JiTS: Just-in-Time Scheduling for Real-Time Sensor Data Dissemination

We consider the problem of real-time data dissemination in wireless sensor networks, in which data are associated with deadlines and it is desired for data to reach the sink(s) by their deadlines. To this end, existing real-time data dissemination work have developed packet scheduling schemes that prioritize packets according to their deadlines. In this paper, we first demonstrate that not only the scheduling discipline but also the routing protocol has a significant impact on the success of real-time sensor data dissemination. We show that the shortest path routing using the minimum number of hops leads to considerably better performance than Geographical Forwarding, which has often been used in existing real-time data dissemination work. We also observe that packet prioritization by itself is not enough for real-time data dissemination, since many high priority packets may simultaneously contend for network resources, deteriorating the network performance. Instead, real-time packets could be judiciously delayed to avoid severe contention as long as their deadlines can be met. Based on this observation, we propose a Just-in-Time Scheduling (JiTS) algorithm for scheduling data transmissions to alleviate the shortcomings of the existing solutions. We explore several policies for non-uniformly delaying data at different intermediate nodes to account for the higher expected contention as the packet gets closer to the sink(s). By an extensive simulation study, we demonstrate that JiTS can significantly improve the deadline miss ratio and packet drop ratio compared to existing approaches in various situations. Notably, JiTS improves the performance requiring neither lower layer support nor synchronization among the sensor nodes

Supporting Preemptive Task Executions and Memory Copies in GPGPUs

GPGPUs (General Purpose Graphic Processing Units) provide massive computational power. However, applying GPGPU technology to real-time computing is challenging due to the non-preemptive nature of GPGPUs. Especially, a job running in a GPGPU or a data copy between a GPGPU and CPU is non-preemptive. As a result, a high priority job arriving in the middle of a low priority job execution or memory copy suffers from priority inversion. To address the problem, we present a new lightweight approach to supporting preemptive memory copies and job executions in GPGPUs. Moreover, in our approach, a GPGPU job and memory copy between a GPGPU and the hosting CPU are run concurrently to enhance the responsiveness. To show the feasibility of our approach, we have implemented a prototype system for preemptive job executions and data copies in a GPGPU. The experimental results show that our approach can bound the response times in a reliable manner. In addition, the response time of our approach is significantly shorter than those of the unmodified GPGPU runtime system that supports no preemption and an advanced GPGPU model designed to support prioritization and performance isolation via preemptive data copies

Towards Context-Aware Real-Time Information Dissemination

Real-time information dissemination is essential for the success of key applications such as transportation management and battlefield monitoring. In these applications, relevant information should be disseminated to interested users in a timely fashion. However, it is challenging to support timely information dissemination due to the limited and even time-varying network bandwidth. Thus, a naive approach disseminating every data with no consideration of the context that describes where and when the data is acquired and how it can satisfy users may only provide poor performance and user perceived quality of service (QoS). To address the problem, we design a novel context-aware protocol to disseminate real-time data in a cost-effective manner by considering the spatio-temporal semantics associated with information. More specifically, we define (1) context attributes, (2) develop how to analyze the utility of a specific data item based on the attributes, (3) and adjust the utility based on a cost-benefit analysis for costeffective real-time information dissemination especially in the context of visual surveillance

Active Queue Management via Event-Driven Feedback Control

Active queue management (AQM) is investigated to avoid incipient congestion in gateways to complement congestion control run by the transport layer protocol such as the TCP. Most existing work on AQM can be categorized as (1) ad-hoc event-driven control and (2) time-driven feedback control approaches based on control theory. Ad hoc event-driven approaches for congestion control, such as RED (random early detection), lack a mathematical model. Thus, it is hard to analyze their dynamics and tune the parameters. Time-driven control theoretic approaches based on solid mathematical models have drawbacks too. As they sample the queue length and run AQM algorithm at every fixed time interval, they may not be adaptive enough to an abrupt load surge. Further, they can be executed unnecessarily often under light loads due to the time-driven nature. To seamlessly integrate the advantages of both event-driven and control-theoretic time-driven approaches, we present an event-driven feedback control approach based on formal control theory. As our approach is based on a mathematical model, its performance is more analyzable and predictable than ad hoc event-driven approaches are. Also, it is more reactive to dynamic load changes due to its event-driven nature. Our simulation results show that our event-driven controller effectively maintains the queue length around the specified set-point. It achieves shorter E2E (end-to-end) delays and smaller E2E delay fluctuations than several existing AQM approaches, which are ad hoc event-driven and based on time-driven control theory, while achieving almost the same E2E delays and E2E delay fluctuations as the two other advanced control theoretic AQM approaches. Further, our AQM algorithm is invoked much less frequently than the tested baseline

Robust fuzzy CPU utilization control for dynamic workloads

In a number of real-time applications such as target tracking, precise workloads are unknown a priori but may dynamically vary, for example, based on the changing number of targets to track. It is important to manage the CPU utilization, via feedback control, to avoid severe overload or underutilization even in the presence of dynamic workloads. However, it is challenge to model a real-time system for feedback control, as computer systems cannot be modeled via physics laws. In this paper, we present a novel closed-loop approach for utilization control based on formal fuzzy logic control theory, which is very effective to support the desired performance in a nonlinear dynamic system without requiring a system model. We mathematically prove the stability of thefuzzy closed-loop system. Further, in a real-time kernel, we implement and evaluate our fuzzy logic utilization controller as well as two existing utilization controllers based on the linear and model predictive control theory for an extensive set of workloads. Our approach supports the specified average utilization set-point, while showing the best transient performance in terms of utilization control among the tested approaches

Clinical outcomes of spontaneous bacterial peritonitis due to extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species: A retrospective matched case-control study

<p>Abstract</p> <p>Background</p> <p>Clinical outcomes of spontaneous bacterial peritonitis (SBP) due to extended-spectrum β-lactamase-producing <it>Escherichia coli </it>and <it>Klebsiella </it>species (ESBL-EK) have not been adequately investigated.</p> <p>Methods</p> <p>We conducted a retrospective matched case-control study to evaluate the outcomes of SBP due to ESBL-EK compared with those due to non-ESBL-EK. Cases were defined as patients with liver cirrhosis and SBP due to ESBL-EK isolated from ascites. Control patients with liver cirrhosis and SBP due to non-ESBL-EK were matched in a 3:1 ratio to cases according to the following five variables: age (± 5 years); gender; species of infecting organism; Child-Pugh score (± 2); Acute Physiological and Chronic Health Evaluation II score (± 2). 'Effective initial therapy' was defined as less than 72 hours elapsing between the time of obtaining a sample for culture and the start of treatment with an antimicrobial agent to which the EK was susceptible. Cephalosporin use for ESBL-EK was considered 'ineffective', irrespective of the minimum inhibitory concentration. ESBL production was determined according to the Clinical and Laboratory Standards Institute guidelines on stored isolates.</p> <p>Results</p> <p>Of 1026 episodes of SBP in 958 patients from Jan 2000 through Dec 2006, 368 (35.9%) episodes in 346 patients were caused by SBP due to EK, isolated from ascites. Of these 346 patients, twenty-six (7.5%) patients with SBP due to ESBL-EK were compared with 78 matched controls. Treatment failure, evaluated at 72 hours after initial antimicrobial therapy, was greater among the cases (15/26, 58% <it>vs</it>. 10/78, 13%, <it>P </it>= .006); 30-day mortality rate was also higher than in the controls (12/26, 46% <it>vs</it>. 11/78, 15%, <it>P </it>= .001). When the case were classified according to the effectiveness of the initial therapy, 'ineffective initial therapy' was associated with higher 30-day mortality rate (11/18, 61% <it>vs</it>. 1/8, 13%, <it>P </it>= .036).</p> <p>Conclusion</p> <p>SBP due to ESBL-EK had poorer outcomes than SBP due to non-ESBL-EK. Ineffective initial therapy seems to be responsible for the higher rate of treatment failure and mortality in SBP due to ESBL-EK.</p