Emerging Distributed/Parallel Computing Systems
This Reprint presents eight papers from the Special Issue “Emerging Distributed and Parallel Computing Systems” that span the core system challenges where computation, networking, and trust meet. Two contributions develop lightweight authentication and key agreement schemes for distributed wireless...
में बचाया:
| स्वरूप: | Online |
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| भाषा: | अंग्रेज़ी |
| प्रकाशित: |
MDPI - Multidisciplinary Digital Publishing Institute
2026
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| विषय: | |
| ऑनलाइन पहुंच: | ONIX_20260416T142754_9783725868582_27 |
| टैग: |
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| _version_ | 1869529252300324864 |
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| collection | Directory of Open Access Books |
| description | This Reprint presents eight papers from the Special Issue “Emerging Distributed and Parallel Computing Systems” that span the core system challenges where computation, networking, and trust meet. Two contributions develop lightweight authentication and key agreement schemes for distributed wireless sensor networks and for the 5G Internet of Vehicles, using practical hardware security and anonymous negotiation to strengthen resilience in resource constrained settings. Privacy-preserving distributed analytics is represented by a framework for origin–destination matrix computation that balances utility and overhead via hybrid differential privacy. Regarding data-driven computing, the Reprint includes advances in machine learning methods, including a deep reinforcement learning recommender with multi-level attention and a tensor-based multi-view projection clustering approach. Three surveys consolidate current knowledge on trends in parallel and distributed systems, analysing TLS 1.3-encrypted traffic, and software-defined wide-area networks, outlining design trade-offs and open research directions. Together, these papers provide an up-to-date snapshot of methods and insights for building scalable, secure, and intelligent distributed computing platforms. |
| format | Online |
| id | doab-20.500.12854ir-175422 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1754222026-04-16T20:49:21Z Emerging Distributed/Parallel Computing Systems Chen, Yawen Dai, Fei SD-WAN SDN Traffic engineering Network optimization and systems Service orchestration Security issues Internet of Vehicles Certificate-less aggregate signature Authentication key negotiation scheme Elliptic curve TLS 1.3 Encrypted traffic analysis Machine learning Interception techniques Searchable encryption Origin–destination matrix Differential privacy Distributed privacy-preserving framework Recommendation systems Multi-level attention mechanisms High-reward item features Deep reinforcement learning Authentication protocol Physical impersonation attack Physically unclonable function Chebyshev chaotic mapping Distributed wireless sensor networks Parallel computing Distributed systems Emerging trends System challenges Future directions Multi-view clustering Tensor kernel norm Projection learning Graph learning N A thema EDItEUR::A The Arts thema EDItEUR::A The Arts::AM Architecture This Reprint presents eight papers from the Special Issue “Emerging Distributed and Parallel Computing Systems” that span the core system challenges where computation, networking, and trust meet. Two contributions develop lightweight authentication and key agreement schemes for distributed wireless sensor networks and for the 5G Internet of Vehicles, using practical hardware security and anonymous negotiation to strengthen resilience in resource constrained settings. Privacy-preserving distributed analytics is represented by a framework for origin–destination matrix computation that balances utility and overhead via hybrid differential privacy. Regarding data-driven computing, the Reprint includes advances in machine learning methods, including a deep reinforcement learning recommender with multi-level attention and a tensor-based multi-view projection clustering approach. Three surveys consolidate current knowledge on trends in parallel and distributed systems, analysing TLS 1.3-encrypted traffic, and software-defined wide-area networks, outlining design trade-offs and open research directions. Together, these papers provide an up-to-date snapshot of methods and insights for building scalable, secure, and intelligent distributed computing platforms. 2026-04-16T20:49:15Z 2026-04-16T20:49:15Z 2026 book ONIX_20260416T142754_9783725868582_27 9783725868582 9783725868599 https://directory.doabooks.org/handle/20.500.12854/175422 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/ https://mdpi.com/books/pdfview/book/12340 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-6859-9 10.3390/books978-3-7258-6859-9 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725868582 9783725868599 204 CH open access |
| spellingShingle | SD-WAN SDN Traffic engineering Network optimization and systems Service orchestration Security issues Internet of Vehicles Certificate-less aggregate signature Authentication key negotiation scheme Elliptic curve TLS 1.3 Encrypted traffic analysis Machine learning Interception techniques Searchable encryption Origin–destination matrix Differential privacy Distributed privacy-preserving framework Recommendation systems Multi-level attention mechanisms High-reward item features Deep reinforcement learning Authentication protocol Physical impersonation attack Physically unclonable function Chebyshev chaotic mapping Distributed wireless sensor networks Parallel computing Distributed systems Emerging trends System challenges Future directions Multi-view clustering Tensor kernel norm Projection learning Graph learning N A thema EDItEUR::A The Arts thema EDItEUR::A The Arts::AM Architecture Emerging Distributed/Parallel Computing Systems |
| title | Emerging Distributed/Parallel Computing Systems |
| title_full | Emerging Distributed/Parallel Computing Systems |
| title_fullStr | Emerging Distributed/Parallel Computing Systems |
| title_full_unstemmed | Emerging Distributed/Parallel Computing Systems |
| title_short | Emerging Distributed/Parallel Computing Systems |
| title_sort | emerging distributed parallel computing systems |
| topic | SD-WAN SDN Traffic engineering Network optimization and systems Service orchestration Security issues Internet of Vehicles Certificate-less aggregate signature Authentication key negotiation scheme Elliptic curve TLS 1.3 Encrypted traffic analysis Machine learning Interception techniques Searchable encryption Origin–destination matrix Differential privacy Distributed privacy-preserving framework Recommendation systems Multi-level attention mechanisms High-reward item features Deep reinforcement learning Authentication protocol Physical impersonation attack Physically unclonable function Chebyshev chaotic mapping Distributed wireless sensor networks Parallel computing Distributed systems Emerging trends System challenges Future directions Multi-view clustering Tensor kernel norm Projection learning Graph learning N A thema EDItEUR::A The Arts thema EDItEUR::A The Arts::AM Architecture |
| topic_facet | SD-WAN SDN Traffic engineering Network optimization and systems Service orchestration Security issues Internet of Vehicles Certificate-less aggregate signature Authentication key negotiation scheme Elliptic curve TLS 1.3 Encrypted traffic analysis Machine learning Interception techniques Searchable encryption Origin–destination matrix Differential privacy Distributed privacy-preserving framework Recommendation systems Multi-level attention mechanisms High-reward item features Deep reinforcement learning Authentication protocol Physical impersonation attack Physically unclonable function Chebyshev chaotic mapping Distributed wireless sensor networks Parallel computing Distributed systems Emerging trends System challenges Future directions Multi-view clustering Tensor kernel norm Projection learning Graph learning N A thema EDItEUR::A The Arts thema EDItEUR::A The Arts::AM Architecture |
| url | ONIX_20260416T142754_9783725868582_27 |