Scalable Multimedia Streaming in Wireless Networks with Device-to-Device Cooperation

Jahed, Karim; Sharafeddine, Sanaa; Moussawi, Abdallah; Daya, Abbas Abou; Dbouk, Hassan; Kassir, Saadallah; Dawy, Zaher; Valsalan, Preethi; Cherif, Wael; Filali, Fethi

doi:10.1145/2964284.2973837

Cited by 5 publications

(7 citation statements)

References 7 publications

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“…End for (16) Initialize τ as "0" (17) For t � 1 to T do (18) Compute τ t according to formula (27) ( 19) If (m tk �� 1 and d tk < x% • d cluster and τ < τ t ) then {τ � τ t ; z � t} End if (20) End for (21) x k � x z and y k � y z (22) End for ALGORITHM 1: e K-means-based D2D clustering algorithm.…”

Section: E Solving Methods For D2d Multicast Transmission Powermentioning

confidence: 99%

“…In [15][16][17][18][19], the authors thought that the group-aware mobile social video streaming sharing problem has aroused great interest in the academic and industry community. For example, live sports content should be delivered to a group of supporters' devices at the same time.…”

Section: Related Workmentioning

confidence: 99%

“…On the contrary, if the amount of the power from a DCH is too much, then the MCP would give up this DCH at the expense of increased base station transmission power. From formula (17), it is obvious that providing more power for D2D multicast services will bring more revenue to a DCH. However, once such a DCH is abandoned by the MCP, it will not get any benefit.…”

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confidence: 99%

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Improving Energy Efficiency of Multimedia Content Dissemination by Adaptive Clustering and D2D Multicast

Long

Gui

Zeng

2019

Mobile Information Systems

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While achieving desired performance, there exist still many challenges in current cellular networks to support the multimedia content dissemination services. The conventional multimedia transmission schemes tend to serve all multicast group members with the data rate supported by the receiving user with the worst channel condition. The recent work discusses how to provide satisfactory quality of service (QoS) for all receiving users with different quality of experience (QoE) requirements, but the energy efficiency improvement of multimedia content dissemination is not its focus. In this paper, we address it based on adaptive clustering and device-to-device (D2D) multicast and propose an energy-efficient multimedia content dissemination scheme under a consistent QoE constraint. Our scheme extends the recent work with the proposed K-means-based D2D clustering method and the proposed game-based incentive mechanism, which can improve energy efficiency of multimedia content dissemination on the premise of ensuring the desired QoE for most multicast group members. In the proposed scheme, we jointly consider the cellular multicast, intracluster D2D multicast, and intercluster D2D multicast for designing the energy-efficient multimedia content dissemination scheme. In particular, we formulate the energy-efficient multicast transmission problem as a Stackelberg game model, where the macro base station (MBS) is the leader and the candidate D2D cluster heads (DCHs) are the followers. Also, the MBS acts as the buyer who buys the power from the candidate DCHs for intracluster and intercluster D2D multicast communications, and the candidate DCHs act as the sellers who earn reward by helping the MBS with D2D multicast communications. Through analyzing the above game model, we derive the Stackelberg equilibrium as the optimal allocation for cellular multicast power, intracluster D2D multicast power, and intercluster D2D multicast power, which can maximize the MBS’s utility function. Finally, the proposed scheme is verified through the simulation experiments designed in this paper.

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Section: E Solving Methods For D2d Multicast Transmission Powermentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

mentioning

confidence: 99%

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Improving Energy Efficiency of Multimedia Content Dissemination by Adaptive Clustering and D2D Multicast

Long

Gui

Zeng

2019

Mobile Information Systems

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“…Finally, we extend the contributions to experimental evaluation using test bed implementation in order to demonstrate the algorithm's feasibility and effectiveness under realistic operational conditions. It is important to note that very few studies in the literature include practical test bed implementation due to the challenges in integrating intelligence into devices especially when dealing with off the shelf smartphones; for example, see [29], [30] for WiFi-Direct ad hoc network formation among Android phones, however, without dealing with intelligence related to cluster head election. Moreover, the authors in [16] present Android based implementation to demonstrate the practical implementation of their group creation and intercommunication approach using a network scenario composed of five devices.…”

Section: B Contributionsmentioning

confidence: 99%

A proactive scalable approach for reliable cluster formation in wireless networks with D2D offloading

Sharafeddine

Farhat

2018

Ad Hoc Networks

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With the current exponential growth in traffic and service demands, device-to-device (D2D) cooperation is identified as a major mechanism to enable 5G networks to effectively and efficiently augment network resources. The effectiveness of D2D cooperation depends on a wide range of decision making processes that include cluster formation, resource allocation, in addition to connection and mobility management. Irrespective of the D2D cooperation scenario whether in sensor, ad hoc, or cellular networks, the literature normally assumes that devices selected as relays or data sources are reliable; this means that they will maintain the connection till the communication session ends. Yet, this assumption is challenged in practice since devices' batteries can be depleted (e.g., sensors in an IoT network) and devices can move leading to connection termination (e.g., mobile users in a WiFi network or cars in a vehicular ad hoc network). To this end, we address the problem of reliable D2D cooperation in wireless networks by proposing a novel approach that is proactive by utilizing reliability metrics in the decision making process, and scalable by having low implementation complexity suitable for dense networks. These differentiating factors are shown to enhance the overall network reliability compared to standard techniques and to facilitate dynamic operation which is essential for practical implementation. Performance is evaluated using extensive simulations in addition to test bed experimental demonstration in order to quantify gains and extract insights on a range of existing design tradeoffs.

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“…Data sharing over device-to-device (D2D) links has been shown to provide a multitude of performance gains in terms of throughput and spectral efficiency enhancement [4][5][6], energy consumption reduction [7][8][9][10], and end user cost savings and incentives [11][12][13]. However, reliable and efficient D2D data sharing in practice hinges on several factors that include content availability, users' proximity and ability to connect to each other, users' mobility patterns, and contact intervals [14], in addition to other aspects such as cooperation incentives and trust establishment [15,16].…”

Section: Introductionmentioning

confidence: 99%

Social‐Aware Device‐to‐Device Offloading Based on Experimental Mobility and Content Similarity Models

Aoude

Dawy

Sharafeddine

et al. 2018

Wireless Communications and Mobile Computing

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Device-to-device (D2D) offloading has been shown to be a highly effective technique to enhance the performance of wireless networks. Yet, for any two mobile users to share data efficiently and reliably via D2D links, they should be in close proximity for long enough period of time, share similar content interests, and have some level of incentive and trust to cooperate. In this work, we focus on the practical implementation aspects of D2D data sharing taking into account realistic operational conditions. To this end, we design and conduct an experimental study to collect location and neighbor discovery data from 38 mobile users in a university campus over several weeks using our own customized crowdsourcing Android mobile application. The collected data is then processed and utilized to empirically model mobility-related parameters that include contact frequency, contact duration, and intercontact duration. The participating users did also fill a user interest survey in order to correlate mobility and connectivity patterns with content interests and social network relations. The obtained insights are then used to develop a practical implementation framework for designing effective D2D data sharing strategies. To test the proposed ideas under realistic operational constraints, we design and implement a social-aware D2D data sharing Android mobile application and demonstrate its functionality and effectiveness using an example case study scenario.

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Scalable Multimedia Streaming in Wireless Networks with Device-to-Device Cooperation

Cited by 5 publications

References 7 publications

Improving Energy Efficiency of Multimedia Content Dissemination by Adaptive Clustering and D2D Multicast

Improving Energy Efficiency of Multimedia Content Dissemination by Adaptive Clustering and D2D Multicast

A proactive scalable approach for reliable cluster formation in wireless networks with D2D offloading

Social‐Aware Device‐to‐Device Offloading Based on Experimental Mobility and Content Similarity Models

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