Emerging Distributed/Parallel Computing Systems

Overview & Synopsis

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.