Adaptive unequal protection for wireless video transmission over IEEE 802.11e networks

Wan, Zheng; Xiong, Naixue; Ghani, Nasir; Vasilakos, Athanasios V.; Zhou, Liang

doi:10.1007/s11042-013-1378-z

Cited by 80 publications

(34 citation statements)

References 21 publications

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“…Most of the recently proposed resource allocation schemes are designed based on QoE models [45]. The performances of these methods can be improved by considering the transmission impairments and video content related parameters, and their impact on QoE [26,39,44]. With respect to these works, here we are not focusing on the effect of delaying control information or on the impact of improved resource allocation scheme; we propose to study the impact of network impairments and to understand the masking or enhancing effect of different content on the perceived quality.…”

Section: Introductionmentioning

confidence: 99%

Impact of video content and transmission impairments on quality of experience

Paudyal

Battisti

Carli

2016

Multimed Tools Appl

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The analysis of the impact of video content and transmission impairments on Quality of Experience (QoE) is a relevant topic for the robust design and adaptation of multimedia infrastructures, services, and applications. The goal of this paper is to study the impact of video content on QoE for different levels of impairments. In more details, this contribution aims at i) the study of the impact of delay, jitter, packet loss, and bandwidth on QoE, ii) the analysis of the impact of video content on QoE, and iii) the evaluation of the relationship between content related parameters (spatial-temporal perceptual information, motion, and data rate) and the QoE for different levels of impairments.

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Section: Introductionmentioning

confidence: 99%

Impact of video content and transmission impairments on quality of experience

Paudyal

Battisti

Carli

2016

Multimed Tools Appl

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“…In addition, the connectivity of an ad hoc network purely depends on the cooperation established by the intermediate nodes towards the establishment of a reliable routing path [25][26][27][28][29]. However, the connectivity is drastically influenced by the presence of selfish nodes, since these node decreases the packet delivery ratio and throughput while increasing the energy consumption rate, packet drop rate and average end-to-end delay [30,31].…”

Section: Simulation Results and Analysismentioning

confidence: 99%

A futuristic trust coefficient-based semi-Markov prediction model for mitigating selfish nodes in MANETs

Janakiraman

Manoharan

2015

J Wireless Com Network

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In mobile ad hoc networks (MANETs), network survivability is considered as a potential factor required for maintaining maximum degree of connectivity among the mobile nodes even during failures and attacks. But, the selfish mobile nodes pose devastating influence towards network survivability. Hence, a prediction model that assesses network survivability through stochastic properties derived from nodes' behaviour becomes essential. This paper proposes a futuristic trust coefficient-based semi-Markov prediction model (FTCSPM) that investigates and quantifies the impact of selfish behaviour towards the survivability of the network. This FTCSPM approach incorporates a non birth-death process for manipulating futuristic trust coefficient since it does not consider the transition of a mobile node from the failed state to a selfish state into account. This semi-Markov prediction model also aids in framing a lower and upper bound for network survivability. Extensive simulations were carried out through ns-2 and the results indicates that FTCSPM show better performance than the existing benchmark mitigation mechanisms like correlated node behaviour model (CNBM), probabilistic behavior model (PBM) and epidemic correlated node behavioural model (ECNBM) proposed for selfish nodes. Further, FTCSPM isolates the selfish nodes rapidly at the rate of 33 % than the considered benchmark systems. Furthermore, the validation of this prediction model performed through Weibull distribution has a high degree of correlation with the simulation results and thus assures the reliability and correctness of the proposed approach. In addition, this approach computes the mean transition time incurred by a mobile node to transit from cooperative to selfish mode as 6.49 s and also identifies the minimum and maximum selfish behaviour detection time as 140 and 180 s, respectively.

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“…Zhang et al [32] improved the performance control over heterogeneous receivers for video multicast. Recently, Wan [29] et al proposed an adaptive unequal protection for wireless video transmission over IEEE 802.11e networks.…”

Section: Image and Video Transmission Techniquesmentioning

confidence: 99%

Personalized and efficient social image transmission scheme in mobile wireless network

Zhuang

Jiang

et al. 2015

Multimed Tools Appl

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This paper presents a Personalized large Social Image Transmission method in mobile wireless network(MWN) environment, called the PSIT. The whole transmission process of the PSIT works as follows: first, when a social image I S is prepared to transmit from a sender node to user U R , a preprocessing step is then conducted to obtain the optimal image fragment(IF) replica based on the users' preference model and the network bandwidth at the sender node. After that, the candidate IFs are transferred to the receiver node from the slave one according to the transmission priorities. Finally, the IFs can be recovered and displayed at the receiver node level. The proposed method includes five enabling techniques: 1) neighborhood-based tag enrichment processing, 2) user attention degree(UAD) derivation of the regions of interest(ROI), 3) an adaptive multi-resolution-based IF replica selection method, 4) a UAD-based IF replica placement method, and 5) a priority-based robust IF transmission scheme. The experimental results show that the performance of our approach is both efficient and effective, minimizing the response time by decreasing the network transmission cost while increasing the parallelism of I/O and CPU.

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Adaptive unequal protection for wireless video transmission over IEEE 802.11e networks

Cited by 80 publications

References 21 publications

Impact of video content and transmission impairments on quality of experience

Impact of video content and transmission impairments on quality of experience

A futuristic trust coefficient-based semi-Markov prediction model for mitigating selfish nodes in MANETs

Personalized and efficient social image transmission scheme in mobile wireless network

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