arXiv subjects

Giacomo Giuliari

Publications and source records attributed to Giacomo Giuliari.

5 recordsLinked to original sources

arXiv2026

Walrus: An Efficient Decentralized Storage Network

Decentralized storage faces a fundamental trade-off between replication overhead, recovery efficiency, and security guarantees. Current approaches either rely on full replication, incurring substantial storage costs, or employ erasure-coding schemes that struggle with efficient recovery, especially under high churn. We present Walrus, a decentralized blob storage system that addresses these limitations through multiple technical innovations. At the core of Walrus is Red Stuff, a two-dimensional erasure-coding protocol that achieves high security with only a 4.5x replication factor, while providing self-healing of lost data. This means that recovery is done without centralized coordination and requires bandwidth proportional to the amount of lost data. However, Red Stuff on its own is not sufficient for Walrus, as it is designed with a static set of participants in mind. To further support decentralization, we also introduce a multi-stage epoch-change protocol that efficiently handles storage node churn while maintaining uninterrupted availability during committee transitions. Our system incorporates authenticated data structures to defend against malicious clients and ensure data consistency throughout storage and retrieval. Walrus has been deployed in production since March 2025 and has secured 686 TB of data by July 2026. We conduct an experimental evaluation of the deployed system and demonstrate that Walrus achieves practical performance at scale and outperforms the Arweave decentralized storage system.

cs.DC↗

arXiv2025

Hummingbird: Fast, Flexible, and Fair Inter-Domain Bandwidth Reservations

To realize the long-standing vision of providing quality-of-service (QoS) guarantees on a public Internet, this paper introduces Hummingbird: a lightweight QoS-system that provides fine-grained inter-domain reservations for end hosts. Hummingbird enables flexible and composable reservations with end-to-end guarantees, and addresses an often overlooked, but crucial, aspect of bandwidth-reservation systems: incentivization of network providers. Hummingbird represents bandwidth reservations as tradable assets, allowing markets to emerge. These markets then ensure fair and efficient resource allocation and encourage deployment by remunerating providers. This incentivization is facilitated by decoupling reservations from network identities, which enables novel control-plane mechanisms and allows the design of a control plane based on smart contracts. Hummingbird also provides an efficient reservation data plane, which streamlines the processing on routers and thus simplifies the implementation, deployment, and traffic policing, while maintaining robust security properties. Our prototype implementation demonstrates the efficiency and scalability of Hummingbird's asset-based control plane, and our high-speed software implementation can fill a 160 Gbps link with Hummingbird packets on commodity hardware.

cs.NI↗

arXiv2023

Inter-Domain Routing with Extensible Criteria

With the rapid evolution and diversification of Internet applications, their communication-quality criteria are continuously evolving. To globally optimize communication quality, the Internet's control plane thus needs to optimize inter-domain paths on diverse criteria, and should provide flexibility for adding new criteria or modifying existing ones. However, existing inter-domain routing protocols and proposals satisfy these requirements at best to a limited degree. We propose IREC, an inter-domain routing architecture that enables multi-criteria path optimization with extensible criteria through parallel execution and real-time addition of independent routing algorithms, together with the possibility for end domains to express their desired criteria to the control plane. We show IREC's viability by implementing it on a global testbed, and use simulations on a realistic Internet topology to demonstrate IREC's potential for path optimization in real-world deployments.

cs.NI↗

arXiv2022

Protecting Critical Inter-Domain Communication through Flyover Reservations

To protect against naturally occurring or adversely induced congestion in the Internet, we propose the concept of flyover reservations, a fundamentally new approach for addressing the availability demands of critical low-volume applications. In contrast to path-based reservation systems, flyovers are fine-grained "hop-based" bandwidth reservations on the level of individual autonomous systems. We demonstrate the scalability of this approach experimentally through simulations on large graphs. Moreover, we introduce Helia, a protocol for secure flyover reservation setup and data transmission. We evaluate Helia's performance based on an implementation in DPDK, demonstrating authentication and forwarding of reservation traffic at 160 Gbps. Our security analysis shows that Helia can resist a large variety of powerful attacks against reservation admission and traffic forwarding. Despite its simplicity, Helia outperforms current state-of-the-art reservation systems in many key metrics.

cs.NI↗

arXiv2021

GMA: A Pareto Optimal Distributed Resource-Allocation Algorithm

To address the rising demand for strong packet delivery guarantees in networking, we study a novel way to perform graph resource allocation. We first introduce allocation graphs, in which nodes can independently set local resource limits based on physical constraints or policy decisions. In this scenario we formalize the distributed path-allocation (PAdist) problem, which consists in allocating resources to paths considering only local on-path information -- importantly, not knowing which other paths could have an allocation -- while at the same time achieving the global property of never exceeding available resources. Our core contribution, the global myopic allocation (GMA) algorithm, is a solution to this problem. We prove that GMA can compute unconditional allocations for all paths on a graph, while never over-allocating resources. Further, we prove that GMA is Pareto optimal with respect to the allocation size, and it has linear complexity in the input size. Finally, we show with simulations that this theoretical result could be indeed applied to practical scenarios, as the resulting path allocations are large enough to fit the requirements of practically relevant applications.

cs.NI↗