OLSRp: Predicting Control Information to Achieve Scalability in OLSR Ad Hoc Networks

Medina, Esunly; Meseguer, Roc; Molina, Carlos; Royo, Dolors

doi:10.1007/978-3-642-21444-8_20

Cited by 8 publications

(13 citation statements)

References 10 publications

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“…Medina et al [12] showed that Topology Control (TC) messages, which are used to distribute information about the local neighborhood in the network, tend to be similar over longer periods. This indicates that the neighborhood has not changed and thus also similar HELLOs were exchanged.…”

Section: B Refresh Methodsmentioning

confidence: 99%

Reducing MANET neighborhood discovery overhead

Ernst

Jopen

Bartelt

2014

39th Annual IEEE Conference on Local Computer Networks

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Routing in MANETs still is a challenging task. Especially for proactive protocols where nodes periodically send control messages, a vast amount of the available data rate is used for link detection and the dissemination of topology information. Numerous enhancements to existing routing protocols to reduce the overhead caused by control messages have been proposed. Most of them use complex algorithms or keep track of previous messages. Due to the complexity and sometimes requirements for special hardware or information sources, none of these extensions are widely used. Therefore, we propose two extensions which are simple to implement yet provide significant overhead reduction for typical control messages. The first extension removes unnecessary bytes and redundancy from control messages. The second extension introduces smaller messages sent as replacements when the information did not change since the last message. Both extensions can be used in parallel or individually, providing a good amount of overhead reduction while being simple to implement and integrate

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Section: B Refresh Methodsmentioning

confidence: 99%

Reducing MANET neighborhood discovery overhead

Ernst

Jopen

Bartelt

2014

39th Annual IEEE Conference on Local Computer Networks

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“…These communication limitations have frequently been addressed using mobile ad hoc or opportunistic networks, as well as routing protocols on these networks [4][5][6]. These networks have low bandwidth and their topology is highly dynamic, and as such, they require the exchange of an goals, e.g., to support message delivery in mobile ad hoc networks (MANETs) [25][26][27][28], reduce the traffic [29][30][31] and keep the energy consumption in these infrastructures under control [32][33][34].…”

Section: Introductionmentioning

confidence: 99%

“…Concerning the prediction of topology propagation (TP) messages based on historical information, in previous works, the authors have shown that the traffic generated by a link-state routing protocol, like OLSR [35], grows almost exponentially with the number of nodes when different node densities are considered in the analysis [29,30]. Therefore, a network with a large number of nodes requires the exchange of a huge amount of TP messages to inform the nodes about the topology changes.…”

Section: Introductionmentioning

confidence: 99%

“…These messages not only overload the communication links, but also increase the energy consumption of the nodes. The authors have also shown that the problem of delivering so much control information through the network can be addressed using predictions [29,31]. Particularly, the OLSRp protocol was proposed to eliminate redundant control information, and thus, reduce CPU and energy consumption in MANETs.…”

Section: Introductionmentioning

confidence: 99%

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Predicting Topology Propagation Messages in Mobile Ad Hoc Networks: The Value of History

Millan

Aliagas

Molina

et al. 2019

Sensors

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The mobile ad hoc communication in highly dynamic scenarios, like urban evacuations or search-and-rescue processes, plays a key role in coordinating the activities performed by the participants. Particularly, counting on message routing enhances the communication capability among these actors. Given the high dynamism of these networks and their low bandwidth, having mechanisms to predict the network topology offers several potential advantages; e.g., to reduce the number of topology propagation messages delivered through the network, the consumption of resources in the nodes and the amount of redundant retransmissions. Most strategies reported in the literature to perform these predictions are limited to support high mobility, consume a large amount of resources or require training. In order to contribute towards addressing that challenge, this paper presents a history-based predictor (HBP), which is a prediction strategy based on the assumption that some topological changes in these networks have happened before in the past, therefore, the predictor can take advantage of these patterns following a simple and low-cost approach. The article extends a previous proposal of the authors and evaluates its impact in highly mobile scenarios through the implementation of a real predictor for the optimized link state routing (OLSR) protocol. The use of this predictor, named OLSR-HBP, shows a reduction of 40-55% of topology propagation messages compared to the regular OLSR protocol. Moreover, the use of this predictor has a low cost in terms of CPU and memory consumption, and it can also be used with other routing protocols.Sensors 2020, 20, 24 2 of 24 important number of topology propagation (TP) messages to keep the delivery of regular messages under control. The exchange of TP messages helps reduce the probability of overflowing the network with regular messages that do not reach the destination, rendering the communication system useless at supporting the coordination of the emergency response activities. Provided that many of these communication systems involve mobile ad hoc networks, the routing protocols used to support interactions among nodes (i.e., the first responders) must be simple, efficient and reliable and have the capability of quickly adapting themselves to changes in the network topology [7-10]. Thus, these protocols intend to maximize the reachability of the target nodes, by consuming as little energy from the network as possible.Regardless of the extensive research done in the area, addressing this communication challenge, considering the previous constraints, is still an open issue. Some recent proposals try to deal with this challenge using deep learning in static or quasi-static networks [11]. Although deep learning techniques have shown positive results, these approaches are quite limited when used in mobile scenarios, like emergency responses. Moreover, they require a previous training stage to generate the network model. Novel solutions are therefore required to reduce the number of TP messages ex...

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“…Such a proposal was based on Optimized Link State Routing with prediction (OLSRp) [8] and it included adaptations to be used on a HWSN. The evaluation of such a topology prediction strategy showed promising results in terms of energy savings; however it considered only a particular work scenario.…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks

Meseguer

Molina

Ochoa

et al. 2014

Sensors

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The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices' battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.

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OLSRp: Predicting Control Information to Achieve Scalability in OLSR Ad Hoc Networks

Cited by 8 publications

References 10 publications

Reducing MANET neighborhood discovery overhead

Reducing MANET neighborhood discovery overhead

Predicting Topology Propagation Messages in Mobile Ad Hoc Networks: The Value of History

Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks

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