Energy Efficient Offloading of 3G Networks

Abstract

Abstract-The increase in data consumed by smartphones is becoming a huge problem for mobile operators. In three years, mobile data traffic in AT&T's network rose 5000%. The US operators invest $50 billion in the data networks every year and the technology upgrades and innovation still fail to keep up with the demand.In this paper we design two algorithms for delaytolerant offloading of bulky, socially recommended content from 3G networks. The first one, called "MixZones", uses opportunistic, ad hoc transfers between users, and is assisted by predictions made by the network operator. The second one, called "HotZones", exploits delay tolerance and tries to download contents when users are close to Wi-Fi access points; it is also assisted by predictions made by the operator. We evaluate both algorithms using a large data set, obtained from a major mobile operator and a realistic application similar to Apple's Ping music social network. The metrics address the amount of offloading, delay and mobile energy efficiency.We find that both solutions succeed in offloading a significant amount of traffic, with a positive impact on user battery lifetime. Surprisingly, we also find that all the benefit obtained from the operator with the MixZones algorithm (i.e with ad hoc exchanges between users) can be achieved with the HotZones algorithm and a small investment in Wi-Fi access points. Note that the latter is considerably less complex to deploy than the former.

Vehicular WiFi offloading: Challenges and solutions

“…Offloading schemes aiming to improve the mobile devices' energy efficiency can be found in [18,19,20]. An effort is made in [18] to reduce the energy consumption in the application of uploading delay-tolerant videos captured by smart phones.…”

“…Through real trace driven simulation, the proposed algorithm can save 10-40% of the total energy capacity of the smart phone battery. Motivated by the fact that WiFi radio wastes a lot of energy in scanning transmission opportunities and remaining idle, a prediction-based offloading scheme is proposed in [19] to save energy of user devices. The operator collects its subscribers' user mobility profile (UMP) and deploys WiFi APs in the places which are mostly visited.…”

“…Therefore, a well-planed WiFi deployment can offer a good offloading performance at a low cost. The WiFi deployment strategies considering the popularity of locations are proposed and evaluated in [11] and [19]. The main idea is to deploy WiFi APs at locations with high popularity, i.e., visited by users with high frequency.…”

“…In [23], an offloading scheme is proposed to schedule applications with different size and delay tolerance requirement in order to minimize cellular usage, which is adaptive to the varying coverage and bandwidth of the WiFi and cellular networks. The prediction of mobility and offloading performance is investigated in [19,24,25]. The security issues in WiFi offloading are studied in [26].…”

Enabling energy-aware collaborative mobile data offloading for smartphones

“…Hou et al [11] propose a transport layer protocol to offload 3G data traffic to WiFi hotspots for vehicular access networks. Ristanovic et al [20] propose an algorithm, called HotZones, to offload delay-tolerant cellular content to WiFi APs and evaluate the performance through trace-driven simulations.…”