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| 2. |
- Eker, Johan, et al.
(författare)
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A Nonlinear Observer for the Inverted Pendulum
- 1996
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Konferensbidrag (refereegranskat)abstract
- This paper deals with the design of a nonlinear observer for the inverted pendulum. The observer uses the standard structure of the linear observer with the linear model replaced by a nonlinear model. Nominal observer gains are determined from a linearised model. This model is also used to find a compromise between robustness and performance. The stability of the observer is then discussed and conditions for the stability of the observer are given. The results are illustrated by simulation and experiments on a real pendulum
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| 3. |
- Heimerson, Albin, et al.
(författare)
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Automatic Differentiation over Fluid Models for Holistic Load Balancing
- 2022
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Ingår i: 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C). - 9781665451420 ; , s. 13-18
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Konferensbidrag (refereegranskat)abstract
- Microservice applications consist of a set of smaller services interacting in a graph structure to deliver the full application. Jobs will traverse this graph in different paths, both depending on the type of job, but also on the current load of different service replicas. Different paths will incur different scenario-specific costs, dependent on, e.g., deployment and the underlying cloud system. In this paper, we demonstrate how automatic differentiation over data-driven fluid models can be used to optimize a running microservice application, by designing a load balancer that minimizes some holistic cost function under response time percentile constraints. The cost function is based on performance metrics from a fluid model retrieved through logs from the application. The gradient of this cost, with respect to the load balancing parameters, is calculated via automatic differentiation. This enables parameter updates, using e.g. gradient descent, that steers the application towards a setting of less cost. In an experimental evaluation on a small microservice application running on Ericsson Research Datacenter, it is shown that the method can quickly step towards optimal values while supporting complicated cost functions such as solutions to a system of ordinary differential equations.
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| 4. |
- Tärneberg, William, et al.
(författare)
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Dynamic application placement in the Mobile Cloud Network
- 2017
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Ingår i: Future generations computer systems. - : Elsevier BV. - 0167-739X .- 1872-7115. ; 70, s. 163-177
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Tidskriftsartikel (refereegranskat)abstract
- To meet the challenges of consistent performance, low communication latency, and a high degree of user mobility, cloud and Telecom infrastructure vendors and operators foresee a Mobile Cloud Network that incorporates public cloud infrastructures with cloud augmented Telecom nodes in forthcoming mobile access networks. A Mobile Cloud Network is composed of distributed cost- and capacityheterogeneous resources that host applications that in turn are subject to a spatially and quantitatively rapidly changing demand. Such an infrastructure requires a holistic management approach that ensures that the resident applications’ performance requirements are met while sustainably supported by the underlying infrastructure. The contribution of this paper is three-fold. Firstly, this paper contributes with a model that captures the cost- and capacity-heterogeneity of a Mobile Cloud Network infrastructure. The model bridges the Mobile Edge Computing and Distributed Cloud paradigms by modelling multiple tiers of resources across the network and serves not just mobile devices but any client beyond and within the network. A set of resource management challenges is presented based on this model. Secondly, an algorithm that holistically and optimally solves these challenges is proposed. The algorithm is formulated as an application placement method that incorporates aspects of network link capacity, desired user latency and user mobility, as well as data centre resource utilisation and server provisioning costs. Thirdly, to address scalability, a tractable locally optimal algorithm is presented. The evaluation demonstrates that the placement algorithm significantly improves latency, resource utilisation skewness while minimising the operational cost of the system. Additionally, the proposed model and evaluation method demonstrate the viability of dynamic resource management of the Mobile Cloud Network and the need for accommodating rapidly mobile demand in a holistic manner.
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| 5. |
- Balador, Ali, et al.
(författare)
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AORTA: Advanced Offloading for Real-time Applications
- 2023
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Konferensbidrag (refereegranskat)abstract
- We are currently witnessing the second wave of cloud services that go beyond web storefronts and IT systems, aiming for digitalization of industrial systems. Automation and time-sensitive systems are now taking their first steps toward the cloud. The AORTA project aims to facilitate this transition by providing key technology components needed for real-time services running in the cloud. The ambition is to support a future robotics ecosystem that enables a new level of flexible productivity in industrial production. AORTA will develop technologies that allow offloading of real-time services/functions to the edge and cloud. We will build upon recent advances in 5G, cloud, and networking technologies. The AORTA framework will support a fluid compute model where functionality will be dynamically deployed locally, in the edge, or in the cloud and support integration and real-time performance irrespective of where it executes. Results of the project will be demonstrated in a real-world robotics manufacturing and construction scenarios operating via a 5G network with real-time edge and large-scale cloud service. The AORTA technologies will provide opportunities for automation enterprises and system integrators by adding real-time capabilities needed to evolve beyond the currently closed ecosystem. They will also add value to telecom providers and operators that may host these new automation services in addition to their current portfolio.
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| 6. |
- Bhattacharyya, Shuvra S., et al.
(författare)
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Overview of the MPEG Reconfigurable Video Coding Framework
- 2011
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Ingår i: Journal of Signal Processing Systems. - : Springer Science and Business Media LLC. - 1939-8115 .- 1939-8018. ; 63:2, s. 251-263
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Tidskriftsartikel (refereegranskat)abstract
- Abstract in UndeterminedVideo coding technology in the last 20 yearshas evolved producing a variety of different and com-plex algorithms and coding standards. So far the speci-fication of such standards, and of the algorithms thatbuild them, has been done case by case providingmonolithic textual and reference software specifica-tions in different forms and programming languages.However, very little attention has been given to pro-vide a specification formalism that explicitly presentscommon components between standards, and the incre-mental modifications of such monolithic standards. TheMPEG Reconfigurable Video Coding (RVC) frame-work is a new ISO standard currently under its final stage of standardization, aiming at providing videocodec specifications at the level of library componentsinstead of monolithic algorithms. The new concept is tobe able to specify a decoder of an existing standard ora completely new configuration that may better satisfyapplication-specific constraints by selecting standardcomponents from a library of standard coding algo-rithms. The possibility of dynamic configuration andreconfiguration of codecs also requires new method-ologies and new tools for describing the new bitstreamsyntaxes and the parsers of such new codecs. TheRVC framework is based on the usage of a new actor/dataflow oriented language called Cal for the specifi-cation of the standard library and instantiation of theRVC decoder model. This language has been specifi-cally designed for modeling complex signal processingsystems. Cal dataflow models expose the intrinsic con-currency of the algorithms by employing the notionsof actor programming and dataflow. The paper givesan overview of the concepts and technologies buildingthe standard RVC framework and the non standardtools supporting the RVC model from the instantiationand simulation of the Cal model to software and/orhardware code synthesis.
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| 7. |
- Bini, Enrico, et al.
(författare)
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Resource Management on Multicore Systems: The ACTORS Approach
- 2011
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Ingår i: IEEE Micro. - 0272-1732. ; 31:3, s. 72-81
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Tidskriftsartikel (refereegranskat)abstract
- High-performance embedded systems require the execution of many applications on multicore platforms and are subject to stringent restrictions and constraints. The actors project approach provides temporal isolation through resource reservation over a multicore platform, adapting the available resources on the basis of the overall quality requirements. The architecture is fully operational on both ARM MPCore and x86 multicore platforms.
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| 9. |
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| 10. |
- Brännvall, Rickard, 1975-
(författare)
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Machine learning based control of small-scale autonomous data centers
- 2020
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The low-latency requirements of 5G are expected to increase the demand for distributeddata storage and computing capabilities in the form of small-scale data centers (DC)located at the edge, near the interface between mobile and wired networks. These edgeDC will likely be of modular and standardized designs, although configurations, localresource constraints, environments and load profiles will vary and thereby increase theDC infrastructure diversity. Autonomy and energy efficiency are key objectives for thedesign, configuration and control of such data centers. Edge DCs are (by definition)decentralized and should continue operating without human intervention in the presenceof disturbances, such as intermittent power failures, failing components and overheating.Automatic control is also required for efficient use of renewable energy, batteries and theavailable communication, computing and data storage capacity.These objectives demand data-driven models of the internal thermal and electricprocesses of an autonomous edge DC, since the resources required to manually defineand optimize the models for each DC would be prohibitive. In this thesis machinelearning methods that are implemented in a modular design are evaluated for thermalcontrol of such modular DCs. Experiments with small server clusters are presented, whichwere performed in order to investigate what parameters that are important in the designof advanced control strategies for autonomous edge DC. Furthermore, recent transferlearning results are discussed to understand how to develop data driven models thatcan be deployed to modular DC in varying configurations and environmental contextswithout training from scratch.The first study demonstrates how a data driven thermal model for a small clusterof servers can be calibrated to sensor data and used for constructing a model predictivecontroller for the server cooling fan. The experimental investigations of cooling fancontrol continues in the next study which explores operational sweet-spots and energyefficient holistic control strategies. The machine learning based controller from the firststudy is then re-purposed to maintain environmental conditions in an exhaust chamberfavourable for drying apples, as part of a practical study how excess heat produced bycomputation can be used in the food processing industry. A fourth study describes theRISE EDGE lab - a test bed for small data centers - built with the intention to exploreand evaluate related technologies for micro-grids with renewable energy and batteries,5G connectivity and coolant storage. Finally the last work presented develops the modelfrom the first study towards an application for thermal based load balancing.
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