Formal Scheduling Constraints for Time-Sensitive Networks

In recent years, the IEEE 802.1 Time Sensitive Networking (TSN) task group has been active standardizing time-sensitive capabilities for Ethernet networks ranging from distributed clock synchronization and time-based ingress policing to frame preemption, redundancy management, and scheduled traffic enhancements. In particular the scheduled traffic enhancements defined in IEEE 802.1Qbv together with the clock synchronization protocol open up the possibility to schedule communication in distributed networks providing real-time guarantees. In this paper we formalize the necessary constraints for creating window-based IEEE~802.1Qbv Gate Control List schedules for Time-sensitive Networks (TSN). The resulting schedules allow a greater flexibility in terms of timing properties while still guaranteeing deterministic communication with bounded jitter and end-to-end latency

A Real-time Calculus Approach for Integrating Sporadic Events in Time-triggered Systems

In time-triggered systems, where the schedule table is predefined and statically configured at design time, sporadic event-triggered (ET) tasks can only be handled within specially dedicated slots or when time-triggered (TT) tasks finish their execution early. We introduce a new paradigm for synthesizing TT schedules that guarantee the correct temporal behavior of TT tasks and the schedulability of sporadic ET tasks with arbitrary deadlines. The approach first expresses a constraint for the TT task schedule in the form of a maximal affine envelope that guarantees that as long as the schedule generation respects this envelope, all sporadic ET tasks meet their deadline. The second step consists of modeling this envelope as a burst limiting constraint and building the TT schedule via simulating a modified Least-Laxity-First (LLF) scheduler. Using this novel technique, we show that we achieve equal or better schedulability and a faster schedule generation for most use-cases compared to other approaches inspired by, e.g., hierarchical scheduling. Moreover, we present an extension to our method that finds the most favourable schedule for TT tasks with respect to ET schedulability, thus increasing the probability of the computed TT schedule remaining feasible when ET tasks are later added or changed

Design Optimization of Cyber-Physical Distributed Systems using IEEE Time-sensitive Networks (TSN)

In this paper we are interested in safety-critical real-time applications implemented on distributed architectures supporting the Time-SensitiveNetworking (TSN) standard. The ongoing standardization of TSN is an IEEE effort to bring deterministic real-time capabilities into the IEEE 802.1 Ethernet standard supporting safety-critical systems and guaranteed Quality-of-Service. TSN will support Time-Triggered (TT) communication based on schedule tables, Audio-Video-Bridging (AVB) flows with bounded end-to-end latency as well as Best-Effort messages. We first present a survey of research related to the optimization of distributed cyber-physical systems using real-time Ethernet for communication. Then, we formulate two novel optimization problems related to the scheduling and routing of TT and AVB traffic in TSN. Thus, we consider that we know the topology of the network as well as the set of TT and AVB flows. We are interested to determine the routing of both TT and AVB flows as well as the scheduling of the TT flows such that all frames are schedulable and the AVB worst-case end-to-end delay is minimized. We have proposed an Integer Linear Programming (ILP) formulation for the scheduling problem and a Greedy Randomized Adaptive Search Procedure (GRASP)-based heuristic for the routing problem. The proposed approaches have been evaluated using several test cases

Intramedullary tumors: Clinical, radiological and histological correlations

Intramedullary spinal cord (SC) tumors are relatively rare tumors, accounting for only 2% to 4% ofcentral nervous systemtumors.These tumorsaregenerallyslow-growing tumorsthatcouldbenefitfromsurgical removal. A pre-surgery identification of the tumor histology might improve the surgical management of the tumor and also properly predict the functional outcome after surgery. The neuroimaging techniques, provide crucial information about tumors anatomy. By adding the medical history of the present illness and detailed clinical examination, the imaging data might however be extremely helpful in the prediction of tumor histology. This will allow anappropriate surgical managementofthese lesions and provide pertinent predictors of the functional outcome post-surgery. Therefore, the surgeon can set the patient’s expectations at a realistic level.The present studyis a prospective study,aiming to use combined clinical and imaging data to predictthe intramedullary SC tumor histology. The primary objectiveis to identify the pathognomonic clinical and imaging pattern for eachtumor type.The study was conducted in the Neurosurgery Clinic Emergency Clinic Hospital Bagdasar-Arseni between 2006 and 2009. A total of 36 patients (19 females/17 males) participated. All patients were evaluated for motor, sensory, sphincter, walking and balance functions. MRI assessment was used to determine the presence of an intramedullary SC tumor as well as its characteristics.All histological types have a long history of symptoms, which depends of locations in longitudinal plane. All intramedullary tumors presented spinal cord dilatation on MRI. We confined the clinico-radiological characteristics of each histological type, strongly correlated with histopathological analysis, extensively presented in the paper. By combining a careful medical history, clinical examination and MRI data, we could predict with a reasonable accuracy in preoperative stage the histological type of an intramedullary tumor.&nbsp

Deontological issues - possible misdiagnosis of cerebral metastases

Authors analyses a number of 4588 (52, 24% over 50 years old) patients operated for cerebral tumors in the Clinic Emergency Hospital “Bagdasar-Arseni” from Bucharest, between 2000-2010, with peculiar attention to the concordance between the preoperative and postoperative diagnosis, related to the actual policy to evaluate a neurosurgical patient before surgery. 903 cases were cerebral metastases and 69,5% aged over 50 years old. In 9,7% of cases we recorded a preoperative misdiagnosis of a metastasis due to few main reasons: unavailable information about a present primitive cancer, treacherous MRI image with a single confusing appearance of a cerebral lesion, age less than 50 years old, clinical presentation and biological evaluation inconsistent with malignancy. Authors point that these situations can have serious consequences related to professional competence, deterioration of the patient-doctor relationship, increasing costs for completion of diagnosis and treatment, and inadequate information about patient’s prognosis

Power-aware Temporal Isolation with Variable-Bandwidth Servers

Variable-bandwidth servers (VBS) control process execution speed by allocating variable CPU bandwidth to processes. VBS enables temporal isolation of EDF-scheduled processes in the sense that the variance in CPU throughput and latency of each process is bounded independently of any other concurrently running processes. In this paper we aim at reducing CPU power consumption with VBS by CPU voltage and frequency scaling while maintaining temporal isolation. Scaling to lower frequencies is possible whenever there is CPU slack in the system. We first show that, in the presence of CPU slack, frequency scaling of EDFscheduled, possibly non-periodic tasks (as they arise with VBS) is safe up to full CPU utilization and propose a frequency-scaling VBS algorithm that exploits CPU slack to minimize operating frequencies with maximal CPU utilization while maintaining temporal isolation. This may lead to improvements in power consumption while hiding the real-time effects of frequency scaling. Additional power may be saved by redistributing computation time of individual processes while still maintaining temporal isolation if the system has knowledge of future events. We introduce an offline algorithm as an optimal baseline and an online algorithm that approximates the baseline. While the offline algorithm works for various, possibly complex power consumption models, the online algorithm may reduce power consumption only for a simplified power consumption model by reducing the CPU utilization jitter in the system