Call for Papers: Special Issue on The Edge–Cloud Continuum: Software Challenges and Innovations

The software-powered world increasingly spans from constrained devices and on‑premise micro‑datacenters to regional edge sites and public clouds. Building and operating software across this edge‑to‑cloud continuum poses unique challenges such as intermittent connectivity, diverse hardware accelerators, strict latency requirements, data residency constraints, Operational Complexity and many others.

Cloud‑native foundations (containers, serverless, service meshes) are being reimagined for the edge; AI/ML pipelines are moving closer to where data is produced; and advances in 5G/6G and time‑sensitive networking are expanding what’s possible.

This special issue aims to surface cutting‑edge approaches, architectures, and practices that enable dependable, secure, and sustainable software spanning edge and cloud. We welcome contributions that clarify how engineering teams design, deliver, observe, and govern software across the continuum; report on impact to quality, reliability, cost, performance, and sustainability; and share lessons learned from real‑world deployments in industry and the public sector.

We invite researchers, practitioners, and industry experts to submit original contributions to the IEEE Software Special Issue on Edge‑to‑Cloud Continuum and Infrastructures. Topics of interest include, but are not limited to:

• Reference architectures & patterns for edge–cloud applications (event‑driven, digital twins, streaming, offline‑first).
• CI/CD and progressive delivery across the continuum (OTA updates, canary/blue‑green at the edge, safe rollback, compliance gates).
• Orchestration & resource management across constrained/heterogeneous nodes (containers, micro‑VMs/unikernels, multi‑cluster, accelerator‑aware scheduling).
• Serverless and service meshes spanning WAN and intermittency; function fabrics from device to cloud.
• Data pipelines & management (state synchronization, consistency models, conflict resolution, data residency/sovereignty).
• Observability, SRE & AIOps for edge–cloud systems (cross‑layer telemetry, anomaly detection, incident response at the edge).
• MLOps on the continuum (on‑device inference, model rollout/drift, federated learning, privacy‑preserving training).
• Security, privacy & trust (zero trust for edge, confidential computing/attestation, secure boot, SBOM and supply‑chain risk).
• Reliability & resilience (fault tolerance, self‑healing, network partitions, real‑time constraints, chaos engineering for edge).
• Network‑aware engineering (5G/6G, MEC, slicing, TSN, satellite‑edge integration) and their implications for software design.
• Testing, verification & benchmarking for distributed edge–cloud software; representative testbeds and reproducibility.
• Sustainability & cost effectiveness (energy‑/carbon‑aware placement, FinOps for edge, lifecycle impacts).
• Developer experience & platform engineering (SDKs/abstractions, APIs, policy‑as‑code, governance and compliance).
• Domain case studies and experience reports (smart railway, smart transportation, industrial IoT/Industry 4.0, automotive, healthcare, retail, smart cities, public safety).
• Intent-based management and orchestration (policy translation, closed-loop control, intent verification, conflict resolution, self-optimizing orchestration).

Submission Instructions:

For author information and guidelines on submission criteria, visit the IEEE Software Author Information page. Please submit papers through the IEEE Author Portal system, and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the IEEE Author Portal. If requested, abstracts should be sent by email to the guest editors directly.

In addition to submitting your paper to IEEE Software, you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE's data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission.