To Centralize or Not to Centralize: A Tale of Swarm Coordination
Large swarms of autonomous devices are increasing in size and importance. When it comes to controlling the devices of large-scale swarms there are two main lines of thought. Centralized control, where all decisions - and often compute - happen in a centralized back-end cloud system, and distributed...
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| creator | Hu, Justin Bruno, Ariana Zagieboylo, Drew Zhao, Mark Ritchken, Brian Jackson, Brendon Chae, Joo Yeon Mertil, Francois Espinosa, Mateo Delimitrou, Christina |
| description | Large swarms of autonomous devices are increasing in size and importance.
When it comes to controlling the devices of large-scale swarms there are two
main lines of thought. Centralized control, where all decisions - and often
compute - happen in a centralized back-end cloud system, and distributed
control, where edge devices are responsible for selecting and executing tasks
with minimal or zero help from a centralized entity. In this work we aim to
quantify the trade-offs between the two approaches with respect to task
assignment quality, latency, and reliability. We do so first on a local swarm
of 12 programmable drones with a 10-server cluster as the backend cloud, and
then using a validated simulator to study the tail at scale effects of swarm
coordination control. We conclude that although centralized control almost
always outperforms distributed in the quality of its decisions, it faces
significant scalability limitations, and we provide a list of system challenges
that need to be addressed for centralized control to scale. |
| doi_str_mv | 10.48550/arxiv.1805.01786 |
| format | Article |
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When it comes to controlling the devices of large-scale swarms there are two
main lines of thought. Centralized control, where all decisions - and often
compute - happen in a centralized back-end cloud system, and distributed
control, where edge devices are responsible for selecting and executing tasks
with minimal or zero help from a centralized entity. In this work we aim to
quantify the trade-offs between the two approaches with respect to task
assignment quality, latency, and reliability. We do so first on a local swarm
of 12 programmable drones with a 10-server cluster as the backend cloud, and
then using a validated simulator to study the tail at scale effects of swarm
coordination control. We conclude that although centralized control almost
always outperforms distributed in the quality of its decisions, it faces
significant scalability limitations, and we provide a list of system challenges
that need to be addressed for centralized control to scale.</description><identifier>DOI: 10.48550/arxiv.1805.01786</identifier><language>eng</language><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><creationdate>2018-05</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,780,885</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/1805.01786$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.1805.01786$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Hu, Justin</creatorcontrib><creatorcontrib>Bruno, Ariana</creatorcontrib><creatorcontrib>Zagieboylo, Drew</creatorcontrib><creatorcontrib>Zhao, Mark</creatorcontrib><creatorcontrib>Ritchken, Brian</creatorcontrib><creatorcontrib>Jackson, Brendon</creatorcontrib><creatorcontrib>Chae, Joo Yeon</creatorcontrib><creatorcontrib>Mertil, Francois</creatorcontrib><creatorcontrib>Espinosa, Mateo</creatorcontrib><creatorcontrib>Delimitrou, Christina</creatorcontrib><title>To Centralize or Not to Centralize: A Tale of Swarm Coordination</title><description>Large swarms of autonomous devices are increasing in size and importance.
When it comes to controlling the devices of large-scale swarms there are two
main lines of thought. Centralized control, where all decisions - and often
compute - happen in a centralized back-end cloud system, and distributed
control, where edge devices are responsible for selecting and executing tasks
with minimal or zero help from a centralized entity. In this work we aim to
quantify the trade-offs between the two approaches with respect to task
assignment quality, latency, and reliability. We do so first on a local swarm
of 12 programmable drones with a 10-server cluster as the backend cloud, and
then using a validated simulator to study the tail at scale effects of swarm
coordination control. We conclude that although centralized control almost
always outperforms distributed in the quality of its decisions, it faces
significant scalability limitations, and we provide a list of system challenges
that need to be addressed for centralized control to scale.</description><subject>Computer Science - Distributed, Parallel, and Cluster Computing</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNpNj8uKwjAYRrNxIdUHcGVeoJ3E5lZXluLogOjC7stvLhBoG4lldObpx8ssXH3wHThwEJpRkjHFOfmAePPfGVWEZ4RKJcZoVQdc2X6I0Ppfi0PE-zDg4f1c4hLX0N6hw8crxA5XIUTjexh86Cdo5KC92On_Jqj-XNfVNt0dNl9VuUtBSJEqqSXXJ8eMYlTqgjlNc6UX1EkmBAWTW2AESOHAcMZswbkhd15YIeyC2zxB85f2mdCco-8g_jSPlOaZkv8BXr5CyA</recordid><startdate>20180504</startdate><enddate>20180504</enddate><creator>Hu, Justin</creator><creator>Bruno, Ariana</creator><creator>Zagieboylo, Drew</creator><creator>Zhao, Mark</creator><creator>Ritchken, Brian</creator><creator>Jackson, Brendon</creator><creator>Chae, Joo Yeon</creator><creator>Mertil, Francois</creator><creator>Espinosa, Mateo</creator><creator>Delimitrou, Christina</creator><scope>AKY</scope><scope>GOX</scope></search><sort><creationdate>20180504</creationdate><title>To Centralize or Not to Centralize: A Tale of Swarm Coordination</title><author>Hu, Justin ; Bruno, Ariana ; Zagieboylo, Drew ; Zhao, Mark ; Ritchken, Brian ; Jackson, Brendon ; Chae, Joo Yeon ; Mertil, Francois ; Espinosa, Mateo ; Delimitrou, Christina</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a676-87c75cbf4d8417c94fc138c21f74661ad3ea40a09fad544e955d08c29e66e25e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Computer Science - Distributed, Parallel, and Cluster Computing</topic><toplevel>online_resources</toplevel><creatorcontrib>Hu, Justin</creatorcontrib><creatorcontrib>Bruno, Ariana</creatorcontrib><creatorcontrib>Zagieboylo, Drew</creatorcontrib><creatorcontrib>Zhao, Mark</creatorcontrib><creatorcontrib>Ritchken, Brian</creatorcontrib><creatorcontrib>Jackson, Brendon</creatorcontrib><creatorcontrib>Chae, Joo Yeon</creatorcontrib><creatorcontrib>Mertil, Francois</creatorcontrib><creatorcontrib>Espinosa, Mateo</creatorcontrib><creatorcontrib>Delimitrou, Christina</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hu, Justin</au><au>Bruno, Ariana</au><au>Zagieboylo, Drew</au><au>Zhao, Mark</au><au>Ritchken, Brian</au><au>Jackson, Brendon</au><au>Chae, Joo Yeon</au><au>Mertil, Francois</au><au>Espinosa, Mateo</au><au>Delimitrou, Christina</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>To Centralize or Not to Centralize: A Tale of Swarm Coordination</atitle><date>2018-05-04</date><risdate>2018</risdate><abstract>Large swarms of autonomous devices are increasing in size and importance.
When it comes to controlling the devices of large-scale swarms there are two
main lines of thought. Centralized control, where all decisions - and often
compute - happen in a centralized back-end cloud system, and distributed
control, where edge devices are responsible for selecting and executing tasks
with minimal or zero help from a centralized entity. In this work we aim to
quantify the trade-offs between the two approaches with respect to task
assignment quality, latency, and reliability. We do so first on a local swarm
of 12 programmable drones with a 10-server cluster as the backend cloud, and
then using a validated simulator to study the tail at scale effects of swarm
coordination control. We conclude that although centralized control almost
always outperforms distributed in the quality of its decisions, it faces
significant scalability limitations, and we provide a list of system challenges
that need to be addressed for centralized control to scale.</abstract><doi>10.48550/arxiv.1805.01786</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Computer Science - Distributed, Parallel, and Cluster Computing |
| title | To Centralize or Not to Centralize: A Tale of Swarm Coordination |
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