| 1. |
- Alizadeh Noghani, Kyoomars
(författare)
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Service Migration in Virtualized Data Centers
- 2020
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Modern virtualized Data Centers (DCs) require efficient management techniques to guarantee high quality services while reducing their economical cost. The ability to live migrate virtual instances, e.g., Virtual Machines (VMs), both inside and among DCs is a key operation for the majority of DC management tasks that brings significant flexibility into the DC infrastructure. However, live migration introduces new challenges as it ought to be fast and seamless while at the same time imposing a minimum overhead on the network. In this thesis, we study the networking problems of live service migration in modern DCs when services are deployed in virtualized environments, e.g., VMs and containers. In particular, this thesis has the following main objectives: (1) improving the live VM migration in Software-Defined Network (SDN) enabled DCs by addressing networking challenges of live VM migration, and (2) investigating the trade-off between the reconfiguration cost and optimality of the Service Function Chains (SFCs) placement after the reconfiguration has been applied when SFCs are composed of stateful Virtual Network Functions (VNFs).To achieve the first objective, in this thesis, we use distinctive characteristics of SDN architectures such as their centralized control over the network to accelerate the network convergence time and address suboptimal routing problem. Consequently, we enhance the quality of intra- and inter-DC live migrations. Furthermore, we develop an SDN-based framework to improve the inter-DC live VM migration by automating the deployment, improving the management, enhancing the performance, and increasing the scalability of interconnections among DCs.To accomplish the second objective, we investigate the overhead of dynamic reconfiguration of stateful VNFs. Dynamic reconfiguration of VNFs is frequently required in various circumstances, and live migration of VNFs is an integral part of this operation. By mathematically formulating the reconfiguration costs of stateful VNFs and developing a multi-objective heuristic solution, we explore the trade-off between the reconfiguration cost required to improve a given placement and the degree of optimality achieved after the reconfiguration is performed. Results show that the cost of performing the reconfiguration operations required to realize an optimal VNF placement might hamper the gain that could be achieved.
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| 2. |
- Aupke, Phil, et al.
(författare)
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Impact of Clustering Methods on Machine Learning-based Solar Power Prediction Models
- 2022
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Ingår i: 2022 IEEE International Smart Cities Conference (ISC2). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665485616
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Konferensbidrag (refereegranskat)abstract
- Prediction of solar power generation is important in order to optimize energy exchanges in future micro-grids that integrate a large amount of photovoltaics. However, an accurate prediction is difficult due to the uncertainty of weather phenomena that impact produced power. In this paper, we evaluate the impact of different clustering methods on the forecast accuracy for predicting hourly ahead solar power when using machine learning based prediction approaches trained on weather and generated power features. In particular, we compare clustering methods using clearness index and K-means clustering, where we use both euclidian distance and dynamic time-warping. For evaluating prediction accuracy, we develop and compare different prediction models for each of the clusters using production data from a swedish SmartGrid. We demonstrate that proper tuning of thresholds for the clearness index improves prediction accuracy by 20.19% but results in worse performance than using K-means with all weather features as input to the clustering.
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| 3. |
- Aupke, Phil, et al.
(författare)
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PV Power Production and Consumption Estimation with Uncertainty bounds in Smart Energy Grids
- 2023
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Ingår i: 2023 IEEE International Conference on Environment and Electrical Engineering and 2023 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). - : IEEE. - 9798350347432 - 9798350347449
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Konferensbidrag (refereegranskat)abstract
- For efficient energy exchanges in smart energy grids under the presence of renewables, predictions of energy production and consumption are required. For robust energy scheduling, prediction of uncertainty bounds of Photovoltaic (PV) power production and consumption is essential. In this paper, we apply several Machine Learning (ML) models that can predict the power generation of PV and consumption of households in a smart energy grid, while also assessing the uncertainty of their predictions by providing quantile values as uncertainty bounds. We evaluate our algorithms on a dataset from Swedish households having PV installations and battery storage. Our findings reveal that a Mean Absolute Error (MAE) of 16.12W for power production and 16.34W for consumption for a residential installation can be achieved with uncertainty bounds having quantile loss values below 5W. Furthermore, we show that the accuracy of the ML models can be affected by the characteristics of the household being studied. Different households may have different data distributions, which can cause prediction models to perform poorly when applied to untrained households. However, our study found that models built directly for individual homes, even when trained with smaller datasets, offer the best outcomes. This suggests that the development of personalized ML models may be a promising avenue for improving the accuracy of predictions in the future.
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| 4. |
- Bayram, Firas, et al.
(författare)
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DA-LSTM: A dynamic drift-adaptive learning framework for interval load forecasting with LSTM networks
- 2023
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Ingår i: Engineering applications of artificial intelligence. - : Elsevier. - 0952-1976 .- 1873-6769. ; 123
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Tidskriftsartikel (refereegranskat)abstract
- Load forecasting is a crucial topic in energy management systems (EMS) due to its vital role in optimizing energy scheduling and enabling more flexible and intelligent power grid systems. As a result, these systems allow power utility companies to respond promptly to demands in the electricity market. Deep learning (DL) models have been commonly employed in load forecasting problems supported by adaptation mechanisms to cope with the changing pattern of consumption by customers, known as concept drift. A drift magnitude threshold should be defined to design change detection methods to identify drifts. While the drift magnitude in load forecasting problems can vary significantly over time, existing literature often assumes a fixed drift magnitude threshold, which should be dynamically adjusted rather than fixed during system evolution. To address this gap, in this paper, we propose a dynamic drift-adaptive Long Short-Term Memory (DA-LSTM) framework that can improve the performance of load forecasting models without requiring a drift threshold setting. We integrate several strategies into the framework based on active and passive adaptation approaches. To evaluate DA-LSTM in real-life settings, we thoroughly analyze the proposed framework and deploy it in a real-world problem through a cloud-based environment. Efficiency is evaluated in terms of the prediction performance of each approach and computational cost. The experiments show performance improvements on multiple evaluation metrics achieved by our framework compared to baseline methods from the literature. Finally, we present a trade-off analysis between prediction performance and computational costs.
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| 5. |
- Brunström, Anna, et al.
(författare)
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NEWCOM++ DR11.3: Final report on the activities and results of WPR11
- 2010
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This document is the last deliverable of WPR.11 and presents an overview of the final activities carried out within the NEWCOM++ Workpackage WPR.11 during the last 18 months. We provide a description of the most consolidated Joint Research Activities (JRAs) and the main results so far obtained. We also address some considerations on the future activities which are expected to continue at the end of NEWCOM++
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| 6. |
- Doolin, Kevin, et al.
(författare)
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Context-Aware Multimedia Services in a Pervasive Environment : The Daidalos Approach
- 2008
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Ingår i: Proceedings of the 2008 Ambi-Sys workshop on Software Organisation and MonIToring of Ambient Systems. - : ICST. - 9789639799165
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Konferensbidrag (refereegranskat)abstract
- There is a clear trend towards making multimedia applications context-aware so as to customize them by taking into account any collection of information which may be relevant, such as e.g. user location. However, current multimedia services are dominated by IMS, which is seen as a service platform that uses the SIP protocol to access all services that the internet can provide. In this paper, we describe the Daidalos approach on making IMS based multi-media services context-aware. We also demonstrate, how generic sensor networks can be integrated into the context management system of our platform thus enabling sensor network detected events to influence behavior of context-aware multimedia applications
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| 7. |
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| 8. |
- Guenkova-Luy, Teodora, et al.
(författare)
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A Session-Initiation-Protocol-based Middleware for Multi-Application Management
- 2007
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Konferensbidrag (refereegranskat)abstract
- The deployment of multimedia services in next-generation networks is a challenge due to the high configuration complexity of the streaming process in different stationary and mobile sub-networks and for various user devices. The Session Initiation Protocol (SIP) has proven to be a suitable mechanism to handle the control of multimedia services in such networks. However, the current standardization and implementation of SIP do not allow the simultaneous coordination of multiple concurrent applications on a single device, as the prescribed realization of the SIP state machines (transactions) does not consider mutual access of applications to a single SIP stack. This paper presents a SIP-based mechanism for synchronized management of services in a shared environment. We have developed a middleware that facilitates the uniform access of multiple applications towards one or multiple SIP stacks to enable prioritization of services and centralized resource coordination of concurrent SIP applications on a single terminal or server
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| 9. |
- Guenkova-Luy, Teodora, et al.
(författare)
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Advanced Multimedia Management Control Model and Content Adaptation
- 2006
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Konferensbidrag (refereegranskat)abstract
- The delivery and adaptation of multimedia content in distributed and heterogeneous environments requires flexible control and management mechanisms in terminals and in control entities inside the network. In the near future, it is important to reach interoperability between the IETF approaches on multimedia session establishment and control and the MPEG-21 efforts for multimedia streaming and adaptation to bring advanced multimedia service provisioning and adaptation services towards the customer. MPEG-21 Digital Item Adaptation (DIA) provides normative descriptions for supporting adaptation of multimedia content, but does not define interactions with transport and control mechanisms. On the other hand, the IETF standardization efforts on multimedia session control provide the necessary transport (e.g. RTP) and control mechanisms (SDP/SDPng). We thus bridge the gap between those approaches by creating a converged XML model that enables the integration of session management and negotiation protocols (e.g. SIP or Megaco) inspired by the XML formats of MPEG-21 DIA and SDPng. We also present preliminary implementation results of the converged model along with concepts and implementation of network-based content adaptation mechanisms through media gateways that enable flexible multimedia management for heterogeneous consumer terminals
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| 10. |
- Kassler, Andreas, et al.
(författare)
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Network-Based Content Adaptation of Streaming Media Using MPEG-21 DIA and SDPng
- 2006
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Konferensbidrag (refereegranskat)abstract
- The dynamic adaptation of multimedia content in distributed heterogeneous environments is a key enabler for next generation ubiquitous and pervasive services. Systems implementing the Universal Multimedia Access (UMA) approaches are predominantly combinations of MPEG-centric and/or proprie-tary solutions. However, it is important to reach interoperability between the IETF approach for multimedia-session establish-ment and control and the MPEG-21 efforts for metadata-driven adaptation, in order to enable personalized multimedia delivery for ubiquitous users, where media is delivered and adapted on the fly taking into account context and environment. In this pa-per, we present a format-independent model that enables con-verging IETF and MPEG-21 descriptions for streaming media. We introduce the architecture of a multimedia stream-adaptation service to enable communication between terminals having het-erogeneous capabilities and communicating over heterogeneous networks. We demonstrate how the service utilizes the converged session description model and how it can be deployed inside special adaptation nodes within any part of the network to enable dynamic content adaptation both at the terminal and within the network
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