CubeTrace: Microscopic Network Tracing for Heterogeneous Cloud Gateways

A Cloud Continuum Research Infrastructure for Distributed CPS Experimentation

The proposed approach separates the research-infrastructure layer, which exposes and manages distributed resources, from the application layer, where Cyber-Physical workflows are organized according to an Edge-Fog-Cloud pattern in which placement, timing, and data provenance are treated as first-class experimental concerns.

Spanergy: Energy-Aware Distributed Tracing for Microservices

Cloud computing is gaining popularity by giving access to seemingly unlimited virtual resources. However, Cloud data centres are built with physical resources and their electricity consumption has been continuously growing over the past decades. Microservices are an important building block of Cloud applications, calling for new solutions to observe their energy consumption. Distributed tracing is widely deployed to diagnose latency and failures in microservice-based applications, yet it does not expose the energy cost of individual end-user requests. Such a gap limits energy-aware debugging, accountability, and control. This paper presents Spanergy, an energy-aware distributed tracing approach that correlates permicroservice power measurements with traces and that attributes measured energy consumption to request segments, i.e. trace spans. We showcase Spanergy with synchronous request chains and asynchronous interactions across microservices. We present a rigorous experimental protocol and statistical analysis plan to quantify overhead and to validate conservation and coverage properties on realistic configurations. Enabling OpenTelemetry tracing increased total experiment energy by 59.1% relative to the uninstrumented baseline, and Spanergy post-processing added 15.2% of the baseline energy. Hence, Spanergy's incremental energy cost is smaller than the energy overhead of enabling tracing itself, making the approach lightweight in practice. Spanergy also reveals that a non-negligible fraction of request energy comes from spans outside the latency-critical path. These results show that energy-aware tracing is feasible at modest overhead and provides actionable insights for energy-efficient microservices.

Dorado: Scaling SmartNIC Session Tables on Commodity DDRs

Dorado is a novel design that scales SmartNIC session tables entirely on inexpensive DDR modules and uses three new techniques that extract commodity DDR performance by restructuring session table layout, decomposing processing pipelines to reduce locking, and scheduling memory accesses to minimize stalls.

The network fabric as a storage orchestrator: a switch-centric architecture

Edge Computing Architectures for Ultra-Low Latency Applications

The evaluation of the proposed architecture through analytical models and simulation-based evaluations shows that the proposed architecture can reduce the latency onto 65 percent of the time relative to the conventional cloud-based architecture, affirm the claim that edge computing is an essential enabler of the next-generation applications that demand deterministic response time, high reliability and localized intelligence.

Spillway: Orchestrating DPU and Host into a Unified vSwitching Fabric

Spillway introduces a DPU-host hybrid data plane that repurposes idle host CPU resources to process spillover traffic when the DPU becomes the bottleneck, and decouples virtual switching capacity from static DPU hardware limits.