Robust Flow Admission Control and Routing for Mobile Ad Hoc Networks

Zhang, Runhe; Rubin, I.

doi:10.1109/milcom.2006.302327

Cited by 10 publications

(22 citation statements)

References 10 publications

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“…However, in most cases, the methods presented are still more accurate than the predictions offered by the simple πr 2 /A (disk-covering) model that researchers often use (e.g. [11], [14]) to estimate the chance of a node to be within another's transmission range r in an area A, and hence other connectivity-related properties.…”

Section: Per-node Capacity Predictionmentioning

confidence: 99%

“…The reciprocal of the fraction of the area covered by a node's cs-range gives an estimation for the spatial reuse factor (SRF) of the network. The SRF represents the number of simultaneous transmissions that may occur within a CSMA/CA-based network (see, for example, [14]). Again, Figure 2.…”

Section: Per-node Capacity Predictionmentioning

confidence: 99%

“…For networks of multi-rate-capable nodes, obviously, the SRF should just be used to provide an estimate of the average fraction of channel time available to a node, instead. The work in [14] is an example of the disk-covering approach being used, with RWPMM-governed nodes, to predict the SRF and hence the network capacity. We compare this approach, for uniformly-distributed nodes (as in the paused RWPMM or the RWkRMM), to the method of predicting the per-node transmission capacity using (7).…”

Section: Per-node Capacity Predictionmentioning

confidence: 99%

“…for calculating the network capacity as C · SRF , we then divided this by the average route length (as in [14]), to yield an estimate of the end-to-end capacity of the network. This estimate lay between 700kbps and 850kbps, depending on the transmission/cs-range.…”

Section: Per-node Capacity Predictionmentioning

confidence: 99%

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Connectivity-Related Properties of Mobile Nodes Obeying the Random Walk and Random Waypoint Mobility Models

Hanzo

Tafazolli

2008

VTC Spring 2008 - IEEE Vehicular Technology Conference

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Abstract-This paper independently derives the probability of any pair of uniformly-distributed nodes to be within transmission range of each other in a square-shaped area. It then explores, via simulation, some new applications of this expression. The applications are relevant for scenarios where node mobility is governed by the popular random walk or random waypoint mobility models (RWkMM and RWPMM). Under the RWPMM with pausing, at any time, some nodes will be mobile and some stationary. The positions of mobile nodes are drawn from a nonuniform distribution, while a uniform distribution applies to the stationary nodes. In various forms of the RWkMM, the node spatial distribution is uniform in its steady state. The studied applications include calculating the expected node degree and the node isolation probability. Simulation results show that the considered model is able to predict these connectivity-related properties near-perfectly under a paused RWPMM and with all mobility scenarios under the RWk with reflection model. With the RWPMM, the accuracy decreases as the fraction of time the nodes spend moving increases. However, it is still generally better than the simple πr 2 /A disk-covering model, which is often employed for calculating network connectivityrelated properties in ad hoc networks. Further application of the considered methods is exemplified by calculation of an accurate upper bound on the per-node transmission capacity for contention-based networks, when the nodes are uniformly distributed.

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Section: Per-node Capacity Predictionmentioning

confidence: 99%

Section: Per-node Capacity Predictionmentioning

confidence: 99%

Section: Per-node Capacity Predictionmentioning

confidence: 99%

Section: Per-node Capacity Predictionmentioning

confidence: 99%

See 2 more Smart Citations

Connectivity-Related Properties of Mobile Nodes Obeying the Random Walk and Random Waypoint Mobility Models

Hanzo

Tafazolli

2008

VTC Spring 2008 - IEEE Vehicular Technology Conference

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“…Details of these methods will be presented in the sections to come. INSIGNIA [33] MPARC [36] PDAC [39] QPART [43] INORA [32] QoS−AODV [19] CACP [11] StAC [12] AAC [25] ACOR [27] AQOR [18] CCAODV [15] HRAC [30] QACRP [41] QAODV−AC [42] SoftMAC [16] TAC [45] CACP−CS [11] MACMAN [35] DACME [17] ACSCQS [28] RFAR [44] ACRMP [29] IFCAC [31] IQOLSR [34] PAC [38] PMAC [39] MRCACP [37] Fig. 1.…”

Section: Protocols and Their Classificationmentioning

confidence: 99%

Admission control schemes for 802.11-based multi-hop mobile ad hoc networks: a survey

Hanzo

Tafazolli

2009

IEEE Commun. Surv. Tutorials

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Abstract-Mobile ad hoc networks (MANETs) promise unique communication opportunities. The IEEE 802.11 standard has allowed affordable MANETs to be realised. However, providing Quality of Service (QoS) assurances to MANET applications is difficult due to the unreliable wireless channel, the lack of centralised control, contention for channel access and node mobility. One of the most crucial components of a system for providing QoS assurances is admission control (AC). It is the job of the AC mechanism to estimate the state of the network's resources and thereby to decide which application data sessions can be admitted without promising more resources than are available and thus violating previously made guarantees. Unfortunately, due to the aforementioned difficulties, estimating the network resources and maintaining QoS guarantees are non-trivial tasks. Accordingly, a large body of work has been published on AC protocols for addressing these issues. However, as far as it is possible to tell, no wide-ranging survey of these approaches exists at the time of writing. This paper thus aims to provide a comprehensive survey of the salient unicast AC schemes designed for IEEE 802.

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Quality-Aware Voice Convergecast in Mobile Low Power Wireless Networks

Adkins

Han

Pasricha

2019

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Several recent disasters have shown the critical need for reliable voice communication for mobile users. Low power ad hoc wireless networks have become a promising alternative for voice communication in emergency scenarios because of their low cost and portability. In order to increase communication amongst moving emergency personnel and disaster victims, we have developed a novel convergecast voice streaming system that guarantees robust voice quality in a low power wireless network. The system integrates routing and mobility-aware admission control along with voice compression adjustment to ensure the quality of voice streams. The system is evaluated using Arduino Due micro-controllers with XBee 802.15.4 radios. We create mobile scenarios by placing the Arduino Dues on iRobot Create mobile robots. Our results show that our system can adequately adapt to changing network and routing conditions to deliver sufficient voice quality by maintaining a certain number of concurrent voice streams. To the best of our knowledge, this work is the first complete system for quality-aware voice streaming in mobile lower power wireless networks.

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Robust Flow Admission Control and Routing for Mobile Ad Hoc Networks

Cited by 10 publications

References 10 publications

Connectivity-Related Properties of Mobile Nodes Obeying the Random Walk and Random Waypoint Mobility Models

Connectivity-Related Properties of Mobile Nodes Obeying the Random Walk and Random Waypoint Mobility Models

Admission control schemes for 802.11-based multi-hop mobile ad hoc networks: a survey

Quality-Aware Voice Convergecast in Mobile Low Power Wireless Networks

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