A design methodology for data-parallel applications

High-end computing is suffering a data deluge from experiments, simulations, and apparatus that creates overwhelming application dataset sizes. This has led to the proliferation of high-end mass storage systems, storage area clusters, and data centers. These storage facilities offer a large range of choices in terms of capacity and access rate, as well as strong data availability and consistency support. However, for most end-users, the “last mile” in their analysis pipeline often requires data processing and visualization at local computers, typically local desktop workstations. End-user workstations---despite having more processing power than ever before---are ill-equipped to cope with such data demands due to insufficient secondary storage space and I/O rates. Meanwhile, a large portion of desktop storage is unused.We propose the FreeLoader framework, which aggregates unused desktop storage space and I/O bandwidth into a shared cache/scratch space, for hosting large, immutable datasets and exploiting data access locality. This article presents the FreeLoader architecture, component design, and performance results based on our proof-of-concept prototype. Its architecture comprises contributing benefactor nodes, steered by a management layer, providing services such as data integrity, high performance, load balancing, and impact control. Our experiments show that FreeLoader is an appealing low-cost solution to storing massive datasets by delivering higher data access rates than traditional storage facilities, namely, local or remote shared file systems, storage systems, and Internet data repositories. In particular, we present novel data striping techniques that allow FreeLoader to efficiently aggregate a workstation's network communication bandwidth and local I/O bandwidth. In addition, the performance impact on the native workload of donor machines is small and can be effectively controlled. Further, we show that security features such as data encryptions and integrity checks can be easily added as filters for interested clients. Finally, we demonstrate how legacy applications can use the FreeLoader API to store and retrieve datasets.

PurposeThe paper aims to present an approach to cost-benefit analysis with stochastic data. Determining the type and the values of alternative’s factors are probably the most important issue in this approach. Therefore, in the proposed approach, a competitive advantage model was built to measure the values of alternative’s factors. Then, a satisfactory cost-benefit analysis model with random data was proposed to evaluate the alternatives. The cost-benefit analysis of each alternative was carried out to obtain the real and satisfactory cost-benefit of the decision-maker.Design/methodology/approachThis paper is orientationally expressed as a mathematical problem in which the optimization problem needs to analyze the approach. This paper is written based on uncertainty linear optimization. Optimization under uncertainty refers to this branch of optimization where there are uncertainties involved in the data or the model and is popularly known as stochastic optimization problems.FindingsAs was seen in the purpose part, in this paper, an approach is presented to cost-benefit analysis by the use of competitive advantage with stochastic data. In this regards, a stochastic optimization problem to assess competitive advantage is proposed. This optimization problem recognizes the values of alternative’s factors which is the most important step in cost-benefit analysis. An optimization problem is proposed to cost benefit analysis, as well.Practical implicationsTo investigate different aspects of the proposed approach, a case study with random data of 21 economic projects was considered.Originality/valueCost–benefit analysis is a systematic approach to estimating the strengths and weaknesses of alternatives used to determine options which provide the best approach to achieving benefits while preserving savings. Cost–benefit analysis is related to cost-effectiveness analysis. Benefits and costs are expressed in monetary terms and are adjusted for the time value of money; all flows of benefits and costs over time are expressed on a common basis in terms of their net present value, regardless of whether they are incurred at different times. As seen the paper using competitive advantage tries to determine the values of alternative’s factor. As competitive advantage model analyze the advantages and disadvantages of alternatives, this paper by the use of this idea tries to determine the costs and benefits. Two stochastic optimization problems in the middle of this approach are proposed, which assess competitive advantage and cost–benefit analysis, respectively.

Developing SPMD applications with load balancing

The concept known as Vehicle-to-Grid (V2G) is to provide power to help balance loads by charging at night when demand is low and sending power to the grid when demand is high. Therefore, it is important to model the cost-benefit characteristics of Electric vehicle(EV)'s operation considering the negawatt market in real time. This paper proposes a methodology to formulate the various costs and economic benefits for sending the EV's power back to the grid, including a concept of inconvenience costs caused by operating the EV as a battery. This paper also introduces the general decision-making process based on the cost-benefit analysis in order to simulate the reasonable participation of V2G service. In the case study, it is confirmed by two-case simulations that the proposed approach is useful to help EV owners' decision-making. In the future, it is expected that the proposed methodology can be used as a decision-making guideline to help prepare the EV' power transmission.

Design of efficient system-on-chips (SoCs) requires thorough application analysis to identify various compute intensive parts. These compute intensive parts can be mapped to hardware in order to meet the cost as well as the performance constraints. However, faster time to market requires automation of synthesis of these code segments of the application from high level specification such as C along with its interfaces. Such a synthesis system should be able to generate hardware which is easily pluggable in various types of architectures, as well as augment the application code to automatically take advantage of this new hardware component. In this paper, we address this problem and present an approach for complete SoC synthesis. We automatically generate synthesizable VHDL for the compute intensive part of the application along with necessary interfaces. Our approach is generic in the sense that it supports various processors and buses by keeping a generic hardware interface on one end and a dedicated one on the other. The generated hardware can be used in a tightly or loosely coupled manner in terms of memory and register communication. We present the effectiveness of this approach for some commonly used image processing spatial filter applications.

Residents' journal review

Many data‐gathering protocols for wireless sensor networks use clustering technology for prolonging network lifetime. Cluster‐based protocols reduce the total energy consumption via data aggregation and balance energy consumption via clusterhead rotation. However, most existing protocols focus on load balance within each cluster. The energy consumption of the entire network is still unbalanced and this uneven energy dissipation can significantly reduce network lifetime. We propose an even energy dissipation protocol (EEDP) for efficient cluster‐based data gathering in wireless sensor networks. In EEDP, sensor data are forwarded to the base station (BS) via multiple chains of clusterheads. Each chain uses a rotation scheme to balance energy consumption among clusterheads and avoid the formation of a hot spot. We developed efficient algorithms to organize clusterheads into multiple chains, such that the traffic load is evenly distributed among different chains. Analysis and simulation results show that EEDP achieves better load balance than several existing protocols and significantly increases network lifetime. Copyright © 2007 John Wiley & Sons, Ltd.

We highlight the advantages of dynamic wavelength allocation and path rerouting in hybrid optical flow-switched data center networks compared with static electronic packet-switched data center networks. Current electronic packet-switched networks perform routing based on lookup tables and shortest path routing over high speed optical connections. However, load balancing and path rerouting are not designed in coordination with the optical data plane. In this work, we design and analyze the performance of load balancing and resource allocation in hybrid flow data center architectures. In the hybrid flow architecture, the transport layer and control plane are responsible for load balancing, congestion control and reliable data delivery in wavelength division multiplexed networks. The transport layer abstracts the underlying network and data link layers from user applications. Applications are unaware of whether flows are transmitted via the electronic data plane, optical data plane, or both, where the relevant metric for applications is transaction delay. We show that the data center architecture that minimizes delay in the presence of elephant flows and dynamic loads is the hybrid flow architecture with dynamic resource allocation.

-3 HHE work of several writers appears largely to have succeeded in mak..Ling disreputable the once fashionable practice of crediting public investment activities in the development of water resources, in particular, with substantial "secondary" or "indirect" benefits.2 Secondary benefits in one guise or another still appear to be much in style, however, in dealing with the benefits of investments in highways and other transportation facilities. Among the benefits of highway investment to which reference is commonly made are those presumed to accrue to property owners. More specifically, many studies have demonstrated that land values tend to increase sometimes dramatically-in the vicinity of newly improved highways.3 Since these increases are independent of the extent to which the affected property owners use the highway facilities involved, such gains are quite properly labeled "non-user benefits." They are, furthermore, commonly regarded as benefits over and above those that accrue to highway users. That is to say, they are regarded as benefits that must in some way be added to those arising directly from highway use if total highway benefits are to be estimated accurately. Although widely accepted (particularly among highway planners), this final conclusion is, as it happens, fallacious. That property values increase in the vicinity of highway improvements does reflect the existence of highway benefits. Careful analysis of highwayland value relationships can yield valuable information on the magnitude of these benefits. Increases in land value are not in themselves net highway benefits, however. Rather, they reflect an actual or potential transfer of benefits derived from highways from one population group to another. Furthermore, the fact that land values generally do increase in the vicinity of highway improvements by no means guarantees that a net effect of these improvements is to increase land values as a whole. The primary goal of this paper is to demonstrate these assertions by exploring the relationship between land values on the one hand and transportation costs and reductions in them on the other. More specifically, Section I demonstrates the effects of certain types of transporta1 I am indebted to Robert Clower, William Garrison, William Pendleton, and Stephen Sobotka for much helpful advice. Richard Morrill undertook one of the preliminary analyses underlying the material reported in Section II, while Harold Williamson, Jr., directed most of the statistical work entailed in this section. The work reported here was undertaken as part of a larger study of the nature and measurement of highway benefits carried out with the support of the Bureau of Public Roads. My views do not necessarily reflect those of the Bureau, however.

Data processing and communication strategies for lifetime optimization in wireless sensor networks

Alone with “The Internet of Things” development and expanding in the areas of life, it also brings some big challenges to the traditional software application design and development; especially with the corresponding technologies and strategies of the internet of things enhancement and improvement, and further more with some new equipments and technologies appended or changed in the existing environment, it needs rapidly and easily add some new functionalities to the existing working software applications. But the traditional application design and development still thinking of solution from designers and developers and not from the business point of view, this results in the traditional software applications and its scalability cannot be easily and rapidly satisfy to business requirements. Here, by research on XML, software bus, software component and task-oriented technologies, it illustrates a new way for the software application design and development and try to use task-oriented technology to improve the software application flexibility and scalability to satisfy to enterprise business changes.

Applied Welfare Economics: Cost-Benefit Analysis for Project and Policy Evaluation presents a consistent framework for applied welfare economics and is grounded in a comprehensive theory of cost-benefit analysis, specifically focused on offering a practical approach to policy and project evaluation. After opening with a theoretical discussion of the concept of social welfare, a critical analysis of the traditional doctrine of welfare economics embodied in the Two Fundamental Theorems, and a presentation of social cost-benefit analysis, the book introduces readers to an applied framework. This includes the empirical estimation of shadow prices of goods, the social cost of labour and capital, and the assessment of risk. The book also examines real-life experiences with cost-benefit analysis, including ex-post evaluation of major projects, economic rates of return in different sectors, and a case study on privatisation. These chapters draw on first-hand research gained by the author team from years of advisory work for the European Commission and other international and national institutions. This second edition presents updated data, more international examples, and more coverage of topics such as very long run discounting effects and climate change as an intergenerational effect. It also includes more practical examples and end-of-chapter questions to aid student’s learning. Applied Welfare Economics is a valuable textbook for upper-level courses on welfare economics, cost-benefit analysis, public policy analysis and related areas.

We present the Operator design pattern which can be used for the design of both sequential and data parallel applications. To reach this goal, we show how the participants of this pattern can be implemented either for a sequential or a parallel execution. Besides, reusing the sequential design for a parallel application decreases the cost of parallelization by allowing the maintenance of a unique application for the two execution environments. The proposed approach for parallel programming does not require any dedicated compiler or code pre-processing. Nothing but object oriented features, such as inheritance and polymorphism, is used to provide the distributed behaviour of the parallel participants of the pattern. The Operator pattern can help to solve many design issues in relation with the development of reusable software components for data collection processing. Moreover, we are confident that many programmers who want to migrate their applications towards parallelism can find it helpful.

Cost Benefit Analysis (CBA) is an important financial analytical tool which gives an insight to the viability and feasibility of a project. With the growing prominence of the smart grids, various smart grid pilot projects are supported by the Ministry of Power, India. These projects should be evaluated by performing the CBA. The profitability indicators used to evaluate a project is the Net Present Value (NPV), Internal Rate of Return (IRR), Benefits to Cost Ratio (B/C) and the Payback Period (PB). Advanced Metering Infrastructure (AMI) is the backbone of the smart grid and is the largest cost component of the total cost. This paper focuses on the deployment of AMI for two scenarios. In scenario A, smart meters are deployed for all the customers on 1000 feeders and in scenario B, only the customers whose monthly consumption is greater than 200 units are considered for the deployment. This is an extended case study of the India Smart Grid Forum (ISGF). The pecuniary value of the costs and the benefits are considered by consulting various utilities. Only the monetary values of the benefits and the costs are obtained from the base case. In this paper three sub-cases are created in each scenario by choosing different percentages of the loan being taken to check the worst-case feasibility of the project. CBA is performed for both the scenarios. Subsequently, financial analyses done for both the cases are reported and discussed. The results identify the threshold values of loan. The sensitivity analysis show that project is viable and profitable up to reduction of benefit by 20% with no changes in the cost.

Waste generation nowadays is rising in the world and it seems hard to prevent it. Municipal Solid Waste (MSW) has been a major problem worldwide, especially in the fast growing cities and towns in the developing countries. This study aims to estimate the cost benefit and mitigation of greenhouse gases (GHGs) by converting the on-campus food and green waste generated in Universiti Teknologi of Malaysia (UTM) campus to compost. This study calculated the costing which includes the transportation, operating and equipment costs if green and food waste were converted into compost. The analyses were made with the basis of the pilot scale operation in Phase I operation. Extrapolation was made to project the further four phases of composting with higher amount of waste to estimate the potential profit. The results obtained from this study indicated that composting has the potential to generate a significant profit of Malaysia Ringgit (MYR)1.6 M/y based on 2,700 t/y of food and green waste composted. At the same time, the total solid waste supposedly to be sent to the landfill can be reduced by at least 47 %. Moreover, this study revealed that the composting process is able to reduce the GHGs emission rate by 90 %, i.e. the GHGs produced by the composting process is shown to be only 10 % of the total GHGs produced by landfill dumping given the same amount of solid waste to be disposed at the landfill site.