CERLA-SFC: hierarchical orchestration of cost-efficient, reliable and low-latency SFCs in multi-access edge computing

Hierarchical Scheduler with Adaptive Time-Budget Reallocation for Time-Triggered Edge-Fog-Cloud Architectures

The lack of determinism restricts the integration of safety-critical applications into Edge–Fog–Cloud (EFC) architectures. Existing EFC schedulers are typically designed for dynamic, best-effort operation based on unmanaged resource allocation and elastic virtualization. This paradigm introduces unbounded queueing, resource contention, and timing jitter, making standard schedulers unsuitable for hard-deadline workloads. Moreover, most approaches focus on computational placement, while communication is abstracted or treated as a secondary cost term. As a result, bounded-latency routing and deterministic task execution are rarely co-optimized under a unified timing model. This paper addresses these gaps by utilizing a managed Time-Triggered Edge–Fog–Cloud (TTEFC) architecture that supports safety-critical workloads, orchestrates IEEE Time-Sensitive Networking (TSN) for local intra-domain communication, and uses IETF Deterministic Networking (DetNet) for routed inter-domain paths. On this infrastructure, a hierarchical genetic algorithm (HGA) is proposed to jointly schedule partition-to-execution-location allocation, partition execution order, inter-partition route selection, and negotiated per-partition time budgets that act as temporal boundaries for parallel partition-level optimizers. An adaptive slack reallocation operator redistributes unused temporal slack from over-satisfied partitions to budget-violating partitions, improving feasibility convergence. Experiments on synthetic DAG workloads with 100–500 tasks compare the proposed HGA against HEFT and round-robin baselines. These baselines are included as scoped external references to contextualize the end-to-end scheduling performance of the proposed method. Ablation results show that slack reallocation improves partition-budget feasibility, reaches feasible budget assignments earlier, and produces tighter budget–makespan alignment than feedback-free and static-budget variants. An automotive-characteristic DAG case study further evaluates the method on an application-oriented workload under the same timing and communication assumptions.

QMScaler: A QoS-Constrained Resource-Efficient Microservice Autoscaling Framework for Edge Environments

QMScaler is proposed, a QoS-driven microservice horizontal scaling framework based on Monte Carlo Tree Search (MCTS) that aims to minimize the number of container instances while meeting the QoS requirements of multiple application functions.

UDP-Based Virtual Network Slicing Simulator with Resource Borrowing and Jain Fairness Evaluation

Network slicing is a key enabling technology for fifth-generation (5G) and beyond mobile networks, which enables operators to run multiple logical networks on top of common physical infrastructure while meeting heterogeneous quality-ofservice (QoS) requirements. In this paper, we summarize the design, implementation, and evaluation of a UDP-based virtual network slicing simulator modeling four slices in accordance with 3GPP service types: enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), Massive Machine-Type Communications (mMTC), and a dedicated Best Effort slice. The simulator uses real UDP sockets on localhost in a multi-threaded framework and implements separate admission control per slice, supporting three configurable resourceborrowing modes—none, full, and controlled—in which the primary slices (eMBB, URLLC, mMTC) may borrow unused capacity from the Best Effort slice when their own allocation runs out. QoS metrics including throughput, packet loss ratio, one-way delay, and jitter are collected in a thread-safe manner per slice. Experimental results under controlled borrowing (60 s, 16 nodes, 3 MB per slice, 40% borrow cap) demonstrate activation of the borrowing mechanism with nonzero borrowed-in and borrowedout values, and illustrate the trade-off between primary-slice throughput and Best Effort protection.

Rule-Aware VNE for SDN Resource Management

IsoBFT: A Novel Byzantine Fault-Tolerant Consensus Algorithm for Ultra-Low-Latency Decentralized Networks in Critical Infrastructure and Industrial IoT

-The networks that run operational technology (OT) substations, water treatment plants, oil and gas pipelines, and manufacturing lines are moving from a centralized control to a federated, multi-stakeholder architecture coordinated by permissioned distributed ledgers. Protection and control loops in the electrical grid and other critical infrastructure have protection-relay tripping times, IEC 61850 GOOSE message classes, and SCADA/PMU polling cycles that impose multi-millisecond to sub-second deadlines on protection and control operations, while Byzantine fault-tolerant (BFT) consensus protocols like PBFT, Tendermint, HotStuff, and HoneyBadgerBFT were designed for settlement workloads that can tolerate hundreds of milliseconds to seconds of latency. In this paper, we survey four representative BFT families, discuss their structural latency and scalability constraints for OT deployment, and introduce a hybrid consensus algorithm called IsoBFT (Isochronous Byzantine Fault Tolerance), which combines an optimistic single-round-trip fast path with a PBFT-style fallback mechanism based on a network-stability monitor, and elects a small rotating committee using a verifiable random function (VRF). A formal system model, safety/liveness/termination proof, and security analysis for eight attack classes are provided, with a proposition quantifying the degradation of the practical availability of the safety guarantee when the global Byzantine fraction is approaching one-third. Using realistic Modbus/DNP3/IEC 61850 OT traffic, the discrete-event simulation of the design IsoBFT managed to execute realistic workloads with median consensus latency ranging from 4.90ms at n = 10-50 to 9.17-11.26ms at n = 100 and n = 500, remaining competitive with or better than PBFT and Tendermint across this range. Committee-bounded communication overhead stayed essentially flat with respect to the number of validators from n = 10 to n = 50, but newly completed runs at n = 100 and n = 500 (n = 200 still outstanding) show overhead growing faster than the quadratic scaling of PBFT and Tendermint over that range, together with a heavy P95/P99 latency tail not present at smaller scale; this discrepancy with the theoretical scale-independence result is reported and discussed rather than resolved. IsoBFT could reduce the median latency by approximately 81% and 56% under up to 33% Byzantine faults compared to HotStuff and HoneyBadgerBFT, respectively, at n = 10-50, while maintaining the safety of the system; a Byzantine-resilience sweep at n = 100 shows a narrower advantage over PBFT/Tendermint than at smaller scale.

Proximal Policy Optimization for Latency-Aware Service Function Chain Placement in Edge-Enabled Networks

This work proposes an enhanced Proximal Policy Optimization (PPO) framework for resource-aware and latency-sensitive SFC placement in edge-enabled networks, and demonstrates the applicability of the proposed framework in mission-critical and latency-sensitive service environments.