the reliability of grid scheduling system. The proposed scheduling model integrates an active redundancy and backup majority voting together. After the detection of an error, multiple check-pointing as a recovery technique is invoked by the proposed scheduler. This method can be used at each level of scheduling based on a hierarchical and dynamic architecture. This scheduling model does not have a significant time overhead on other performance criteria such as waiting time, completion time and throughput. The proposed scheduling model also tries to reduce the resource cost in economic grids. Simulation results of proposed model in the presence of faults and resource failure show the improvement of reliability when compared with non-fault tolerance scheduler and other classic methods.

The present dissertation describes the research work carried out towards: I. developing of analytical and numerical models for accurate and efficient analysis of laminates and sandwiches under different loading conditions (static analyses, impulsive loading and low velocity impacts); II. developing of techniques to improve structural performances of composites structures by tuning their energy absorption mechanism; A higher order theory (AD-ZZ) including zig-zag effects, transverse shear continuity, variable transverse displacement and layerwise representation is presented for analysis of laminates and sandwiches. This theory is cast in such a way that the unknowns in the model will involve only five variables like equivalent single layer models: the three displacement components and the two shear rotations of the normals on the reference surface. It is advantageous to formulate the theory in this way, as it provides the opportunity to refine its through-the-thickness representation by adding computational layers in the thickness direction without increasing the number of unknowns. After extensive evaluation of the accuracy obtained by the above mentioned theory for a variety of structures, the AD-ZZ model is enriched by adding a set of continuity functions in order to treat laminates and structures with in-plane discontinuities (e.g. bonded joints, two material wedge) under a unified approach without adding new unknowns. Speaking of techniques to improve structural performances, two approaches are presented: variable stiffness composites and stitching. The former tool works on the strain energy of the structure computing fibre distributions that minimize unwanted energy contributions and maximize the wanted ones. The latter prescribes the insertions of transverse reinforcements in sandwich structures. The homogenized mechanical properties of this structure, required by the AD-ZZ model to perform the analysis, are evaluated through virtual material tests using a 3D FE model. The results obtained applying these techniques demonstrate that both are effective in reducing transverse stresses at critical interfaces and, in certain cases, in improving bending stiffness. New C0 displacement-based and stress-based finite elements for analysis of laminated and sandwich plates based on the AD-ZZ model are developed. To achieve this goal, a new technique that converts derivatives of functional degrees of freedom contained in the AD-ZZ is presented. Both the elements satisfy all the requirements of computationally efficient finite element models for analysis of multilayered structures, namely 1) the number of degrees of freedom is independent from the number of layers; 2) no shear correction factors or penalty number are added in the formulation. Consistent shear fields are obtained for the present finite element formulations. Numerical results demonstrate that these new elements are robust, accurate and computationally efficient for analysis of multilayered structures. In order to study structures subjected to impact loading a new simulation procedure is developed. It is based on the AD-ZZ model and considers the crushing behaviour of soft-like media without performing each time a detailed 3D finite element analysis. Numerical results show that the response of composites undergoing low velocity impact is very accurately predicted with low computational effort. Overall, the present procedure holds great promise for analysis of laminated and sandwich structures undergoing low velocity impact

Quantifying above ground biomass of grasslands is important information for grassland management and the understanding of ecological processes in grassland habitats. Often, allometric relationships between grassland height and biomass are used for biomass estimation. While these methods may be used in intensively used grassland with a homogenous canopy surface, in heterogenous grasslands it is not possible to repeat these measurements on larger areas. Recent technological advances in active and passive remote sensing offering new opportunities for estimations of grassland biomass. Many studies using remote sensing data for biomass estimation are based on the analysis of optical remote sensing sensors and are situated in forests and agricultural crops. Small temporal and spatially heterogenous grasslands were often neglected due to their complex vegetation structure. Just recently, point cloud data based either on terrestrial laser measurements (TLS) or on photogrammetric image analysis (SfM) approaches were investigated for their potential of biomass estimation in grasslands. The focus of this talk will be on evaluating the potential of TLS and SfM derived point clouds in deriving biomass estimation of grasslands with very different land use intensities. Both approaches show promising results for predicting grassland biomass (R2 ranging from 0.48 to 0.79 and from 0.35 to 0.81 for TLS and SfM respectively). TLS always performs better, which could be explained by the higher point densities and thus higher information content about the vegetation structure. However, under consideration of price and expert knowledge UAV based point clouds also produce satisfying results. Another aspect of the talk will be the comparison of performance aspects (e.g. computing time) of different point cloud analysis strategies. It can be shown that two scans of the same location from different aspects already provide detailed information about biomass and additional scans only lead to an unnecessary increase in data volume while maintaining consistent prediction quality. Various analysis methods will be test for extracting information from the point clouds. Here methods based on canopy surface height show the best prediction performance for biomass. Concluding, it is possible to say that both TLS and SfM-based point clouds have a good potential for deriving biomass information of grasslands, independent of land use intensity. However, to derive final conclusions the stability of the statistical relationships needs to be test over several growing periods. For the future, also the fusion of point cloud information with spectral information should be tested, as better biomass prediction models can be expected from this.

An Effective and Practical Performance Prediction Model for Parallel Computing on Nondedicated Heterogeneous NOW