49 research outputs found

    Maat: Performance Metric Anomaly Anticipation for Cloud Services with Conditional Diffusion

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    Ensuring the reliability and user satisfaction of cloud services necessitates prompt anomaly detection followed by diagnosis. Existing techniques for anomaly detection focus solely on real-time detection, meaning that anomaly alerts are issued as soon as anomalies occur. However, anomalies can propagate and escalate into failures, making faster-than-real-time anomaly detection highly desirable for expediting downstream analysis and intervention. This paper proposes Maat, the first work to address anomaly anticipation of performance metrics in cloud services. Maat adopts a novel two-stage paradigm for anomaly anticipation, consisting of metric forecasting and anomaly detection on forecasts. The metric forecasting stage employs a conditional denoising diffusion model to enable multi-step forecasting in an auto-regressive manner. The detection stage extracts anomaly-indicating features based on domain knowledge and applies isolation forest with incremental learning to detect upcoming anomalies. Thus, our method can uncover anomalies that better conform to human expertise. Evaluation on three publicly available datasets demonstrates that Maat can anticipate anomalies faster than real-time comparatively or more effectively compared with state-of-the-art real-time anomaly detectors. We also present cases highlighting Maat's success in forecasting abnormal metrics and discovering anomalies.Comment: This paper has been accepted by the Research track of the 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023

    Quality of experience and access network traffic management of HTTP adaptive video streaming

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    The thesis focuses on Quality of Experience (QoE) of HTTP adaptive video streaming (HAS) and traffic management in access networks to improve the QoE of HAS. First, the QoE impact of adaptation parameters and time on layer was investigated with subjective crowdsourcing studies. The results were used to compute a QoE-optimal adaptation strategy for given video and network conditions. This allows video service providers to develop and benchmark improved adaptation logics for HAS. Furthermore, the thesis investigated concepts to monitor video QoE on application and network layer, which can be used by network providers in the QoE-aware traffic management cycle. Moreover, an analytic and simulative performance evaluation of QoE-aware traffic management on a bottleneck link was conducted. Finally, the thesis investigated socially-aware traffic management for HAS via Wi-Fi offloading of mobile HAS flows. A model for the distribution of public Wi-Fi hotspots and a platform for socially-aware traffic management on private home routers was presented. A simulative performance evaluation investigated the impact of Wi-Fi offloading on the QoE and energy consumption of mobile HAS.Die Doktorarbeit beschäftigt sich mit Quality of Experience (QoE) – der subjektiv empfundenen Dienstgüte – von adaptivem HTTP Videostreaming (HAS) und mit Verkehrsmanagement, das in Zugangsnetzwerken eingesetzt werden kann, um die QoE des adaptiven Videostreamings zu verbessern. Zuerst wurde der Einfluss von Adaptionsparameters und der Zeit pro Qualitätsstufe auf die QoE von adaptivem Videostreaming mittels subjektiver Crowdsourcingstudien untersucht. Die Ergebnisse wurden benutzt, um die QoE-optimale Adaptionsstrategie für gegebene Videos und Netzwerkbedingungen zu berechnen. Dies ermöglicht Dienstanbietern von Videostreaming verbesserte Adaptionsstrategien für adaptives Videostreaming zu entwerfen und zu benchmarken. Weiterhin untersuchte die Arbeit Konzepte zum Überwachen von QoE von Videostreaming in der Applikation und im Netzwerk, die von Netzwerkbetreibern im Kreislauf des QoE-bewussten Verkehrsmanagements eingesetzt werden können. Außerdem wurde eine analytische und simulative Leistungsbewertung von QoE-bewusstem Verkehrsmanagement auf einer Engpassverbindung durchgeführt. Schließlich untersuchte diese Arbeit sozialbewusstes Verkehrsmanagement für adaptives Videostreaming mittels WLAN Offloading, also dem Auslagern von mobilen Videoflüssen über WLAN Netzwerke. Es wurde ein Modell für die Verteilung von öffentlichen WLAN Zugangspunkte und eine Plattform für sozialbewusstes Verkehrsmanagement auf privaten, häuslichen WLAN Routern vorgestellt. Abschließend untersuchte eine simulative Leistungsbewertung den Einfluss von WLAN Offloading auf die QoE und den Energieverbrauch von mobilem adaptivem Videostreaming

    A Survey of Scheduling in 5G URLLC and Outlook for Emerging 6G Systems

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    Future wireless communication is expected to be a paradigm shift from three basic service requirements of 5th Generation (5G) including enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency communication (URLLC) and the massive Machine Type Communication (mMTC). Integration of the three heterogeneous services into a single system is a challenging task. The integration includes several design issues including scheduling network resources with various services. Specially, scheduling the URLLC packets with eMBB and mMTC packets need more attention as it is a promising service of 5G and beyond systems. It needs to meet stringent Quality of Service (QoS) requirements and is used in time-critical applications. Thus through understanding of packet scheduling issues in existing system and potential future challenges is necessary. This paper surveys the potential works that addresses the packet scheduling algorithms for 5G and beyond systems in recent years. It provides state of the art review covering three main perspectives such as decentralised, centralised and joint scheduling techniques. The conventional decentralised algorithms are discussed first followed by the centralised algorithms with specific focus on single and multi-connected network perspective. Joint scheduling algorithms are also discussed in details. In order to provide an in-depth understanding of the key scheduling approaches, the performances of some prominent scheduling algorithms are evaluated and analysed. This paper also provides an insight into the potential challenges and future research directions from the scheduling perspective

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum

    A comprehensive survey on reinforcement-learning-based computation offloading techniques in Edge Computing Systems

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    Producción CientíficaIn recent years, the number of embedded computing devices connected to the Internet has exponentially increased. At the same time, new applications are becoming more complex and computationally demanding, which can be a problem for devices, especially when they are battery powered. In this context, the concepts of computation offloading and edge computing, which allow applications to be fully or partially offloaded and executed on servers close to the devices in the network, have arisen and received increasing attention. Then, the design of algorithms to make the decision of which applications or tasks should be offloaded, and where to execute them, is crucial. One of the options that has been gaining momentum lately is the use of Reinforcement Learning (RL) and, in particular, Deep Reinforcement Learning (DRL), which enables learning optimal or near-optimal offloading policies adapted to each particular scenario. Although the use of RL techniques to solve the computation offloading problem in edge systems has been covered by some surveys, it has been done in a limited way. For example, some surveys have analysed the use of RL to solve various networking problems, with computation offloading being one of them, but not the primary focus. Other surveys, on the other hand, have reviewed techniques to solve the computation offloading problem, being RL just one of the approaches considered. To the best of our knowledge, this is the first survey that specifically focuses on the use of RL and DRL techniques for computation offloading in edge computing system. We present a comprehensive and detailed survey, where we analyse and classify the research papers in terms of use cases, network and edge computing architectures, objectives, RL algorithms, decision-making approaches, and time-varying characteristics considered in the analysed scenarios. In particular, we include a series of tables to help researchers identify relevant papers based on specific features, and analyse which scenarios and techniques are most frequently considered in the literature. Finally, this survey identifies a number of research challenges, future directions and areas for further study.Consejería de Educación de la Junta de Castilla y León y FEDER (VA231P20)Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42, PID2021-124463OBI00 y RED2018-102585-T, financiados por MCIN/AEI/10.13039/501100011033

    A Comprehensive Bibliometric Analysis on Social Network Anonymization: Current Approaches and Future Directions

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    In recent decades, social network anonymization has become a crucial research field due to its pivotal role in preserving users' privacy. However, the high diversity of approaches introduced in relevant studies poses a challenge to gaining a profound understanding of the field. In response to this, the current study presents an exhaustive and well-structured bibliometric analysis of the social network anonymization field. To begin our research, related studies from the period of 2007-2022 were collected from the Scopus Database then pre-processed. Following this, the VOSviewer was used to visualize the network of authors' keywords. Subsequently, extensive statistical and network analyses were performed to identify the most prominent keywords and trending topics. Additionally, the application of co-word analysis through SciMAT and the Alluvial diagram allowed us to explore the themes of social network anonymization and scrutinize their evolution over time. These analyses culminated in an innovative taxonomy of the existing approaches and anticipation of potential trends in this domain. To the best of our knowledge, this is the first bibliometric analysis in the social network anonymization field, which offers a deeper understanding of the current state and an insightful roadmap for future research in this domain.Comment: 73 pages, 28 figure

    LIPIcs, Volume 274, ESA 2023, Complete Volume

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    LIPIcs, Volume 274, ESA 2023, Complete Volum

    Packet switch architecture for efficient unicast and multicast traffic switching

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    У дисертацији је предложена једноставна архитектура свича као и алгоритми за ефикасно распоређивање и комутацију уникаст и мултикаст саобраћаја, што је од великог значаја за савремене телекомуникационе мреже у којима количина саобраћаја константно расте. Први дио доприноса ове дисертације чини приједлог рјешења свича за ефикасно управљање уникаст саобраћајем. Ово рјешење је развијено комбинујући најбоље особине постојећих рјешења, при том избјегавајући одређене њихове недостатке. Циљ је да се омогући што брже прослијеђивање пакета уз прихватљив ниво хардверске комплексности. Свич који је развијен у овој дисертацији представља комбинацију свичева са баферима на улазу и свичева који користе Биркхоф-фон Нојман принцип детерминистичког конфигурисања комутационог модула па се не захтијева прорачун конфигурација комутатора. При томе, за разлику од већине рјешења која користе Биркхоф-фон Нојман принцип конфигурисања, у предложеном рјешењу могуће је користити само један физички комутациони модул који би обављао функције оба логичка комутациона модула. Да би се гарантовало да није дошло до поремећаја редослиједа пакета, предложен је и једноставан алгоритам за одабир пакета за слање. Такође, дат је и приједлог унапријеђења подршке за фер сервис првобитно предложеног рјешења за комутацију уникаст саобраћаја. У другом дијелу дисертације, пажња је посвећена унапријеђењу предложеног рјешења за ефикасно управљање и мултикаст саобраћајем. Потреба за овим се јавила као посљедица развоја нових сервиса (нпр. IPTV, онлајн игре итд.) који генеришу такав тип саобраћаја. Како је удио мултикаст саобраћаја у мрежи постао незанемарљив, перформансе свичева који су развијени примарно за уникаст саобраћај значајно опадају. Рјешење које је предложено у првом дијелу дисертације је унапријеђено додавањем модула који служи за управљање мултикаст саобраћајем. Овдје је идеја да се оптерећење са улазног порта који прима мултикаст пакете распореди на више портова који треба да приме те пакете. Овако је на релативно једноставан начин омогућено ефикасно управљање мултикаст саобраћајем. У оквиру дисертације су урађене софтверске симулације које су показале да ова рјешења постижу врло добре перформансе у односу на постојећа. Такође, урађена је и хардверска имплементација предложеног основног уникаст рјешења која је показала релативно скромне захтјеве у погледу хардверских ресурса.The dissertation proposes a simple switch architecture as well as algorithms for efficient scheduling and switching of unicast and multicast traffic, which is of great importance for modern telecommunication networks because their traffic load is constantly and rapidly increasing. The first part of the dissertation’s contributions comprises a proposed switch which efficiently manages unicast traffic. The proposed switch is developed by using the best characteristics of the existing solutions while avoiding some of their drawbacks. The aim is to enable fast packet forwarding while achieving an acceptable level of hardware complexity. The proposed solution combines architecture with buffers at input ports and Birkhoff-von Neumann architecture based on deterministic switch module configurations. Hence, calculation of switch module configurations is not needed. Also, folded architecture is possible, which means that only one physical switching module is used for both switching stages of Birkhoff-von Neumann architecture. A simple algorithm for packet scheduling has been developed in order to avoid packet out-of-sequence problems. Finally, fair service support improvement is introduced for the originally proposed switch solution. The second part of the dissertation is devoted to the enhancement of the proposed unicast switch for efficient management of multicast traffic. The need for multicast support has emerged as a consequence of the development and introduction of new services (such as IPTV, online gaming, etc.) that generate multicast traffic. As the amount of multicast traffic is not negligible anymore, the performance of packet switches that were primarily developed for the unicast traffic is significantly degraded. The solution proposed in the first part of the diseration is enhanced with the module used for multicast traffic management. Here, the idea is that the multicast load at some input port is distributed over ports that are also destination for the multicast packets. This approach enables relatively simple but efficient management of multicast traffic. In this dissertation, software simulations were conducted, which confirmed that proposed solutions achieve very good performances compared to existing solutons. Furthermore, hardware implementation of the proposed basic unicast switch solution shows modest requirements in terms of needed hardware resources
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