On the Energy Efficiency of Device Discovery in Mobile Opportunistic Networks: a Systematic Approach 3

IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. X, NO. X, XXXXX 20XX 1 On the Energy Efficiency of Device Discovery in Mobile Opportunistic Networks: A Systematic Approach Bo Han, Jian Li and Aravind Srinivasan Fellow, IEEE Abstract—In this paper, we propose an energy efficient device discovery protocol, eDiscovery, as the first step to bootstrapping opportunistic communications for smartphones, the most popular mobile devices. We chose Bluetooth over WiFi as the underlying wireless technology of device discovery, based on our measurement study of their operational power at different states on smartphones. eDiscovery adaptively changes the duration and interval of Bluetooth inquiry in dynamic environments, by leveraging history information of discovered peers. We implement a prototype of eDiscovery on Nokia N900 smartphones and evaluate its performance in three different environments. To the best of our knowledge, we are the first to conduct extensive performance evaluation of Bluetooth device discovery in the wild. Our experimental results demonstrate that compared with a scheme with constant inquiry duration and interval, eDiscovery can save around 44% energy at the expense of discovering only about 21% less peers. The results also show that eDiscovery performs better than other existing schemes, by discovering more peers and consuming less energy. We also verify the experimental results through extensive simulation studies in the ns-2 simulator. Index Terms—Device discovery, opportunistic communications, energy efficiency, smartphones, Bluetooth. ✦ 1 INTRODUCTION by discovering and sharing media content among users 2 Mobility itself is a significant problem in mobile net- in proximity. Nintendo 3DS’s StreetPass enables players working. On the one hand, protocols designed for mobile to exchange game data with other users they pass on networks should solve the challenges caused by the mo- the street, through the direct device-to-device communi- bility of wireless devices. For example, routing protocols, cation between 3DS systems. Other similar applications such as DSR (Dynamic Source Routing) [16], are required include Sony PS Vita’s Near and Apple’s iGroups. to handle frequent routing changes and reduce the corre- Device discovery is essentially the first step of op- sponding communication overhead. On the other hand, portunistic communications. However, there are very mobility can increase the capacity of wireless networks few practical protocols proposed for it and most of through opportunistic communications [13], where mo- the existing work mainly utilizes (trace-driven) simu- bile devices moving into wireless range of each other lation to evaluate the performance of various device can exchange information opportunistically during their discovery protocols [9], [29]. Moreover, although there periods of contact [7], [21]. are several real-world mobility traces in the CRAWDAD 3 Opportunistic communications have been widely ex- repository which were collected using Bluetooth device plored in delay-tolerant networks [32], mobile social discovery, most of them used very simple discovery applications [21], [31] and mobile advertising [1], to fa- protocols with constant inquiry duration and interval. A cilitate message forwarding, media sharing and location- recently proposed opportunistic Twitter application [24] based services. Meanwhile, there are more and more ap- also uses a 2-minute inquiry interval for Bluetooth device plications leveraging opportunistic communications for discovery. It is known that these kinds of discovery various purposes. For example, LoKast1 is an iPhone ap- protocols are not energy efficient [29] and thus may plication that provides mobile social networking services not be desirable for power-constrained mobile devices, such as smartphones. In this paper, we bridge this gap by developing an energy-aware device discovery proto- • B. Han is with AT&T Labs – Research, 1 AT&T Way, Bedminster, NJ, 07921. This work was done when he was a graduate student at the col for smartphone-based opportunistic communications University of Maryland. and evaluating its performance in practice. E-mail: [email protected] There are two major challenges in designing, imple- • J. Li is with the Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing 100084, China. menting and evaluating energy efficient device discovery E-mail: [email protected] protocols for smartphones. First, the selection of un- • A. Srinivasan is with the Department of Computer Science and the derlying communication technology is complicated by Institute for Advanced Computer Studies, University of Maryland, College Park, MD, 20742. the multiple wireless interfaces on smartphones, such E-mail: [email protected] 2. http://www.nintendo.com/3ds/features/ 1. http://www.lokast.com/ 3. http://crawdad.cs.dartmouth.edu/ 2 IEEE TRANSACTIONS ON MOBILE COMPUTING, VOL. X, NO. X, XXXXX 20XX as Bluetooth and WiFi (a.k.a., IEEE 802.11).4 Although Compared with the STAR protocol proposed by Bluetooth is a low-power radio, its device discovery Wang et al. [29], eDiscovery consumes less energy duration is much longer than WiFi (∼10s for Bluetooth and discovers more peers. eDiscovery also per- vs. ∼1s for WiFi active scanning), which may cause more forms better than another protocol in the literature. energy consumption on smartphones. Similarly, WiFi is Compared with its preliminary version [15], this pa- known to be power-hungry for mobile devices [22], [26]. per makes two new contributions. First, we add the Thus, it is not clear which of them is more suitable for theoretical analysis of device-discovery missing prob- device discovery on smartphones. ability (Section 5), which motivates us to design the Second, given the dynamic nature of human mobility, eDiscovery protocol. Second, we port the implemen- we need to adaptively tune device discovery parame- tation of eDiscovery into the ns-2 simulator enhanced ters, such as inquiry duration and interval, to reduce with the UCBT Bluetooth module5 and offer a detailed smartphone energy consumption. Schemes with constant evaluation of its parameters (Section 8). We also compare inquiry intervals have been proven to be optimal for the performance of eDiscovery and STAR with more minimizing discovery-missing probability [29]. How- network topologies using ns-2 simulations. ever, their energy consumption is usually higher than the adaptive ones, which may miss more devices during dis- 2 DEVICE DISCOVERY IN BLUETOOTH AND covery procedures. Therefore, there is a tradeoff between WIFI energy consumption and discovery-missing probability. We make the following contributions in this paper. In the following, we discuss device discovery of Blue- tooth and WiFi, the two most commonly available local • We present a systematic measurement study of the energy consumption of Bluetooth and WiFi device wireless communication technologies on smartphones. discovery on smartphones, by measuring both the electrical power at various states and the discov- 2.1 Bluetooth ery duration (Section 4). Our results show that The Bluetooth specification (Version 2.1) [3] defines all the energy consumption depends on the number layers of a typical network protocol stack, from the of discovered peers. Based on our measurement baseband radio layer to the application layer. Bluetooth results, we chose Bluetooth as the underlying wire- operates in the 2.4 GHz ISM (Industrial, Scientific and less technology, because even its high-power state Medical) frequency band, shared with other devices such consumes less energy than the low-power state of as IEEE 802.11 stations, baby monitors and microwave WiFi during device discovery. We emphasize that ovens [12]. Therefore, it uses Frequency-Hopping Spread although previous works have studied the power Spectrum (FHSS) to avoid cross-technology interference, of Bluetooth/WiFi devices [9], [11], [22], they either by randomly changing its operating frequency bands. focus on only Bluetooth [9] or ignore the duration of Bluetooth has 79 frequency bands (1 MHz width) in the device discovery [11], [22], without which it is hard range 2402-2480 MHz and the duration of a Bluetooth to evaluate the energy consumption of these devices. time slot is 625 µs. In the following we focus on device • We design an energy-aware device discovery proto- discovery and refer interested readers to Smith et al. [27] col, named eDiscovery, as the first and very im- for further study of the Bluetooth protocol stack. portant step to bootstrapping smartphone-based op- During device discovery, an inquiring device sends portunistic communications (Section 6). By trading out inquiry messages periodically and waits for re- energy consumption for a limited discovery loss, we sponses, and a scanning device listens to wireless demonstrate that eDiscovery is highly effective channels and sends back responses after receiving in- in saving energy on smartphones. eDiscovery dy- quiries [3]. The inquiring device uses two trains of 16 namically tunes the discovery duration and interval frequency bands each, selected from 79 bands. The 32 according to history information of the number of bands of these two trains are selected according to a discovered peers. It also introduces randomization pseudo-random scheme and a Bluetooth device switches into device discovery, in order to explore the search its trains every 2.56 seconds. In every time slot, the space further. inquiring device sends out two inquiry messages on • Our major

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