Enabling energy-aware collaborative mobile data offloading for smartphones

Ding, Aaron Yi; Han, Bo; Xiao, Yu; Hui, Pan; Srinivasan, Aravind; Kojo, Markku; Tarkoma, Sasu

doi:10.1109/sahcn.2013.6645020

Cited by 80 publications

(41 citation statements)

References 27 publications

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“…Thus, UEs cannot reasonably respond to realtime wireless network states. MADNet [40] is a collaborative mobile data offloading architecture, which is designed mainly for extending mobile battery life. However, MADNet has focused on the vertical handover.…”

Section: Related Workmentioning

confidence: 99%

Game-Theoretic Scalable Offloading for Video Streaming Services over LTE and WiFi Networks

Park

Song

2018

IEEE Trans. on Mobile Comput.

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Abstract-This paper presents a game-theoretic scalable offloading system that provides seamless video streaming services by effectively offloading parts of video traffic in all video streaming services to a WiFi network to alleviate cellular network congestion. The system also consolidates multiple physical paths in a cost-effective manner. In the proposed system, the fountain encoding symbols of compressed video data are transmitted through long term evolution (LTE) and WiFi networks concurrently to flexibly control the amount of video traffic through the WiFi network as well as mitigate video quality degradation caused by wireless channel errors. Furthermore, the progressive second price auction mechanism is employed to allocate the limited LTE resources to multiple user equipment in order to maximize social welfare while converging to the ε-Nash equilibrium.Specifically, we design an application-centric resource valuation that explicitly considers both the realistic wireless network conditions and characteristics of video streaming services. In addition, the scalability and convergence properties of the proposed system are verified both theoretically and experimentally. The proposed system is implemented using network simulator 3. Simulation results are provided to demonstrate the performance improvement of the proposed system.

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Section: Related Workmentioning

confidence: 99%

Game-Theoretic Scalable Offloading for Video Streaming Services over LTE and WiFi Networks

Park

Song

2018

IEEE Trans. on Mobile Comput.

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“…This is known as mobile data and computation offloading. Several works have identified the benefits of WiFi data offloading [13][14][15]. The work in [13] showed that deferring the uploading tasks until WiFi access points are available can save the energy of smartphones.…”

Section: Abundance Of Spare Resources In D2d Networkmentioning

confidence: 99%

“…The work in [13] showed that deferring the uploading tasks until WiFi access points are available can save the energy of smartphones. By jointly considering the power consumption and link capacity of wireless network interfaces, Ding et al in [14] studied the criterion of downloading data from WiFi, as well as the WiFi access point selection problem.…”

Section: Abundance Of Spare Resources In D2d Networkmentioning

confidence: 99%

Blockchain-Empowered Fair Computational Resource Sharing System in the D2D Network

et al. 2017

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Device-to-device (D2D) communication is becoming an increasingly important technology in future networks with the climbing demand for local services. For instance, resource sharing in the D2D network features ubiquitous availability, flexibility, low latency and low cost. However, these features also bring along challenges when building a satisfactory resource sharing system in the D2D network. Specifically, user mobility is one of the top concerns for designing a cooperative D2D computational resource sharing system since mutual communication may not be stably available due to user mobility. A previous endeavour has demonstrated and proven how connectivity can be incorporated into cooperative task scheduling among users in the D2D network to effectively lower average task execution time. There are doubts about whether this type of task scheduling scheme, though effective, presents fairness among users. In other words, it can be unfair for users who contribute many computational resources while receiving little when in need. In this paper, we propose a novel blockchain-based credit system that can be incorporated into the connectivity-aware task scheduling scheme to enforce fairness among users in the D2D network. Users' computational task cooperation will be recorded on the public blockchain ledger in the system as transactions, and each user's credit balance can be easily accessible from the ledger. A supernode at the base station is responsible for scheduling cooperative computational tasks based on user mobility and user credit balance. We investigated the performance of the credit system, and simulation results showed that with a minor sacrifice of average task execution time, the level of fairness can obtain a major enhancement.

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“…However neither of the works consider the energy consumed by mobile devices in the process of offloading mobile data through opportunistic communication. In a recent work Ding et al [23] recognize the importance of decreasing energy consumption during the offloading process, and study the energy savings that can be achieved when mobile data is offloaded to WiFi networks. In contrast, we investigate the energy savings achieved when mobile data is offloaded via opportunistic communication.…”

Section: A Mobile Data Offloadingmentioning

confidence: 99%

Energy-aware opportunistic mobile data offloading for users in urban environments

Kouyoumdjieva

Karlsson

2015

2015 IFIP Networking Conference (IFIP Networking)

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Abstract-Opportunistic networking (a.k.a. device-to-device communication) is considered a feasible means for offloading mobile data traffic. Since mobile nodes are battery-powered, opportunistic networks must be expected to satisfy the user demand without greatly affecting battery lifetime. To address this requirement, this work introduces progressive selfishness, an adaptive and scalable energy-aware algorithm for opportunistic networks used in the context of mobile data offloading. The paper evaluates the performance of progressive selfishness in terms of both application throughput and energy consumption via extensive trace-driven simulations of realistic pedestrian behavior, and demonstrates that the proposed algorithm is robust against the distributions of node density and initial content availability. The results show that in certain scenarios progressive selfishness achieves up to 85% energy savings during opportunistic downloads while sacrificing less than 1% in application throughput. Furthermore, the study demonstrates that in terms of total energy consumption (by both cellular and opportunistic downloads) in dense environments the performance of progressive selfishness is comparable to downloading contents directly from a mobile network.

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Enabling energy-aware collaborative mobile data offloading for smartphones

Cited by 80 publications

References 27 publications

Game-Theoretic Scalable Offloading for Video Streaming Services over LTE and WiFi Networks

Game-Theoretic Scalable Offloading for Video Streaming Services over LTE and WiFi Networks

Blockchain-Empowered Fair Computational Resource Sharing System in the D2D Network

Energy-aware opportunistic mobile data offloading for users in urban environments

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