455 research outputs found

    Scheduling & routing time-triggered traffic in time-sensitive networks

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    The application of recent advances in computing, cognitive and networking technologies in manufacturing has triggered the so-called fourth industrial revolution, also referred to as Industry 4.0. Smart and flexible manufacturing systems are being conceived as a part of the Industry 4.0 initiative to meet the challenging requirements of the modern day manufacturers, e.g., production batch sizes of one. The information and communication technologies (ICT) infrastructure in such smart factories is expected to host heterogeneous applications ranging from the time-sensitive cyber-physical systems regulating physical processes in the manufacturing shopfloor to the soft real-time analytics applications predicting anomalies in the assembly line. Given the diverse demands of the applications, a single converged network providing different levels of communication guarantees to the applications based on their requirements is desired. Ethernet, on account of its ubiquity and its steadily growing performance along with shrinking costs, has emerged as a popular choice as a converged network. However, Ethernet networks, primarily designed for best-effort communication services, cannot provide strict guarantees like bounded end-to-end latency and jitter for real-time traffic without additional enhancements. Two major standardization bodies, viz., the IEEE Time-sensitive Networking (TSN) Task Group (TG) and the IETF Deterministic Networking (DetNets) Working Group are striving towards equipping Ethernet networks with mechanisms that would enable it to support different classes of real-time traffic. In this thesis, we focus on handling the time-triggered traffic (primarily periodic in nature) stemming from the hard real-time cyber-physical systems embedded in the manufacturing shopfloor over Ethernet networks. The basic approach for this is to schedule the transmissions of the time-triggered data streams appropriately through the network and ensure that the allocated schedules are adhered with. This approach leverages the possibility to precisely synchronize the clocks of the network participants, i.e., end systems and switches, using time synchronization protocols like the IEEE 1588 Precision Time Protocol (PTP). Based on the capabilities of the network participants, the responsibility of enforcing these schedules can be distributed. An important point to note is that the network utilization with respect to the time-triggered data streams depends on the computed schedules. Furthermore, the routing of the time-triggered data streams also influences the computed transmission schedules, and thus, affects the network utilization. The question however remains as to how to compute transmission schedules for time-triggered data streams along with their routes so that an optimal network utilization can be achieved. We explore, in this thesis, the scheduling and routing problems with respect to the time-triggered data streams in Ethernet networks. The recently published IEEE 802.1Qbv standard from the TSN-TG provides programmable gating mechanisms for the switches enabling them to schedule transmissions. Meanwhile, the extensions specified in the IEEE 802.1Qca standard or the primitives provided by OpenFlow, the popular southbound software-defined networking (SDN) protocol, can be used for gaining an explicit control over the routing of the data streams. Using these mechanisms, the responsibility of enforcing transmission schedules can be taken over by the end systems as well as the switches in the network. Alternatively, the scheduling can be enforced only by the end systems or only by the switches. Furthermore, routing alone can also be used to isolate time-triggered data streams, and thus, bound the latency and jitter experienced by the data streams in absence of synchronized clocks in the network. For each of the aforementioned cases, we formulate the scheduling and routing problem using Integer Linear Programming (ILP) for static as well as dynamic scenarios. The static scenario deals with the computation of schedules and routes for time-triggered data streams with a priori knowledge of their specifications. Here, we focus on computing schedules and routes that are optimal with respect to the network utilization. Given that the scheduling problems in the static setting have a high time-complexity, we also present efficient heuristics to approximate the optimal solution. With the dynamic scheduling problem, we address the modifications to the computed transmission schedules for adding further or removing already scheduled time-triggered data streams. Here, the focus lies on reducing the runtime of the scheduling and routing algorithms, and thus, have lower set-up times for adding new data streams into the network

    Ant Colony Heuristic for Mapping and Scheduling Tasks and Communications on Heterogeneous Embedded Systems

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    To exploit the power of modern heterogeneous multiprocessor embedded platforms on partitioned applications, the designer usually needs to efficiently map and schedule all the tasks and the communications of the application, respecting the constraints imposed by the target architecture. Since the problem is heavily constrained, common methods used to explore such design space usually fail, obtaining low-quality solutions. In this paper, we propose an ant colony optimization (ACO) heuristic that, given a model of the target architecture and the application, efficiently executes both scheduling and mapping to optimize the application performance. We compare our approach with several other heuristics, including simulated annealing, tabu search, and genetic algorithms, on the performance to reach the optimum value and on the potential to explore the design space. We show that our approach obtains better results than other heuristics by at least 16% on average, despite an overhead in execution time. Finally, we validate the approach by scheduling and mapping a JPEG encoder on a realistic target architecture

    04231 Abstracts Collection -- Scheduling in Computer and Manufacturing Systems

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    During 31.05.-04.06.04, the Dagstuhl Seminar 04231 "Scheduling in Computer and Manufacturing Systems" was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available

    Improved Mixed-Integer Programming Models for Multiprocessor Scheduling with Communication Delays

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    We revise existing and introduce new mixed-integer programming models for the Multiprocessor Scheduling Problem with Communication Delays. At first, we show how to provably reduce the number of product variables necessary to explicitly linearize the so-called packing formulation that contains bilinear terms. Then, we reveal that the feasible region of almost all existing formulations contains redundant solutions and formulate new constraints in order to exclude these. At the same time, by exploiting further structural properties, the models are improved concerning their size, strength, and modeling complexity. The discussion of these improvements leads to new much more compact formulations which are then experimentally compared with each other and with other formulations from the literature. We set up a realistic scenario with a preprocessing of the task graphs, delivering the gained information equally to all the tested models and evaluate not only running times but also the obtained lower and upper bounds on the makespan objective for unsolved instances of a large scale benchmark set

    Optimization of Military Convoy Routing

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    Motoriseeritud rännakukolonnide optimeerimine on matemaatilise optimeerimise probleem, milles püütakse leida optimaalset marsruutimislahendust ja vastavat ajakava samaaegsetelt liikuvatele rännakukolonnidele. Käesolevas töös luuakse valik erinevatel optimeerimistehnikatel põhinevaid meetodeid, mida testides püütakse leida parimat Eesti oludele vastavat rännakukolonnide marsruutimise optimeerimismeetodit. Häid tulemusi saavutati kasutades osalise täisarvulise planeerimise mudelit koos heuristiliste täiendustega, rakendades jaga-ja-piira tehnikal põhinevat täpset algoritmi, kui ka kasutades fikseeritud järjestusega marsruutimislahendust. Lisaks töötati bakalaureusetöö koostamise käigus välja optimeerimismeetodeid kasutav rakendus, mille abil on võimalik võrrelda erinevate meetodite käitumist ja omadusi, esitada arvutuste tulemusena leitud teekondi ja ajagraafikuid ning animeerida Eesti kaardil rännakukolonnide liikumist. Töö tulemusena võib väita, et matemaatilise optimeerimise meetodid on sobivad päriseluliste rännakukolonnide optimeerimisprobleemide kiireks ja kvaliteetseks lahendamiseks ja et neid meetodeid kasutades on võimalik parandada rännakukolonnide kavandamisel tehtavate planeerimisotsuste kvaliteeti.Convoy movement problem is a mathematical optimization problem which tries to find optimal routing and scheduling solution for concurrent military convoy movements. In this thesis several optimization methodologies are designed and tested to find best suited algorithm for solving practical convoy routing instances in Estonia. Encouraging results are obtained by using a mixed integer programming model together with simple heuristics, by creating an exact branch-and-bound methodology and by developing fixed-order based routing approach. Bachelor’s thesis also provides a complementary application to compare qualities of designed methods, to present calculated routes and schedules and to display convoy movement animations on the map of Estonia. Thesis illustrates that methods of mathematical optimization can be used to solve realworld instances of convoy movement problem fast and with quality results and hence improve decisionmaking in operational convoy planning practice
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