Distributed Real-time Systems Research Articles

Fast multi-phase gain matrix computation for real time distribution system state estimation

Efficient distribution system state estimation (DSSE) is becoming increasingly important in modern grids. Building the gain matrix is carried out at every iteration of the weighted least squares (WLS) DSSE algorithm that employs the normal equations approach, and the computation of this matrix occupies a substantial portion of the total execution time. This paper presents a two-phase algorithm for the efficient gain matrix calculation suitable for modern CPU architectures. The preparation phase creates the necessary structures for effective data streaming and code execution. The gain matrix is calculated in the second phase using the prepared data and single instruction multiple data (SIMD) intrinsics. The Jacobian measurement matrix is organized as a sparse matrix of small dense blocks with double-precision complex values. The implementation exploits memory-aligned data blocks that require fewer CPU instructions and provide higher memory access speeds, in addition to modern C++ features for utilizing the instruction pipelining technique fully. Numerical results are reported on sizeable distribution networks having up to 3124 multi-phase nodes and 9537 three-phase nodes. They show that the proposed approach for computing the gain matrix is up to three times faster than the sparse matrix–matrix multiplication function in the SuiteSparse package, which makes the procedure useful for the development of real-time DSSE software.

Joint Link Rate Selection and Adaptive Forward Error Correction for High-Rate Wireless Multicast

Multicast communication over wireless networks has many potential applications, such as real-time audiovisual content distribution or digital signage systems with multiple remote terminals. However, today’s common 802.11 networks cannot fully support such applications at the link layer due to the technical challenges in achieving both high transmission rate and high reliability for multicast data transfers. Those challenges primarily emerge from the inapplicability of immediate acknowledgment mechanisms of unicast transmissions to the multicast case and the need for finding a common transmission rate for all receivers with diverse channel conditions. The research literature in this domain mainly addresses the problem at the higher layers of the protocol stack. In this article, we present a novel approach that combines wireless link rate selection with an adaptive packet-level Forward Error Correction (FEC) mechanism in order to achieve high-rate and highly reliable multicast in 802.11 wireless networks. The integration of FEC into the 802.11 MAC layer allows direct interaction between the transmission rate and the coding scheme. As a result, potential packet losses caused by higher link rates can be compensated by the adjustable redundancy provided by FEC. In combination with an aggregated receiver feedback mechanism, this yields improved transmission efficiency and reliability for wireless multicast. We investigate this approach in a simulation environment under a realistic wireless channel model in various application scenarios with up to 50 receivers. The results represent significant performance improvements, in terms of throughput, channel utilization, and packet loss, over the state-of-the-art methods for reliable wireless multicast.

Priority assignment in hierarchically scheduled time-partitioned distributed real-time systems with multipath flows

The increasing complexity in the design of industrial embedded systems represents a challenge in the development of scheduling algorithms for such systems, which are essential to guarantee that they meet their deadlines even in the worst-case situation. In this work, we propose a new collection of non-iterative priority assignment algorithms for multipath flows within hierarchical schedulers based on state-of-the-art scheduling algorithms, which have been adapted to this complex system model. They are applied to an industrial railway use case that has motivated this work, and then their performance is evaluated in different general synthetic scenarios, with the aim of providing a view on how they behave in a wider range of system configurations.

A Novel Reliability Index Based Approach for EV Charging Station Allocation in Distribution System

Large-scale deployment of electric vehicles (EVs) is deleterious for distribution system operations. Unplanned installation of EV charging station (EVCS) deteriorates the voltage stability, reliability, and power quality of the distribution system leading to customer discontentment. This article proposes a novel approach for the proper placement of EVCS in a distribution network maintaining the system performance. The design of a test station with vehicle-to-grid (V2G) capability is outlined in this work. The test station is developed with five charging columns taking into consideration the standards and guidelines outlined in the Government of India EV policy. The charging station is connected to the power grid by a dc bus to which numerous EVs are attached. EVCS placement in the IEEE-33 bus radial distribution system is performed by developing six test scenarios. The test case results substantiate the potency of the reliability-index based approach for allocating EVCS both slow and fast chargers in a distribution network. Further, the maximal threshold value for placing the EVCS in various buses in a distribution system is determined using a novel electric vehicle placement index (EVPI). The novelty of the approach lies in the fact that it can include all operational parameters influenced owing to EV deployment, thereby maintaining the overall system performance without any physical restructuring of the network. The efficacy of the approach and the severity level of EVCS placement are validated for a real-time distribution system in Kerala, India.

Clock Synchronization in Virtualized Distributed Real-Time Systems using IEEE 802.1AS and ACRN

Virtualization of distributed real-time systems enables the consolidation of mixed-criticality functions on a shared hardware platform thus easing system integration. Time-triggered communication and computation can act as an enabler of safe hard real-time systems. A time-triggered hypervisor that activates virtual CPUs according to a global schedule can provide the means to allow for a resource efficient implementation of the time-triggered paradigm in virtualized distributed real-time systems. A prerequisite of time-triggered virtualization for hard real-time systems is providing access to a global time base to VMs as well as to the hypervisor. A global time base is the result of clock synchronization with an upper bound on the clock synchronization precision. We present a formalization of the notion of time in virtualized real-time systems. We use this formalization to propose a virtual clock condition that enables us to test the suitability of a virtual clock for the design of virtualized time-triggered real-time systems. We discuss and model how virtualization, in particular resource consolidation versus resource partitioning, degrades clock synchronization precision. Finally, we apply our insights to model the IEEE~802.1AS clock synchronization protocol and derive an upper bound on the clock synchronization precision of IEEE 802.1AS. We present our implementation of a dependent clock for ACRN that can be synchronized to a grandmaster clock. The results of our experiments illustrate that a type-1 hypervisor implementing a dependent clock yields native clock synchronization precision. Furthermore, we show that the upper bound derived from our model holds for a series of experiments featuring native as well as virtualized setups.

The Impact of GIS/GPS Network Information Systems on the Logistics Distribution Cost of Tobacco Enterprises

The improvement of logistics operation management for many tobacco companies highly depends on the reduction of distribution costs. In order to optimize routes, cigarettes are delivered through online real-time distribution system equipped with GIS/GPS. These network information technologies are crucial to creating and maintaining an efficient distribution system. Considering the applicability and flexibility of GIS/GPS network information system, this paper assesses the impact of its implementation on the logistics distribution cost from both overall and household levels. Specifically, DID and pseudo-DID models were adopted and monthly panel data of 14 prefecture-level branches of Hunan Tobacco Company during 2016-2019 were used for regression.We find that the implementation of GIS/GPS network information systems increased the total distribution cost. However, the average distribution cost was significantly reduced at per household level as the customer base expanded. A series of robustness and sensitivity tests supported above results. Furthermore, the implementation of GIS/GPS network information system is beneficial to service quality and employee performance. In addition, more time and logistics costs were saved when drivers chose “dynamic + fixed optimization” route model.

Actuator Fault Tolerant Control of Variable Cycle Engine Using Sliding Mode Control Scheme

This paper presents a fault tolerant control (FTC) design for the actuator faults in a variable cycle engine (VCE). Ensured by the multiple variable geometries structure of VCE, the design is realized by distributing the control effort among the unfaulty actuators with the “functional redundancy” idea. The FTC design consists of two parts: the fault reconstruction part and the fault tolerant control part, which use a sliding mode observer (SMO) and a sliding mode control (SMC) scheme respectively. Considering the inaccuracy of the fault reconstruction result, the proposed design requires only inaccurate fault information. The stability of the closed-loop control system is proved and the existence condition for the proposed control law is analyzed. This work also reveals its relation to the sliding mode control allocation design and the adaptive SMC design. An application case is then studied for tolerating the loss of effectiveness fault of the nozzle area actuator. Results show that the FTC design is able to tolerate the fault and achieves the same control goal as in the fault-free situation. Finally, a hardware-in-the-loop test is carried out to verify the design in a real-time distributed control system, which demonstrates its use from the engineering perspective.

Clock Synchronization in Virtualized Distributed Real-Time Systems Using IEEE 802.1AS and ACRN

Virtualization of distributed real-time systems enables the consolidation of mixed-criticality functions on a shared hardware platform, easing system integration. Time-triggered communication and computation can act as an enabler of safe hard real-time systems. A time-triggered hypervisor that activates virtual CPUs according to a global schedule can provide the means to allow for a resource-efficient implementation of the time-triggered paradigm in virtualized distributed real-time systems. A prerequisite of time-triggered virtualization for hard real-time systems is providing access to a global time base to VMs and the hypervisor. A global time base results from clock synchronization with an upper bound on the clock synchronization precision . We present a formalization of the notion of time in virtualized distributed real-time systems. We use this formalization to propose a virtual clock condition that enables us to test the suitability of a virtual clock for the design of virtualized time-triggered real-time systems focusing on clock synchronization. We discuss and model how virtualization, particularly resource consolidation versus resource partitioning, degrades clock synchronization precision. Finally, we apply our insights to model the IEEE 802.1AS clock synchronization protocol and derive an upper bound on the clock synchronization precision of IEEE 802.1AS in a virtualized distributed real-time system. We present our implementation of a dependent clock for ACRN that can be synchronized to a grandmaster clock. The results of our experiments illustrate that a type-1 hypervisor like ACRN implementing the dependent clock paradigm yields native clock synchronization precision. Furthermore, we show that the upper bound of clock synchronization precision derived from our model holds for a series of experiments featuring native and virtualized setups.

Cooperative and Non-Cooperative Frameworks with Utility Function Design for Intermediate Deadline Assignment in Real-Time Distributed Systems

In real-time distributed systems, it is important to provide offline guarantee for an upper-bound of each real-time task’s end-to-end delay, which has been achieved by assigning proper intermediate deadlines of individual real-time tasks at each node. Although existing studies have succeeded to utilize mathematical theories of distributed computation/control for intermediate deadline assignment, they have assumed that every task operates in a cooperative manner, which does not always hold for real-worlds. In addition, existing studies have not addressed how to exploit a trade-off between end-to-end delay fairness among real-time tasks and performance for minimizing aggregate end-to-end delays. In this paper, we recapitulate an existing cooperative distributed framework, and propose a non-cooperate distributed framework that can operate even with selfish tasks, each of which is only interested in minimizing its own end-to-end delay regardless of achieving the system goal. We then propose how to design utility functions that allow the real-time distributed system to exploit the trade-off. Finally, we demonstrate the validity of the cooperative and non-cooperative frameworks along with the designed utility functions, via simulations.

Numerical method for islanding the location of ground fault in the material based distribution system

Nowadays the location of a ground fault and separating the fault segments are very complicated in the material based distribution networks because the reality to facilitate the fault current is really minute to be calculated. Considering the smart digital meters are installed in the distribution side voltage (11 kV) of the radial distribution systems through the advancement of the smart-grid. This paper presented an identification of fault location and islanding of fault segments using smart digital metering unit on the distribution network side. Generally, superior method is used to locate the faulted segments and the faulted negative sequence by connecting the association between measurement sets and distance of the fault. The proposed technology is experienced in India, a real-time 40-bus radial distribution system and the results provide that it is appropriate for a system with both inactive load demands. This technology does not need any management methods but it uses the wide-area measured data. Together with the breakers, the proposed methodology can locate and island the fault segments without disrupting the healthy distribution network process.

Regulating Accuracy-Efficiency Trade-Offs in Distributed Machine Learning Systems

In this paper we discuss the trade-off between accuracy and efficiency in distributed machine learning (ML) systems and analyze its resulting policy considerations. This trade-off is in fact quite common in multiple disciplines, including law and medicine, and it applies to a wide variety of sub-fields within computer science. Accuracy and efficiency trade-offs have unique implications in ML algorithms because, being probabilistic in nature, such algorithms generally exhibit error tolerance. After describing how the trade-off takes shape in real-world distributed computing systems, we show the interplay between such systems and ML algorithms, explaining in detail how accuracy and efficiency interact particularly in distributed ML systems. We close by making specific calls to action for approaching regulatory policy for the emerging technology of real-time distributed ML systems.

Use case-based evaluation of workflow optimization strategy in real-time computation system

With the start of big data era, data stream computing has emerged as a well-known approach to optimize data-intensive workflows. Apache STORM is an open-source real-time distributed computation system for processing data streams and has been opted by famous organizations such as Twitter, Yahoo, Alibaba, Baidu, Groupon. The workflows are implemented as topologies in STORM. The main aspect that controls the execution performance of a workflow in STORM is the strategy of scheduling the topology components (spout and bolts). In this paper, we evaluate and analyze the performance of our algorithm Partition-based Data-intensive Workflow optimization Algorithm (PDWA) in Apache STORM using a use case workflow, EURExpressII. It is a real-world application-based workflow that builds a transcriptome-wide atlas of gene expression for the developing mouse embryo established by ribonucleic acid (RNA) in situ hybridization. Our proposed algorithm, PDWA, partitions the application task graph so that the data movement between partitions is minimum. Each partition is then mapped on one machine for the execution of tasks of that partition. It provides minimum execution time for that particular partition. Partial task duplication is also part of this algorithm that enhances the performance. A STORM-based computing cluster is developed in OpenStack cloud which is used as a computing environment. The performance of PDWA-based optimizer is evaluated with the data sets of different sizes. The achieved results show that PDWA performs with 21% improved average execution time for different sizes of data sets and varying execution nodes. In addition, the comparative results show that on average the efficiency of PDWA is 20.4% higher as compared to STORM default scheduler (SDS).

Multi‐objective grey wolf optimizer algorithm for combination of network reconfiguration and D‐STATCOM allocation in distribution system

The distribution flexible alternating current system (D-FACT) devices are being increasingly placed in the distribution system due to their several practical and environmental benefits. In this work, a novel grey wolf optimizer (GWO) algorithm as a meta-heuristic technique is applied to solve the reconfiguration problem, the installation of distribution static compensator (D-STATCOM) problem, and the combination of these two problem. The aim of this research is to diminish the total power loss and the load-balancing (LB) index of the radial distribution system. First, the index vector (IV) method is employed to suggest the candidate busses for D-STATCOM allocation. Then, the GWO algorithm is applied to establish the locations and sizes of the D-STATCOM from the candidate busses. An overall accurateness and consistency of the proposed GWO algorithm has been validated and experienced on a 33-bus, a 69-bus, and a real-time 31-bus radial distribution system, India with three kinds of load levels. In addition, the proposed method results are ideal as compared with other intellectual methods like genetic algorithm (GA) and fuzzy GA.

Security-Aware Scheduling for FlexRay-Based Real-Time Automotive Systems

FlexRay is a hybrid communication protocol tailored to the requirements of safety-critical distributed real-time automotive systems, providing support for the transmission of time-critical periodic frames in a static segment and event-triggered frames in a dynamic segment. With the development of intelligence and networking of vehicles, such systems are becoming increasingly connected to external environments; thus, security has become a pressing issue in system design. However, FlexRay-based architecture does not have direct support for secure communication. When deploying the security mechanisms on these architectures, a primary challenge is to guarantee the schedulability of systems, given the tight resource constraints and strict timing constraints. In this paper, we apply an authentication mechanism based on the delayed exposure of one-way key chains to protect the authenticity of messages on FlexRay and make a slight modification to reduce the authentication delay. On that basis, we propose a mixed integer linear programming formulation for solving the scheduling problem of FlexRay-based real-time automotive systems subject to both authentication mechanism constraints and other traditional design constraints. Experimental results demonstrate the effectiveness and efficiency of the proposed method in system design and indicate the necessity of collaborative design between security and other functionalities.

Long-term, real-time and multi-channel distributed temperature monitoring system for tunnels in cold regions

Tunnel frost damage is common in cold regions and is of increasing concern. Temperature monitoring is crucial to reveal the tunnel temperature change laws and distribution characteristics and to complete a reasonable frost prevention design. In this study, a distributed temperature monitoring system for tunnels in cold regions is designed by using A level platinum resistance temperature sensors (PT100 A) and a series of electronic integrated chips to complete a long-term, real-time and multi-channel automatic temperature test in different positions in the tunnel. The constant current source method is adopted to test the platinum resistance of PT100 A, and a high-precision resistor is inserted in the circuit to improve the test accuracy. The resistance test error can be approximately 0.011, that is equal to 0.03 °C. The test resistance results are linearly converted to temperature at a calculation interval of 1 °C due to the strong linear relationship between the platinum resistance and temperature. In addition, the sensor error is compensated for on the basis of the calibrated results of sensors at 0 °C. Therefore, the accuracy of the final temperature results can be enhanced. The monitoring system has been applied in the actual tunnel, which can provide accurate, adequate and comprehensive temperature data for the optimal design of the thermal insulation layer thickness and length.

Implementation and Comparative Analysis of k-means and Fuzzy c-means Clustering Algorithms for Tasks Allocation in Distributed Real Time System

Distributing tasks to processors in distributed real time systems is an important step for obtaining high performance. Scheduling algorithms play a vital role in achieving better performance and high throughput in heterogeneous distributed real time systems. To make the best use of the computational power available, it is essential to assign the tasks to the processor whose characteristics are most appropriate for the execution of the tasks in a distributed processing system. This study develops two algorithms for clustering the heavily-communicating tasks to reduce the inter-tasks communication costs by using k-means and fuzzy c-means clustering techniques respectively. In order to minimize the system cost and response time, an algorithm is developed for the proper allocation of formed clusters to the most suitable processor. The present algorithms are collated with problems in literature. The proposed algorithms are formulated and applied to numerous numerical examples to demonstrate their effectiveness.

A Systematic Approach on Modeling Refinement and Regression Testing of Real-Time Distributed Systems

Industry 4.0 aims at highly flexible and digitized model of industrial production. This requires vertical integration of different operations in the manufacturing process to promote reconfigurability and better collaboration between distributed components (Modularity & Integrability) and to handle growing complexity in manufacturing systems. On the other hand, the flexibility of reconfiguration leads to new challenges for the testing process (i.e Diagnosability). It has now become a priority to quality assurance team to ensure that reconfiguration did not introduce any new faults, often referred to as Regression Testing. In this paper, we present a testing framework for real-time distributed manufacturing systems to verify reconfiguration correctness and to generate tests for its implementation testing. We present a systematic modeling refinement approach where several refinements (reconfigurations) can be modelled separately from an abstract model and composed with it. We use the reconfiguration model derived by refinements to demonstrate distributed regression testing by partitioning it into a set of distributed communicating testers making model based testing for manufacturing automation systems scalable.

High speed error correction for continuous-variable quantum key distribution with multi-edge type LDPC code

Error correction is a significant step in postprocessing of continuous-variable quantum key distribution system, which is used to make two distant legitimate parties share identical corrected keys. We propose an experiment demonstration of high speed error correction with multi-edge type low-density parity check (MET-LDPC) codes based on graphic processing unit (GPU). GPU supports to calculate the messages of MET-LDPC codes simultaneously and decode multiple codewords in parallel. We optimize the memory structure of parity check matrix and the belief propagation decoding algorithm to reduce computational complexity. Our results show that GPU-based decoding algorithm greatly improves the error correction speed. For the three typical code rate, i.e., 0.1, 0.05 and 0.02, when the block length is 106 and the iteration number are 100, 150 and 200, the average error correction speed can be respectively achieved to 30.39 Mbits/s (over three times faster than previous demonstrations), 21.23 Mbits/s and 16.41 Mbits/s with 64 codewords decoding in parallel, which supports high-speed real-time continuous-variable quantum key distribution system.

Survey of Apache Storm Scheduler

The computational need of multimedia, social networking data processing is rapidly increasing as a use of an internet is increasing which demand a need for real-time distributed stream processing system. Apache Storm is a distributed real-time computation system which is open source and available free of cost. A Storm is gaining popularity day by day due to its feature like scalability, high reliability, fault-tolerance, and easy to set up and operate. The deployment of Storm topology on cluster affects the performance of system i.e. how the execution of every component of topology available on computing infrastructure can be scheduled by Storm. A Storm topology is a network of Storm components on which data is transferred and processed. But Storm like different other stream processing systems does not have smart scheduling mechanism. In this paper, a comparative study of seven different schedulers including Storm's default round-robin scheduler is presented.

Introduction to the special issue

As program chairs, we have the pleasure to introduce this special issue dedicated to the 4 th edition of REACTION, the International Workshop on Real-time Computing and Distributed Systems, that was held in Porto on December 29 th , 2016 as a co-located event to RTSS. REACTION aims at presenting contributions with a clear applied vision around, but not limited to, the challenging problems in the integration of real-time computing and distributed systems. The focus of the event is at the confluence area between distributed systems and real-time applications, that includes communication middleware, operating systems, virtualization technology, modeling or timely operation in distributed systems, among others.