An Adaptive Congestion Control and Fairness Scheduling Strategy for Wireless Mesh Networks

Sheikh, Sajid M.; Wolhuter, Riaan; Engelbrecht, Herman A.

doi:10.1109/ssci.2015.169

Cited by 8 publications

(3 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the simulation experiment, the energy model used in this is the energy consumption model in [53], the node will consume energy when sending data and receiving data. The energy consumption formula is as follows:…”

Section: The Experimental Results and Analysismentioning

confidence: 99%

“…Because the node is congested, the packet with lower priority will be dropped, so it is possible that the packet with lower priority will never be received. In [53], a fairness-based congestion control method is proposed. The storage queue of the sensor node is divided into three queues, which are high priority queue, medium priority, and low priority queue.…”

Section: Background and Related Workmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient Information Maximization Based Adaptive Congestion Control Scheme in Wireless Sensor Network

et al. 2019

View full text Add to dashboard Cite

Intelligent communication technology can enhance user experience and improve people's lifestyle. However, due to the limited resources of wireless sensor networks (WSNs), the congestion occurs when the node's traffic load exceeds it's the available capacity. Congestion may cause serious problems such as high packet loss and low throughput, which is an extremely deleterious impact on the performance of WSNs. To tackle this issue, a differentiated rate control data collection (DRCDC) scheme is proposed to avoid or alleviate the network congestion. Different from the previous scheme, the DRCDC scheme can mitigate the congestion by intelligently reducing the data that contains less information, and maintain the distortion rate of information collected by the network is small. The DRCDC mainly avoids or mitigates congestion on the spatial and temporal through information entropy theory, and at the same time makes the information collected by the network has the lowest distortion rate. 1) Congestion mitigation in spatial. Since there is a spatial correlation between sensing data, so in the case of collecting a certain amount of data, some missing data in space can be recovered from another spatially acquired data by matrix completion theory. Therefore, in the DRCDC scheme, when congestion occurs, the amount of data transmitted (forwarded) for nodes are congested will be reduced by an intelligent approach, thereby being able to mitigate congestion. 2) Congestion mitigation in temporal. when congestion occurs, reducing the data collection of time slots containing small information to reduce the flow rate that needs to be transmitted, thereby avoiding congestion while minimizing data distortion rate of the network. The experimental results of the DRCDC scheme in a planar network show better performance than the traditional data collection schemes and reducing the packet loss 2.8%-6.8% while reduce the maximum delay by 34.2%-76.3%.

show abstract

Section: The Experimental Results and Analysismentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

An Efficient Information Maximization Based Adaptive Congestion Control Scheme in Wireless Sensor Network

et al. 2019

View full text Add to dashboard Cite

show abstract

“…We use Jain's fairness index, which was proposed in [14] and has been extensively used in the networking literature, e.g., in [12], [13], [15], as a fairness metric. One way to optimize the total throughput-fairness trade-off in cellular systems is to allocate resources such that the total throughput is maximized subject to the constraint that the throughput of each MS must exceed some predefined lower bound [12].…”

mentioning

confidence: 99%

Achieving Arbitrary Throughput–Fairness Trade-offs in the Inter-cell Interference Coordination with Fixed Transmit Power Problem

Gupta

Kasbekar

2019

Static &Amp; Dynamic Game Theory: Foundations &Amp; Applications

View full text Add to dashboard Cite

We study the problem of inter cell interference coordination (ICIC) with fixed transmit power in OFDMA-based cellular networks, in which each base station (BS) needs to decide as to which subchannel, if any, to allocate to each of its associated mobile stations (MS) for data transmission. In general, there exists a trade-off between the total throughput (sum of throughputs of all the MSs) and fairness under the allocations found by resource allocation schemes. We introduce the concept of τ − α−fairness by modifying the concept of α−fairness, which was earlier proposed in the context of designing fair end-to-end window-based congestion control protocols for packet-switched networks. The concept of τ − α−fairness allows us to achieve arbitrary trade-offs between the total throughput and degree of fairness by selecting an appropriate value of α in [0, ∞). We show that for every α ∈ [0, ∞) and every τ > 0, the problem of finding a τ − α−fair allocation is NP-Complete. Further, we show that for every α ∈ [0, ∞), there exist thresholds such that if the potential interference levels experienced by each MS on every subchannel are above the threshold values, then the problem can be optimally solved in polynomial time by reducing it to the bipartite graph matching problem. Also, we propose a simple, distributed subchannel allocation algorithm for the ICIC problem, which is flexible, requires a small amount of time to operate, and requires information exchange among only neighboring BSs. We investigate via simulations as to how the algorithm parameters should be selected so as to achieve any desired trade-off between the total throughput and fairness.

show abstract

Scheduling Strategies to Improve Reliability and Fairness for Priority Based Smart Rural Contention Based Applications Over Low-Cost Wireless Mesh Backbone Networks

Sheikh

Wolhuter

Engelbrecht

2016

E-Business and Telecommunications

View full text Add to dashboard Cite

An Adaptive Congestion Control and Fairness Scheduling Strategy for Wireless Mesh Networks

Cited by 8 publications

References 22 publications

An Efficient Information Maximization Based Adaptive Congestion Control Scheme in Wireless Sensor Network

An Efficient Information Maximization Based Adaptive Congestion Control Scheme in Wireless Sensor Network

Achieving Arbitrary Throughput–Fairness Trade-offs in the Inter-cell Interference Coordination with Fixed Transmit Power Problem

Scheduling Strategies to Improve Reliability and Fairness for Priority Based Smart Rural Contention Based Applications Over Low-Cost Wireless Mesh Backbone Networks

Contact Info

Product

Resources

About