SearcharxivSearch

arXiv · 1410.0337

Cross layer Interaction Models for SCTP and OLSR

Abstract

The evolution from wired system to the wireless environment opens a set of challenge for the improvement of the wireless system performances because of many of their weakness compared to wired networks. To achieve this goal, cross layer techniques are used to facilitate the sharing of information between the layers of the OSI model. In some precedent works, the Reverse Cross Layer (RCL) method has been proposed to facilitate the design of cross layer conceptual models. The method has the advantage to highlight the impact of each cross layer interaction on each protocol in order to update its source code and to describe the intuitive gains that can be achieve. The method may be applied to a given protocol stack or to an existent cross layer model to integrate new interactions. In this paper, we are applying the RCL method on the stack that uses the Stream Control Transport Protocol (SCTP) at the transport layer and the Optimized Link State Routing (OLSR) at the network layer. Cross layer conceptual models are produced based on new cross layer interactions that are proposed to populate the environment subsystem built with the application of the RCL method. The improvement of the environment subsystem is specified through the performance gains provide by the new interactions. The implementation of the interactions that impact the SCTP protocol is described in the Interaction Description Array. After the introduction, Section II of this paper presents an overview of the SCTP protocol. Section III is related to the overview of the OLSR protocol. Section IV is used for the application of the RCL method and the different interaction arrays it generates. Section V presents the improvement of the environment subsystem and the definition of the performance gain of each Cross Layer Atomic Action (CLAA).

Explore related subjects

Keep this discovery

BibTeXRIS

Mahmadou Issoufou Tiado, Riadh Dhaou, André-Luc Beylot. 2014-10-01. Cross layer Interaction Models for SCTP and OLSR. https://arxiv.org/abs/1410.0337

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