Dynamic replication strategies in data grid systems: A survey

In data grid systems, data replication aims to increase availability, fault tolerance, load balancing and scalability while reducing bandwidth consumption, and job execution time. Several classification schemes for data replication were proposed in the literature, (i) static vs. dynamic, (ii) centralized vs. decentralized, (iii) push vs. pull, and (iv) objective function based. Dynamic data replication is a form of data replication that is performed with respect to the changing conditions of the grid environment. In this paper, we present a survey of recent dynamic data replication strategies. We study and classify these strategies by taking the target data grid architecture as the sole classifier. We discuss the key points of the studied strategies and provide feature comparison of them according to important metrics. Furthermore, the impact of data grid architecture on dynamic replication performance is investigated in a simulation study. Finally, some important issues and open research problems in the area are pointed out

Identifying critical architectural components with spectral analysis of fault trees

We increasingly rely on software-intensive embedded systems. Increasing size and complexity of these hardware/software systems makes it necessary to evaluate reliability at the system architecture level. One aspect of this evaluation is sensitivity analysis, which aims at identifying critical components of the architecture. These are the components of which unreliability contributes the most to the unreliability of the system. In this paper, we propose a novel approach for sensitivity analysis based on spectral analysis of fault trees. We show that measures obtained with our approach are both consistent and complementary with respect to the recognized metrics in the literature.TÜBİTA

Moving switching functions to continuous domain

This paper proposes a method for moving switching functions to continuous domain. The benefits of this approach are twofold. First, the elementary calculus works with the transformed functions. Second, this transformation approach facilitates various analyses relying on Boolean algebra and other existing Boolean-based calculi like Boolean difference. We present one of the potential applications and show how MCDC test pairs can be computed solely by means of elementary calculus

Optimal control for real-time feedback rate-monotonic schedulers

This paper presents an optimal control scheme for a real-time feedback control rate-monotonic scheduling (FC-RMS) system. We consider two-version tasks composed of a mandatory and an optional part to be scheduled according to the FC-RMS. In FC-RMS, the controller provides a feedback strategy for deciding about the execution or rejection of the optional sub-tasks. By modeling the task execution times as random variables, we first find the statistical model of FC-RMS and then we design a pure optimal controller and an optimal controller with feedforward integral compensation. The comparison of these two schemes with common Proportional-Integral-Derivative (PID) controller highlights the benefit of the optimal scheme with integral compensation. The results are demonstrated through the real implementation of FC-RMS on RT-Linux

Stability Properties of Adaptive Real-Time Feedback Scheduling: A Statistical Approach

This paper focuses on the statistical analysis of an adaptive real-time feedback scheduling technique based on imprecise computation. We consider two-version tasks made of a mandatory and an optional part to be scheduled according to a feedback control rate-monotonic algorithm. A Proportional-Integral-Derivative (PID) control action provides the feedback strategy for deciding about the execution or rejection of the optional sub-tasks. By modelling the task execution times as random variables, we compute the probability density of the CPU utilization and derive conditions on PID parameters guaranteeing the stability of the overall system around a desired level of CPU utilization. This allows us to highlight the tasks statistics and the scheduling parameters that affect critically stability. The analysis is developed by first exploiting a number of simplifying assumptions that are progressively removed. The main results are also demonstrated through monte-carlo simulations of the scheduling algorithm

Stability properties of adaptive real-time.feedback scheduling: A statistical approach.

This paper focuses on the statistical analysis of an adaptive real-time feedback scheduling technique based on imprecise computation. We consider two-version tasks made of a mandatory and an optional part to be scheduled according to a feedback control rate-monotonic algorithm. A Proportional-Integral-Derivative (PID) control action provides the feedback strategy for deciding about the execution or rejection of the optional sub-tasks. By modelling the task execution times as random variables, we compute the probability density of the CPU utilization and derive conditions on PID parameters guaranteeing the stability of the overall system around a desired level of CPU utilization. This allows us to highlight the tasks statistics and the scheduling parameters that affect critically stability. The analysis is developed by first exploiting a number of simplifying assumptions that are progressively removed. The main results are also demonstrated through monte-carlo simulations of the scheduling algorithm

Dynamic replication strategies in data grid systems: a survey

In data grid systems, data replication aims to increase availability, fault tolerance, load balancing and scalability while reducing bandwidth consumption, and job execution time. Several classification schemes for data replication were proposed in the literature, (i) static vs. dynamic, (ii) centralized vs. decentralized, (iii) push vs. pull, and (iv) objective function based. Dynamic data replication is a form of data replication that is performed with respect to the changing conditions of the grid environment. In this paper, we present a survey of recent dynamic data replication strategies. We study and classify these strategies by taking the target data grid architecture as the sole classifier. We discuss the key points of the studied strategies and provide feature comparison of them according to important metrics. Furthermore, the impact of data grid architecture on dynamic replication performance is investigated in a simulation study. Finally, some important issues and open research problems in the area are pointed out. © 2015, Springer Science+Business Media New York

Human–robot interfaces of the neuroboscope: A minimally invasive endoscopic pituitary tumor surgery robotic assistance system

Endoscopic endonasal surgery is a commonly practiced minimally invasive neurosurgical operation for the treatment of a wide range of skull base pathologies including pituitary tumors. A common shortcoming of this surgery is the necessity of a third hand when the endoscope has to be handled to allow active use of both hands of the main surgeon. The robot surgery assistant NeuRoboScope system has been developed to take over the endoscope from the main surgeon’s hand while providing the surgeon with the necessary means of controlling the location and direction of the endoscope. One of the main novelties of the NeuRoboScope system is its human–robot interface designs which regulate and facilitate the interaction between the surgeon and the robot assistant. The human–robot interaction design of the NeuRoboScope system is investigated in two domains: direct physical interaction (DPI) and master–slave teleoperation (MST). The user study indicating the learning curve and ease of use of the MST is given and this paper is concluded via providing the reader with an outlook of possible new human–robot interfaces for the robot assisted surgery systems. Copyright VC 2021 by ASM