An Efficient Real-Time Fault-Tolerant Scheduling Algorithm Based on Multiprocessor Systems

In the context of real-time fault-tolerant scheduling in multiprocessor systems, Primary-backup scheme plays an important role. A backup copy is always preferred to be executed as passive backup copy whenever possible because it can take the advantages of backup copy de-allocation technique and overloading technique to improve schedulability. In this paper, we propose a novel efficient fault-tolerant ratemonotonic best-fit algorithm efficient fault-tolerant rate-monotonic best-fit （ERMBF） based on multiprocessors systems to enhance the schedulability. Unlike existing scheduling algorithms that start scheduling tasks with only one processor. ERMBF pre-allocates a certain amount of processors before starting scheduling tasks, which enlarge the searching spaces for tasks. Besides, when a new processor is allocated, we reassign the task copies that have already been assigned to the existing processors in order to find a superior tasks assignment configuration. These two strategies are all aiming at making as many backup copies as possible to be executed as passive status. As a result, ERMBF can use fewer processors to schedule a set of tasks without losing real-time and fault-tolerant capabilities of the system. Simulation results reveal that ERMBF significantly improves the schedulability over existing, comparable algorithms in literature.     

A Chord-based resource scheduling approach in drug discovery grid

This paper presents a resource scheduling approach in grid computing environment. Using P2P technology, this novel approach can schedule dynamic grid computing resources efficiently. Grid computing resources in different domains are organized into a structured P2P overlay network. Available resource information is published in type of grid services. Task requests for computational resources are also presented as grid services. Problem of resources scheduling is translated into services discovery. Different from central scheduling approaches that collect available resources information, this Chord-based approach forwards task requests in the overlay network and discovers satisfied resources for these tasks. Using this approach, the computational resources of a grid system can be scheduled dynamically according to the real-time workload on each peer. Furthermore, the application of this approach is introduced into DDG, a grid system for drug discovery and design, to evaluate the performance. Experimental results show that computational resources of a grid system can be managed efficiently, and the system can hold a perfect load balance state and robustness.     

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.     

Clustering and Scheduling Method Based on Task Duplication

A new heuristic approach that resembles the evolution of interpersonal relationships in human society is put forward for the problem of scheduling multitasks represented by a directed acyclic graph. The algorithm includes dynamic-group, detachgraph and front-sink components. The priority rules used are new. Relationship number, potentiality, weight and merge degree are defined for cluster＇s priority, and task potentiality for tasks＇ priority. Experiments show the algorithm could get good result in short time. The algorithm produces another optimal solution for the classic MJD benchmark. Its average performance is better than five latter-day representative algorithms, especially six benchmarks of the nines.     

Broadcast Scheduling Strategy Based on the Priority of Real-Time Data in a Mobile Environment

Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel, scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels. In order to meet the requirement of real-time data disseminating and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing     

Broadcast Scheduling Strategy Based on the Priority of Real.Time Data in a Mobile Environment

Data broadcast is an important data dissemination approach in mobile environment. On broadcast channel,scalability and efficiency of data transmission are satisfied. In a mobile environment, there exists a kind of real-time database application in which both the transactions and data can have their timing constraints and priorities of different levels.In order to meet the requirement of real-time data disseminaring and retrieving, a broadcast scheduling strategy HPF-ED F (Highest Priority First with Earlier Deadline and Frequency) is proposed under the BoD (Broadcast on Demand) model. Using the strategy, data items are scheduled according to their priority the transaction imposed on them or system set for them. The strategy also considers other characteristics of data items such as deadline and popularity of data. The extensive simulation experiments have been conducted to evaluate the performance of the proposed algorithm. Results show that it can achieve excellent performance compared with existing strategies.     

Issues in Learner Strategy

There is an urgent need in China that learning strategy and strategy training be given the attenion and status that it deserves. Strategy training can help students make effcetive use of multipleers has proved a useful way of investigating how strategies affectstrategies. Studying good language learn-language learning. The first approach to strategy trsJning suggested by Cohen is targets isolated strategies by including explicit modeling and explanation of the benefits of applying a specific strategy, extensive functional practice with the strategy. The second approach outlined by Oxford is to raise stu-dents‘ awareness as to the purpose and rationale of strategy use. The third approach by Cohen is to help students to com-plete language learning tasks through planning, monitoring, problem solving and evaluation. Teachers play an important part in strategy training.     

An improvement on algorithm of grid-workflow based on QoS

With the emergencc of grid computing. new challenges have arisen in workflow tasks scheduling. The goal of grid-workflow task scheduling is to achieve high system throughput and to match the application needs with the available computing resources. This matching of resources in a non-deterministically share heterogeneous environment leads to concerns on quality of service (QoS). Grid concept is presented in this paper, coupled with the QoS requirement of workflow task and an improved algorithm-ILGSS algorithm. has been brought out. The complexity of the improved sched uling algorithm has been analyzed. The experiment results show that the improved algorithm can lead to significant performance gain in various applicatkms. An important research domain adaptive workflow transaction in grid computing environment, has been explored and a new solution for the scheduling of distribute workflow has been hring forward in grid environment.     

An improved method of support vector machine and its applications to financial time series forecasting

A novel method for kernel function of support vector machine is presented based on the information geometry theory. The kernel function is modified using a conformal mapping to make the kernel data-dependent so as to increase the ability of predicting high noise data of the method. Numerical simulations demonstrate the effectiveness of the method. Simulated results on the prediction of the stock price show that the improved approach possesses better forecasting precision and ability of generalization than the conventional models.     

Parallel scheduling strategy of web-based spatial computing tasks in multi-core environment

In order to improve the concurrent access performance of the web-based spatial computing system in cluster,a parallel scheduling strategy based on the multi-core environment is proposed,which includes two levels of parallel processing mechanisms.One is that it can evenly allocate tasks to each server node in the cluster and the other is that it can implement the load balancing inside a server node.Based on the strategy,a new web-based spatial computing model is designed in this paper,in which,a task response ratio calculation method,a request queue buffer mechanism and a thread scheduling strategy are focused on.Experimental results show that the new model can fully use the multi-core computing advantage of each server node in the concurrent access environment and improve the average hits per second,average I/O Hits,CPU utilization and throughput.Using speed-up ratio to analyze the traditional model and the new one,the result shows that the new model has the best performance.The performance of the multi-core server nodes in the cluster is optimized; the resource utilization and the parallel processing capabilities are enhanced.The more CPU cores you have,the higher parallel processing capabilities will be obtained.     

A Novel Processor Scheduling Schema in Programmable Router Based on Queue Length Thresholds

Programmable router may execute computing tasks except for forwarding IP packets. How to schedule the CPU in the programmable router is an important issue that needs to be solved. In this paper, the authors establish general software architecture of programmable router firstly. Based on this architecture, authors present a novel CPU scheduling algorithm based on queue length thresholds. We model this algorithm using stochastic Petri nets. The analytic results show that this scheduling algorithm can guarantee the requirements of computing of best-effort flows and QoS flows in prograrmmable router at the same time.     

X-RESTORE:Middleware for XML‘s Relational Storage and Retrieve

We propose a new approach to store and query XML data in an RDBMS basing on the idea of the numbering scheme and inverted list. Our approach allows us to quickly determine the precedence, sibling and ancestor/descendant relationships between any pair of nodes in the hierarchy of XML, and utilize path index to speed up calculating of path expressions. Examples have demonstrated that our approach can effectively and efficiently support both XQuery queries and keyword searches. our approach is also flexible enough to support XML documents both with Schema and without Schema, and applications both retrieval and update. We also present the architecture of middleware for application accessing XML documents stored in relations, and an algorithm translating a given XML document into relation effectively.     

Planning to Plan-Integrating Control Flow

In many planning situations, computation itself becomes a resource to be planned and scheduled.We model such computational resources as conventional resources which are used by control-flow actions,e.g., to direct the planning process. Control-flow actions and conventional actions are planned/scheduled in an integrated way and can interact with each other. Control-flow actions are then executed by the planning engine itself. The approach is illustrated by examples, e. g., for hierarchical planning, in which tasks that are temporally still far away impose only rough constraints on the current schedule, and control-flow tasks ensure that these tasks are refined as they approach the current time. Using the same mechanism, anytime algorithms can change appropriate search methods or parameters over time, and problems like scheduling critical time-outs for garbage collection can be made part of the planning itself.     

Optimal Component Types for the Design of Construction Processes

Within the project preparation phase, experienced professionals manually map design information onto process information with the aim to develop realistic and practical schedules. Unfortunately, the mapping itself is neither part of any underlying data model nor is it supported by current scheduling tools. As a consequence the process of setting up the data model for a schedule is still not supported formally. Huhnt and Enge described a modelling technique that addresses the missing linkage between design and process information[1]. The approach makes use of so called component types. These are template sub-processes that describe the fabrication procedure of typical building components. Decomposing the building into com-ponents and assigning a component type to each component allows for formal support while scheduling. Depending on the decomposition of the building into components and the complexity of the involved component types the specification effort differs. The question about optimal component types arises: Which layout of building components and component types results in minimal specification effort? This paper presents a branch and bound algorithm to determine optimal component types. For a given schedule, which has been modelled based on component types, all possible decompositions into sub-processes are determined. During the decomposition process the encountered configurations are compared. Those with minimal specifica-tion effort are registered. Theoretical and practical examples are examined and discussed.     

A partition checkpoint strategy based on data segment priority

A partition checkpoint strategy based on data segment priority is presented to meet the timing constraints of the data and the transaction in embedded real-time main memory database systems(ERTMMDBS) as well as to reduce the number of the transactions missing their deadlines and the recovery time.The partition checkpoint strategy takes into account the characteristics of the data and the transactions associated with it;moreover,it partitions the database according to the data segment priority and sets the corresponding checkpoint frequency to each partition for independent checkpoint operation.The simulation results show that the partition checkpoint strategy decreases the ratio of trans-actions missing their deadlines.     

Algorithms for semi on-line multiprocessor scheduling problems

In the classical multiprocessor scheduling problems, it is assumed that the problems are considered in off-line or on-line enviromnent. But in practice, problems are often not really off-line or on-line but somehow in between. This means that, with respect to the on-line problem, some further information about the tasks is available, which allows the improvement of the performance of the best possible algorithms. Problems of this class are called semi on-line ones. The authors studied two semi on-line multiprocessor scheduling problems, in which, the total processing time of all tasks is known in advance, or all processing times lie in a given interval. They proposed approximation algorithms for minimizing the makespan and analyzed their performance guarantee. The algorithms improve the known results for 3 or more processor cases in the literature.     

Politeness Strategies in American Presidential Inaugural Addresses

American presidential inaugural address (PIA)is a very important variety with worldwide influence and long-lasting significance. Its main task and purpose is to outline the main policies of the new government and win people's support. However, the prerequisite of winning people's sympathy and support lies in people's good relationship with and trust in the government. Therefore almost all the speakers resort to "approached-based" positive politeness strategy quite often which performs this function very well.     

Active set strategy of optimized extreme learning machine

Extreme learning machine （ELM） has been introduced as a simple and efficient learning approach for regression and classification applications. From the opti- mization point of view, optimized ELM is equivalent to SVM, but with less constraints in the optimization formu- lation and random ELM kernel. This paper introduces an active set based optimized ELM approach to solve bound constrained optimization problem in a straightforward way, which operates on a small working set of variables at each iteration. Thus, the constrained problem can be eventually solved by an unconstrained algorithm, and this enables us to establish a global convergence theory. The approach requires less time for quadratic programming solving and provides better generalization performance. In addition, the proposed approach with much smaller number of non- bound support values is significantly faster than SVM with active set strategy for large training data set.     

Concurrent processes scheduling with scarce resources in small and medium enterprises

Scarce resources , precedence and non-determined time-lag are three constraints commonly found in small and medium manufacturing enterprises (SMEs), which are deemed to block the ap-plication of workflow management system ( WfMS ) .To tackle this problem , a workflow scheduling approach is proposed based on timing workflow net (TWF-net) and genetic algorithm (GA).The workflow is modelled in a form of TWF-net in favour of process simulation and resource conflict checking .After simplifying and reconstructing the set of workflow instance , the conflict resolution problem is transformed into a resource-constrained project scheduling problem ( RCPSP ) , which could be efficiently solved by a heuristic method , such as GA.Finally, problems of various sizes are utilized to test the performance of the proposed algorithm and to compare it with first-come-first-served ( FCFS) strategy.The evaluation demonstrates that the proposed method is an overwhelming and effective approach for scheduling the concurrent processes with precedence and resource con -straints .     

Particle Swarm Optimization Embedded in Variable Neighborhood Search for Task Scheduling in Cloud Computing

In cloud computing system,it is a hot and hard issue to find the optimal task scheduling method that makes the processing cost and the running time minimum. In order to deal with the task assignment,a task interaction graph was used to analyze the task scheduling; a modeling for task assignment was formulated and a particle swarm optimization (PSO)algorithm embedded in the variable neighborhood search (VNS) to optimize the task scheduling was proposed. The experimental results show that the method is more effective than the PSO in processing cost,transferring cost, and running time. When the task is more complex,the effect is much better. So,the algorithm can resolve the task scheduling in cloud computing and it is feasible,valid,and efficient.