Evaluation of mesh routing protocols for wireless community networks

Neumann, Axel; Lopez, Ester; Navarro, Leandro

doi:10.1016/j.comnet.2015.07.018

Cited by 20 publications

(19 citation statements)

References 20 publications

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“…These routing protocols have been further characterized by studying their control overheads, convergence delay, CPU and memory consumption, and stability. Our experimental evaluation results show the relative merits, costs, and limitations of the three protocols [7]. The results show a very lightweight Babel protocol but too expensive in large, dense and changing networks.…”

Section: Routing Protocolsmentioning

confidence: 92%

Advances in wireless community networks with the community-lab testbed

et al. 2016

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Abstract:Beyond traditional telecom providers, citizens and organizations pool their own resources and coordinate in order to build local network infrastructures to address the digital divide in many parts of the world. These crowdsourced network infrastructures can be self-organized and shared by a community for the collective benefit of its members. Several of these networks have developed open, free, and neutral agreements, and are governed as a common-pool resource: Community networks. These are built using a variety of commodity wireless hardware (e.g. Wi-Fi long range point to point links, WiFi and GSM access points, and mesh networks), sometimes optical fibre links, heterogeneous nodes, routing protocols and applications. A group of researchers, developers and community networks developed the CommunityLab testbed, and for the last five years have worked together to overcome obstacles, improve the technologies, tools and operational models being used, as well as model best practices for more effective and sustainable community networks. This article presents the challenges for experimentation, the testbeds built, results, lessons learned and the impact of that work to place wireless community networks as one sustainable way towards an Internet accessible to All.

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Section: Routing Protocolsmentioning

confidence: 92%

Advances in wireless community networks with the community-lab testbed

et al. 2016

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“…The network-aware strategy does not necessarily add the fastest new end if 25: end for 26: return(nodes below threshold, min(bottleneck)) link. It rather evaluates all the candidate neighbor nodes as to how a link to them impacts the performance of the whole network (through the checkStopCondition at line 6 in Algorithm 3 that returns R min ) and then selecting n maximizing this value (lines [11][12][13][14][15]. The fastest link is used as a fallback node selection criterion only if there is a tie.…”

Section: Network Aware Strategymentioning

confidence: 99%

“…One might argue that as the CN grows, the overhead of the routing protocol may be a potential third metric. However, scalability studies for typical mesh routing protocols [13], such as OLSR, Babel, and BMX, show the negligible CPU (less than 10% load in a 10 e router [14]) and memory costs even for large mesh networks with 50-100 or more nodes. Network overhead is small for distance vector protocols and it grows roughly linearly with the nubmer of nodes (less than 200 bit/s for a 25 node network, and still less than 0.5-1 kbit/s for a 100 node network for a typical topology) while Link State protocols (like OLSRv2) generate a higher overhead.…”

Section: Graph Metricsmentioning

confidence: 99%

Towards scalable Community Networks topologies

et al. 2019

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Community Networks (CNs) are grassroots bottom-up initiatives that build local infrastructures, normally using Wi-Fi technology, to bring broadband networking in areas with inadequate offer of traditional infrastructures such as ADSL, FTTx or wide-band cellular (LTE, 5G). Albeit they normally operate as access networks to the Internet, CNs are ad-hoc networks that evolve based on local requirements and constraints, often including additional local services on top of Internet access. These networks grow in highly decentralized manner that radically deviates from the top-down network planning practiced in commercial mobile networks, depending, on the one hand, on the willingness of people to participate, and, on the other hand, on the feasibility of wireless links connecting the houses of potential participants with each other. In this paper, we present a novel methodology and its implementation into an automated tool, which enables the exercise of (light) centralized control to the dynamic and otherwise spontaneous CN growth process. The goal of the methodology is influencing the choices to connect a new node to the CN so that it can grow with more balance and to a larger size. Input to our methodology are open source resources about the physical terrain of the CN deployment area, such as Open Street Map and very detailed (less than 1 m resolution) LIDAR-based data about buildings layout and height, as well as technical descriptions and pricing data about off-the-shelf networking devices that are made available by manufacturers. Data related to demographics can be easily added to refine the environment description. With these data at hand, the tool can estimate the technical and economic feasibility of adding new nodes to the CN and actively assist new CN users in selecting proper equipment and CN node(s) to connect with to improve the CN scalability. We test our methodology in four different areas representing standard territorial characterization categories: urban, suburban, intermediate, and rural. In all four cases our tool shows that CNs scale to much larger size using the assisted, network-aware methodology when compared with de facto practices. Results also show that the CNs deployed with the assisted methodology are more balanced and have a lower per-node cost for the same per-node guaranteed bandwidth. Moreover, this is achieved with fewer devices per node, which means that the network is cheaper to build and easier to maintain.

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“…CNs have characteristic properties, such as, varied latencies between nodes [5], dynamic routing changes and low-capacity devices used for node interconnection. Also, node connectivity is based on mesh routing protocols [6].…”

Section: Background a Wireless Mesh Networkmentioning

confidence: 99%

Gossip-based service monitoring platform for wireless edge cloud computing

Apolónia

Freitag

Navarro

et al. 2017

2017 IEEE 14th International Conference on Networking, Sensing and Control (ICNSC)

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Edge cloud computing proposes to support shared services, by using the infrastructure at the network's edge. An important problem is the monitoring and management of services across the edge environment. Therefore, dissemination and gathering of data is not straightforward, differing from the classic cloud infrastructure. In this paper, we consider the environment of community networks for edge cloud computing, in which the monitoring of cloud services is required. We propose a monitoring platform to collect near real-time data about the services offered in the community network using a gossip-enabled network. We analyze and apply this gossip-enabled network to perform service discovery and information sharing, enabling data dissemination among the community. We implemented our solution as a prototype and used it for collecting service monitoring data from the real operational community network cloud, as a feasible deployment of our solution. By means of emulation and simulation we analyze in different scenarios, the behavior of the gossip overlay solution, and obtain average results regarding information propagation and consistency needs, i.e. in high latency situations, data convergence occurs within minutes.

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Evaluation of mesh routing protocols for wireless community networks

Cited by 20 publications

References 20 publications

Advances in wireless community networks with the community-lab testbed

Advances in wireless community networks with the community-lab testbed

Towards scalable Community Networks topologies

Gossip-based service monitoring platform for wireless edge cloud computing

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