886 resultados para management control


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For a given TCP flow, exogenous losses are those occurring on links other than the flow's bottleneck link. Exogenous losses are typically viewed as introducing undesirable "noise" into TCP's feedback control loop, leading to inefficient network utilization and potentially severe global unfairness. This has prompted much research on mechanisms for hiding such losses from end-points. In this paper, we show through analysis and simulations that low levels of exogenous losses are surprisingly beneficial in that they improve stability and convergence, without sacrificing efficiency. Based on this, we argue that exogenous loss awareness should be taken into account in any AQM design that aims to achieve global fairness. To that end, we propose an exogenous-loss aware Queue Management (XQM) that actively accounts for and leverages exogenous losses. We use an equation based approach to derive the quiescent loss rate for a connection based on the connection's profile and its global fair share. In contrast to other queue management techniques, XQM ensures that a connection sees its quiescent loss rate, not only by complementing already existing exogenous losses, but also by actively hiding exogenous losses, if necessary, to achieve global fairness. We establish the advantages of exogenous-loss awareness using extensive simulations in which, we contrast the performance of XQM to that of a host of traditional exogenous-loss unaware AQM techniques.

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With the increased use of "Virtual Machines" (VMs) as vehicles that isolate applications running on the same host, it is necessary to devise techniques that enable multiple VMs to share underlying resources both fairly and efficiently. To that end, one common approach is to deploy complex resource management techniques in the hosting infrastructure. Alternately, in this paper, we advocate the use of self-adaptation in the VMs themselves based on feedback about resource usage and availability. Consequently, we define a "Friendly" VM (FVM) to be a virtual machine that adjusts its demand for system resources, so that they are both efficiently and fairly allocated to competing FVMs. Such properties are ensured using one of many provably convergent control rules, such as AIMD. By adopting this distributed application-based approach to resource management, it is not necessary to make assumptions about the underlying resources nor about the requirements of FVMs competing for these resources. To demonstrate the elegance and simplicity of our approach, we present a prototype implementation of our FVM framework in User-Mode Linux (UML)-an implementation that consists of less than 500 lines of code changes to UML. We present an analytic, control-theoretic model of FVM adaptation, which establishes convergence and fairness properties. These properties are also backed up with experimental results using our prototype FVM implementation.

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We propose and evaluate an admission control paradigm for RTDBS, in which a transaction is submitted to the system as a pair of processes: a primary task, and a recovery block. The execution requirements of the primary task are not known a priori, whereas those of the recovery block are known a priori. Upon the submission of a transaction, an Admission Control Mechanism is employed to decide whether to admit or reject that transaction. Once admitted, a transaction is guaranteed to finish executing before its deadline. A transaction is considered to have finished executing if exactly one of two things occur: Either its primary task is completed (successful commitment), or its recovery block is completed (safe termination). Committed transactions bring a profit to the system, whereas a terminated transaction brings no profit. The goal of the admission control and scheduling protocols (e.g., concurrency control, I/O scheduling, memory management) employed in the system is to maximize system profit. We describe a number of admission control strategies and contrast (through simulations) their relative performance.

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The pervasiveness of personal computing platforms offers an unprecedented opportunity to deploy large-scale services that are distributed over wide physical spaces. Two major challenges face the deployment of such services: the often resource-limited nature of these platforms, and the necessity of preserving the autonomy of the owner of these devices. These challenges preclude using centralized control and preclude considering services that are subject to performance guarantees. To that end, this thesis advances a number of new distributed resource management techniques that are shown to be effective in such settings, focusing on two application domains: distributed Field Monitoring Applications (FMAs), and Message Delivery Applications (MDAs). In the context of FMA, this thesis presents two techniques that are well-suited to the fairly limited storage and power resources of autonomously mobile sensor nodes. The first technique relies on amorphous placement of sensory data through the use of novel storage management and sample diffusion techniques. The second approach relies on an information-theoretic framework to optimize local resource management decisions. Both approaches are proactive in that they aim to provide nodes with a view of the monitored field that reflects the characteristics of queries over that field, enabling them to handle more queries locally, and thus reduce communication overheads. Then, this thesis recognizes node mobility as a resource to be leveraged, and in that respect proposes novel mobility coordination techniques for FMAs and MDAs. Assuming that node mobility is governed by a spatio-temporal schedule featuring some slack, this thesis presents novel algorithms of various computational complexities to orchestrate the use of this slack to improve the performance of supported applications. The findings in this thesis, which are supported by analysis and extensive simulations, highlight the importance of two general design principles for distributed systems. First, a-priori knowledge (e.g., about the target phenomena of FMAs and/or the workload of either FMAs or DMAs) could be used effectively for local resource management. Second, judicious leverage and coordination of node mobility could lead to significant performance gains for distributed applications deployed over resource-impoverished infrastructures.

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This thesis presents a framework for aggregated congestion management for TCP flows and shows how to integrate such an approach in an existing TCP protocol stack. The thesis presents an initial implementation of this congestion management scheme in Linux, with performance evaluation in ns as well.

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The Border Gateway Protocol (BGP) is the current inter-domain routing protocol used to exchange reachability information between Autonomous Systems (ASes) in the Internet. BGP supports policy-based routing which allows each AS to independently adopt a set of local policies that specify which routes it accepts and advertises from/to other networks, as well as which route it prefers when more than one route becomes available. However, independently chosen local policies may cause global conflicts, which result in protocol divergence. In this paper, we propose a new algorithm, called Adaptive Policy Management Scheme (APMS), to resolve policy conflicts in a distributed manner. Akin to distributed feedback control systems, each AS independently classifies the state of the network as either conflict-free or potentially-conflicting by observing its local history only (namely, route flaps). Based on the degree of measured conflicts (policy conflict-avoidance vs. -control mode), each AS dynamically adjusts its own path preferences—increasing its preference for observably stable paths over flapping paths. APMS also includes a mechanism to distinguish route flaps due to topology changes, so as not to confuse them with those due to policy conflicts. A correctness and convergence analysis of APMS based on the substability property of chosen paths is presented. Implementation in the SSF network simulator is performed, and simulation results for different performance metrics are presented. The metrics capture the dynamic performance (in terms of instantaneous throughput, delay, routing load, etc.) of APMS and other competing solutions, thus exposing the often neglected aspects of performance.

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The Border Gateway Protocol (BGP) is the current inter-domain routing protocol used to exchange reachability information between Autonomous Systems (ASes) in the Internet. BGP supports policy-based routing which allows each AS to independently define a set of local policies on which routes it accepts and advertises from/to other networks, as well as on which route it prefers when more than one route becomes available. However, independently chosen local policies may cause global conflicts, which result in protocol divergence. In this paper, we propose a new algorithm, called Adaptive Policy Management Scheme(APMS), to resolve policy conflicts in a distributed manner. Akin to distributed feedback control systems, each AS independently classifies the state of the network as either conflict-free or potentially conflicting by observing its local history only (namely, route flaps). Based on the degree of measured conflicts, each AS dynamically adjusts its own path preferences---increasing its preference for observably stable paths over flapping paths. APMS also includes a mechanism to distinguish route flaps due to topology changes, so as not to confuse them with those due to policy conflicts. A correctness and convergence analysis of APMS based on the sub-stability property of chosen paths is presented. Implementation in the SSF network simulator is performed, and simulation results for different performance metrics are presented. The metrics capture the dynamic performance (in terms of instantaneous throughput, delay, etc.) of APMS and other competing solutions, thus exposing the often neglected aspects of performance.

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This thesis examines the relationship between initial loss events and the corporate governance and earnings management behaviour of these firms. This is done using four years of corporate governance information spanning the report of an initial loss for companies listed on the UK Stock Exchange. An industry- and sizematched control sample is used in a difference-in-difference analysis to isolate the impact of the initial loss event during the period. It is reported that, in general, an initial loss motivates an improvement in corporate governance in those loss firms where a relative weakness existed prior to the loss and that these changes mainly occur before the initial loss is announced. Firms with stronger (i.e. better quality) corporate governance have less need to alter it in response to the loss. It is also reported that initial loss firms use positive abnormal accruals in the year before the loss in an attempt to defer/avoid the loss — the weaker corporate governance the more likely is it that loss firms manage earnings in this manner. Abnormal accruals are also found to be predictive of an initial loss and when used as a conditioning variable, the quality of corporate governance is an important mitigating factor in this regard. Once the loss is reported, loss firms unwind these abnormal accruals although no evidence of big-bath behaviour is found. The extent to which these abnormal accruals are subsequently unwound are also found to be a function of both the quality of corporate governance as well as the severity of the initial loss.

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The abundance of many commercially important fish stocks are declining and this has led to widespread concern on the performance of traditional approach in fisheries management. Quantitative models are used for obtaining estimates of population abundance and the management advice is based on annual harvest levels (TAC), where only a certain amount of catch is allowed from specific fish stocks. However, these models are data intensive and less useful when stocks have limited historical information. This study examined whether empirical stock indicators can be used to manage fisheries. The relationship between indicators and the underlying stock abundance is not direct and hence can be affected by disturbances that may account for both transient and persistent effects. Methods from Statistical Process Control (SPC) theory such as the Cumulative Sum (CUSUM) control charts are useful in classifying these effects and hence they can be used to trigger management response only when a significant impact occurs to the stock biomass. This thesis explores how empirical indicators along with CUSUM can be used for monitoring, assessment and management of fish stocks. I begin my thesis by exploring various age based catch indicators, to identify those which are potentially useful in tracking the state of fish stocks. The sensitivity and response of these indicators towards changes in Spawning Stock Biomass (SSB) showed that indicators based on age groups that are fully selected to the fishing gear or Large Fish Indicators (LFIs) are most useful and robust across the range of scenarios considered. The Decision-Interval (DI-CUSUM) and Self-Starting (SS-CUSUM) forms are the two types of control charts used in this study. In contrast to the DI-CUSUM, the SS-CUSUM can be initiated without specifying a target reference point (‘control mean’) to detect out-of-control (significant impact) situations. The sensitivity and specificity of SS-CUSUM showed that the performances are robust when LFIs are used. Once an out-of-control situation is detected, the next step is to determine how much shift has occurred in the underlying stock biomass. If an estimate of this shift is available, they can be used to update TAC by incorporation into Harvest Control Rules (HCRs). Various methods from Engineering Process Control (EPC) theory were tested to determine which method can measure the shift size in stock biomass with the highest accuracy. Results showed that methods based on Grubb’s harmonic rule gave reliable shift size estimates. The accuracy of these estimates can be improved by monitoring a combined indicator metric of stock-recruitment and LFI because this may account for impacts independent of fishing. The procedure of integrating both SPC and EPC is known as Statistical Process Adjustment (SPA). A HCR based on SPA was designed for DI-CUSUM and the scheme was successful in bringing out-of-control fish stocks back to its in-control state. The HCR was also tested using SS-CUSUM in the context of data poor fish stocks. Results showed that the scheme will be useful for sustaining the initial in-control state of the fish stock until more observations become available for quantitative assessments.

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This study explores the role of livestock insurance to complement existing risk management strategies adopted by smallholder farmers. Using survey data, first, it provides insights into farmers’ risk perception of livestock farming, in terms of likelihood and severity of risk, attitude to risk and their determinants. Second, it examines farmers’ risk management strategies and their determinants. Third, it investigates farmers’ potential engagement with a hypothetical cattle insurance decision and their intensity of participation. Factor analysis is used to analyse risk sources and risk management, multiple regressions are used to identify the determinants; a Heckman model was used to investigate cattle insurance participation and intensity of participation. The findings show different groups of farmers display different risk attitude in their decision-making related to livestock farming. Production risk (especially livestock diseases) was perceived as the most likely and severe source of risk. Disease control was perceived as the best strategy to manage risk overall. Disease control and feed management were important strategies to mitigate the production risks. Disease control and participation on safety net program were found to be important to counter households’ financial risks. With regard to the hypothetical cattle insurance scheme, 94.38% of households were interested to participate in cattle insurance. Of those households that accepted cattle insurance, 77.38% of the households were willing to pay the benchmark annual premium of 4% of the animal value while for the remaining households this was not affordable. The average number of cattle that farmers were willing to insure was 2.71 at this benchmark. Results revealed that income (log income) and education levels influenced positively and significantly farmers’ participation in cattle insurance and the number of cattle to insure. The findings prompt policy makers to consider livestock insurance as a complement to existing risk management strategies to reduce poverty in the long-run.

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The mobile cloud computing model promises to address the resource limitations of mobile devices, but effectively implementing this model is difficult. Previous work on mobile cloud computing has required the user to have a continuous, high-quality connection to the cloud infrastructure. This is undesirable and possibly infeasible, as the energy required on the mobile device to maintain a connection, and transfer sizeable amounts of data is large; the bandwidth tends to be quite variable, and low on cellular networks. The cloud deployment itself needs to efficiently allocate scalable resources to the user as well. In this paper, we formulate the best practices for efficiently managing the resources required for the mobile cloud model, namely energy, bandwidth and cloud computing resources. These practices can be realised with our mobile cloud middleware project, featuring the Cloud Personal Assistant (CPA). We compare this with the other approaches in the area, to highlight the importance of minimising the usage of these resources, and therefore ensure successful adoption of the model by end users. Based on results from experiments performed with mobile devices, we develop a no-overhead decision model for task and data offloading to the CPA of a user, which provides efficient management of mobile cloud resources.

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OBJECTIVES: Side-effects of standard pain medications can limit their use. Therefore, nonpharmacologic pain relief techniques such as auriculotherapy may play an important role in pain management. Our aim was to conduct a systematic review and meta-analysis of studies evaluating auriculotherapy for pain management. DESIGN: MEDLINE,(®) ISI Web of Science, CINAHL, AMED, and Cochrane Library were searched through December 2008. Randomized trials comparing auriculotherapy to sham, placebo, or standard-of-care control were included that measured outcomes of pain or medication use and were published in English. Two (2) reviewers independently assessed trial eligibility, quality, and abstracted data to a standardized form. Standardized mean differences (SMD) were calculated for studies using a pain score or analgesic requirement as a primary outcome. RESULTS: Seventeen (17) studies met inclusion criteria (8 perioperative, 4 acute, and 5 chronic pain). Auriculotherapy was superior to controls for studies evaluating pain intensity (SMD, 1.56 [95% confidence interval (CI): 0.85, 2.26]; 8 studies). For perioperative pain, auriculotherapy reduced analgesic use (SMD, 0.54 [95% CI: 0.30, 0.77]; 5 studies). For acute pain and chronic pain, auriculotherapy reduced pain intensity (SMD for acute pain, 1.35 [95% CI: 0.08, 2.64], 2 studies; SMD for chronic pain, 1.84 [95% CI: 0.60, 3.07], 5 studies). Removal of poor quality studies did not alter the conclusions. Significant heterogeneity existed among studies of acute and chronic pain, but not perioperative pain. CONCLUSIONS: Auriculotherapy may be effective for the treatment of a variety of types of pain, especially postoperative pain. However, a more accurate estimate of the effect will require further large, well-designed trials.

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BACKGROUND: Despite the impact of hypertension and widely accepted target values for blood pressure (BP), interventions to improve BP control have had limited success. OBJECTIVES: We describe the design of a 'translational' study that examines the implementation, impact, sustainability, and cost of an evidence-based nurse-delivered tailored behavioral self-management intervention to improve BP control as it moves from a research context to healthcare delivery. The study addresses four specific aims: assess the implementation of an evidence-based behavioral self-management intervention to improve BP levels; evaluate the clinical impact of the intervention as it is implemented; assess organizational factors associated with the sustainability of the intervention; and assess the cost of implementing and sustaining the intervention. METHODS: The project involves three geographically diverse VA intervention facilities and nine control sites. We first conduct an evaluation of barriers and facilitators for implementing the intervention at intervention sites. We examine the impact of the intervention by comparing 12-month pre/post changes in BP control between patients in intervention sites versus patients in the matched control sites. Next, we examine the sustainability of the intervention and organizational factors facilitating or hindering the sustained implementation. Finally, we examine the costs of intervention implementation. Key outcomes are acceptability and costs of the program, as well as changes in BP. Outcomes will be assessed using mixed methods (e.g., qualitative analyses--pattern matching; quantitative methods--linear mixed models). DISCUSSION: The study results will provide information about the challenges and costs to implement and sustain the intervention, and what clinical impact can be expected.

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INTRODUCTION: We aimed to inform the design of behavioral interventions by identifying patients' and their family members' perceived facilitators and barriers to hypertension self-management. MATERIALS AND METHODS: We conducted focus groups of African American patients with hypertension and their family members to elicit their views about factors influencing patients' hypertension self-management. We recruited African American patients with hypertension (n = 18) and their family members (n = 12) from an urban, community-based clinical practice in Baltimore, Maryland. We conducted four separate 90-minute focus groups among patients with controlled (one group) and uncontrolled (one group) hypertension, as well as their family members (two groups). Trained moderators used open-ended questions to assess participants' perceptions regarding patient, family, clinic, and community-level factors influencing patients' effective hypertension self-management. RESULTS: Patient participants identified several facilitators (including family members' support and positive relationships with doctors) and barriers (including competing health priorities, lack of knowledge about hypertension, and poor access to community resources) that influence their hypertension self-management. Family members also identified several facilitators (including their participation in patients' doctor's visits and discussions with patients' doctors outside of visits) and barriers (including their own limited health knowledge and patients' lack of motivation to sustain hypertension self-management behaviors) that affect their efforts to support patients' hypertension self-management. CONCLUSION: African American patients with hypertension and their family members reported numerous patient, family, clinic, and community-level facilitators and barriers to patients' hypertension self-management. Patients' and their family members' views may help guide efforts to tailor behavioral interventions designed to improve hypertension self-management behaviors and hypertension control in minority populations.

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BACKGROUND: Several trials have demonstrated the efficacy of nurse telephone case management for diabetes (DM) and hypertension (HTN) in academic or vertically integrated systems. Little is known about the real-world potency of these interventions. OBJECTIVE: To assess the effectiveness of nurse behavioral management of DM and HTN in community practices among patients with both diseases. DESIGN: The study was designed as a patient-level randomized controlled trial. PARTICIPANTS: Participants included adult patients with both type 2 DM and HTN who were receiving care at one of nine community fee-for-service practices. Subjects were required to have inadequately controlled DM (hemoglobin A1c [A1c] ≥ 7.5%) but could have well-controlled HTN. INTERVENTIONS: All patients received a call from a nurse experienced in DM and HTN management once every two months over a period of two years, for a total of 12 calls. Intervention patients received tailored DM- and HTN- focused behavioral content; control patients received non-tailored, non-interactive information regarding health issues unrelated to DM and HTN (e.g., skin cancer prevention). MAIN OUTCOMES AND MEASURES: Systolic blood pressure (SBP) and A1c were co-primary outcomes, measured at 6, 12, and 24 months; 24 months was the primary time point. RESULTS: Three hundred seventy-seven subjects were enrolled; 193 were randomized to intervention, 184 to control. Subjects were 55% female and 50% white; the mean baseline A1c was 9.1% (SD = 1%) and mean SBP was 142 mmHg (SD = 20). Eighty-two percent of scheduled interviews were conducted; 69% of intervention patients and 70% of control patients reached the 24-month time point. Expressing model estimated differences as (intervention--control), at 24 months, intervention patients had similar A1c [diff = 0.1 %, 95 % CI (-0.3, 0.5), p = 0.51] and SBP [diff = -0.9 mmHg, 95% CI (-5.4, 3.5), p = 0.68] values compared to control patients. Likewise, DBP (diff = 0.4 mmHg, p = 0.76), weight (diff = 0.3 kg, p = 0.80), and physical activity levels (diff = 153 MET-min/week, p = 0.41) were similar between control and intervention patients. Results were also similar at the 6- and 12-month time points. CONCLUSIONS: In nine community fee-for-service practices, telephonic nurse case management did not lead to improvement in A1c or SBP. Gains seen in telephonic behavioral self-management interventions in optimal settings may not translate to the wider range of primary care settings.