Service Provisioning with Ad-Hoc Deployed High-Speed Access Points in Urban Environments

Hultell, Johan; Lungaro, Pietro; Zander, Jens

doi:10.1109/pimrc.2005.1651794

Cited by 12 publications

(11 citation statements)

References 10 publications

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“…Network providers as well as users can easily and quickly install WiFi access points (APs) with low costs, and in fact many network providers worldwide have already provided WiFi services in hot-spots and residential areas. Recent papers [3]- [5] demonstrate that a huge portion of cellular traffic can be offloaded to WiFi by letting users delay their delay-tolerant data (e.g., movie, software downloads, cloud services), and upload/download data whenever they meet a WiFi AP within a pre-specified delay deadline. We call this delayed WiFi offloading, and about 60-80% of cellular traffic can be reduced when 30 mins to 1 hour delay for human mobility [3] and 10 mins of delay for vehicular mobility [4] are allowed.…”

Section: Introductionmentioning

confidence: 99%

“…We call this delayed WiFi offloading, and about 60-80% of cellular traffic can be reduced when 30 mins to 1 hour delay for human mobility [3] and 10 mins of delay for vehicular mobility [4] are allowed. Also, more than 80% of news can be pre-fetched within 700 seconds on a random mobility model in [5]. This remarkable offloading efficiency is due to users' mobility enabling themselves to be under a WiFi AP during a considerable portion of their business time.…”

Section: Introductionmentioning

confidence: 99%

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Economics of WiFi offloading: Trading delay for cellular capacity

Lee

Chong

et al. 2013

2013 Proceedings IEEE INFOCOM

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Cellular networks are facing severe traffic overloads due to the proliferation of smart handheld devices and traffichungry applications. A cost-effective and practical solution is to offload cellular data through WiFi. Recent theoretical and experimental studies show that a scheme, referred to as delayed WiFi offloading, can significantly save the cellular capacity by delaying users' data and exploiting mobility and thus increasing chance of meeting WiFi APs (Access Points). Despite a huge potential of WiFi offloading in alleviating mobile data explosion, its success largely depends on the economic incentives provided to users and network providers to deploy and use delayed offloading. In this paper, we study how much economic benefits can be generated due to delayed WiFi offloading, by modeling the interaction between a single provider and users based on a two-stage sequential game. We first analytically prove that WiFi offloading is economically beneficial for both the provider and users. Also, we conduct trace-driven numerical analysis to quantify the practical gain, where the increase ranges from 21 to 152% in the provider's revenue, and from 73 to 319% in the users' surplus.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Economics of WiFi offloading: Trading delay for cellular capacity

Lee

Chong

et al. 2013

2013 Proceedings IEEE INFOCOM

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“…Therefore, it is very viable to exploit the existing cost efficient heterogeneous access network infrastructures to supplement 3GPP access technology coverage. Existing major cellular traffic offload solutions [7][8][9] have shown that it is possible to offload a huge portion of mobile data traffic to WiFi access networks by allowing the users delay their delay-tolerant data (For example, cloud services, software downloads, movies, .etc. ), and upload/download data whenever they have a nearby WiFi AP within a predefined delay deadline.…”

Section: Why Wifi As a Practical Offloading Technique?mentioning

confidence: 99%

“…In [7], it is predicted that about 60-80 % of mobile data traffic can be reduced when there is about 30 min to 1 h delay for human mobility, and when a delay of around 10 min is allowed for vehicular mobility [8]. In addition to this, it is also predicted in [9] that more than 80 % of news data can be prefetched on a random model. Such an offloading technique is called delayed WiFi offloading.…”

Section: Why Wifi As a Practical Offloading Technique?mentioning

confidence: 99%

The performance of network-controlled mobile data offloading from LTE to WiFi networks

Hagos

2015

Telecommun Syst

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Global mobile data traffic consumption and usage continues to increase rapidly leading to congested networks. Currently, cellular networks are overloaded with mobile data traffic due to the rapid growth of mobile broadband subscriptions and the increasing popularity of diversified applications for smartphones with multiple wireless interfaces and the flat-rate pricing model of cellular networks. One possible practical solution to alleviate this problem is the offloading of mobile data traffic from the primary access technology to the WiFi infrastructure to gain extra capacity and improve the overall network performance. As the strategy what and when to offload data is non-trivial, it is of vital importance to develop novel algorithms to guide this process. This paper addresses solutions for network-controlled WiFi offloading in Long Term Evolution (LTE) cellular networks when performance needs exceed the capability of the LTE access. It then compares the performance of each access technology using different network performance metrics. In detail, an optimized signal-to-noise ratio-threshold based handover solution and extension to the 3rd Generation Partnership Project standard for Access Network Discovery and Selection Function (ANDSF) framework for WiFi offloading is proposed. Our simulation results have shown that ANDSF discovery can be used to control the amount of WiFi offloading.

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“…[2]) is an example of an operator-deployed network providing isolated "pockets" of high bandwidth connectivity. But, in recent years, the wide spread of Wireless Local Area Network (WLAN) APs among private users, is posing a new challenge: being able of opening up to public access the collection of these high-speed APs would create a user-deployed network [3] that might be capable of supporting interesting services [4]. Unlikely to infostation, this paradigm will be exposed to uncoordinated deployment (many different "local" operators) and therefore to a less efficient utilization of resources.…”

Section: Introductionmentioning

confidence: 99%

Service Provisioning and Terminal Cooperation in User-Deployed Networks

Debernardi

Jäger

Laneri

et al. 2006

2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications

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Exploiting high-speed user-deployed Access Points (APs) in public infrastructures has been proposed as one of the candidate solutions for reducing the cost of future radio access. A disadvantage is that, due to lack of deployment coordination, these types of network are likely to provide only partial coverage. For this reason, the set of services that could be successfully provided in these networks might be rather limited.In this paper we present a novel framework for modeling non-interactive "infotainment" services with different degrees of "time criticality", and utilize it for investigating the user service perception in "spotty" coverage networks. In order to hide the infrastructure sparsity to the end users, the terminals are assumed equipped with software agents that can "opportunistically" pre-fetch information, on behalf of their users. This can be done when in contact with an AP, or, through a peer-to-peer file exchange with other terminal agents that have previously accessed the same information. In this paper, for different service types, the relationship between AP density and service perception is investigated. Furthermore, the impact of peerto-peer terminal cooperation is evaluated in respect to both infrastructure requirements and content access delay. The results show that already with moderate AP densities, user-deployed networks deliver acceptable service perception, especially for services with low time criticality. Furthermore, whenever a "critical" mass of users shares common interests, the adoption of a peer-to-peer exchange strategy brings the significant gains of infrastructure reduction and/or improved service perception.

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Service Provisioning with Ad-Hoc Deployed High-Speed Access Points in Urban Environments

Cited by 12 publications

References 10 publications

Economics of WiFi offloading: Trading delay for cellular capacity

Economics of WiFi offloading: Trading delay for cellular capacity

The performance of network-controlled mobile data offloading from LTE to WiFi networks

Service Provisioning and Terminal Cooperation in User-Deployed Networks

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