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report.lyx
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Cametrics: A Novel Data Logger, Aggregator, and Visualizer Cloud Service
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Olmo Maldonado,
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ibolmo@ucla.edu
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, UCLA Department of Electrical Engineering
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Abstract
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Logging and visualization of data collected is becoming practical to implement in many projects due to a growing number of tools and web services. There are difficulties in transferring custom visualizations or measurements between projects, however, because of losing compatibility or a heavy learning curve in understanding the logging and visualization tools. Likewise, the actual logging system, visualization tool, and storage protocols are all separate from each other. This makes management and deployment a consuming process. In order to mitigate these challenges, we propose to standardize the measurement interface, centralize all the collected data, and to format the retrieval and visualization of the measured data. Cametrics, or campaign metrics, does this by providing a developer with client libraries with a simple
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functions. Furthermore, the data is stored in Google App Engine's datastore, which allows the system to scale to demand. Cametrics can also accept any type of data, and is able to return any format that the organizer requests. Cametrics has large support for standard statistical summaries, which can be visualized with Google Charts or Maps API. This paper details the design choices and requirements made to complete the first iteration of Cametrics. Moreover, we discuss the issues, limitations, evaluation, and future work needed for Cametrics.
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Introduction
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Logging and measuring usage of a system is an important feedback for system debugging and design. A developer can monitor the usage of a website by injecting logging calls inside of their scripts that log to a flat file or database. After some time, the developer creates a script to parse the log and uses third party libraries to construct a visualization of the data. A trend of number of users per month, for example would be a metric to understand if a website is becoming more popular. What if the developer wanted to visualize the geolocation of the user's IP address? The developer has to create yet another script to mine the logs of their web server for all the visitor IP addresses and then geocode the IP address. Then, he would take the GPS coordinates and use another third party service to display the data on a world map. As the complexity of the visualization or requirements of the developer grows more and more, more scripts are created which may eventually become incompatible across projects or difficult to maintain because of the rapid development of the scripts.
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This is an ongoing challenge in participatory sensing (coordinated data gathering by individuals, groups, and communities to explore the world around them) campaigns. Campaigns are targeted and coordinated data collection efforts between an organizer (anyone with an interest in coordinating a data-gathering campaign) and a large number of participants of the campaign. In order to manage the campaign, an organizer typically creates a new web site to personalize the campaign for the participants and other guests that might like to join the campaign. Although the act of creating a new website is trivial, migrating subsystems like a logging system are non-trivial due to organizers expertise in the subsystem. Moreover, the original author of the scripts may not be the current organizer of the campaign. Due to the environment of participatory sensing there is a need to minimize the amount of code and settings changes that an organizer must do in order for the system to be a fully functional campaign.
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In this paper, we discuss such a participatory sensing campaign: What's Invasive
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1
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. What's Invasive is a test pilot campaign that is an effort to equip the National Park Services with GPS-ready smart phones that can be used to map the Santa Monica mountains for invasive species. Invasive species are species that are not native to the area that if otherwise left alone would consume resources, which may endanger the indigenous plants.
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Cametrics, or campaign metrics, was created to reduce the complexity in migrating the logging systems between new campaigns and to reduce the amount of code to produce visualization of the data collected from participants and/or the systems that the campaign is running on. After extensive work, and research, we have found that Cametrics' scope is no longer narrowed to just campaigns. Cametrics has become a general-purpose logging, aggregator, and visualization web service that any device that supports the HTTP protocol can use to log data, which can then be rendered as visualization or any other requested format. Cametrics lives in the cloud and is capable of scaling between large numbers of concurrent users. Most important, due to the mission to be simple and flexible, Cametrics is easy to get started and producing visualizations. This is a divergence from other logging and visualization web services. Furthermore, Cametrics is unique in its way it aggregates the data by having standard summarization classes per data type. Cametrics also supports large number of types, which is contrary to many web services, which would constrict an organizer to a fixed set of types. For example, location and GPS data types are now supported and summarized to simplify the organizer's time in understanding the area covered by a participant. If the system does not support a format or type, Cametrics can be easily be extended by a developer contributed classes which will work as plug and play classes.
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In this paper, we discuss related web services that have a similar scope as Cametrics and how they compare. We list the contributions made by this research and how we stand apart from the previous works. The requirements and choices made on the design of the system and the architecture of the system are also included. Lastly, we conclude with the evaluation of the system with quantitative and qualitative measurements and future work that is interesting or are required for Cametrics to move forward.
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http://whatsinvasive.com/
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Related Work
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The following table compares other web services against Cametrics.
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