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Title: New Abstractions for Mobile Connectivity and Resource Management
Authors: Kiefer, Robert
Advisors: Freedman, Michael J
Contributors: Computer Science Department
Keywords: management
Subjects: Computer science
Issue Date: 2016
Publisher: Princeton, NJ : Princeton University
Abstract: Mobile devices have become an important—and for many, primary—means of connecting to the Internet. They offer great flexibility in how and where they are used, even with constraints like battery life and data caps. However, their network stack and operating system are lacking when it comes to network mobility and managing their limited resources. First, mobility, if even addressed by devices and apps, is done in an ad-hoc manner to “hide” connectivity issues rather than fix underlying shortcomings. Second, resource management is dealt with in broad strokes, scattered among various app and device settings pages. In this thesis, we provide new abstractions addressing these issues. To better handle mobility in the network stack, we need to remove the overloading of IP/port as both app-level connection identifiers and network addresses, thereby allowing apps to maintain a connection even when addresses change. To that end, we present ECCP, a protocol that splits the current transport layer into two: one for connection management (e.g., startup, teardown, migration) and one for data delivery semantics (e.g., reliable, best-effort, etc). ECCP is part of a larger network architecture, Serval, which addresses several pain points with today’s networked systems, consisting of replicated backend services and mobile, multi-homed clients. We derive a state machine for ECCP supporting migration and multipath, and through Serval, we demonstrate ECCP’s value in scenarios utilizing mobility (e.g., VM migration) while achieving par performance with TCP. To utilize better mobility support, devices need a more expressive resource management system. Currently, network choice and resource management is limited to broad decisions (e.g., if cellular network usage is allowed). Users must either choose “good enough” settings or else micromanage their device and apps, e.g., turning WiFi on/off while streaming music between hotspots. Instead, we introduce Tango, a programmatic, policy-based network resource management platform, that works at the device and app levels to offer more flexiblity. Users and apps define policies that dynamically monitor device state to adjust resource usage on their behalf. Using Tango, a user can, e.g., minimize cellular data while streaming music (using it only to prevent playback pauses), saving up to 60-95%.
Alternate format: The Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog:
Type of Material: Academic dissertations (Ph.D.)
Language: en
Appears in Collections:Computer Science

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