Heterogeneous Access: Survey and Design Considerations

As voice, multimedia, and data services are converging to IP, there is a need for a new networking architecture to support future innovations and applications. Users are consuming Internet services from multiple devices that have multiple network interfaces such as Wi-Fi, LTE, Bluetooth, and possibly wired LAN. Such diverse network connectivity can be used to increase both reliability and performance by running applications over multiple links, sequentially for seamless user experience, or in parallel for bandwidth and performance enhancements. The existing networking stack, however, offers almost no support for intelligently exploiting such network, device, and location diversity. In this work, we survey recently proposed protocols and architectures that enable heterogeneous networking support. Upon evaluation, we abstract common design patterns and propose a unified networking architecture that makes better use of a heterogeneous dynamic environment, both in terms of networks and devices. The architecture enables mobile nodes to make intelligent decisions about how and when to use each or a combination of networks, based on access policies. With this new architecture, we envision a shift from current applications, which support a single network, location, and device at a time to applications that can support multiple networks, multiple locations, and multiple devices

Energy-aware web browsing in 3g based smartphones

Abstract—Smartphone based web browsing wastes a lot of power when downloading webpages due to the special characteristics of the 3G radio interface. In this paper, we identify these special characteristics, and address power consumption issues through two novel techniques. First, we reorganize the computation sequence of the web browser when loading a webpage, so that the web browser can first run the computations that will generate new data transmissions and retrieve these data from the web server. Then, the web browser can put the 3G radio interface into low power state, release the radio resource, and then run the remaining computations. Second, we introduce a practical data mining based method to predict the user reading time of webpages, based on which the smartphone can switch to low power state when the reading time is longer than a threshold. To demonstrate the effectiveness of our energy-aware approaches, we develop a testbed with Android phones on T-Mobile UMTS network. Experimental results show that our approach can reduce the power consumption of smartphone by more than 30 % during web browsing, and reduce the webpage loading time by 17%. I