arXiv subjects

Novak Boškov

Publications and source records attributed to Novak Boškov.

5 recordsLinked to original sources

arXiv2026

Safety Signals to Verify NetOps Agents with Action-Level Granularity

Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. While agents have proven their value in incident summarization and telemetry signal extraction, their effectiveness as autonomous control-loop engines heavily relies on their long-horizon reliability. One such setting is the datacenter fabric, where an agent must respond to alarms and operator intents while abstaining from high-risk actions that may cause or extend downtime. Abstention, however, presupposes that an action's impact is known pre-execution, which necessitates a per-action ground truth that NetOps agent benchmarks do not provide. We construct such a ground truth for the network repair task of NetArena. A symbolic replay of the emulated network, validated against the environment at every turn, yields the exact value of every action. From the action-level value, we derive two pre-execution targets, namely whether an action reduces the repair distance (progress) and whether it increases it (harm). We show across 10 agent models, that agent verifiers leveraging internal signals predict both harm and progress more reliably than a baseline using observable signals only. Perspectively, we aim to use these signals as safety feedback to an agent harness to abstain from risky actions and protect the target system.

cs.AI↗

arXiv2026

CSR-RAG: An Efficient Retrieval System for Text-to-SQL on the Enterprise Scale

Natural language to SQL translation (Text-to-SQL) is one of the long-standing problems that has recently benefited from advances in Large Language Models (LLMs). While most academic Text-to-SQL benchmarks request schema description as a part of natural language input, enterprise-scale applications often require table retrieval before SQL query generation. To address this need, we propose a novel hybrid Retrieval Augmented Generation (RAG) system consisting of contextual, structural, and relational retrieval (CSR-RAG) to achieve computationally efficient yet sufficiently accurate retrieval for enterprise-scale databases. Through extensive enterprise benchmarks, we demonstrate that CSR-RAG achieves up to 40% precision and over 80% recall while incurring a negligible average query generation latency of only 30ms on commodity data center hardware, which makes it appropriate for modern LLM-based enterprise-scale systems.

cs.CL↗

arXiv2025

A Ranking Framework for Network Resource Allocation and Scheduling via Hypergraphs

Resource allocation and scheduling are a common problem in various distributed systems. Although widely studied, the state-of-the-art solutions either do not scale or lack the expressive power to capture the most complex instances of the problem. To that end, we present a mathematical framework for hypergraph ranking and analysis, unifying graph theory, lattice theory, and semantic analysis. In our fundamental theorem, we prove the existence of partial order on entities of hypergraphs, extending traditional hypergraph analysis by introducing semantic operators that capture relationships between vertices and hyperedges. Within the boundaries of our framework, we introduce an algorithm to rank the node-hyperedge pairs with respect to the captured semantics. The strength of our approach lies in its applicability to complex ranking problems that can be modeled as hypergraphs, including network resource allocation, task scheduling, and table selection in Text-to-SQL. Through simulations, we demonstrate that our framework delivers nearly optimal problem solutions at a superior run time performance.

cs.DS↗

arXiv2023

Enabling Cost-Benefit Analysis of Data Sync Protocols

The problem of data synchronization arises in networked applications that require some measure of consistency. Indeed data synchronization approaches have demonstrated a significant potential for improving performance in various applications ranging from distributed ledgers to fog-enabled storage offloading for IoT. Although several protocols for data sets synchronization have been proposed over the years, there is currently no widespread utility implementing them, unlike the popular Rsync utility available for file synchronization. To that end, we describe a new middleware called GenSync that abstracts the subtleties of the state-of-the-art data synchronization protocols, allows users to choose protocols based on a comparative evaluation under realistic system conditions, and seamlessly integrate protocols in existing applications through a public API. We showcase GenSync through a case study, in which we integrate it into one of the world's largest wireless emulators and compare the performance of its included protocols.

cs.DC↗

arXiv2023

SREP: Out-Of-Band Sync of Transaction Pools for Large-Scale Blockchains

Synchronization of transaction pools (mempools) has shown potential for improving the performance and block propagation delay of state-of-the-art blockchains. Indeed, various heuristics have been proposed in the literature to this end, all of which incorporate exchanges of unconfirmed transactions into their block propagation protocol. In this work, we take a different approach, maintaining transaction synchronization outside (and independently) of the block propagation channel. In the process, we formalize the synchronization problem within a graph theoretic framework and introduce a novel algorithm (SREP - Set Reconciliation-Enhanced Propagation) with quantifiable guarantees. We analyze the algorithm's performance for various realistic network topologies, and show that it converges on any connected graph in a number of steps that is bounded by the diameter of the graph. We confirm our analytical findings through extensive simulations that include comparison with MempoolSync, a recent approach from the literature. Our simulations show that SREP incurs reasonable overall bandwidth overhead and, unlike MempoolSync, scales gracefully with the size of the network.

cs.DC↗