Routing Multipoint Relay Optimization for the Optimized Link State Routing Protocol Version 2 (OLSRv2)

Clausen, Thomas; Dearlove, Christopher

doi:10.17487/rfc7187

Cited by 7 publications

(5 citation statements)

References 7 publications

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“…Prince is the open source implementation of the Pop-Routing principle for the successor of the OLSRd routing daemon. Recently, the standardization of the second version of OLSR was completed with a set of RFCs [32]- [35] that detail the messages, the metrics and the way this link state protocol works. The collection of these specifications takes the name OLSRv2.…”

Section: B the Architecture Of Princementioning

confidence: 99%

Improving Routing Convergence With Centrality: Theory and Implementation of Pop-Routing

Maccari

Cigno

2018

IEEE/ACM Trans. Networking

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One of the key features of a routing protocol is its ability to recover from link or node failures, recomputing routes efficiently without creating temporary loops. Link-State protocols perform better than Distance-Vector ones and they are often presented as ideal from this perspective. Indeed, in real conditions there is always a trade-off between the overhead due to the periodic generation of control messages and route convergence time. This work formalizes the problem of the choice of timers for control message generation as an optimization problem that minimizes the route convergence time constrained to a constant signaling overhead. The solution requires the knowledge of nodes' centrality in the topology and can be obtained with a computational complexity low enough to allow on-line computation of the timers. Results on both synthetic and real topologies show a significant shrinkage of the transient duration with the consequent performance gain in terms of reduced number of unreachable destinations and routing loops that lead to traffic loss. Next, we present the extension of OLSRv2 with our proposal, named Pop-Routing, and discuss its performance and the stability of centrality metrics in three large-scale real wireless mesh networks. This exhaustive analysis on traces of the topology evolution of real networks for one entire week show that Pop-Routing outperforms the non-enhanced protocol in every situation, even when it runs with sub-optimal timers due to centrality computation on stale information. This situation must be taken into account, as, albeit computationally lightweight, the optimization cannot run in real-time on wireless routers.

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Section: B the Architecture Of Princementioning

confidence: 99%

Improving Routing Convergence With Centrality: Theory and Implementation of Pop-Routing

Maccari

Cigno

2018

IEEE/ACM Trans. Networking

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“…As we use OLSR to exemplify the experiments that can be done with RoRoute, we recall some basic concepts. The reader can find more details in the RFCs that standardize the first [8] and the second version of OLSR [11] and in the relevant literature on its features as convergence speed, Multi-Point-Relays (MPRs) selection, or Fish Eye [4], [12], [13]. OLSR is, as the name states, a link-state routing protocol.…”

Section: Background and Related Workmentioning

confidence: 99%

RoRoute: Tools to experiment with routing protocols in WMNs

Segata

Facchi

Maccari

et al. 2018

2018 14th Annual Conference on Wireless on-Demand Network Systems and Services (WONS)

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Routing in wireless mesh networks is a well studied topic, but indeed, a deeper analysis in real world deployments shows that there are still many open issues, the real world is complex enough so that theoretic design, simulations and emulators can hardly encode it. This paper presents a set of tools and best practices we developed thanks to the WiSHFUL 1 experimental platform that enables the analysis of routing protocols robustness and resilience in face of failures and other impairments when the protocols run in real networks with all the complexity and non-linear interactions that characterize wireless meshes. We present results obtained with Optimized Link State Routing (OLSR) and possible extensions to this protocol that clearly document phenomena that are not visible or implementable in either simulation or emulation environments. This work has been supported by the H2020 GA No. 645274 "Wireless Software and Hardware platforms for Flexible and Unified radio and network controL (WiSHFUL)" with the project "Pop-Routing On WiSHFUL (POPROW)" financed in Open Call 3. 1 WiSHFUL is a European H2020 project supporting an experimental distributed testbed for wireless networks http://www.wishful-project.eu/

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“…Thus, by applying the ant colony algorithm, our principal aim is to migrate a virtual machine, which is considered as large amount of data, by dividing it into small pieces transported through several other nodes to a destination node (edge server). To implement this approach, we will also profit from the advantages the OLSR protocol [7][8]. Following its proactive principle, the control messages exchanged between the nodes serve, on the one hand, to disseminate information on the processing capacities and, on the other hand, to decide on the paths adopted to send the composite pieces of the virtual machine.…”

Section: Introductionmentioning

confidence: 99%

Virtual machine migration in MEC based artificial intelligence technique

Ouacha

Ghmary

2021

IJ-AI

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<span id="docs-internal-guid-bef24e0c-7fff-7c19-7865-2ba99054831c"><span>The whole world is inundated with smaller devices equipped with wireless communication interfaces. At the same time, the amount of data generated by these devices is becoming more important. The smaller size of these devices has the disadvantage of being short of processing and storage resources (memory, processes, energy,...), especially when it needs to process larger amounts of data. In order to overcome this weakness and process massive data, devices must help each other. A low-resource node can delegate the execution of a set of computionly heavy tasks to another machine in the network to process them for it. The machine with sufficient computational resources must also deposit the appropriate environment represented by the adapted virtual machine. Thus, in this paper, in order to migrate the virtual machine to an edge server in a mobile edge computing environment, we have proposed an approach based on artificial intelligence. More specifically, the main idea of this paper is to cut a virtual machine into several small pieces and then send them to an appropriate target node (Edge Server) using the ant colony algorithm. In order to test and prove the effectiveness of our approach, several simulations are made by NS3. The obtained results show that our approach is well adapted to mobile environments.</span></span>

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Routing Multipoint Relay Optimization for the Optimized Link State Routing Protocol Version 2 (OLSRv2)

Abstract: This specification updates the Optimized Link State Routing Protocol version 2 (OLSRv2) with an optimization to improve the selection of routing multipoint relays. The optimization retains full interoperability between implementations of OLSRv2 with and without this optimization.

Cited by 7 publications

References 7 publications

Improving Routing Convergence With Centrality: Theory and Implementation of Pop-Routing

Improving Routing Convergence With Centrality: Theory and Implementation of Pop-Routing

RoRoute: Tools to experiment with routing protocols in WMNs

Virtual machine migration in MEC based artificial intelligence technique

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