rice/context2007052330200705232007-08-17rice/contextDataset of context information from cellular and Wi-Fi networks through participants from a major US urban area.

We gathered field data about cellular and Wi-Fi networks through participants from the Rice community in Houston, Texas, a major US urban area.

the initial version2007-08-012007-01-162007-02-28rahmati-contextREADME126127http://www.crawdad.org/rice/contexthttp://www.crawdad.org/wiki/pmwiki.php?n=Main.Dataset.rice-context802.11cellular networkEnergy-efficient Wireless Network802.11 infrastructurecellular networkIn order to check how close we are toward ubiquitous connectivity in our everyday life, we have gathered network data from a number of mobile users on multiple mobile phones through measurement. We explore the use of different context information, including time, history, cellular network conditions, and device motion, to accurately estimate Wi-Fi network conditions without powering up its network interface.We have used multiple HTC Wizard PDA phones for our data collection. The HTC Wizard is commercially available under a variety of brands, including T-Mobile MDA and Cingular 8125. It is a Windows Mobile 5.0 GSM phone with integrated 802.11b and is capable of EDGE data connectivity. It has a battery capacity of 1250mAh at 3.7 volts.We have developed logging software to record various network characteristics with minimal intrusion to the normal phone operation. We have converted eleven HTC Wizards into experimental mobile phones by installing our logging software. 14 volunteers from the Rice campus participated in our data gathering. They carried around our experimental phones for at least three weeks and could opt to use their own SIM card on the phone. We requested all participants to carry the phone as they would carry their own phone. We interviewed each participant regularly to document any significant diversion from their daily activities, for example, travels and forgetting carrying the phone.This dataset is from different time periods than the traces used in the mobisys paper [rahmati-context]. We continued our logging after the paper, and have included those. We also used some logs from older versions of TowerLogger in the paper that do not exist here.42200708012007-08-17rice/context/availabilityTraceset of network availability, signal levels, and context information.

This traceset contains logs of network availability, signal levels, and context information, measured on Wi-Fi enabled GSM cellular phones.

the initial version2007-08-082007-01-162007-02-28Energy-efficient Wireless Network802.11 infrastructurecellular network- Tower Logger: Measuring Network Conditions Our logging software, called Tower Logger, measures network availability and signal levels, and context information. It records the cell tower ID, signal strength, and channel of the currently-associated GSM cell and those of up to 6 other visible cells every 30 seconds or 60 seconds. It also records the unique Basic Service Set Identifier (BSSID), signal strength and the security property of all visible Wi-Fi access points.Each BSSID / Cell Tower is assigned a unique ID that is consistent throughout all our traces. Further, participant IDs are randomized ("01" - "10" in the traces do not correspond to P1 - P10 in our paper). Wi-Fi: The BSSID is anonymized except for the first 3 octets. Cell towers: LAC and CI are anonymized for each cell tower (MCC:MNC:LAC:CI)./download/rice/context/Context-for-Wireless_Logs.tar.gzrice/context105200708012007-08-17rice/context/availability/GSMGSM Cellular logs of availability and signal strength.

This trace contains GSM Cellular logs of availability and signal strength, measured on 10 participants' Wi-Fi enabled GSM cellular phones.

the initial versionfalse2007-08-012007-01-162007-02-28This trace contains Tower Logger network GSM Cellular logs: availability and signal strength, measured on 10 participants' Wi-Fi enabled GSM cellular phones.The trace tarball consists of 10 directories "01"-"10", which are the logs from 10 participatants' phones ("01" - "10" in the traces do not correspond to P1 - P10 in our paper.) Each directory contains either GSM log or Wi-Fi log. GSM logs are named 'log2GSM_yyyy-mm-dd.txt'. They are in csv (comma-separated value) file format, where each line consists of the following fields: version no. connected Orbit Sensor ID (0 = none) date time battery level charge status no. of visible cell towers list of visible cell towers (starting with associated tower): Cell ID: MCC MNC LAC (anonymized) CI (anonymized) signal strength channel BSICrice/context/availability106200708012007-08-17rice/context/availability/Wi-FiWi-Fi logs of availability and signal strength.

This trace contains Wi-Fi logs of availability and signal strength, measured on 10 participants' Wi-Fi enabled GSM cellular phones.

the initial versionfalse2007-08-012007-01-162007-02-28This trace contains Tower Logger network Wi-Fi logs: availability and signal strength, measured on 10 participants' Wi-Fi enabled GSM cellular phones.The trace tarball consists of 10 directories "01"-"10", which are the logs from 10 participatants' phones ("01" - "10" in the traces do not correspond to P1 - P10 in our paper.) Each directory contains either GSM log or Wi-Fi log. Wi-Fi logs are named 'log2WiFi_yyyy-mm-dd.txt'. They are in csv (comma-separated value) file format, where each line consists of the following fields: version no. connected Orbit Sensor ID (0 = none) date time battery level charge status list of visible AP info: BSSID (anonymized except the first 3 octets) signal strength encrypted? infrastructure mode?rice/context/availability126rice/contextAhmad Rahmatirahmati@rice.eduRice UniversityDept. of Electrical & Computer EngineeringPh.D Studenthttp://www.ruf.rice.edu/~rahmati/127rice/contextLin Zhonglzhong@rice.eduRice UniversityDept. of Electrical & Computer Engineering, Dept. of Computer ScienceAssistant Professor

Rice University, MS-380, 6100 Main St. Houston, TX 77005

http://www.ruf.rice.edu/~lzhong/index.htmrahmati-contextAhmad RahmatiLin ZhongProceedings of the Fifth International Conference on Mobile Systems, Applications, and Services (MobiSys)--06--2007http://doi.acm.org/10.1145/1247660.1247681

San Juan, Puerto Rico

USENIX AssociationEnergy-efficient wireless, multiple wireless interfaces, contextfor-wirelessUbiquitous connectivity on mobile devices will enable numerous new applications in healthcare and multimedia. We set out to check how close we are towards ubiquitous connectivity in our daily life. The findings from our recent field-collected data from an urban university population show that while network availability is decent, the energy cost of network interfaces poses a great challenge. Based on our findings, we propose to leverage the complementary strength of Wi-Fi and cellular networks by choosing wireless interfaces for data transfers based on network condition estimation. We show that an ideal selection policy can more than double the battery lifetime of a commercial mobile phone, and the improvement varies with data transfer patterns and Wi-Fi availability. We formulate the selection of wireless interfaces as a statistical decision problem. The key to attaining the potential battery improvement 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, for this purpose. We consequently devise algorithms that can effectively learn from context information and estimate the probability distribution of Wi-Fi network conditions. Simulations based on field-collected traces show that our algorithms can improve the average battery lifetime of a commercial mobile phone for a three-channel electrocardiogram (ECG) reporting application by 39%, very close to the theoretical upper bound of 42%. Finally, our field validation of our most simple algorithm demonstrates a 35% improvement in battery lifetime.wireless-meas,crawdadmeasurementwirelessrice_contextcrawdadrice/context20070601