This paper investigates a network side-channel vulnerability in multi-tenant datacenter fabrics caused by shared congestion behavior, achieving up to 97.3% run-level accuracy in workload inference.

This paper proposes a host-driven method for flowlet balancing using Segment Routing over IPv6 (SRv6), reducing tail latency by 15% and 33% compared to random flowlet balancing and ECMP, respectively.

The paper proposes n-VM, a novel Layer-1 architecture that unifies multiple heterogeneous virtual machines (VMs) onto a shared consensus and state layer, solving cross-chain fragmentation issues.

Proposed ProFlow, a proactive flow-placement framework using distributed telemetry signals and offline-trained RL for identifying precursor congestion conditions and rerouting protected flows in multi…

The ZCube topology, which eliminates path multiplicity and reduces switching hardware, delivers better performance for large model training and inference than traditional multipath datacenter networks…

This paper proposes cross-IP request coalescing to reduce latency in virtualized cloud data centers by submitting multi-device I/O as a single compound request.

This paper proposes CAPS, a scheduling layer for data centers that separates rate computation and packet scheduling, reducing queue occupancy by up to 10x without throughput loss.

The paper introduces an open-source security framework that significantly improves cloud infrastructure security assessment by unifying identity and resource data, reducing false positives, and automa…

This paper argues that idle cores on contemporary multicore processors can return compute capacity and proposes a budget-centric view of service core systems.

The I/O Resource Manager (IORM) is presented as a multi-stage distributed scheduler to maintain consistent performance and enforce global I/O limits in shared-nothing disaggregated storage clusters.

The paper introduces Spandana, an architecture that decouples SLO enforcement from cost optimization in cloud-based online services, achieving high utilization, strict SLO adherence, and cost savings.

SPARK introduces a predictive, traffic-aware autoscaling toolchain for Kubernetes that uses eBPF to enhance security and significantly reduce timeout errors during sudden traffic spikes.

The paper identifies and demonstrates the existence of a covert sublayer, called the Exclusive Network, within the I2P anonymous network, which allows nodes to host services without being discoverable…

The paper proposes a federated, high-throughput stream-processing framework for cross-sector threat detection and automated containment, achieving end-to-end operational convergence within 12-20 secon…

The paper proposes a method to improve the performance of fine-grained offloads on servers by overlapping the offload with other requests using server-side routing.

This paper demonstrates that standard privacy guarantees for multi-tenant RAG services fail when multiple accounts from the same tenant collude, proposing a novel audit protocol to quantify this joint…

This study analyzed I2P's routing topology and found no significant evidence that peer selection is influenced by geographic location, suggesting highly random global mixing.

The paper introduces Kumo, a novel security-focused simulator that enables controlled analysis of resource sharing and scheduling risks in serverless cloud environments, demonstrating that scheduler c…