A Comprehensive Survey on Offload Techniques and Management in Wireless Access and Core Networks

Maallawi, Rachad; Agoulmine, Nazim; Radier, Benoît; Meriem, Tayeb Ben

doi:10.1109/comst.2014.2373356

Cited by 37 publications

(23 citation statements)

References 73 publications

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“…Offloading certain traffic from a primary network onto other networks that are more suitable becomes appealing in many scenarios. Particularly in mobile networks, which are struggling, with the increasing amount of traffic, offloading is seen as one method to mitigate capacity constraints [28]. In order to enable offloading in mobile networks, three different key offloading techniques exist, which are Selected IP Traffic Offload (SIPTO), Local IP Access (LIPA) and IP Flow Mobility (IFOM), as described in [29].…”

Section: Traffic Offloadingmentioning

confidence: 99%

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Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Niephaus

Modeker

Ghinea

2019

IEEE Trans. on Broadcast.

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Whilst broadband Internet connectivity has become highly important, providing broadband connectivity nonetheless remains a considerable challenge, particularly in rural and remote regions where the deployment of optical fibers faces economical obstacles. A promising option to address this issue is that of the most recent satellite systems, capable of providing high capacities virtually everywhere. However, compared to most terrestrial systems, satellite networks have very different link and, more importantly, latency characteristics, which often render them only barely usable for delay intolerant traffic. Thus, convergence of terrestrial and satellite networks is required, so that only certain traffic flows can be offloaded onto a supplemental satellite connection. In this work, we propose a network architecture relying on modern Software Defined Network (SDN) concepts, which enable dynamic traffic offloading in a converged satellite and terrestrial network, in order to relieve the load in a narrowband terrestrial network. We show that with limited overhead, a traffic can be offloaded, leading to an increase in the user's Quality-of-Experience (QoE).

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Section: Traffic Offloadingmentioning

confidence: 99%

“…Moreover, SIPTO often uses Access Point Names (APNs) to differentiate which portion of the traffic should be offloaded, which also does not provide the required level of traffic differentiation. A holistic overview of offloading techniques in mobile networks can be found in [28].…”

Section: Traffic Offloadingmentioning

confidence: 99%

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Niephaus

Modeker

Ghinea

2019

IEEE Trans. on Broadcast.

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“…Some have focused on the optimization of the video's QoE through mechanisms on a single network layer. Classification and survey of these mechanisms can be found in [7,8,9]. In this section we only focus on cross-layer designs that have been proposed to optimize the QoE of video traffic.…”

Section: Related Workmentioning

confidence: 99%

A quality of experience-aware cross-layer architecture for optimizing video streaming services

2016

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The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture).

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“…points (APs) [3] [4]. From the network operators' perspective, offloading traffic can effectively exploit the additional network capacities provided by the multi-tiers small cells and reduce the needs of costly and time-consuming network infrastructure upgrade.…”

mentioning

confidence: 99%

“…This is also motivated by the rapid growth of user-generated contents (such as user-generated videos on social networks), which has significantly increased the MUs' uplink traffic volume 3. In future work, we will extend our model to the case of multiple APs, where an MU selects which AP to offload traffic to 4. The small cell may operate on a separated licensed spectrum (such as the "separate carrier" scheme for femtocell[25]) or on a separate unlicensed spectrum (such as the case of WiFi AP).…”

mentioning

confidence: 99%

Traffic scheduling and power allocations for mobile data offloading via dual-connectivity

Qian

et al. 2016

2016 IEEE International Conference on Communications (ICC)

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With the rapid growth of mobile traffic demand, a promising approach to relieve cellular network congestion is to offload users' traffic to small-cell networks. In this paper, we investigate how the mobile users (MUs) can effectively offload traffic by taking advantage of the capability of dual-connectivity, which enables an MU to simultaneously communicate with a macro base station (BS) and a small-cell access point (AP) via two radio-interfaces. Offloading traffic to the AP usually reduces the MUs' mobile data cost, but often at the expense of suffering increased interferences from other MUs at the same AP.We thus formulate an optimization problem that jointly determines each MU's traffic schedule (between the BS and AP) and power control (between two radio-interfaces). The system objective is to minimize all MUs' total cost, while satisfying each MU's transmit-power constraints through proper interference control. In spite of the non-convexity of the problem, we design both a centralized algorithm and a distributed algorithm to solve the joint optimization problem. Numerical results show that the proposed algorithms can achieve the close-to-optimum results comparing with the ones achieved by the LINGO (a commercial optimization software), but with significantly less computational complexity. The results also show that the proposed adaptive offloading can significantly reduce the MUs' cost, i.e., save more than 75% of the cost without offloading traffic and 65% of the cost with a fixed offloading.

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A Comprehensive Survey on Offload Techniques and Management in Wireless Access and Core Networks

Cited by 37 publications

References 73 publications

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

Toward Traffic Offload in Converged Satellite and Terrestrial Networks

A quality of experience-aware cross-layer architecture for optimizing video streaming services

Traffic scheduling and power allocations for mobile data offloading via dual-connectivity

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