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  • 1. Berglund, Åsa
    et al.
    Bjurling, Björn
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Dantas, Ramide
    Engberg, Susanne
    Giambiagi, Pablo
    RISE, Swedish ICT, SICS.
    Ohlman, Börje
    Towards goal-based autonomic networking2009In: Proceedings of the Distributed Autonomous Network Magagement Systems Workshop (DANMS 2008), November 2008, 2009, 1, , p. 5Conference paper (Refereed)
    Abstract [en]

    The ability to quickly deploy and efficiently manage services is critical to the telecommunications industry. Currently, services are designed and managed by different teams with expertise over a wide range of concerns, from high-level business to low level network aspects. Not only is this approach expensive in terms of time and resources, but it also has problems to scale up to new outsourcing and/or multi-vendor models, where subsystems and teams belong to different organizations. We endorse the idea, upheld among others in the autonomic computing community, that the network and system components involved in the provision of a service must be crafted to facilitate their management. Furthermore, they should help bridge the gap between network and business concerns. In this paper, we sketch an approach based on early work on the hierarchical organization of autonomic entities that possibly belong to different organizations. An autonomic entity governs over other autonomic entities by defining their goals. Thus, it is up to each autonomic entity to decide its line of actions in order to fulfill its goals, and the governing entity needs not know about the internals of its subordinates. We illustrate the approach with a simple but still rich example of a telecom service.

    Download full text (pdf)
    fulltext
  • 2.
    Bjurling, Björn
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    A Labelled Deductive System for Reasoning about Random Experiments2006Doctoral thesis, monograph (Other academic)
  • 3.
    Bjurling, Björn
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Contracts for Resources in Crisis Management2010Conference paper (Refereed)
  • 4.
    Bjurling, Björn
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Aronsson, Martin
    RISE - Research Institutes of Sweden, ICT, SICS.
    DOIT WP4 Final Report on Planning and Optimization2018Report (Other academic)
    Download full text (pdf)
    fulltext
  • 5.
    Bjurling, Björn
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Giambiagi, Pablo
    RISE, Swedish ICT, SICS.
    Contracts for controlling business processes in dynamic environments2008Conference paper (Refereed)
  • 6.
    Bjurling, Björn
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Hansen, Preben
    RISE, Swedish ICT, SICS.
    Contracts for Information Sharing in Collaborative Networks2010Conference paper (Refereed)
  • 7.
    Bjurling, Björn
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Kreuger, Per
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Marsh, Ian
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Data Readiness for BADA: BADA main study 1, FFI/Vinnova grant 2015-006772017Report (Other academic)
    Download full text (pdf)
    fulltext
  • 8.
    Bjurling, Björn
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Rasmusson, Lars
    RISE, Swedish ICT, SICS, Computer Systems Laboratory.
    Johansson, Ulf M
    Qualitative policies for bandwidth priorities in ad-hoc networks2008In: Proc. IEEE 27th Conference on Computer Communications, 2008, 1Conference paper (Refereed)
  • 9.
    Bjurling, Björn
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Steinert, Rebecca
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Gillblad, Daniel
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Translation of Probabilistic QoS in a Decentralized Hierarchical Setting2011Conference paper (Refereed)
  • 10.
    Bjurling, Björn
    et al.
    RISE Research Institutes of Sweden, Digital Systems, Data Science.
    Thore, Andreas
    RISE Research Institutes of Sweden, Digital Systems, Industrial Systems.
    Riad, Stella
    RISE Research Institutes of Sweden, Digital Systems, Data Science.
    Foreign Information Manipulation & Interference: A Large Language Model Perspective2024Report (Other academic)
    Abstract [en]

    This report focus on the intersection ofForeign Information Manipulation andInterference and Large Language Models.The aim is to give a non-technicalcomprehensive understanding of howweaknesses in the language models canbe used for creating malicious content tobe used in FIMI.

    Download full text (pdf)
    fulltext
  • 11. Chong, May Yee
    et al.
    Bjurling, Björn
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Dantas, Ramide
    Kamienski, Carlos
    Ohlman, Börje
    Goal-based service creation using autonomic entities2009Conference paper (Refereed)
    Abstract [en]

    This paper presents an approach for facilitating the setting-up and management of new multi-organizational telecom services. We are addressing factors that currently impede the development of new complex telecom services. One factor is the gap between high-level business goals and low-level network management policies making it hard for business managers to quickly implement new business ideas. A second factor, due to the trends towards outsourcing and multi-organizational structures, is the increasing complexity of the services which leads to high demands on the management environments. These factors translate into high costs and long time-to-market for the introduction of new complex telecom services. As a suggestion for a solution to these issues, we propose a goal-based approach towards self-management of complex telecom services. In our suggestion lies a new breed of network devices called Autonomic Entities which should be able both to orchestrate services fulfilling given goals, and to refine and combine goals for the purpose of self-management. This paper focuses on how Autonomic Entities can be combined via a goal combining method for the creation of new services. Our approach is illustrated with examples and an application to a scenario.

  • 12.
    Holst, Anders
    et al.
    RISE, Swedish ICT, SICS.
    Bjurling, Björn
    RISE, Swedish ICT, SICS.
    A bayesian parametric statistical anomaly detection method for finding trends and patterns in criminal behavior2013In: Proceedings - 2013 European Intelligence and Security Informatics Conference, EISIC 2013, 2013, p. 83-88Conference paper (Refereed)
    Abstract [en]

    In this paper we describe how Bayesian Principal Anomaly Detection (BPAD) can be used for detecting long and short term trends and anomalies in geographically tagged alarm data. We elaborate on how the detection of such deviations can be used for high-lighting suspected criminal behavior and activities. BPAD has previously been successively deployed and evaluated in several similar domains, including Maritime Domain Awareness, Train Fleet Maintenance, and Alarm filtering. Similar as for those applications, we argue in the paper that the deployment of BPAD in area of crime monitoring potentially can improve the situation awareness of criminal activities, by providing automatic detection of suspicious behaviors, and uncovering large scale patterns.

  • 13.
    Holst, Anders
    et al.
    RISE, Swedish ICT, SICS.
    Bjurling, Björn
    RISE, Swedish ICT, SICS.
    Ekman, Jan
    RISE, Swedish ICT, SICS.
    Rudström, Åsa
    RISE, Swedish ICT, SICS.
    Wallenius, Klas
    Saab, Sweden.
    Björkman, Mats
    Saab, Sweden.
    Fooladvandi, Farzad
    Saab, Sweden.
    Laxhammar, Rikard
    Saab, Sweden.
    Trönninger, J.
    Saab, Sweden.
    A joint statistical and symbolic anomaly detection system: Increasing performance in maritime surveillance2012In: 15th International Conference on Information Fusion, FUSION 2012, 2012, p. 1919-1926, article id 6290535Conference paper (Refereed)
    Abstract [en]

    The need for improving the capability to detect illegal or hazardous activities and yet reducing the workload of operators involved in various surveillance tasks calls for research on more capable automatic tools. To maximize their performance, these tools should be able to combine automatic capturing of normal behavior from data with domain knowledge in the form of human descriptions. In a proposed Joint Statistical and Symbolic Anomaly Detection System, statistical and symbolic methods are tightly integrated in order to detect the majority of critical events in the situation while minimizing unwanted alerts. We exemplify the proposed system in the domain of maritime surveillance.

  • 14.
    Olsson, Tomas
    et al.
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Bjurling, Björn
    RISE, Swedish ICT, SICS, Decisions, Networks and Analytics lab.
    Chong, May Yee
    Ohlman, Börje
    Goal Refinement for Automated Service Discovery2011Conference paper (Refereed)
    Abstract [en]

    An important prerequisite for service composition is a versatile and efficient service discovery mechanism. The trends in service computing currently point toward a veritable explosion in the number of services that are or will become available as components in compositions of new services—Cloud Computing and the ’Internet of Things’ are just two examples of such new trends. We hypothesize that it will become critical to be able to filter the discovered services with respect to pre- and postconditions, as well as other semantic aspects such as relevance. We have studied the use of goals as a means for describing semantic aspects of services (e.g., their effects). By using goals, services can be described on any arbitrary and useful level of abstraction. By a goal refinement algorithm, goals can be used not only for describing services, but also for improving the performance of service discovery. In this paper, we describe the goal refinement algorithm and our approach to incorporating it into our service discovery machinery.

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