Real Time Available-Bandwidth Estimation (ABE) Algorithm Based Selection in Heterogeneous Network for WiMAX and 3G

Ahuja, Kiran; Khanna, Rajesh; Singh, Brahmjit

doi:10.1109/ngmast.2011.38

Cited by 9 publications

(3 citation statements)

References 11 publications

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“…One-way delay model was used to estimate available bandwidth in which proportional share of link capacity concept imp roved the measurement latency and accuracy [20]. The proposed algorith m in [21] selects network on the basis of available bandwidth estimation. It estimates the available lin k bandwidth on the basis of averaging of current sample only.…”

Section: Related Workmentioning

confidence: 99%

Available Link Bandwidth Based Network Selection in Multi-access Networks

Ahuja¹,

Singh²,

Khanna³

2014

IJISA

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In a heterogeneous wireless environment, one of the important aspects of seamless communicat ion for ubiquitous computing is the dynamic selection of the best access network. The problem of access network selection has been addressed through various decision methods based on available network information. Available lin k bandwidth is one of the important in formation parameters, which can be used as criterion for network selection. In this paper, we consider available bandwidth as a dynamic parameter to select the network in heterogeneous environment. First, we propose a bootstrap approximat ion based technique to estimate available bandwidth and then utilize it for the selection of the best suitable network in the heterogeneous environment consisting of 2G and 3G standards based wireless networks. The proposed algorith m is imp lemented in temporal and spatial domains to check its robustness. Estimation time with varying size o f files is used as the performance met ric. Through numerical results, it is shown that the proposed algorith m gives imp roved performance as co mpared to the existing algorithm.

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Section: Related Workmentioning

confidence: 99%

Available Link Bandwidth Based Network Selection in Multi-access Networks

Ahuja¹,

Singh²,

Khanna³

2014

IJISA

Self Cite

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“…However, the discussed solutions fall short in different aspects (such as required access to cross-layer information or dedicated server support) for the bandwidth estimation application on cellular networks. In fact, the research which is directly related to measuring the achievable bandwidth on cellular networks is very limited [62,7,114]. The general conclusion of this work is that it is very costly (regarding data exchange and server support) to effectively estimate the achievable bandwidth given the many factors that impact the bandwidth.…”

Section: Packet's Round-trip-timementioning

confidence: 99%

Collaborative streaming of on demand videos for mobile devices

Zhong¹

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The number of mobile users with a variety of applications that require on demand video content is growing rapidly. However, bandwidth insufficiency is an obstacle in providing high quality smooth video playout in cellular networks. There are two kinds of solutions in the literature that provide high bandwidth communication channels. One is bandwidth aggregation that aggregates the bandwidth from multiple radio access technologies (RATs) on a single device to create a high-bandwidth logical link for an application. Another is collaboration with peers. This kind of content distribution solutions originated from content sharing in peer-to-peer networks, and then evolved through BitTorrent (which maximises the downloading performance) to the mobile environment. To provide effective collaborative streaming to mobile devices, several functionalities are required including e.g. device discovery, activity recognition and bandwidth estimation.In the current approaches to collaborative streaming, the first step of collaborative streaming has not been fully addressed, because unlike traditional device discovery methods in P2Pand BitTorrent in which peers share the same network, the discovery of devices in heterogeneous wireless networks is a very challenging problem. These devices access the Internet via heterogeneous wireless networks without pre-knowledge of the existence of nearby devices, and no effective solution exists except for very energy costly GPS based methods that track device locations all the time. In addition, in mobile environments user mobility and available bandwidth directly affect the performance of collaborative streaming. For example, the connection between a stationary user and a user in vehicle drops within a few seconds. Thus finding the collaborative devices with similar mobility pattern and high-bandwidth is important for collaborative streaming, but the existing solutions on activity recognition and on bandwidth estimation perform poorly on mobile devices. As for activity recognition, there exist solutions for smart environments and wearable sensor networks, however they cannot be simply applied to mobile devices. Google published its activity recognition service on Android phones in 2013, and it is the first publicly available service providing activity recognition on Android phones. However its recognition accuracy is not very high and needs to be improved. Bandwidth estimation is important for collaborative streaming as the quality of the streamed video depends to a large extent on the bandwidth of the selected collaborating devices. Most of the existing bandwidth estimation approaches designed for wired and wireless computer networks fail in cellular networks, due to the bandwidth fluctuation in these networks and the cost of servers and user's data quota.i The research on the functionalities of collaborative streaming for mobile devices are still in early stages. The primary goal of the research presented in this thesis is to develop new algorithms and mechanisms for collaborati...

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“…webpages) based on exceptionally low or high QoS metrics. These metrics can also be used at lower levels in the smartphone operating system to perform optimizations for tasks like network selection [21]. Measuring throughput, as mentioned above, is difficult, slow, and inaccurate.…”

Section: Cellular Access Networkmentioning

confidence: 99%

Predicting Delay-Bound Violations for Cellular Transmissions: Pre-Hospital ECGs Uploaded from Moving Vehicles

Gessner

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Real Time Available-Bandwidth Estimation (ABE) Algorithm Based Selection in Heterogeneous Network for WiMAX and 3G

Cited by 9 publications

References 11 publications

Available Link Bandwidth Based Network Selection in Multi-access Networks

Available Link Bandwidth Based Network Selection in Multi-access Networks

Collaborative streaming of on demand videos for mobile devices

Predicting Delay-Bound Violations for Cellular Transmissions: Pre-Hospital ECGs Uploaded from Moving Vehicles

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