Zegura, Ellen W.

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Now showing 1 - 6 of 6
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    Innovation in Public Impact Research Across Georgia Tech
    ( 2017-04-19) Ross, Catherine ; Wagner Dahl, Margaret ; Zegura, Ellen W.
    Join the Georgia Tech Center for Health & Humanitarian Systems (CHHS) for a presentation and discussion with faculty across campus on new research and technology relating to resilience, social impact, public health, international development, and other topics. Learn about research, project-based courses, and internships taking place at the Center for Quality Growth and Regional Development, Computing for Good (C4G) at the College of Computing, the Serve Learn Sustain Initiative (SLS), Data Science for Social Good, and the Enterprise Innovation Institute (Ei2), as well as related partnerships with local and federal government and organizations around the world.
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    Health and Humanitarian Logistics - Panel 2: Managing Complex Supply Chains in Refugee Crisis Response
    (Georgia Institute of Technology., 2016-08-29) Hapnes, Svein ; Wilson, Edward ; Zegura, Ellen W.
    The challenges in timely response to the needs of international refugees and internally displaced people include complex political and security contexts, physical movement of the beneficiaries, variable demand patterns from emergencies with high peaks to ongoing protracted situations. In addition, the wide scope of response from feeding and sheltering beneficiaries on the move or in camps to resettling them in new locations multiplies these challenges. However, some factors are addressed by innovative operations and policy design and coordinated response of the stakeholders. The panel will discuss challenges and opportunities in the context of both the highly publicized current Middle East emergency response and the global ongoing operations.
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    IC-Cloud: Computation Offloading to an Intermittently-Connected Cloud
    (Georgia Institute of Technology, 2013) Shi, Cong ; Pandurangan, Pranesh ; Ni, Kangqi ; Yang, Juyuan ; Ammar, Mostafa H. ; Naik, Mayur ; Zegura, Ellen W.
    Offloading computation-intensive components of mobile applications to the cloud is of great potential to speedup the execution and reduce the energy consumption for mobile devices. The gain from computation offloading is typically counterbalanced by communication costs and delays. It is, therefore, important to undertake offloading decisions based on future prediction of Internet access timeliness and quality. Previous approaches have considered this question under the assumption that network connectivity is relatively stable. In this paper, we present IC-Cloud, a computation-offloading system for mobile environments where Internet access to remote computation resources is of highly variable quality and often intermittent. IC-Cloud uses three key ideas: lightweight connectivity prediction, lightweight execution prediction and prediction use in a risk controlled manner tomake offloading decisions. Our connectivity-prediction method only uses the signal strength and user historical information to obtain a coarse-grained estimation of the network access quality. Our execution-prediction mechanism uses machine learning on dynamic program features to automatically, efficiently, and accurately predict the execution time of offloadable tasks, both on the phone and in the cloud. Acknowledging the uncertainties in these predictions, we propose a risk-control mechanism to reduce the impact of inaccurate predictions. We implemented IC-Cloud on Android and tested the system with different applications in various types of mobile environment. Results we obtained from the prototype show speedup and energy consumption reduction benefits in many computational contexts and intermittent connectivity environments.
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    Design and Analysis of Schedules for Virtual Network Migration
    (Georgia Institute of Technology, 2012) Lo, Samantha ; Ammar, Mostafa H. ; Zegura, Ellen W.
    The Internet faces well-known challenges in realizing modifications to the core architecture. To help overcome these limitations, virtual networks run over physical networks and use Internet paths and protocols as essentially a link layer in the virtual network. Effective use of the underlying network requires intelligent placement of virtual networks so that underlying resources do not incur over-subscription. Additionally, because virtual networks may come and go over time, and underlying networks may experience their own dynamic changes, virtual networks may need to be migrated— re-mapped to the physical network during active operation— to maintain good performance. In this paper we consider the problem of scheduling the sequence of node moves that take a virtual network from an original placement to a new placement. We build on prior work that achieves migration of a single node with minimal disruption to develop a model for the migration cost and latency for a given network migration schedule. We then develop algorithms for determining a single-node-at-a-time sequence of moves to minimize migration cost, and further consider multiple node moves in parallel to minimize migration time and cost. Our algorithms are the first we are aware of to systematically address the virtual network migration scheduling problem.
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    Serendipity: A Distributed Computing Platform for Disruption Tolerant Networks
    (Georgia Institute of Technology, 2011-01) Shi, Cong ; Lakafosis, Vasileios ; Ammar, Mostafa H. ; Zegura, Ellen W.
    The opportunistic or disruption tolerant networking (DTN) paradigm shows up in a variety of settings, from military to disasters to the developing world to deep space; anywhere that fixed infrastructure is either unavailable or expensive. Simple messaging applications have substantial value for communication and coordination. We posit that these settings can also leverage applications that are computationally complex and will benefit from distributed computing to take full advantage of nearby computational resources. Computing over these networks is not trivial, however, since network disconnections are common and persist over many time scales. In this paper we present the design and implementation of Serendipity, a general purpose distributed computing platform designed to run over a DTN. We have designed a simple but powerful job structure that is suitable for such an underlying network. As opposed to traditional distributed computing platforms in data centers and clusters, where a central master is used to allocate tasks and monitor the working nodes, Serendipity relies on the collaboration among DTN nodes on these functionalities. Smart task allocation algorithms are designed to disseminate tasks among mobile devices by accounting for the special properties of DTNs. The extensive evaluation of our system on Emulab demonstrates that Serendipity efficiently speeds up various kinds of distributed computing jobs by a factor of 2.3 to 10.1 in a diverse set of DTN environments.
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    Collaborative Research: NeTS-NBD: Construction of robust and efficient disruption tolerant networks
    (Georgia Institute of Technology, 2010-11-14) Zegura, Ellen W. ; Ammar, Mostafa H. ; Clark, Russ