{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/130715"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/130715","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Measuring and optimizing for network conditions on drones","abstract":"As drones emerge as viable vehicles for mobile computation, a world where we can deploy a fleet of drones to execute tasks, like streaming real-time video, sounds less like sci-fi and more like a quickly-approaching reality. In order to take full advantage of the capability of drones, we must understand the state of network conditions in the air and determine how we can best optimize for them. Here, we contribute twofold. First, we developed and deployed a set of tools to collect network data on a flying drone and then process it to characterize the network conditions the drone experienced. Second, we developed a simulator to play back the collected network traces and help understand how to harness the power of a fleet of drones working in coordination to compensate for unstable network conditions in the air.","abstract_html":"As drones emerge as viable vehicles for mobile computation, a world where we can deploy a fleet of drones to execute tasks, like streaming real-time video, sounds less like sci-fi and more like a quickly-approaching reality. In order to take full advantage of the capability of drones, we must understand the state of network conditions in the air and determine how we can best optimize for them. Here, we contribute twofold. First, we developed and deployed a set of tools to collect network data on a flying drone and then process it to characterize the network conditions the drone experienced. Second, we developed a simulator to play back the collected network traces and help understand how to harness the power of a fleet of drones working in coordination to compensate for unstable network conditions in the air.","abstract_has_math":false,"creators":["Srinivasan, Aditi(Aditi H.)"],"institution":"Massachusetts Institute of Technology","degree_name":"Master","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","school":null,"contributors":[],"advisors":["Hari Balakrishnan."],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021","date_published":"2021","updated_at":"2026-07-22T22:21:28Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/130715","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Hari Balakrishnan."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","EECS"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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Second, we developed a simulator to play back the collected network traces and help understand how to harness the power of a fleet of drones working in coordination to compensate for unstable network conditions in the air."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M. Eng."]},{"key":"dc:title","label":"Title","values":["Measuring and optimizing for network conditions on drones"]}]}],"canonical_facts":{"dc:contributor.advisor":["Hari Balakrishnan."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science","EECS"],"dc:contributor.other":["Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science."],"dc:creator":["Srinivasan, Aditi(Aditi H.)"],"dc:date.accessioned":["2021-05-24T19:52:45Z"],"dc:date.available":["2021-05-24T19:52:45Z"],"dc:date.issued":["2021"],"dc:description":["Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2021","Cataloged from the official PDF of thesis.","Includes bibliographical references (pages 43-44)."],"dc:description.abstract":["As drones emerge as viable vehicles for mobile computation, a world where we can deploy a fleet of drones to execute tasks, like streaming real-time video, sounds less like sci-fi and more like a quickly-approaching reality. In order to take full advantage of the capability of drones, we must understand the state of network conditions in the air and determine how we can best optimize for them. Here, we contribute twofold. First, we developed and deployed a set of tools to collect network data on a flying drone and then process it to characterize the network conditions the drone experienced. Second, we developed a simulator to play back the collected network traces and help understand how to harness the power of a fleet of drones working in coordination to compensate for unstable network conditions in the air."],"dc:description.degree":["M. Eng."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/130715"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Measuring and optimizing for network conditions on drones"],"dc:type":["Thesis"],"thesis:degree_name":["Master"]},"updated_at":"2026-07-22T22:21:28Z"}