SearcharxivSearch

arXiv · 1905.01137

VeriVANca: An Actor-Based Framework for Formal Verification of Warning Message Dissemination Schemes in VANETs

Abstract

One of the applications of vehicular ad-hoc networks is warning message dissemination among vehicles in dangerous situations to prevent more damage. The only communication mechanism for message dissemination is multi-hop broadcast; in which, forwarding a received message have to be regulated using a scheme regarding the selection of forwarding nodes. When analyzing these schemes, simulation-based frameworks fail to provide guaranteed analysis results due to the high level of concurrency in this application. Therefore, there is a need to use model checking approaches for achieving reliable results. In this paper, we have developed a framework called VeriVANca, to provide model checking facilities for the analysis of warning message dissemination schemes in VANETs. To this end, an actor-based modeling language, Rebeca, is used which is equipped with a variety of model checking engines. To illustrate the applicability of VeriVANca, modeling and analysis of two warning message dissemination schemes are presented. Some scenarios for these schemes are presented to show that concurrent behaviors of the system components may cause uncertainty in both behavior and performance which may not be detected by simulation-based techniques. Furthermore, the scalability of VeriVANca is examined by analyzing a middle-sized model.

Explore related subjects

Keep this discovery

BibTeXRIS

Farnaz Yousefi, Ehsan Khamespanah, Mohammed Gharib, Marjan Sirjani, Ali Movaghar. 2019-04-16. VeriVANca: An Actor-Based Framework for Formal Verification of Warning Message Dissemination Schemes in VANETs. https://arxiv.org/abs/1905.01137

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Message-Level Scheduling for RLNC-Coded Multi-Source Traffic

This paper studies weighted decoding-delay minimization for multiple RLNC-coded message streams that compete for finite processing capacity at a destination. Packet arrivals are exogenous, while the scheduler only determines the processing order of packets already available at the destination. A trace-conditioned offline scheduling formulation shows that a batch-release subclass is strongly NP-hard even with a single processing unit. Message-Aware Innovation-Deficit Scheduling (MAIDS) is then developed to prioritize each serviceable message according to its weight and remaining decoding deficit. For a single processing unit, MAIDS is shown to be exactly optimal under nonblocking progressive arrivals with equal weights and under common activation with arbitrary positive weights, while the unrestricted weighted online problem admits no universal deterministic $O(1)$ competitive ratio. Simulation results on streaming and batch benchmarks show that MAIDS consistently reduces weighted decoding delay relative to the tested baselines, remains close to the offline optimum on average, and recovers the predicted exact performance boundaries.

cs.NI

The Towers Were Standing: A Cause Decomposition of Cellular Outages During Hurricane Helene

Hurricane Helene produced the largest absolute cell-site outage in the public FCC record, peaking at 4562 sites. The conventional model is physical: towers destroyed. Helene did destroy over 1700 miles of fibre, but almost none of it was cell sites. We present the first cause-decomposed study of the FCC's Disaster Information Reporting System, reconstructing 80 state-days and 580 county-days from 24 daily filings by two reconciled independent extractions. Damage to cell sites is negligible: 1.1% of attributed cell-site-days across six states, at most 3.8% anywhere. The sites were standing. What took them out divides by terrain: pooled, power dominates at 63.2%, but in mountainous North Carolina severed transport (backhaul) reaches 52.2% against 47.3%, and in Tennessee 69.9%. North Carolina's transport share rises from 7.0% to 85.0% across the event (\r{ho} = 0.92). Seventeen days after landfall, on 15 October, 47 sites lost transport across six contiguous North Carolina counties with no rainfall, no power loss, no damage, and recovery by the next report. Independent active-probe measurement corroborates it: responsive /24s fall 1.02% for twelve hours while Tennessee stays flat. We release the dataset. Backup power is the standard resilience investment; here it addresses the smaller half of the problem.

cs.NI

terms.txt: A Consent and Compensation Protocol for Agentic Web Access

The open web ran on an unwritten bargain: sites admitted crawlers, and search engines sent visitors back. Public measurements show that bargain breaking under AI crawlers and agents. Automated clients now make up most requests, training dominates Cloudflare-classified crawling, and the largest AI platforms fetch thousands of pages for each visitor they return. The web's common control, robots.txt, cannot express identity, purpose, terms, or price, can be circumvented, and newer alternatives are largely proprietary CDN features. We specify terms.txt, a robots.txt-style file for per-path, per-purpose machine-access terms, plus an origin-enforced exchange using Web Bot Auth signatures, signed intent, delegation tokens, HTTP 402 negotiation, and signed receipts. We define what the exchange can enforce, audit, and leave to contract. A dependency-free implementation adds 0.20 to 0.65 ms per request on one vCPU.

cs.NI