publish-assistant/site/data/cloud-edge/papers/TCC-2024-digest.yaml

venue: TCC
year: 2024
selected:
  - title: "FaaSCtrl: A Comprehensive-Latency Controller for Serverless Platforms"
    authors:
    - Abhisek Panda
    - Smruti R. Sarangi
    tldr: "FaaSCtrl is a feedback-control system for serverless platforms that jointly manages cold-start, queuing, and execution latency to meet end-to-end SLOs."
    why_notable: "One of the few serverless controllers that addresses all three latency components together, providing a principled alternative to ad-hoc autoscaling heuristics."

  - title: "FUSIONIZE++: Improving Serverless Application Performance Using Dynamic Task Inlining and Infrastructure Optimization"
    authors:
    - Trever Schirmer
    - Joel Scheuner
    - Tobias Pfandzelter
    - David Bermbach
    tldr: "FUSIONIZE++ dynamically fuses serverless functions at runtime and co-optimizes infrastructure selection to cut invocation overhead and cost."
    why_notable: "Demonstrates concrete end-to-end performance gains from function fusion in real serverless deployments, directly relevant to practitioners optimizing FaaS pipelines."

  - title: "BaaSLess: Backend-as-a-Service (BaaS)-Enabled Workflows in Federated Serverless Infrastructures"
    authors:
    - Thomas Larcher
    - Philipp Gritsch
    - Stefan Nastic
    - Sashko Ristov
    tldr: "BaaSLess integrates BaaS capabilities into serverless workflow execution across federated multi-provider infrastructures, enabling stateful cross-cloud function orchestration."
    why_notable: "Addresses the underexplored intersection of BaaS, serverless, and federation, offering a practical blueprint for multi-cloud serverless applications."

  - title: "Slim and Fast: Low-Overhead Container Overlay Network With Fast Connection Setup"
    authors:
    - Fusheng Lin
    - Xin Zhang 0117
    - Guo Chen 0001
    - Li Chen 0008
    - Kenli Li 0001
    - Hongbo Jiang 0001
    tldr: "A redesigned container overlay network that minimizes control-plane overhead and dramatically reduces connection setup latency for microservice-dense deployments."
    why_notable: "The implementation targets real Kubernetes environments and directly improves east-west latency for microservices at scale."

  - title: "Trustless Collaborative Cloud Federation"
    authors:
    - Bishakh Chandra Ghosh
    - Sandip Chakraborty 0001
    tldr: "A blockchain-backed protocol that enables resource sharing across competing cloud providers without requiring a trusted third party."
    why_notable: "Tackles the fundamental trust barrier in multi-cloud federation with a practical, decentralized design that avoids provider lock-in."

  - title: "An Adaptive Cloud Resource Quota Scheme Based on Dynamic Portraits and Task-Resource Matching"
    authors:
    - Zuodong Jin
    - Dan Tao
    - Peng Qi 0006
    - Ruipeng Gao
    tldr: "Builds dynamic workload portraits per tenant and matches them to resource quotas in real time, improving utilization while respecting SLAs in IaaS/PaaS clouds."
    why_notable: "Moves beyond static quota assignment with a data-driven approach validated on production cloud workload traces."

  - title: "Aggregate Monitoring for Geo-Distributed Kubernetes Cluster Federations"
    authors:
    - Chih-Kai Huang 0001
    - Guillaume Pierre
    tldr: "Proposes a scalable monitoring architecture for Kubernetes federations that aggregates metrics across geo-distributed clusters with low overhead."
    why_notable: "Practical multi-cloud observability is rarely addressed at the federation layer; this work provides a deployable solution with measured performance on real clusters."

  - title: "Root Cause Analysis for Cloud-Native Applications"
    authors:
    - Bartosz Zurkowski
    - Krzysztof Zielinski
    tldr: "A graph-based RCA framework for microservice architectures that correlates traces, metrics, and logs to pinpoint fault origins in cloud-native deployments."
    why_notable: "Directly applicable to production microservice operations, offering automated diagnosis that reduces mean time to recovery in complex service graphs."

  - title: "RAM: A Resource-Aware DDoS Attack Mitigation Framework in Clouds"
    authors:
    - Fangyuan Xing
    - Fei Tong 0001
    - Jialong Yang
    - Guang Cheng 0001
    - Shibo He
    tldr: "RAM dynamically allocates cloud resources for DDoS mitigation based on attack intensity, balancing protection effectiveness against resource cost."
    why_notable: "Combines attack detection and elastic resource provisioning in a single framework, making it immediately relevant for cloud security operations."

  - title: "Enabling Multi-Layer Threat Analysis in Dynamic Cloud Environments"
    authors:
    - Salman Manzoor
    - Antonios Gouglidis
    - Matthew Bradbury
    - Neeraj Suri
    tldr: "A multi-layer threat analysis system that correlates security events across IaaS, PaaS, and application layers to detect composite attacks in dynamic cloud deployments."
    why_notable: "Addresses the gap between per-layer security tools and cross-layer attack detection, which is critical for securing modern cloud stacks."

  - title: "Hyperion: Hardware-Based High-Performance and Secure System for Container Networks"
    authors:
    - Myoungsung You
    - Minjae Seo
    - Jaehan Kim
    - Seungwon Shin 0001
    - Jaehyun Nam
    tldr: "Hyperion offloads container network security enforcement to programmable hardware, achieving line-rate packet processing with strong isolation guarantees."
    why_notable: "Shows that hardware offload can simultaneously improve both throughput and security in container networking, with real implementation results."

  - title: "D-STACK: High Throughput DNN Inference by Effective Multiplexing and Spatio-Temporal Scheduling of GPUs"
    authors:
    - Aditya Dhakal
    - Sameer G. Kulkarni
    - K. K. Ramakrishnan
    tldr: "D-STACK multiplexes multiple DNN inference jobs on shared GPUs via spatio-temporal scheduling, significantly increasing throughput without latency SLO violations."
    why_notable: "Addresses a critical cloud resource management challenge for AI inference services, with a real system implementation and evaluation against production workloads."