Buffer-aided instantly decodable network coding for wireless video broadcasting with unequal packet-priority retransmission

Niu, Teng; Zhang, Dongmei; Xu, Kui; Wu, Lianguo; Jiang, Ying

doi:10.1109/iscit.2016.7751604

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…An unequal packet priority parameter is exploited for Smart RED in [20] for its application in TCP to UDP traffic with different needs of bandwidth inspired by smart access point with limited advertised window (SAP-LAW) concepts. The research in [26] proposed a hybrid technique for clustering and queuing is attained by arranging the packets in queues before been processed for routing. Differentiated services parameter was used for setting the priority of packets and selecting them for drop in case of congestion.…”

Section: Related Workmentioning

confidence: 99%

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

2021

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Routing protocols in Mobile Ad Hoc Networks (MANETs) play a pivotal role in ensuring quality of service (QoS) and improving network performance. Selection of optimal routing protocol and suitable parameters for a given network scenario is a major task that ultimately affects the behavior of network. This work exploits machine learning (ML) techniques for the selection of adequate routing parameters and protocol by regression of parameters in given network scenario to ensure optimal performance. The network is trained based on parametric setup of expanding ring search mechanism (ERS) and random early detection (RED) technique to estimate network throughput, end to end (E2E) delay and packets delivery ratio (PDR) and is tested via wide-ranging simulations in varying network topologies. Both RED and ERS mechanisms are aimed to control link and node level congestion in the reactive routing protocols and our aim is to select the best suited parameters for given network topologies based on ERS and RED parametric setups and improve performance for ensuring QoS. ML algorithms are trained and tested for their performance in varying network topologies. We have exploited these models with best performance for ERS and RED based routing in given topological arrangements. The performance of the ML algorithms is evaluated on the basis of root mean squared error (RMSE) and mean absolute error (MAE) for regression settings. Prediction models with up to par RMSE and MAE out-turns are attained and exploited for selection of suitable ERS and RED parameters and routing protocols in order to ensure the QoS for given network scenario. Variants of standard routing protocols are devised based on their performance and the ML techniques are exploited for prediction of QoS parameters to decide on the optimal variant that attains significant improvement in performance. Results are shown to confirm that considerable improvement in QoS is attained. INDEX TERMS Ad hoc multi hop wireless networks, congestion control, expanding ring search, machine learning, mobile ad hoc networks, on demand routing protocols, random early detection, regression, quality of service.

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Section: Related Workmentioning

confidence: 99%

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

2021

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“…The proposed scheme attains a class based priorities to the ERS rings and combines the advantage of using proportional fair scheduling. Similar mechanism as in [14] works on unequal packet priority based on ERS that is utilized for wireless video broadcasting. Retransmissions are managed through buffer aided decodable network coding and priority aid.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Expanding Ring Search Based Per Hop Behavior Rendition of Routing in MANETs

Durr-e-Nayab¹,

Zafar²,

Basheri³

2021

Computers, Materials &Amp; Continua

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Routing protocols in Mobile Ad Hoc Networks (MANETs) operate with Expanding Ring Search (ERS) mechanism to avoid ooding in the network while tracing step. ERS mechanism searches the network with discerning Time to Live (TTL) values described by respective routing protocol that save both energy and time. This work exploits the relation between the TTL value of a packet, traf c on a node and ERS mechanism for routing in MANETs and achieves an Adaptive ERS based Per Hop Behavior (AERSPHB) rendition of requests handling. Each search request is classi ed based on ERS attributes and then processed for routing while monitoring the node traf c. Two algorithms are designed and examined for performance under exhaustive parametric setup and employed on adaptive premises to enhance the performance of the network. The network is tested under congestion scenario that is based on buffer utilization at node level and link utilization via back-off stage of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). Both the link and node level congestion is handled through retransmission and rerouting the packets based on ERS parameters. The aim is to drop the packets that are exhausting the network energy whereas forward the packets nearer to the destination with priority. Extensive simulations are carried out for network scalability, node speed and network terrain size. Our results show that the proposed models attain evident performance enhancement.

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On minimizing average packets decoding delay based on B-DLNC for wireless broadcasting

Niu

Chen

Zhang

et al. 2017

2017 IEEE 17th International Conference on Communication Technology (ICCT)

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Buffer-aided instantly decodable network coding for wireless video broadcasting with unequal packet-priority retransmission

Cited by 3 publications

References 15 publications

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

Prediction of Scenarios for Routing in MANETs Based on Expanding Ring Search and Random Early Detection Parameters Using Machine Learning Techniques

Adaptive Expanding Ring Search Based Per Hop Behavior Rendition of Routing in MANETs

On minimizing average packets decoding delay based on B-DLNC for wireless broadcasting

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