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  • 1.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    A Parameter Tuning Framework for Metaheuristics Based on Design of Experiments and Artificial Neural Networks2010In: Proceeding of the International Conference on Computer Mathematics and Natural Computing 2010 / [ed] B. Brojack, WASET , 2010Conference paper (Refereed)
    Abstract [en]

    In this paper, a framework for the simplification andstandardization of metaheuristic related parameter tuning by applyinga four phase methodology, utilizing Design of Experiments andArtificial Neural Networks, is presented. Metaheuristics are multipurposeproblem solvers that are utilized on computational optimizationproblems for which no efficient problem-specific algorithmexists. Their successful application to concrete problems requires thefinding of a good initial parameter setting, which is a tedious andtime-consuming task. Recent research reveals the lack of approachwhen it comes to this so called parameter tuning process. In themajority of publications, researchers do have a weak motivation fortheir respective choices, if any. Because initial parameter settingshave a significant impact on the solutions quality, this course ofaction could lead to suboptimal experimental results, and therebya fraudulent basis for the drawing of conclusions.

  • 2.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    A parameter-tuning framework for metaheuristics based on design of experiments and artificial neural networks2010In: World Academy of Science, Engineering and Technology: An International Journal of Science, Engineering and Technology, ISSN 2010-376X, E-ISSN 2070-3740, Vol. 64, p. 213-216Article in journal (Refereed)
    Abstract [en]

    In this paper, a framework for the simplification and standardization of metaheuristic related parameter-tuning by applying a four phase methodology, utilizing Design of Experiments and Artificial Neural Networks, is presented. Metaheuristics are multipurpose problem solvers that are utilized on computational optimization problems for which no efficient problem specific algorithm exist. Their successful application to concrete problems requires the finding of a good initial parameter setting, which is a tedious and time consuming task. Recent research reveals the lack of approach when it comes to this so called parameter-tuning process. In the majority of publications, researchers do have a weak motivation for their respective choices, if any. Because initial parameter settings have a significant impact on the solutions quality, this course of action could lead to suboptimal experimental results, and thereby a fraudulent basis for the drawing of conclusions.

  • 3.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    An Adaptive, Searchable and Extendable Context Model,enabling cross-domain Context Storage, Retrieval and Reasoning: Architecture, Design, Implementation and Discussion2009Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The specification of communication standards and increased availability of sensors for mobile phones and mobile systems are responsible for a significantly increasing sensor availability in populated environments. These devices are able to measure physical parameters and make this data available via communication in sensor networks. To take advantage of the so called acquiring information for public services, other parties have to be able to receive and interpret it. Locally measured datacould be seen as a means of describing user context. For a generic processing of arbitrary context data, a model for the specification ofenvironments, users, information sources and information semantics has to be defined. Such a model would, in the optimal case, enable global domain crossing context usage and hence a broader foundation for context interpretation and integration.This thesis proposes the CII-(Context Information Integration) model for the persistence and retrieval of context information in mobile, dynamically changing, environments. It discusses the terms context and context modeling under the analysis of former publications in thefield. Further-more an architecture and prototype are presented.Live and historical data are stored and accessed by the same platform and querying processor, but are treated in an optimized fashion.Optimized retrieval for closeness in n-dimensional context-spaces is supported by a dedicated method. The implementation enables self-aware,shareable agents that are able to reason or act based upon the global context,including their own. These agents can be considered as being a part of the wholecontext, being movable and executable for all context-aware applications.By applying open source technology, a gratifying implementation of CII is feasible. The document contains a thorough discussion concerning the software design and further prototype development. The use cases at the end of the document show the flexibility and extendability of the model and its implementation as a context-base for three entirely different applications.

  • 4.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    An experimental study on robust parameter settings2010In: Proceedings of the 12th annual conference comp on Genetic and evolutionary computation, ACM Press, 2010, p. 1999-2002Conference paper (Refereed)
    Abstract [en]

    That there is no best initial parameter setting for a metaheuristicon all optimization problems is a proven fact (nofree lunch theorem). This paper studies the applicability ofso called robust parameter settings for combinatorial optimizationproblems. Design of Experiments supported parameterscreening had been carried out, analyzing a discreteParticle Swarm Optimization algorithm on three demographicallyvery dissimilar instances of the Traveling SalesmenProblem. First experimental results indicate that parametersettings produce varying performance quality forthe three instances. The robust parameter setting is outperformedin two out of three cases. The results are evensignicantly worse when considering quality/time trade-o.A methodology for problem generalization is referred to asa possible solution.

  • 5.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Automatic Instance-based Tailoring of Parameter Settings for Metaheuristics2011Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Many industrial problems in various fields, such as logistics, process management, orproduct design, can be formalized and expressed as optimization problems in order tomake them solvable by optimization algorithms. However, solvers that guarantee thefinding of optimal solutions (complete) can in practice be unacceptably slow. Thisis one of the reasons why approximative (incomplete) algorithms, producing near-optimal solutions under restrictions (most dominant time), are of vital importance.

    Those approximative algorithms go under the umbrella term metaheuristics, each of which is more or less suitable for particular optimization problems. These algorithmsare flexible solvers that only require a representation for solutions and an evaluation function when searching the solution space for optimality.What all metaheuristics have in common is that their search is guided by certain control parameters. These parameters have to be manually set by the user andare generally problem and interdependent: A setting producing near-optimal resultsfor one problem is likely to perform worse for another. Automating the parameter setting process in a sophisticated, computationally cheap, and statistically reliable way is challenging and a significant amount of attention in the artificial intelligence and operational research communities. This activity has not yet produced any major breakthroughs concerning the utilization of problem instance knowledge or the employment of dynamic algorithm configuration.

    The thesis promotes automated parameter optimization with reference to the inverse impact of problem instance diversity on the quality of parameter settings with respect to instance-algorithm pairs. It further emphasizes the similarities between static and dynamic algorithm configuration and related problems in order to show how they relate to each other. It further proposes two frameworks for instance-based algorithm configuration and evaluates the experimental results. The first is a recommender system for static configurations, combining experimental design and machine learning. The second framework can be used for static or dynamic configuration,taking advantage of the iterative nature of population-based algorithms, which is a very important sub-class of metaheuristics.

    A straightforward implementation of framework one did not result in the expected improvements, supposedly because of pre-stabilization issues. The second approach shows competitive results in the scenario when compared to a state-of-the-art model-free configurator, reducing the training time by in excess of two orders of magnitude.

  • 6.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    End-to-End Quality of Service Guarantees for Wireless Sensor Networks2015Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Wireless sensor networks have been a key driver of innovation and societal progressover the last three decades. They allow for simplicity because they eliminate ca-bling complexity while increasing the flexibility of extending or adjusting networksto changing demands. Wireless sensor networks are a powerful means of fillingthe technological gap for ever-larger industrial sites of growing interconnection andbroader integration. Nonetheless, the management of wireless networks is difficultin situations wherein communication requires application-specific, network-widequality of service guarantees. A minimum end-to-end reliability for packet arrivalclose to 100% in combination with latency bounds in the millisecond range must befulfilled in many mission-critical applications.The problem addressed in this thesis is the demand for algorithmic support forend-to-end quality of service guarantees in mission-critical wireless sensor networks.Wireless sensors have traditionally been used to collect non-critical periodic read-ings; however, the intriguing advantages of wireless technologies in terms of theirflexibility and cost effectiveness justify the exploration of their potential for controland mission-critical applications, subject to the requirements of ultra-reliable com-munication, in harsh and dynamically changing environments such as manufactur-ing factories, oil rigs, and power plants.This thesis provides three main contributions in the scope of wireless sensor net-works. First, it presents a scalable algorithm that guarantees end-to-end reliabilitythrough scheduling. Second, it presents a cross-layer optimization/configurationframework that can be customized to meet multiple end-to-end quality of servicecriteria simultaneously. Third, it proposes an extension of the framework used toenable service differentiation and priority handling. Adaptive, scalable, and fast al-gorithms are proposed. The cross-layer framework is based on a genetic algorithmthat assesses the quality of service of the network as a whole and integrates the phys-ical layer, medium access control layer, network layer, and transport layer.Algorithm performance and scalability are verified through numerous simula-tions on hundreds of convergecast topologies by comparing the proposed algorithmswith other recently proposed algorithms for ensuring reliable packet delivery. Theresults show that the proposed SchedEx scheduling algorithm is both significantlymore scalable and better performing than are the competing slot-based schedulingalgorithms. The integrated solving of routing and scheduling using a genetic al-vvigorithm further improves on the original results by more than 30% in terms of la-tency. The proposed framework provides live graphical feedback about potentialbottlenecks and may be used for analysis and debugging as well as the planning ofgreen-field networks.SchedEx is found to be an adaptive, scalable, and fast algorithm that is capa-ble of ensuring the end-to-end reliability of packet arrival throughout the network.SchedEx-GA successfully identifies network configurations, thus integrating the rout-ing and scheduling decisions for networks with diverse traffic priority levels. Fur-ther, directions for future research are presented, including the extension of simula-tions to experimental work and the consideration of alternative network topologies.

  • 7.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Finding Optimal Size TDMA Schedules using Integer ProgrammingManuscript (preprint) (Other academic)
    Abstract [en]

    The problem of finding a shortest TDMA is formally described as anInteger Program (IP). A brief user manual explains how the attached implementation can be used to find an optimal size TDMA for any givenWSN and routing table, fulfilling the validity criteria.

  • 8.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    InPUT: The Intelligent Parameter Utilization Tool2012In: GECCO Companion 12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion, New York, NY, USA: ACM Press, 2012, p. 149-156Conference paper (Refereed)
    Abstract [en]

    Computer experiments are part of the daily business formany researchers within the area of computational intelligence. However, there is no standard for either human orcomputer readable documentation of computer experiments.Such a standard could considerably improve the collaboration between experimental researchers, given it is intuitiveto use. In response to this deficiency the Intelligent Param-eter Utilization Tool ( InPUT ) is introduced. InPUT offers ageneral and programming language independent format forthe definition of parameters and their ranges. It providesservices to simplify the implementation of algorithms andcan be used as a substitute for input mechanisms of existing frameworks. InPUT reduces code-complexity and increases the reusability of algorithm designs as well as the reproducibility of experiments. InPUT is available as open-source for Java and this will soon also be extended to C++, two ofthe predominant languages of choice for the development ofevolutionary algorithms.

  • 9.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Iteration-wise parameter learning2011In: 2011 IEEE Congress of Evolutionary Computation, CEC 2011, New Orleans, LA: IEEE conference proceedings, 2011, p. 455-462Conference paper (Refereed)
    Abstract [en]

    Adjusting the control parameters of population-based algorithms is a means for improving the quality of these algorithms' result when solving optimization problems. The difficulty lies in determining when to assign individual values to specific parameters during the run. This paper investigates the possible implications of a generic and computationally cheap approach towards parameter analysis for population-based algorithms. The effect of parameter settings was analyzed in the application of a genetic algorithm to a set of traveling salesman problem instances. The findings suggest that statistics about local changes of a search from iteration i to iteration i + 1 can provide valuable insight into the sensitivity of the algorithm to parameter values. A simple method for choosing static parameter settings has been shown to recommend settings competitive to those extracted from a state-of-the-art parameter tuner, paramlLS, with major time and setup advantages.

  • 10.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Recent Development in Automatic Parameter Tuning for Metaheuristics2010In: Proceedings of the 19th Annual Conference of Doctoral Students - WDS 2010 / [ed] J. Safrankova and J. Pavlu, 2010, p. -10Conference paper (Refereed)
    Abstract [en]

    Parameter tuning is an optimization problem with the objective of finding good static pa-rameter settings before the execution of a metaheuristic on a problem at hand. The requirementof tuning multiple control parameters, combined with the stochastic nature of the algorithms,make parameter tuning a non-trivial problem. To make things worse, one parameter vector allowing the algorithm to solve all optimization problems to the best of its potential is verifiable non-existent, as can be inferred from the no free lunch theorem of optimization. Manual tuning can be conducted, with the drawback of being very time consuming and failure prone. Hence, means for automated parameter tuning are required. This paper serves as an overview about recent work within the field of automated parameter tuning.

  • 11.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Zhang, Tinting
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Challenges for the use of data aggregation in industrial Wireless Sensor Networks2015In: IEEE International Conference on Automation Science and Engineering, IEEE Computer Society, 2015, p. 138-144Conference paper (Refereed)
    Abstract [en]

    The provision of quality of service for Wireless Sensor Networks is more relevant than ever now where wireless solutions with their flexibility advantages are considered for the extension/substitution of wired networks for a multitude of industrial applications. Scheduling algorithms that give end-to-end guarantees for both reliability and latency exist, but according to recent investigations is the achieved quality of service insufficient for most control applications. Data aggregation is an effective tool to significantly improve on end-to-end contention and energy efficiency compared to single packet transmissions. In practice, though, it is not extensively used for process data processing on the MAC layer. In this paper, we outline the challenges for the use of data aggregation in Industrial Wireless Sensor Networks. We further extend SchedEx, a reliability-aware scheduling algorithm extension, for packet aggregation. Our simulations for scheduling algorithms from the literature show its great potential for industrial applications. Features for the inclusion of data aggregation into industrial standards such as WirelessHART are suggested, and remaining open issues for future work are presented and discussed.

  • 12.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Larsson, Aron
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Kanter, Theo
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Walters, Jamie
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    An Object-Oriented Model in Support of Context-Aware Mobile Applications2010Conference paper (Refereed)
    Abstract [en]

    Intelligent and context-aware mobile services require usersand applications to share information and utilize services from remotelocations. Thus, context information from the users must be structuredand be accessible to applications running in end-devices. In response tothis challenge, we present a shared object-oriented meta model for a persistentagent environment. The approach enables agents to be contextawarefacilitating the creation of ambient intelligence demonstrated bya sensor-based scenario. The agents are context-aware as agent actionsare based upon sensor information, social information, and the behaviorof co-agents.

  • 13.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Tingting, Zhang
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Latency Improvement Strategies for Reliability-Aware Scheduling in Industrial Wireless Sensor Networks2015In: International Journal of Distributed Sensor Networks, ISSN 1550-1329, E-ISSN 1550-1477, article id 178368Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose novel strategiesfor end-to-end reliability-aware scheduling in Industrial WirelessSensor Networks (IWSN). Because of stringent reliability requirements inindustrial applications where missed packets may have disastrous or lethalconsequences, all IWSN communication standards are based on TimeDivision Multiple Access (TDMA), allowing for deterministic channel access onthe MAC layer. We therefore extend an existing generic and scalablereliability-aware scheduling approach by name SchedEx. SchedEx has proven toquickly produce TDMA schedules that guarantee auser-defined end-to-end reliability level $\underline\rho$ for all multi-hopcommunication in a WSN. Moreover, SchedEx executes orders of magnitude fasterthan recent algorithms in the literature while producing schedules withcompetitive latencies.We generalize the original problem formulation from single-channel tomulti-channel scheduling and propose a scalable integration into the existingSchedEx approach.We further introduce a novel optimal bound that produces TDMAschedules with latencies around 20\% shorter than the original SchedExalgorithm. Combining the novel strategies with multiple sinks, multiplechannels, and the introduced optimal bound, we could through simulationsverify latency improvements by almost an order of magnitude, reducingthe TDMA super-frame execution times from tens of seconds to seconds only, whichallows for a utilization of SchedEx for many time-critical control applications.

  • 14.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Zhang, Tingting
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    A Reliability-Aware Cross-layer Optimization Framework for Wireless Sensor Networks.Manuscript (preprint) (Other academic)
    Abstract [en]

    One of the biggest obstacles for a broad deploymentof Wireless Sensor Networks for industrial applications is the dif-ficulty to ensure end-to-end reliability guarantees while providingas tight latency guarantees as possible. In response, we proposea novel centralized optimization framework for Wireless SensorNetworks that identifies TDMA schedules and routing combi-nations in an integrated manner. The framework is shown toguarantee end-to-end reliability for all events send in a schedulingframe while minimizing the delay of all packet transmissions. Itcan further be applied using alternative Quality of Service ob-jectives and constraints including energy efficiency and fairness.We consider network settings with multiple channels, multiplesinks, and stringent reliability constraints for data collectingflows. We compare the results to those achieved by the onlyscalable reliability-aware TDMA scheduling algorithm to ourknowledge, SchedEx, which conducts scheduling only. By makingrouting part of the problem and by introducing the conceptof source-aware routing, we achieve latency improvements forall topologies, with a notable average improvement of up to31percent.

  • 15.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Zhang, Tingting
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    End-to-End Reliability-aware Scheduling for Wireless Sensor Networks2016In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 12, no 2, p. 758-767Article in journal (Refereed)
    Abstract [en]

    Wireless Sensor Networks (WSN) are gaining popularity as a flexible and economical alternative to field-bus installations for monitoring and control applications. For missioncritical applications, communication networks must provide endto- end reliability guarantees, posing substantial challenges for WSN. Reliability can be improved by redundancy, and is often addressed on the MAC layer by re-submission of lost packets, usually applying slotted scheduling. Recently, researchers have proposed a strategy to optimally improve the reliability of a given schedule by repeating the most rewarding slots in a schedule incrementally until a deadline. This Incrementer can be used with most scheduling algorithms but has scalability issues which narrows its usability to offline calculations of schedules, for networks that are rather static. In this paper, we introduce SchedEx, a generic heuristic scheduling algorithm extension which guarantees a user-defined end-to-end reliability. SchedEx produces competitive schedules to the existing approach, and it does that consistently more than an order of magnitude faster. The harsher the end-to-end reliability demand of the network, the better SchedEx performs compared to the Incrementer. We further show that SchedEx has a more evenly distributed improvement impact on the scheduling algorithms, whereas the Incrementer favors schedules created by certain scheduling algorithms.

  • 16.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Zhang, Tingting
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    QoS Assessment for Mission-critical Wireless Sensor Network Applications2013In: Proceedings - Conference on Local Computer Networks, LCN / [ed] Matthias Wählisch, IEEE Xplore , 2013, p. 663-666Conference paper (Refereed)
    Abstract [en]

    Wireless sensor networks (WSN) must ensure worst-case end-to-end delay and reliability guarantees for mission-critical applications.TDMA-based scheduling offers delay guarantees, thus it is used in industrial monitoring and automation. We propose to evolve pairs of TDMA schedule and routing-tree in a cross-layer in order to fulfill multiple conflicting QoS requirements,exemplified by latency and reliability.The genetic algorithm we utilize can be used as an analytical tool for both the feasibility and expected QoS in production. Near-optimal cross-layer solutions are found within seconds and can be directly enforced into the network.

  • 17.
    Dobslaw, Felix
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Zhang, Tingting
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    QoS-Aware Cross-layer Configuration for Industrial Wireless Sensor Networks2016In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 12, no 5, p. 1679-1691, article id 7485858Article in journal (Refereed)
    Abstract [en]

    In many applications of Industrial Sensor Networks, stringentreliability and maximum delay constraints paired with priority demands ona sensor-basis are present. These QoS requirements pose tough challenges forIndustrial Wireless Sensor Networks that are deployed to an ever largerextent due to their flexibility and extendibility.In this paper, we introduce an integrated cross-layer framework, SchedEx-GA, spanning MAC layer and networklayer. SchedEx-GA attempts to identify a network configuration that fulfills all application-specific process requirements over a topology including the sensorpublish rates, maximum acceptable delay, service differentiation, and eventtransport reliabilities. The network configuration comprisesthe decision for routing, as well as scheduling.

    For many of the evaluatedtopologies it is not possible to find a valid configuration due to the physicalconditions of the environment. We therefore introduce a converging algorithm on top of the frameworkwhich configures a given topology by additional sink positioning in order tobuild a backbone with the gateway that guaranteesthe application specific constraints.The results show that, in order to guarantee a high end-to-end reliability of 99.999% for all flows in a network containing emergency, control loop, andmonitoring traffic, a backbone with multiple sinks is often required for thetested topologies. Additional features, such as multi-channel utilization andaggregation, though, can substantially reduce the demand for required sinks.In its present version, the framework is used for centralized control, butwith the potential to be extended for de-centralized control in future work.

  • 18.
    Jonsson, Patrik
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
    Decision support system for variable speed regulation2012Conference paper (Refereed)
    Abstract [en]

    The problem of recommending a suitable speed limit for roads is important for road authorities in order to increase traffic safety. Nowadays, these speed limits can be given more dynamically, with digital speed regulation signs. The challenge here is input from the environment, in combination with probabilities for certain events. Here we present a decision support model based on a dynamic Bayesian network. The purpose of this model is to predict the appropriate speed on the basis of weather data, traffic density and road maintenance activities. The dynamic Bayesian network principle of using uncertainty for the involved variables gives a possibility to model the real conditions. This model shows that it is possible to develop automated decision support systems for variable speed regulation.

  • 19.
    Jonsson, Patrik
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Thörnberg, Benny
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Electronics Design.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    Vaa, Torgeir
    Road Condition Imaging: Model Development2015Conference paper (Refereed)
    Abstract [en]

    It is important to classify road conditions to plan winter road maintenance, carry out proper actions and issue warnings to road users. Existing sensor systems only cover parts of the road surface and manual observations can vary depending on those who classify the observations. One challenge is to classify road conditions with automatic monitoring systems. This paper presents a model based on data from winter 2013-2014, retrieved from two installations in Sweden and Norway. To address that challenge an innovative and cost effective road condition imaging system, capable of classifying individual pixels of an image as dry, wet, icy or snowy, is evaluated. The system uses a near infra-red image detector and optical wavelength filters. By combining data from images taken from different wavelength filters it is possible to determine the road status by using multiclass classifiers. One classifier for each road condition was developed, which implies that a pixel can be classified to two or more road conditions at the same time. This multiclass problem is solved by developing a Bayesian Network that uses road weather information system data for the calculation of the probabilities for different road conditions.

  • 20.
    Shen, Wei
    et al.
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Zhang, Tingting
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems.
    Gidlund, Mikael
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Information and Communication systems. ABB Corp Res, Vasterås, Sweden.
    Dobslaw, Felix
    Mid Sweden University, Faculty of Science, Technology and Media, Department of Computer and System science.
    SAS-TDMA: A Source Aware Scheduling Algorithm for Real-Time Communication in Industrial Wireless Sensor Networks2013In: Wireless networks, ISSN 1022-0038, E-ISSN 1572-8196, Vol. 19, no 6, p. 1155-1170Article in journal (Refereed)
    Abstract [en]

    Scheduling algorithms play an importantrole for TDMA-based wireless sensor networks. ExistingTDMA scheduling algorithms address a multitude of objectives.However, their adaptation to the dynamics of a realistic wirelesssensor network has not been investigated in a satisfactorymanner. This is a key issue considering the challenges withinindustrial applications for wireless sensor networks, given thetime-constraints and harsh environments.In response to those challenges, we present SAS-TDMA, asource-aware scheduling algorithm. It is a cross-layer solutionwhich adapts itself to network dynamics. It realizes a tradeoffbetween scheduling length and its configurational overheadincurred by rapid responses to routes changes. We implementeda TDMA stack instead of the default CSMA stack and introduceda cross-layer for scheduling in TOSSIM, the TinyOS simulator.Numerical results show that SAS-TDMA improves the qualityof service for the entire network. It achieves significant improvementsfor realistic dynamic wireless sensor networks whencompared to existing scheduling algorithms with the aim tominimize latency for real-time communication.

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