Fueled by its recent success in provisioning on-site wireless Internet access, Wi-Fi is currently perceived as the best positioned technology for pervasive mobile macro network offloading. However, the broad transitions of multiple collocated operators towards this new paradigm may result in fierce competition for the common unlicensed spectrum at hand. In this light, our paper game-theoretically dissects market convergence scenarios by assessing the competition between providers in terms of network performance, capacity constraints, cost reductions, and revenue prospects. We will closely compare the prospects and strategic positioning of fixed line operators offering Wi-Fi services with respect to competing mobile network operators utilizing unlicensed spectrum. Our results highlight important dependencies upon inter-operator collaboration models, and more importantly, upon the ratio between backhaul and Wi-Fi access bit-rates. Furthermore, our investigation of medium-to long-term convergence scenarios indicates that a rethinking of control measures targeting the large-scale monetization of unlicensed spectrum may be required, as otherwise the used free bands may become subject to tragedy-of-commons type of problems.
Due to increasingly overloaded mobile 3G networks, the offload of non-realtime traffic has recently raised significant academic interest @cite_6 . Although manual traffic offload has de facto been a success story (for up to 65
@cite_6
2006121063 2167718801 1986247300 2120492209
Cellular networks, especially 3G networks, are currently overloaded with mobile data traffic. It is thus imperative to develop novel communication architectures and protocols for this problem. In this paper, we propose to exploit the delay-tolerant nature of non-realtime applications to offload mobile data traffic through opportunistic communications and WiFi networks. We argue that it is necessary for cellular network operators, WiFi service providers, and end-users to cooperate to make the offloading more effective. We also present several preliminary experiment results about the work we have been conducting, which show that it is promising to offload mobile data traffic in metropolitan area networks. 3G networks are currently overloaded, due to the increasing popularity of various applications for smartphones. Offloading mobile data traffic through opportunistic communications is a promising solution to partially solve this problem, because there is almost no monetary cost for it. We propose to exploit opportunistic communications to facilitate information dissemination in the emerging Mobile Social Networks (MoSoNets) and thus reduce the amount of mobile data traffic. As a case study, we investigate the target-set selection problem for information delivery. In particular, we study how to select the target set with only k users, such that we can minimize the mobile data traffic over cellular networks. We propose three algorithms, called Greedy, Heuristic, and Random, for this problem and evaluate their performance through an extensive trace-driven simulation study. Our simulation results verify the efficiency of these algorithms for both synthetic and real-world mobility traces. For example, the Heuristic algorithm can offload mobile data traffic by up to 73.66 percent for a real-world mobility trace. Moreover, to investigate the feasibility of opportunistic communications for mobile phones, we implement a proof-of-concept prototype, called Opp-off, on Nokia N900 smartphones, which utilizes their Bluetooth interface for device service discovery and content transfer. Over the last few years, data traffic over cellular networks has seen an exponential rise, primarily due to the explosion of smartphones, tablets, and laptops. This increase in data traffic on cellular networks has caused an immediate need for offloading traffic for optimum performance of both voice and data services. As a result, different innovative solutions have emerged to manage data traffic. Some of the key technologies include Wi-Fi, femtocells, and IP flow mobility. The growth of data traffic is also creating challenges for the backhaul of cellular networks; therefore, solutions such as core network offloading and media optimization are also gaining popularity. This article aims to provide a survey of mobile data offloading technologies including insights from the business perspective as well. The co-existence of cellular and wired networks has been exploited almost exclusively in the direction of OffLoading traffic from the former onto the latter. In this paper we claim that there exist cases that call for the exact opposite, i.e, use the cellular network to assist a fixed wired network. In particular, we show that by "OnLoading'' traffic from the wired broadband network onto the cellular network we can usefully speedup wired connections, on the downlink or the uplink. We consider the technological challenges pertaining to this idea and implement a prototype 3G OnLoading service that we call 3GOL, that can be deployed by an operator providing both the wired and cellular network services. By strategically OnLoading a fraction of the data transfers to the 3G network, one can significantly enhance the performance of particular applications. In particular we demonstrate non-trivial performance benefits of 3GOL to two widely used applications: video-on-demand and multimedia upload. We also consider the case when the operator that provides wired and cellular services is different, adding the analysis on economic constraints and volume cap on cellular data plans that need to be respected. Simulating 3GOL over a DSLAM trace we show that 3GOL can reduce video pre-buffering time by at least 20 for 50 of the users while respecting data caps and we design a simple estimator to compute the daily allowance that can be used towards 3GOL while respecting caps. Our prototype is currently being piloted in 30 households in a large European city by a large network provider.