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001443141 020__ $$a3030924351$$q(electronic bk.)
001443141 020__ $$z9783030924331
001443141 020__ $$z3030924335
001443141 0247_ $$a10.1007/978-3-030-92435-5$$2doi
001443141 035__ $$aSP(OCoLC)1288167426
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001443141 049__ $$aISEA
001443141 050_4 $$aTK5105.5833$$b.F88 2022
001443141 08204 $$a004.6$$223
001443141 24500 $$aFuture intent-based networking :$$bon the QoS robust and energy efficient heterogenous software defined networks /$$cMikhailo Klymash, Mykola Beshley, Andriy Luntovskyy, editors.
001443141 264_1 $$aCham :$$bSpringer,$$c[2022]
001443141 264_4 $$c©2022
001443141 300__ $$a1 online resource :$$billustrations (some color)
001443141 336__ $$atext$$btxt$$2rdacontent
001443141 337__ $$acomputer$$bc$$2rdamedia
001443141 338__ $$aonline resource$$bcr$$2rdacarrier
001443141 347__ $$atext file
001443141 347__ $$bPDF
001443141 4901_ $$aLecture notes in electrical engineering,$$x1876-1119 ;$$vvolume 831
001443141 500__ $$aIncludes author index.
001443141 5058_ $$a2.4 Demarcation of Web Services and Micro-services -- 2.5 Three Main Questions -- 3 Service Composition in Highly-Distributed Systems -- 4 Considering of QoS Robustness and Security -- 4.1 QoS Robustness and QoE -- 4.2 CIDN for IBN -- 5 Summarizing -- 6 Conclusions and Outlook -- References -- Intent-Based Placement of Microservices in Computing Continuums -- 1 Introduction -- 2 Placement, Migration and Other Software Engineering Concerns -- 3 Matchmaking as Planning Phase for Initial Placement -- 3.1 Example Description -- 3.2 Preliminaries: Definitions and Models -- 3.3 Greedy Matching
001443141 5058_ $$a3.4 Rule-Based Matching -- 3.5 SAT Solver Matching -- 3.6 Towards Advanced Intent-Based Matching and Placement -- 4 Conclusion -- References -- Infrastructure as Code and Microservices for Intent-Based Cloud Networking -- 1 Introduction -- 2 AIOps and Benefits of Infrastructure as Code -- 3 GCP Cloud Functions for Microservices -- 4 GCP Cloud Run -- Highly Scalable Containerized Applications -- 5 Conclusion -- References -- Intent-Based Adaptation Coordination of Highly Decentralized Networked Self-adaptive Systems -- 1 Introduction -- 2 Application Scenario
001443141 5058_ $$a3 Intent-Based Self-adaptation with Roles -- 3.1 The MAPE-K Control Loop -- 3.2 Patterns for Decentralization in Control Loops -- 3.3 Foundations of Roles -- 3.4 The Compartment Role Object Model (CROM) -- 3.5 Scala Roles Language (SCROLL) -- 3.6 Modelling Runtime Adaptations -- 3.7 Conceptual Framework for Intent-Based Adaptation Coordination -- 4 Case Study -- 4.1 Monitoring Component -- 4.2 Analysis and Planning -- 4.3 Decentralized Execution of Adaptation Plans -- 5 Conclusion and Future Work -- References -- Intent-Based Routing in Delay- and Disruption-Tolerant Networks -- 1 Introduction
001443141 5058_ $$a2 Foundations -- 2.1 Delay-/Disruption-Tolerant Networking -- 2.2 Intent-Based Networking -- 2.3 Self-Adaptive Systems -- 3 Toward an Intent-Based DTN -- 3.1 Example Scenario -- 3.2 An Intent-Based Networking Approach for DTN -- 3.3 Self-Adaptation Concepts for Intent-Based DTN -- 3.4 Open Issues for Intent-Based DTN -- 4 Adaptive DTN Routing -- 4.1 Contact Prediction-Based DTN Routing -- 4.2 Adaptation of the Routing Algorithm -- 4.3 Application to Example Scenario -- 5 A Multicast Approach for Intent-Based Node Configuration -- 5.1 Multicast in Deterministic DTN -- 5.2 SPSN-Based Multicast
001443141 506__ $$aAccess limited to authorized users.
001443141 520__ $$aThis texSo-called Intent-Based Networking (IBN) is founded on well-known SDN (Software-Defined Networking) and represents one of the most important emerging network infrastructure opportunities. The IBN is the beginning of a new era in the history of networking, where the network itself translates business intentions into appropriate network configurations for all devices. This minimizes manual effort, provides an additional layer of network monitoring, and provides the ability to perform network analytics and take full advantage of machine learning. The centralized, software-defined solution provides process automation and proactive problem solving as well as centralized management of the network infrastructure. With software-based network management, many operations can be performed automatically using intelligent control algorithms (artificial intelligence and machine learning). As a result, network operation costs, application response times and energy consumption are reduced, network reliability and performance are improved, network security and flexibility are enhanced. This will be a benefit for existing networks as well as evolved LTE-based mobile networks, emerging Internet of Things (IoT), Cloud systems, and soon for the future 5G/6G networks. The future networks will reach a whole new level of self-awareness, self-configuration, self-optimization, self-recovery and self-protection. This volume consists of 28 chapters, based on recent research on IBN. The volume is a collection of the most important research for the future intent-based networking deployment provided by different groups of researchers from Ukraine, Germany, Slovak Republic, Switzerland, South Korea, China, Czech Republic, Poland, Brazil, Belarus and Israel. The authors of the chapters from this collection present in depth extended research results in their scientific fields. The presented contents are highly interesting while still being rather practically oriented and straightforward to understand. Herewith we would like to wish all our readers a lot of inspiration by studying of the volume! t will be replaced by the correct backcover text as soon as we get it.
001443141 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 14, 2021).
001443141 650_0 $$aSoftware-defined networking (Computer network technology)
001443141 650_6 $$aRéseaux SDN.
001443141 655_0 $$aElectronic books.
001443141 7001_ $$aKlymash, Mikhailo,$$eeditor.
001443141 7001_ $$aBeshley, Mykola,$$eeditor.
001443141 7001_ $$aLuntovskyy, Andriy,$$eeditor.
001443141 77608 $$iPrint version:$$z3030924335$$z9783030924331$$w(OCoLC)1283140995
001443141 830_0 $$aLecture notes in electrical engineering ;$$v831.$$x1876-1119
001443141 852__ $$bebk
001443141 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-92435-5$$zOnline Access$$91397441.1
001443141 909CO $$ooai:library.usi.edu:1443141$$pGLOBAL_SET
001443141 980__ $$aBIB
001443141 980__ $$aEBOOK
001443141 982__ $$aEbook
001443141 983__ $$aOnline
001443141 994__ $$a92$$bISE