content updates, various fixes

site/content/digests/SEC-2024/index.md

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+---
+title: SEC 2024 Digest
+venue: SEC
+year: 2024
+date: '2024-01-01'
+tags: []
+paper_count: 12
+draft: false
+---
+
+12 papers selected.
+
+---
+
+### EdgeCore: Resource Dependency-Aware Multi-Tenant Orchestration for Mobile Edge Clouds
+
+*Amran Haroon*
+
+**TL;DR** — Introduces a multi-tenant edge orchestration system that captures resource dependencies across co-located workloads, demonstrating significant improvements in task completion latency and resource utilization.
+
+---
+
+### Righteous: Automatic Right-Sizing for Complex Edge Deployments
+
+*Aniruddha Rakshit*
+
+**TL;DR** — Presents an automated right-sizing framework for edge deployments that dynamically adjusts resource allocations to match workload demands without manual intervention.
+
+---
+
+### Colibri: Efficient Collection of Fine-Grained Resource Metrics Necessary for Mobile Edge Computing
+
+*Ke-Jou Hsu*
+
+**TL;DR** — Proposes a low-overhead monitoring system for collecting fine-grained resource metrics at the edge, enabling more accurate profiling for MEC scheduling decisions.
+
+---
+
+### HyperDrive: Scheduling Serverless Functions in the Edge-Cloud-Space 3D Continuum
+
+*Thomas W. Pusztai*
+
+**TL;DR** — Extends serverless scheduling across a three-dimensional edge-cloud-space continuum, addressing latency and resource constraints introduced by satellite and terrestrial tiers.
+
+---
+
+### Falcon: Live Reconfiguration for Stateful Stream Processing on the Edge
+
+*Pritish Mishra*
+
+**TL;DR** — Enables live, low-disruption reconfiguration of stateful stream processing pipelines at the edge, minimizing downtime during topology changes.
+
+---
+
+### FusedInf: Efficient Swapping of DNN Models for On-Demand Serverless Inference Services on the Edge
+
+*Sifat Ut Taki*
+
+**TL;DR** — Reduces cold-start latency for serverless DNN inference at the edge by fusing model loading with active inference through selective layer swapping.
+
+---
+
+### EcoEdgeInfer: Dynamically Optimizing Latency and Sustainability for Inference on Edge Devices
+
+*Sri Pramodh Rachuri*
+
+**TL;DR** — Co-optimizes inference latency and energy sustainability on edge devices by dynamically trading off accuracy and hardware utilization under carbon-aware constraints.
+
+---
+
+### Elastic Execution of Multi-Tenant DNNs on Heterogeneous Edge MPSoCs
+
+*Soroush Heidari*
+
+**TL;DR** — Demonstrates elastic, interference-aware co-execution of multiple DNNs across heterogeneous processing elements in edge MPSoCs to maximize throughput and fairness.
+
+---
+
+### Optimizing Edge Offloading Decisions for Object Detection
+
+*Jiaming Qiu*
+
+**TL;DR** — Formulates and solves an online offloading decision problem for object detection that jointly minimizes latency and energy consumption under variable network conditions.
+
+---
+
+### VideoJam: Self-Balancing Architecture for Live Video Analytics
+
+*Youssouph Faye*
+
+**TL;DR** — Proposes a self-balancing edge architecture for live video analytics that dynamically redistributes pipeline stages to prevent bottlenecks under fluctuating camera workloads.
+
+---
+
+### OVIDA: Orchestrator for Video Analytics on Disaggregated Architecture
+
+*Manavjeet Singh*
+
+**TL;DR** — Designs an orchestration layer for disaggregated edge hardware that places and migrates video analytics microservices to exploit spatial locality and heterogeneous accelerators.
+
+---
+
+### TA-ASF: Attention-Sensitive Token Sampling and Fusing for Visual Transformer Models on the Edge
+
+*Junquan Chen*
+
+**TL;DR** — Accelerates Vision Transformer inference at the edge by pruning and fusing attention tokens based on saliency, achieving accuracy-efficiency trade-offs suitable for resource-constrained devices.
+