Network Bandwidth-aware job scheduling with dynamic information model for Grid resource brokers

A resource broker with a user-friendly interface for job submission developed on a platform constructed using the Globus toolkit is proposed. The broker employs a domain-based network information model and dynamic version to measure network statuses, and also monitors and collects resource statuses and network-related information as the basis of its brokerage. A network bandwidth-aware job scheduling algorithm for brokering suitable Grid resources to communication-intensive jobs based on improving and preserving the advantages of our previously developed network information model is also proposed. Using timely information, the resource broker effectively matches Grid resources and user requests, thus improving job execution efficiency.     

P-GRADE: A Grid Programming Environment

P-GRADE provides a high-level graphical environment to develop parallel applications transparently both for parallel systems and the Grid. P-GRADE supports the interactive execution of parallel programs as well as the creation of a Condor, Condor-G or Globus job to execute parallel programs in the Grid. In P-GRADE, the user can generate either PVM or MPI code according to the underlying Grid where the parallel application should be executed. PVM applications generated by P-GRADE can migrate between different Grid sites and as a result P-GRADE guarantees reliable, fault-tolerant parallel program execution in the Grid. The GRM/PROVE performance monitoring and visualisation toolset has been extended towards the Grid and connected to a general Grid monitor (Mercury) developed in the EU GridLab project. Using the Mercury/GRM/PROVE Grid application monitoring infrastructure any parallel application launched by P-GRADE can be remotely monitored and analysed at run time even if the application migrates among Grid sites. P-GRADE supports workflow definition and co-ordinated multi-job execution for the Grid. Such workflow management can provide parallel execution at both inter-job and intra-job level. Automatic checkpoint mechanism for parallel programs supports the migration of parallel jobs inside the workflow providing a fault-tolerant workflow execution mechanism. The paper describes all of these features of P-GRADE and their implementation concepts.     

基于Mesh技术的矿井应急救灾通信系统设计研究

针对矿井应急通信系统存在的呼吸器影响语音清晰度、缺少视频信息、缺少环境参数监测和传输功能等问题,提出了一种基于无线Mesh技术的矿井应急救灾通信系统设计方案,简要介绍了无线Mesh的基本原理及结构,给出了矿井应急救灾通信系统的组网方式、整体架构和主要设备的设计方案,详细阐述了网络服务质量的保证、无线Mesh网络的动态路由选择、业务准入与控制和音视频流无缝移动传输等关键技术难题及解决办法。实际应用表明,该系统能同时实现井上指挥中心、井下指挥中心和井下救护人员之间的语音和视频通信功能,并能在井上和井下指挥中心实时显示救灾现场的环境参数。     

Securing the mobile device

Much of the information available about wireless security revolves around securing the actual wireless communications; insuring the confidentiality, integrity, and availability of the data on a wireless network. However, what often goes overlooked is the wireless device itself. These devices are wireless for a reason; they are mobile and generally designed to be used in any location a user has access to a network. Phones, laptops, and PDA's are all purchased primarily for their mobility, not their stunning good looks.     

基于无线监控的离子水雾化加湿系统设计

基于现有雾化加湿系统,结合无线物联网技术、电解水技术和传感器检测技术,并对离子水雾化装置进行了研究,提出并设计了基于无线监控的离子水雾化加湿系统,可实时监测室内外温湿度,并通过无线物联网技术对离子水发生装置和其他温控设备进行控制,还可以在加湿过程中对病原体进行有效抑制或杀灭,达到环境保湿和预防病原体滋生的作用.     

Scheduling and planning job execution of loosely coupled applications

Growth in availability of data collection devices has allowed individual researchers to gain access to large quantities of data that needs to be analyzed. As a result, many labs and departments have acquired considerable compute resources. However, effective and efficient utilization of those resources remains a barrier for the individual researchers because the distributed computing environments are difficult to understand and control. We introduce a methodology and a tool that automatically manipulates and understands job submission parameters to realize a range of job execution alternatives across a distributed compute infrastructure. Generated alternatives are presented to a user at the time of job submission in the form of tradeoffs mapped onto two conflicting objectives, namely job cost and runtime. Such presentation of job execution alternatives allows a user to immediately and quantitatively observe viable options regarding their job execution, and thus allows the user to interact with the environment at a true service level. Generated job execution alternatives have been tested through simulation and on real-world resources and, in both cases, the average accuracy of the runtime of the generated and perceived job alternatives is within 5%.     

基于网格的现代协同设计中的监控服务系统*

网格监控在网格和网格支持的现代协同设计(GMCD)中发挥着重要作用。该系统能针对设计单元的性能数据实施分类监控,跟踪任务的分配和执行情况,监测异常并报警。提出了GMCDMSS的组成结构,确定了其基本功能并介绍了各项功能的实现方案。GMCDMSS有效保障了设计任务的顺利实施,方便了用户对网格资源和任务的监控与管理;它还提供了对性能数据进行分析的手段,便于优化系统性能。     

基于网格计算市场模型的资源管理和调度的研究

网格计算市场模型是把经济学的概念应用到网格资源管理和调度的模型。基于计算市场模型的网格资源管理系统借鉴人类社会竞争的市场调节机制，根据用户的经济需求进行资源管理与任务调度，不仅使资源所有者和资源消费者都能实现各自的经济目标，而且使资源消费者使用轻负栽和廉价的资源，达到整个网格资源整体的全局最优及合理利用。     

一个高分子模拟计算网格的作业管理

高分子模拟计算网格为复杂材料研究人员提供了分子模拟软件、计算资源和信息共享的平台。设计和实现了网格作业管理模块,包括作业的提交、调度和监视,为用户提供了一个透明的网格资源的使用方法。该模块已经成功部署到高分子模拟计算网格系统中,试验结果表明,作业管理为网格用户提供更好的服务质量,实现了对网格资源的优化使用。     

Autonomic Clouds on the Grid

Computational clouds constructed on top of existing Grid infrastructure have the capability to provide different entities with customized execution environments and private scheduling overlays. By designing these clouds to be autonomically self-provisioned and adaptable to changing user demands, user-transparent resource flexibility can be achieved without substantially affecting average job sojourn time. In addition, the overlay environment and physical Grid sites represent disjoint administrative and policy domains, permitting cloud systems to be deployed non-disruptively on an existing production Grid. Private overlay clouds administered by, and dedicated to the exclusive use of, individual Virtual Organizations are termed Virtual Organization Clusters. A prototype autonomic cloud adaptation mechanism for Virtual Organization Clusters demonstrates the feasibility of overlay scheduling in dynamically changing environments. Commodity Grid resources are autonomically leased in response to changing private scheduler loads, resulting in the creation of virtual private compute nodes. These nodes join a decentralized private overlay network system called IPOP (IP Over P2P), enabling the scheduling and execution of end user jobs in the private environment. Negligible overhead results from the addition of the overlay, although the use of virtualization technologies at the compute nodes adds modest service time overhead (under 10%) to computationally-bound Grid jobs. By leasing additional Grid resources, a substantial decrease (over 90%) in average job queuing time occurs, offsetting the service time overhead.     

Design and implementation of a workflow-based resource broker with information system on computational grids

The grid is a promising infrastructure that can allow scientists and engineers to access resources among geographically distributed environments. Grid computing is a new technology which focuses on aggregating resources (e.g., processor cycles, disk storage, and contents) from a large-scale computing platform. Making grid computing a reality requires a resource broker to manage and monitor available resources. This paper presents a workflow-based resource broker whose main functions are matching available resources with user requests and considering network information statuses during matchmaking in computational grids. The resource broker provides a graphic user interface for accessing available and the appropriate resources via user credentials. This broker uses the Ganglia and NWS tools to monitor resource status and network-related information, respectively. Then we propose a history-based execution time estimation model to predict the execution time of parallel applications, according to previous execution results. The experimental results show that our model can accurately predict the execution time of embarrassingly parallel applications. We also report on using the Globus Toolkit to construct a grid platform called the TIGER project that integrates resources distributed across five universities in Taichung city, Taiwan, where the resource broker was developed.

Enhancing Availability of Grid Computational Services to Ubiquitous Computing Applications

The Grid is an integrated infrastructure that can play the dual roles of a coordinated resource consumer as well as a donator in distributed computing environments. The enormous growth in the use of mobile and embedded devices in ubiquitous computing environment and their interaction with human beings produces a huge amount of data that need to be processed efficiently anytime anywhere. However, such devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. Thus, there is a need to transfer ubiquitous computing application services to more powerful computational resources. In this paper, we investigate the use of the Grid as a candidate for provisioning computational services to applications in ubiquitous computing environments. In particular, we present a competitive model that describes the possible interaction between the competing resources in the Grid Infrastructure as service providers and ubiquitous applications as subscribers. The competition takes place in terms of quality of service (QoS) and cost offered by different Grid Service Providers (GSPs). We also investigate the job allocation of different GSPs by exploiting the noncooperativeness among the strategies. We present the equilibrium behavior of our model facing global competition under stochastic demand and estimate guaranteed QoS assurance level by efficiently satisfying the requirement of ubiquitous application. We have also performed extensive experiments over Distributed Parallel Computing Cluster (DPCC) and studied overall job execution performance of different GSPs under a wide range of QoS parameters using different strategies. Our model and performance evaluation results can serve as a valuable reference for designing appropriate strategies in a practical grid environment.     

基于压电自供电的采煤机状态无线监测装置

考虑到压电自供电装置中压电振子的几何参数直接影响其共振频率,从而影响压电自供电装置的发电量,因此需要根据环境激励频率设定最佳的压电振子的几何参数,本文对基于压电自供电的采煤机状态无线监测装置进行研究,通过理论分析、仿真以及实验方法对对不同悬臂梁结构在不同外界激励作用下的发电量进行研究。研究结果表明：悬臂梁自由端质量块质量以及悬臂梁长度越大,悬臂梁压电结构的固有频率越低;随着悬臂梁厚度的增加,悬臂梁压电结构的固有频率逐渐增大。以此为依据对采煤机不同监测位置的装置选取最佳匹配的压电结构几何参数,并通过采煤机工作状态监测实验验证了本文研究的压电自供电无线监测装置的可行性。     

A probabilistic and adaptive scheduling algorithm using system-generated predictions for inter-grid resource sharing

Rapid advancement and more readily availability of Grid technologies have encouraged many businesses and researchers to establish Virtual Organizations (VO) and make use of their available desktop resources to solve computing intensive problems. These VOs, however, work as disjointed and independent communities with no resource sharing between them. We, in previous work, have proposed a fully decentralized and reconfigurable Inter-Grid framework for resource sharing among such distributed and autonomous Grid systems (Rao et al. in ICCSA, [2006]). The specific problem that underlies in such a collaborating Grids system is scheduling of resources as there is very little knowledge about availability of the resources due to the distributed and autonomous nature of the underlying Grid entities. In this paper, we propose a probabilistic and adaptive scheduling algorithm using system-generated predictions for Inter-Grid resource sharing keeping collaborating Grid systems autonomous and independent. We first use system-generated job runtime estimates without actually submitting jobs to the target Grid system. Then this job execution estimate is used to predict the job scheduling feasibility on the target system. Furthermore, our proposed algorithm adapted itself to the actual resource behavior and performance. Simulation results are presented to discuss the correctness and accuracy of our proposed algorithm.

Semantic-enabled CARE Resource Broker (SeCRB) for managing grid and cloud environment

Grid computing is mainly helpful for executing high-performance computing applications. However, conventional grid resources sometimes fail to offer a dynamic application execution environment and this increases the rate at which the job requests of users are rejected. Integrating emerging virtualization technologies in grid and cloud computing facilitates the provision of dynamic virtual resources in the required execution environment. Resource brokers play a significant role in managing grid and cloud resources as well as identifying potential resources that satisfy users’ application requests. This research paper proposes a semantic-enabled CARE Resource Broker (SeCRB) that provides a common framework to describe grid and cloud resources, and to discover them in an intelligent manner by considering software, hardware and quality of service (QoS) requirements. The proposed semantic resource discovery mechanism classifies the resources into three categories viz., exact, high-similarity subsume and high-similarity plug-in regions. To achieve the necessary user QoS requirements, we have included a service level agreement (SLA) negotiation mechanism that pairs users’ QoS requirements with matching resources to guarantee the execution of applications, and to achieve the desired QoS of users. Finally, we have implemented the QoS-based resource scheduling mechanism that selects the resources from the SLA negotiation accepted list in an optimal manner. The proposed work is simulated and evaluated by submitting real-world bio-informatics and image processing application for various test cases. The result of the experiment shows that for jobs submitted to the resource broker, job rejection rate is reduced while job success and scheduling rates are increased, thus making the resource management system more efficient.     

Maximizing quality of experience through context‐aware mobile application scheduling in cloudlet infrastructure

Application software execution requests, from mobile devices to cloud service providers, are often heterogeneous in terms of device, network, and application runtime contexts. These heterogeneous contexts include the remaining battery level of a mobile device, network signal strength it receives and quality‐of‐service (QoS) requirement of an application software submitted from that device. Scheduling such application software execution requests (from many mobile devices) on competent virtual machines to enhance user quality of experience (QoE) is a multi‐constrained optimization problem. However, existing solutions in the literature either address utility maximization problem for service providers or optimize the application QoS levels, bypassing device‐level and network‐level contextual information. In this paper, a multi‐objective nonlinear programming solution to the context‐aware application software scheduling problem has been developed, namely, QoE and context‐aware scheduling (QCASH) method, which minimizes the application execution times (i.e., maximizes the QoE) and maximizes the application execution success rate. To the best of our knowledge, QCASH is the first work in this domain that inscribes the optimal scheduling problem for mobile application software execution requests with three‐dimensional context parameters. In QCASH, the context priority of each application is measured by applying min–max normalization and multiple linear regression models on three context parameters—battery level, network signal strength, and application QoS. Experimental results, found from simulation runs on CloudSim toolkit, demonstrate that the QCASH outperforms the state‐of‐the‐art works well across the success rate, waiting time, and QoE. Copyright © 2016 John Wiley & Sons, Ltd.     

Dependable Grid Workflow Scheduling Based on Resource Availability

Due to the highly dynamic feature, dependable workflow scheduling is critical in the Grid environment. Various scheduling algorithms have been proposed, but seldom consider the resource reliability. Current Grid systems mainly exploit fault tolerance mechanism to guarantee the dependable workflow execution, which, however, wastes system resources. The paper proposes a dependable Grid workflow scheduling system (called DGWS). It introduces a Markov Chain-based resource availability prediction model. Based on the model, a reliability cost driven workflow scheduling algorithm is presented. The performance evaluation results, including the simulation on both parametric randomly generated DAGs and two real scientific workflow applications, demonstrate that compared to present workflow scheduling algorithms, DGWS improves the success ratio of tasks and diminishes the makespan of workflow, so improves the dependability of workflow execution in the dynamic Grid environments.     

基于分层和分组的移动网格资源选择算法*

针对移动网格的特殊环境,利用统计学中多次线性回归函数提出一种基于分层和分组的移动网格资源选择算法,该算法考虑了移动设备电池能量低、移动性及其处理能力弱等特征。算法中将移动资源分成不同级别层次并分成K组,将任务同时分配到符合资源请求的n组（n相似文献   

A password based authentication scheme for wireless multimedia systems

In this digital era, where Internet of Things (IoT) is increasing day by day, use of resource constrained devices is also increasing. Indeed, the features such as low cost, less maintenance, more adaptive to hostile environment, etc. make the wireless multimedia devices to be the best choice as the resource constrained devices. For the security, the end user device requires to establish the session key with the server before transferring the data. Mobile is one of the device having more and more usage as wireless multimedia device in recent years. In 2013, Li et al. proposed an efficient scheme for the wireless mobile communications and claimed it to be secure against various attacks. Recently, Shen et al. claimed that the scheme of Li et al. is still vulnerable to the privileged insider attack, the stolen verifier attack and finally proposed a scheme to withstand the mentioned and other attacks. However, in this paper we claim that the scheme of Shen et al. is still susceptible to the user anonymity, the session specific temporary information attack and the replay attack. In addition, Shen et al.’s scheme requires more time due to many operations. Further, we propose an efficient scheme that is secure against various known attacks and due to reduced time complexity our scheme is a preferred choice for the wireless mobile networks and hence for wireless multimedia systems.     

Design and implementation of a smart system for personalization and accurate selection of mobile services

Wireless mobile services are computing applications that run on handheld wireless devices. Such applications must work within the daunting constraints of the devices, which include memory, processing power, input capabilities, and size of display. It is therefore important that mobile services take into account the user’s context, optimize resource usage, and minimize input effort imposed on the user. In this paper, we present the design and implementation of a smart agent-enabled system for personalizing wireless mobile services and advertisements for Java 2 Micro Edition (J2ME) or Java ME, and Wireless Application Protocol (WAP) enabled devices. We use software agents for context filtering because such autonomous software entities have characteristics that can benefit mobile devices and the wireless environment, and the Composite Capability/Preference Profiles (CC/PP) standard for defining profiles for user preferences and device capabilities. The system incorporates the use of artificial neural networks to adaptively and iteratively learn to select the best available service based on contextual information. The system is evaluated using practical operating scenarios, as well as empirical data and results show an 87% success rate in the selection of the best available service.