Showing papers on "Resource management published in 2010"

Mapping Species Distributions: Spatial Inference and Prediction

Abstract: Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management.

A Review of Design Principles for Community-based Natural Resource Management

Abstract: In 1990, Elinor Ostrom proposed eight design principles, positing them to characterize robust institutions for managing common-pool resources such as forests or fisheries. Since then, many studies have explicitly or implicitly evaluated these design principles. We analyzed 91 such studies to evaluate the principles empirically and to consider what theoretical issues have arisen since their introduction. We found that the principles are well supported empirically and that several important theoretical issues warrant discussion. We provide a reformulation of the design principles, drawing from commonalities found in the studies.

Distance-adaptive spectrum resource allocation in spectrum-sliced elastic optical path network [Topics in Optical Communications]

Abstract: The rigid nature of current wavelength-routed optical networks brings limitations on network utilization efficiency. One limitation originates from mismatch of granularities between the client layer and the wavelength layer. The recently proposed spectrum-sliced elastic optical path network (SLICE) is expected to mitigate this problem by adaptively allocating spectral resources according to client traffic demands. This article discusses another limitation of the current optical networks associated with worst case design in terms of transmission performance. In order to address this problem, we present a concept of a novel adaptation scheme in SLICE called distance-adaptive spectrum resource allocation. In the presented scheme the minimum necessary spectral resource is adaptively allocated according to the end-to-end physical condition of an optical path. Modulation format and optical filter width are used as parameters to determine the necessary spectral resources to be allocated for an optical path. Evaluation of network utilization efficiency shows that distance-adaptive SLICE can save more than 45 percent of required spectrum resources for a 12-node ring network. Finally, we introduce the concept of a frequency slot to extend the current frequency grid standard, and discuss possible spectral resource designation schemes.

Energy Efficient Resource Management in Virtualized Cloud Data Centers

Abstract: Rapid growth of the demand for computational power by scientific, business and web-applications has led to the creation of large-scale data centers consuming enormous amounts of electrical power. We propose an energy efficient resource management system for virtualized Cloud data centers that reduces operational costs and provides required Quality of Service (QoS). Energy savings are achieved by continuous consolidation of VMs according to current utilization of resources, virtual network topologies established between VMs and thermal state of computing nodes. We present first results of simulation-driven evaluation of heuristics for dynamic reallocation of VMs using live migration according to current requirements for CPU performance. The results show that the proposed technique brings substantial energy savings, while ensuring reliable QoS. This justifies further investigation and development of the proposed resource management system.

Q-clouds: managing performance interference effects for QoS-aware clouds

Abstract: Cloud computing offers users the ability to access large pools of computational and storage resources on demand. Multiple commercial clouds already allow businesses to replace, or supplement, privately owned IT assets, alleviating them from the burden of managing and maintaining these facilities. However, there are issues that must be addressed before this vision of utility computing can be fully realized. In existing systems, customers are charged based upon the amount of resources used or reserved, but no guarantees are made regarding the application level performance or quality-of-service (QoS) that the given resources will provide. As cloud providers continue to utilize virtualization technologies in their systems, this can become problematic. In particular, the consolidation of multiple customer applications onto multicore servers introduces performance interference between collocated workloads, significantly impacting application QoS. To address this challenge, we advocate that the cloud should transparently provision additional resources as necessary to achieve the performance that customers would have realized if they were running in isolation. Accordingly, we have developed Q-Clouds, a QoS-aware control framework that tunes resource allocations to mitigate performance interference effects. Q-Clouds uses online feedback to build a multi-input multi-output (MIMO) model that captures performance interference interactions, and uses it to perform closed loop resource management. In addition, we utilize this functionality to allow applications to specify multiple levels of QoS as application Q-states. For such applications, Q-Clouds dynamically provisions underutilized resources to enable elevated QoS levels, thereby improving system efficiency. Experimental evaluations of our solution using benchmark applications illustrate the benefits: performance interference is mitigated completely when feasible, and system utilization is improved by up to 35% using Q-states.

PRESS: PRedictive Elastic ReSource Scaling for cloud systems

Abstract: Cloud systems require elastic resource allocation to minimize resource provisioning costs while meeting service level objectives (SLOs). In this paper, we present a novel PRedictive Elastic reSource Scaling (PRESS) scheme for cloud systems. PRESS unobtrusively extracts fine-grained dynamic patterns in application resource demands and adjust their resource allocations automatically. Our approach leverages light-weight signal processing and statistical learning algorithms to achieve online predictions of dynamic application resource requirements. We have implemented the PRESS system on Xen and tested it using RUBiS and an application load trace from Google. Our experiments show that we can achieve good resource prediction accuracy with less than 5% over-estimation error and near zero under-estimation error, and elastic resource scaling can both significantly reduce resource waste and SLO violations.

State of the Art for Genetic Algorithms and Beyond in Water Resources Planning and Management

Abstract: During the last two decades, the water resources planning and management profession has seen a dramatic increase in the development and application of various types of evolutionary algorithms (EAs). This observation is especially true for application of genetic algorithms, arguably the most popular of the several types of EAs. Generally speaking, EAs repeatedly prove to be flexible and powerful tools in solving an array of complex water resources problems. This paper provides a comprehensive review of state-of-the-art methods and their applications in the field of water resources planning and management. A primary goal in this ASCE Task Committee effort is to identify in an organized fashion some of the seminal contributions of EAs in the areas of water distribution systems, urban drainage and sewer systems, water supply and wastewater treatment, hydrologic and fluvial modeling, groundwater systems, and parameter identification. The paper also identifies major challenges and opportunities for the future, ...

Governance Principles for Natural Resource Management

Abstract: Sustainable natural resource use and management make novel demands on governance arrangements, the design of which requires normative guidance. Although governance principles have been developed for diverse contexts, their availability for sustainable natural resource governance is so far limited. In response, we present a suite of governance principles for natural resource governance that, while developed in an Australian multilevel context, has general applicability and significance at local, subnational, and national scales. The principles can be used to direct the design of governance institutions that are legitimate, transparent, accountable, inclusive, and fair and that also exhibit functional and structural integration, capability, and adaptability. Together, they can also serve as a platform for developing governance monitoring and evaluation instruments, crucial for both self-assessment and external audit purposes.

Energy Efficient Allocation of Virtual Machines in Cloud Data Centers

Abstract: Rapid growth of the demand for computational power has led to the creation of large-scale data centers. They consume enormous amounts of electrical power resulting in high operational costs and carbon dioxide emissions. Moreover, modern Cloud computing environments have to provide high Quality of Service (QoS) for their customers resulting in the necessity to deal with power-performance trade-off. We propose an efficient resource management policy for virtualized Cloud data centers. The objective is to continuously consolidate VMs leveraging live migration and switch off idle nodes to minimize power consumption, while providing required Quality of Service. We present evaluation results showing that dynamic reallocation of VMs brings substantial energy savings, thus justifying further development of the proposed policy.

Fundamentals of Human Resource Management

Abstract: Part 1: Introduction Chapter 1. Managing Human Resources Today Chapter 2. Managing Equal Opportunity and Diversity Chapter 3. Strategic Human Resource Management Part 2: Staffing and Talent Management Chapter 4. Recruiting and Talent Management Chapter 5. Selecting Employees Chapter 6. Training and Developing Employees Chapter 7. Performance and Talent Management Chapter 8. Compensating Employees Part 3: Employee and Labor Relations Chapter 9. Ethics, Employee Rights, and Fair Treatment at Work Chapter 10. Working with Unions and Resolving Disputes Chapter 11. Improving Occupational Safety, Health, and Security Part 4: Special Issues in Human Resource Management Chapter 12. Managing Human Resources in Entrepreneurial Firms Chapter 13. Managing HR Globally Chapter 14. Building High-Performance Work

Devolution of environment and resources governance: trends and future

Abstract: How can the governance of environment and resources be devolved in a way that incorporates effective user participation and feedback learning? Approaches that use the idea of adaptive management or learning-by-doing, combined with co-management, are particularly promising. Using an interdisciplinary literature covering many types of resources, and a conceptual model with three phases (communicative action, self-organization and collective action), the paper identifies some of the major processes leading to adaptive co-management. These include deliberation, visioning, building social capital, trust and institutions, capacity-building through networks and partnerships, and action-reflection-action loops for social learning. Such adaptive co-management is not simply a theoretical possibility but something that has been documented in a number of forestry, fisheries, wildlife, protected area, and wetland cases from both developed and developing countries. However, the experience with the decentralization reforms of the 1990s is largely negative for a number of reasons. Effective devolution takes time, requiring a shift in focus from a static concept of management to a dynamic concept of governance shaped by interactions, feedback learning and adaptation over time. Sharing of governance responsibilities and an ability to learn from experience are among the emerging trends in environmental management.

A resource‐based perspective on information technology and firm performance: a meta analysis

Abstract: Purpose – The purpose of this paper is to aggregate previous research that adopts the resource‐based view (RBV) to examine whether information technology (IT) and organizational resources have significant effect on firm performanceDesign/methodology/approach – A framework that includes direct and indirect‐effect models is proposed A meta‐analysis was conducted on 42 published empirical studies to examine how different factors in the RBV affect firm performanceFindings – First, it was found that the mediated model that includes organizational capabilities as mediators between organizational resources and firm performance can better explain the value of IT than the direct‐effect model without organizational capabilities Second, technology resources can improve efficiency performance but may not enhance financial performance directly Third, internal capabilities affect performance but it is external capabilities that affect financial performanceResearch limitations/implications – The limitation of meta

Environmental and natural resource economics

Abstract: The objective of this major is to provide students with the necessary training for the application of economic theory and analysis to environmental and natural resource issues. The flexibility of this major allows students to design (with their advisor) a program of study which focuses on environmental and natural resource issues tailored to the student’s own interests (such as water use and quality, soil protection, waste management, ecosystem management, and land use). The curriculum reflects the breadth of training required to prepare students for careers in private and government sectors dealing with environmental and natural resource management and policy analysis.

Lab experiments for the study of social-ecological systems.

Abstract: Governance of social-ecological systems is a major policy problem of the contemporary era. Field studies of fisheries, forests, and pastoral and water resources have identified many variables that influence the outcomes of governance efforts. We introduce an experimental environment that involves spatial and temporal resource dynamics in order to capture these two critical variables identified in field research. Previous behavioral experiments of commons dilemmas have found that people are willing to engage in costly punishment, frequently generating increases in gross benefits, contrary to game-theoretical predictions based on a static pay-off function. Results in our experimental environment find that costly punishment is again used but lacks a gross positive effect on resource harvesting unless combined with communication. These findings illustrate the importance of careful generalization from the laboratory to the world of policy.

Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures

Abstract: Server consolidation based on virtualization is an important technique for improving power efficiency and resource utilization in cloud infrastructures. However, to ensure satisfactory performance on shared resources under changing application workloads, dynamic management of the resource pool via online adaptation is critical. The inherent tradeoffs between power and performance as well as between the cost of an adaptation and its benefits make such management challenging. In this paper, we present Mistral, a holistic controller framework that optimizes power consumption, performance benefits, and the transient costs incurred by various adaptations and the controller itself to maximize overall utility. Mistral can handle multiple distributed applications and large-scale infrastructures through a multi-level adaptation hierarchy and scalable optimization algorithm. We show that our approach outstrips other strategies that address the tradeoff between only two of the objectives (power, performance, and transient costs).

Elastic Site: Using Clouds to Elastically Extend Site Resources

Abstract: Infrastructure-as-a-Service (IaaS) cloud computing offers new possibilities to scientific communities. One of the most significant is the ability to elastically provision and relinquish new resources in response to changes in demand. In our work, we develop a model of an “elastic site” that efficiently adapts services provided within a site, such as batch schedulers, storage archives, or Web services to take advantage of elastically provisioned resources. We describe the system architecture along with the issues involved with elastic provisioning, such as security, privacy, and various logistical considerations. To avoid over- or under-provisioning the resources we propose three different policies to efficiently schedule resource deployment based on demand. We have implemented a resource manager, built on the Nimbus toolkit to dynamically and securely extend existing physical clusters into the cloud. Our elastic site manager interfaces directly with local resource managers, such as Torque. We have developed and evaluated policies for resource provisioning on a Nimbus-based cloud at the University of Chicago, another at Indiana University, and Amazon EC2. We demonstrate a dynamic and responsive elastic cluster, capable of responding effectively to a variety of job submission patterns. We also demonstrate that we can process 10 times faster by expanding our cluster up to 150 EC2 nodes.

Conservation in the dark? The information used to support management decisions

Abstract: The management requirements for protected areas are frequently complex and urgent; as a result, managers often need to act quickly and make decisions with limited supporting evidence at their disposal. Despite demands for high-quality information, it is unclear how much of this evidence conservation practitioners use to assist with their decision making. We investigated the information used to manage protected areas, based on the evidence reported by practitioners when evaluating their management performance. We examined the management of over 1000 protected areas run by two Australian conservation agencies – Parks Victoria and the New South Wales Department of Environment and Climate Change – an unprecedented scope for this type of study. We found that very few conservation practitioners use evidence-based knowledge to support their management. The evidence used varies with the management issue, reserve type, and reserve size. Around 60% of conservation management decisions rely on experience-based infor...

Dynamic resource allocation and power management in virtualized data centers

Abstract: We investigate optimal resource allocation and power management in virtualized data centers with time-varying workloads and heterogeneous applications. Prior work in this area uses prediction based approaches for resource provisioning. In this work, we take an alternate approach that makes use of the queueing information available in the system to make online control decisions. Specifically, we use the recently developed technique of Lyapunov Optimization to design an online admission control, routing, and resource allocation algorithm for a virtualized data center. This algorithm maximizes a joint utility of the average application throughput and energy costs of the data center. Our approach is adaptive to unpredictable changes in the workload and does not require estimation and prediction of its statistics.

Dynamic Resource Allocation in Computing Clouds Using Distributed Multiple Criteria Decision Analysis

Abstract: In computing clouds, it is desirable to avoid wasting resources as a result of under-utilization and to avoid lengthy response times as a result of over-utilization. In this paper, we propose a new approach for dynamic autonomous resource management in computing clouds. The main contribution of this work is two-fold. First, we adopt a distributed architecture where resource management is decomposed into independent tasks, each of which is performed by Autonomous Node Agents that are tightly coupled with the physical machines in a data center. Second, the Autonomous Node Agents carry out configurations in parallel through Multiple Criteria Decision Analysis using the PROMETHEE method. Simulation results show that the proposed approach is promising in terms of scalability, feasibility and flexibility.

Traditional Ecological Knowledge Trends in the Transition to a Market Economy: Empirical Study in the Doñana Natural Areas

Abstract: Researchers and conservation managers largely agree on the relevance of traditional ecological knowledge for natural resource management in indigenous communities, but its prevalence and role as societies modernize are contested. We analyzed the transmission of traditional knowledge among rural local people in communities linked to protected areas in Donana, southwestern Spain. We studied changes in knowledge related to local practices in agriculture and livestock farming among 198 informants from three generations that cover the period in which the area transited from an economy strongly dependent on local ecosystem services to a market economy with intensified production systems. Our results suggest an abrupt loss of traditional agricultural knowledge related to rapid transformations and intensification of agricultural systems, but maintenance of knowledge of traditional livestock farming, an activity allowed in the protected areas that maintains strong links with local cultural identity. Our results demonstrate the potential of protected areas in protecting remaining bodies of traditional ecological knowledge in developed country settings. Nevertheless, we note that strict protection in cultural-landscape-dominated areas can disrupt transmission of traditional knowledge if local resource users and related practices are excluded from ecosystem management.

Re-thinking environmental flows: from allocations and reserves to sustainability boundaries.

Abstract: Attempts to implement environmental flows have encountered many obstacles. Many water allocation systems include a system of prioritization among water uses that generally does not favor environmental flow protection, or do not allow for protection of high flow events for ecological purposes. It has proven very difficult to implement complicated environmental flow prescriptions that attempt to mimic natural flow variability within water allocation systems. Additionally, many water allocation systems do not adequately address interconnections between surface water and groundwater, or releases from dams. It is time to re-think our approaches to protecting environmental flows. As with water quality protection, environmental flows should be viewed not as an “allocation” of water, but rather as a desirable outcome of integrated management of water and land resources for long-term sustainability. In this sense, environmental flows should be managed in a manner similar to water quality protection, in which the influences of diverse land and water use activities are regulated to ensure that the ecological and social values of water are optimized. Both water quality and environmental flow management protect a vast array of important social benefits that are sustained by managing for healthy freshwater ecosystems. In this paper I offer a definition of sustainable water management that explicitly recognizes the fact that society derives substantial benefits both from out-of-stream extractions of water as well as by maintaining adequate flows of water within freshwater ecosystems. To help facilitate sustainable water management, a ”Sustainability Boundary Approach“ is described for use in setting quantitative water management goals. When the cumulative hydrologic impacts of water and land uses are managed within these sustainability boundaries, the full array of values associated with water can be more fully realized. Copyright © 2009 John Wiley & Sons, Ltd.

Mathematical Bioeconomics: The Mathematics of Conservation

Abstract: Preface Acknowledgments 1 A Generic Bioeconomic Model 11 What is Conservation? 12 What is a Model? 13 A Dynamic Resource-Harvesting Model 14 A Bioeconomic Model 15 A Dynamic Optimization Model 16 A Model of Individual Behavior 17 Individual Vessel Quotas 18 The Veil of Uncertainty 19 Other Resources 2 Dynamic Optimization 21 Constrained Optimization 22 Optimal Control Theory in One Dimension 23 Nonlinear Control Problems 24 Discrete-time Optimal Control 25 Appendix 3 Basic Economic Concepts 31 Interest and Discounting 32 Supply and Demand 33 Demand-limited Bionomic Equilibrium 34 Optimal Harvesting Strategies 35 External Costs 36 Competition, Cooperation, and the Theory of Games 37 The Economics of Uncertainty 4 Investing in Harvesting Capacity 41 Optimal Harvesting Capacity 42 Investment Decisions under Competition 43 Eliminating Excess Capacity 44 Appendix: Optimal Investment 5 Regulation of Renewable Resource Harvesting 51 The Consequences of Unregulated Resource Harvesting 52 Methods of Regulating Resource Harvesting 53 Shadow Prices, Taxes and Tradeable Quotas 54 Regulation without Taxes or Tradeable Quotas 6 Growth and Aging 61 Forestry Models 62 Fisheries: The Cohort Model 63 Multicohort Fisheries 7 Resource Management under Uncertainty 71 Process and Observational Uncertainty 72 Understanding Uncertainty 73 Process Uncertainty 74 An Introduction to Decision Analysis 75 Economic Uncertainties 76 Appendix 8 Disaggregated Resource Models 81 Source-sink Models 82 Predator-prey Models 83 Mixed-species Harvesting 9 Synopsis Problem Solutions References Index

Understanding Performance Interference of I/O Workload in Virtualized Cloud Environments

Abstract: Server virtualization offers the ability to slice large, underutilized physical servers into smaller, parallel virtual machines (VMs), enabling diverse applications to run in isolated environments on a shared hardware platform. Effective management of virtualized cloud environments introduces new and unique challenges, such as efficient CPU scheduling for virtual machines, effective allocation of virtual machines to handle both CPU intensive and I/O intensive workloads. Although a fair number of research projects have dedicated to measuring, scheduling, and resource management of virtual machines, there still lacks of in-depth understanding of the performance factors that can impact the efficiency and effectiveness of resource multiplexing and resource scheduling among virtual machines. In this paper, we present our experimental study on the performance interference in parallel processing of CPU and network intensive workloads in the Xen Virtual Machine Monitors (VMMs). We conduct extensive experiments to measure the performance interference among VMs running network I/O workloads that are either CPU bound or network bound. Based on our experiments and observations, we conclude with four key findings that are critical to effective management of virtualized cloud environments for both cloud service providers and cloud consumers. First, running network-intensive workloads in isolated environments on a shared hardware platform can lead to high overheads due to extensive context switches and events in driver domain and VMM. Second, co-locating CPU-intensive workloads in isolated environments on a shared hardware platform can incur high CPU contention due to the demand for fast memory pages exchanges in I/O channel. Third, running CPU-intensive workloads and network-intensive workloads in conjunction incurs the least resource contention, delivering higher aggregate performance. Last but not the least, identifying factors that impact the total demand of the exchanged memory pages is critical to the in-depth understanding of the interference overheads in I/O channel in the driver domain and VMM.

Key Principles of Community-Based Natural Resource Management: A Synthesis and Interpretation of Identified Effective Approaches for Managing the Commons

Abstract: This article examines recent research on approaches to community-based environmental and natural resource management and reviews the commonalities and differences between these interdisciplinary and multistakeholder initiatives. To identify the most effective characteristics of Community-based natural resource management (CBNRM), I collected a multiplicity of perspectives from research teams and then grouped findings into a matrix of organizational principles and key characteristics. The matrix was initially vetted (or “field tested”) by applying numerous case studies that were previously submitted to the World Bank International Workshop on CBNRM. These practitioner case studies were then compared and contrasted with the findings of the research teams. It is hoped that the developed matrix may be useful to researchers in further focusing research, understanding core characteristics of effective and sustainable CBNRM, providing practitioners with a framework for developing new CBNRM initiatives for managing the commons, and providing a potential resource for academic institutions during their evaluation of their practitioner-focused environmental management and leadership curriculum.

Dynamic Resource Pricing on Federated Clouds

Abstract: Current large distributed systems allow users to share and trade resources. In cloud computing, users purchase different types of resources from one or more resource providers using a fixed pricing scheme. Federated clouds, a topic of recent interest, allows different cloud providers to share resources for increased scalability and reliability. However, users and providers of cloud resources are rational and maximize their own interest when consuming and contributing shared resources. In this paper, we present a dyanmic pricing scheme suitable for rational users requests containing multiple resource types. Using simulations, we compare the efficiency of our proposed strategy-proof dynamic scheme with fixed pricing, and show that user welfare and the percentage of successful requests is increased by using dynamic pricing.