HMAN: Hierarchical Monitoring for Ad Hoc Network

Battat, Nadia; Kheddouci, Hamamache

doi:10.1109/euc.2011.42

Cited by 10 publications

(6 citation statements)

References 12 publications

(11 reference statements)

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“…A node in a MANET normally doesn't communicate with a neighboring peer unless both nodes succeed to capture each others' beacons. Therefore, any sort of feedback in MANET, in particular loss-rate status that relates to video transmission, should in our judgment rely on overloading in-place management frames, such as beacon frames or MANET routing frames [4] such as PERQ and PREP in 802.11s's HWMP [5].…”

Section: Related Workmentioning

confidence: 99%

Modeling adaptive rate video transmission in Wi-Fi MANET

Ben‐Moshe

Berliner

Branderud

et al. 2012

Proceedings of the 7th ACM Workshop on Performance Monitoring and Measurement of Heterogeneous Wireless and Wired Networks

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Broadcast scenarios, such as streaming HD video to one or many clients, seem as a natural fit for the wireless medium, and indeed the two couple well in satellite TV networks. The same kind of compatibility with broadcast may be expected from modern Wi-Fi networks featuring extended-range Access Points (APs). Yet, the 802.11 protocol was not designed with video broadcast in mind, and therefore lacks crucial broadcast mechanisms, most notably, dynamic rateadaptation and efficient Forward Error Correction (FEC). For satisfactory Quality of Experience (QoE), it is important that the video stream reaches its destination in time and with a minimal amount of errors. Therefore, in live broadcast, retransmissions should generally be avoided, a goal that can only be accomplished using a reliable feedback mechanism that informs transmitters of current packet loss rates.In this paper we present a live video transmission model for Wi-Fi MANET networks that dynamically adapts the streams' FEC overhead, by utilizing the fact that in WiFi MANET all nodes are periodically broadcasting beacon frames. By overloading these beacons with packet loss-rate information, the transmitting nodes are able to adapt the rate of FEC-encoded redundant packets, the transmission rate and the modulation scheme, without relying on Wi-Fi ACK frames that are costly and inadequate for broadcast scenarios. Moreover, using beacon frames that are part of the 802.11 standard eliminates the overhead associated with proprietary feedback packets in alternative models of broadcast over Wi-Fi. Thus, our suggested scheme enables Wi-Fi MANET networks to reliably transmit live video over multiple hops. Using NS-3 simulations we validate that our FEC adaptation model is applicative and efficient over one hop. Thereafter, we demonstrate via theoretical analysis the tolerable delay associated with the transmission of video over multiple hops using a pipeline model.

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Section: Related Workmentioning

confidence: 99%

Modeling adaptive rate video transmission in Wi-Fi MANET

Ben‐Moshe

Berliner

Branderud

et al. 2012

Proceedings of the 7th ACM Workshop on Performance Monitoring and Measurement of Heterogeneous Wireless and Wired Networks

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“…Load balancing is an important factor in resource constrained environments such as the envisaged scenario. HMAN by Battat and Kheddouci [23] establishes a three-tiered topology based on weights of nodes. Those weights incorporate factors, such as energy consummation, the distance to other nodes, and the storage capacity left.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Monitoring for Mobile Networks in Challenging Environments

Richerzhagen

Stingl

Richerzhagen

et al. 2015

2015 24th International Conference on Computer Communication and Networks (ICCCN)

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The increasing capabilities of mobile communication devices are changing the way people interconnect today. Similar trends in the communication technology domain are leading to the expectation that data and media are available anytime and everywhere. A result is an increasing load on communication networks. In dynamic mobile networks that particularly rely on wireless communication such data requirements paired with environmental conditions like mobility or node density increase the risk of network failure. Consequently, monitoring is crucial in mobile networks to ensure reliable and efficient operation. Current monitoring mechanisms mostly rely on a static architecture and exhibit problems to handle the changes of mobile networks and environmental conditions over time. In this paper, an adaptive monitoring mechanism is presented to overcome these limitations. The mechanism exploits the connectivity and resource characteristics of mobile communication devices to (i) reconfigure its monitoring topology and (ii) adapt to changes of mobile networks and environmental conditions. Through evaluations we show that our proposed solution reduces the achieved relative monitoring error by a factor of six and represents a robust and reliable monitoring mechanism for these challenging environments.

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“…Among existing decentralized monitoring mechanisms for MANETs, approaches are discussed herein, which operate on clusters, as classified in [2]. The approaches integrate all nodes into the monitoring process but divide them into measuring and collecting entities, which are arranged in a hierarchy.…”

Section: B Decentralized Monitoring In Manetsmentioning

confidence: 99%

“…To establish the hierarchy, Kwak et al [14] create proximitybased clusters, where the elected heads are organized in an overlay. HMAN [2] uses a mathematical function to create the hierarchy, incorporating several aspects of a node (e.g. number of neighbors).…”

Section: B Decentralized Monitoring In Manetsmentioning

confidence: 99%

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BlockTree: Location-aware decentralized monitoring in mobile ad hoc networks

Stingl

Groß

Nobach

et al. 2013

38th Annual IEEE Conference on Local Computer Networks

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Mobile ad hoc networks (MANETs) represent a crucial alternative to deploy applications in urban areas. In those networks, it is inevitable that all nodes are aware of the current system state to adapt their behavior according to the varying conditions. However, existing decentralized monitoring solutions for MANETs only locate the required information at a set of nodes, which are in charge of serving the remaining network, while the availability of information depends on the accessibility of those nodes. To avoid these limitations, BlockTree is a novel, fully decentralized monitoring approach for MANETs that leverages each node's resources to capture and distribute the system state to all nodes. Exploiting its hierarchical structure, BlockTree introduces the concept of location-aware monitoring delivering detailed as well as aggregated information. Through robust communication paired with the stateless design, BlockTree provides accurate results in the presence of fast moving nodes or over an error-prone communication medium.

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HMAN: Hierarchical Monitoring for Ad Hoc Network

Cited by 10 publications

References 12 publications

Modeling adaptive rate video transmission in Wi-Fi MANET

Modeling adaptive rate video transmission in Wi-Fi MANET

Adaptive Monitoring for Mobile Networks in Challenging Environments

BlockTree: Location-aware decentralized monitoring in mobile ad hoc networks

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