Transaction / Regular Paper Title

IEEE TRANSACTIONS ON MOBILE COMPUTING, MANUSCRIPT ID 1 Context-Based Network Estimation for Energy-Efficient Ubiquitous Wireless Connectivity Ahmad Rahmati, Student Member, and Lin Zhong, Member, IEEE Abstract— Context information brings new opportunities for efficient and effective system resource management of mobile devices. In this work, we focus on the use of context information to achieve energy-efficient, ubiquitous wireless connectivity. Our field-collected data show that the energy cost of network interfaces poses a great challenge to ubiquitous connectivity, despite decent availability of cellular networks. We propose to leverage the complementary strengths of Wi-Fi and cellular interfaces by automatically selecting the more efficient one based on context information. We formulate the selection of wireless interfaces as a statistical decision problem. The challenge is to accurately estimate Wi-Fi network conditions without powering up its network interface. We explore the use of different context information, including time, history, cellular network conditions, and device motion, to statistically estimate Wi-Fi network conditions with negligible overhead. We evaluate several context- based algorithms for the estimation and prediction of current and future network conditions. Simulations using field-collected traces show that our network estimation algorithms can improve the average battery lifetime of a commercial mobile phone for an ECG reporting application by 40%, very close to the estimated theoretical upper bound of 42%. Further, our most effective algorithm can predict Wi-Fi availability for one and ten hours into the future with 95% and 90% accuracy, respectively. Index Terms— Network Architecture and Design, Local and Wide-Area Networks. —————————— —————————— 1 INTRODUCTION merging mobile applications in healthcare and mul- energy per MB transfer. Our solution is to employ Wi-Fi timedia demand ubiquitously available wireless net- to improve the energy efficiency of cellular data transfer. Ework connectivity. Despite of the wide deployment of However, unlike cellular networks, Wi-Fi has limited cellular networks and an increasing number of Wi-Fi availability and its network interface needs to remain hot-spots, how close we are to achieving ubiquitous con- powered-off as much as possible due to its overwhelming nectivity in our everyday life is still an open question. In power consumption. The key challenge is to determine if this work, we show the complementary strengths of cellu- attempting a Wi-Fi connection is profitable energywise. lar and Wi-Fi networks and present context-based net- Addressing this challenge requires estimating Wi-Fi network estimation to take advantage of their complementa- work conditions without powering on the Wi-Fi interface. ry strengths and provide ubiquitous energy-efficient In this work, we explore the use of context information wireless connectivity. to estimate Wi-Fi network conditions. Such context in- In order to realistically evaluate context-based network formation includes time, history, cellular network condi- estimation for everyday life, we gathered field data about tions, and device motion. We devise effective algorithms cellular and Wi-Fi networks through participants from to learn the conditional probability distribution of Wi-Fi the Rice community in Houston, Texas, a major US urban network conditions, given context information. With the area from September 2006 to February 2007. Our data conditional probability distribution, we formulate wire- showed a bright picture regarding network availability: less data transfer through multiple interfaces as a statis- on average, our participants spent 99% and 49% of their tical decision problem, and validate our solutions through everyday lives under cellular and accessible Wi-Fi net- both trace-based simulation and field trials. Further, we works, respectively. However, the reality about the ener- evaluate the performance of our algorithms for the pre- gy cost and battery lifetime is not as bright. For example, diction of future network conditions. On average, our wireless data transfer for a three-channel ECG reporting most effective algorithm can predict Wi-Fi availability for application will reduce the battery lifetime of a commer- one and ten hours into the future with 95% and 90% accu- cial mobile phone by over 75%. racy, respectively. For the ECG reporting application, our Compared to Wi-Fi, cellular networks require much most effective algorithm improves the battery lifetime of lower power to stay connected but incur much higher a commercial mobile phone by 40%, close to the theoretical upper bound of 42%. Our field validation for the same ———————————————— application showed a 35% improvement in battery life- Ahmad Rahmati and Lin Zhong are with the Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005. E-mail: {rah- time. mati, lzhong}@rice.edu. We have made the following contributions in this work: • We present a reality check of network availability Manuscript received (insert date of submission if desired). Please note that all acknowledgments should be placed at the end of the paper, before the bibliography. xxxx-xxxx/0x/$xx.00 © 200x IEEE 2 IEEE TRANSACTIONS ON MOBILE COMPUTING, MANUSCRIPT ID and the energy cost of ubiquitous connectivity in cording to the GSM Association [4], there are over 2.5 people’s everyday life, and study the use of Wi-Fi billion global mobile phone users as of October 2006, ac- networks to improve the energy efficiency of cellular counting for 40% of the world population. Moreover, 80% networks. We offer a theoretical analysis on data of the world population is covered by cellular networks, transfer through multiple wireless interfaces. Based double that of year 2000. As a result, the deployment of on our power measurements on a commercial mobile cellular data services has the potential to enable an un- phone, we provided the theoretical upper bound of precedented portion of the world population with increa- energy savings. singly ubiquitous wireless Internet access. The effective • We investigate several algorithms to estimate Wi-Fi expansion of cellular network coverage roots in that it is a network conditions using context information. Fur- wireless metro-area technology and each base station ther, we evaluate their performance for the prediction covers a relatively large area. However, the potentially of future network conditions. Estimated network large distance between a mobile phone and its base sta- conditions can be utilized to minimize the energy tion limits the energy efficiency for data transfers. consumption of data transfers. Our measurements Shorter range wireless networks are also increasingly and field evaluation showed that our estimation algo- available, especially in urban, residential, and business rithms can achieve energy savings close to the theo- settings. Wi-Fi, a wireless local-area network (WLAN) retical upper bound. technology, has seen rapid expansion. It has been recently estimated that there are more than 14 million Wi-Fi access The rest of this paper is organized as follows. In Sec- points in US homes [5]. Several major US cities have an- tion 2, we provide the background for our study and in nounced plans to deploy city-wide Wi-Fi networks. Yet, Section 3, we describe our experiments, field studies, and Wi-Fi still has limited availability compared to cellular energy model. In Section 4, we formulate data transfer networks. On the other hand, the relatively short range of through multiple wireless interfaces as a statistical deci- Wi-Fi enables it to achieve a much higher data rate and sion problem, present a theoretical analysis. We present a lower energy per MB data transfer compared to cellular. suite of context-sensitive algorithms to estimate network Therefore, to achieve energy-efficient ubiquitous wireless conditions in Sections 5, and validate them through a real connectivity, it is important to combine the strength of world traces and a field test with a mobile healthcare ap- both networks, as is the focus of this work. plication in Section 6. We present a discussion in Section 7 and address related work in Section 8. Finally, we con- clude in Sections 9. Early results from this work were pre- sented in Context-for-Wireless [1]. 2 BACKGROUND In addition to traditional applications, such as email and web browsing, emerging applications in mobile healthcare, multimedia, and Web 2.0 have created an in- satiable appetite for ubiquitous wireless data. Emerging mobile healthcare applications seek to collect health in- Figure 1. An HTC Wizard with the sensor board in its battery formation via body-worn or implanted sensors, and de- compartment (left) and an opened battery for power measure- liver health-promoting messages in situ and throughout ment (right) people’s everyday life. Many mobile healthcare applications depend on ubiquitous wireless connectivity from a 3 EXPERIMENTAL PLATFORM mobile device to report health data and deliver messages in time. More importantly, they require a broad range of In order to realistically evaluate context-based network data size and allowable transfer latencies [2, 3]. The in- estimation for everyday life, we have gathered network creasing information capturing and processing capabili- data from a number of mobile users over six months, and ties of mobile devices, especially mobile phones, enables obtained the energy profiles of wireless interfaces on mul- users to

Load more