About the Journal
Aims and Scope. Journal of Scalable Distributed Computing provides a focused venue for research on horizontal scaling, distributed execution, load balancing, elasticity, scalability modeling. The journal prioritizes technically substantive, internationally relevant work in which the principal novelty lies inside the stated computing scope rather than only in the application domain.
Core topics in scope include:
- horizontal scaling
- distributed execution
- load balancing
- elasticity
- scalability modeling
- distributed performance
- distributed computing
- scalability
- parallel services
- large-scale systems
Evidence and methodological expectations. Networking and distributed-systems studies should specify topology, workload, traffic or failure assumptions, compare protocols or systems under controlled conditions, and evaluate scalability, latency, throughput, reliability, consistency, or resource use as appropriate. Traces, configurations, or testbed details should be reproducible.
Normally outside scope. Basic network configuration reports, simulations with undocumented parameters, protocol use without novelty, and small local deployments with no generalizable network or distributed-systems contribution are normally outside scope.
Research integrity and reproducibility. Authors should disclose datasets, software, model or system configurations, experimental protocols, statistical procedures, ethical approvals where applicable, competing interests, funding, and any material use of generative AI. Data and code should be shared when legally and ethically possible, or the restriction must be explained.
