UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Bibliografiska uppgifter
Huvudupphovsmän:	Araf, Sadman, Saha, Adittya Soukarjya, Eunus, Salman Ibne
Övriga upphovsmän:	Kazi, Sadia Hamid
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2021
Ämnen:	Unmanned aerial vehicle(UAV) Cooperative Edge Caching signal-tonoise ratio multi-agent deep deterministic policy gradient K-means clustering Reinforcement learning
Länkar:	http://hdl.handle.net/10361/15469

id	10361-15469
record_format	dspace
spelling	10361-154692022-01-26T10:13:15Z UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning Araf, Sadman Saha, Adittya Soukarjya Eunus, Salman Ibne Kazi, Sadia Hamid Alam, Md. Golam Rabiul Department of Computer Science and Engineering, Brac University Unmanned aerial vehicle(UAV) Cooperative Edge Caching signal-tonoise ratio multi-agent deep deterministic policy gradient K-means clustering Reinforcement learning This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020. Cataloged from PDF version of thesis. Includes bibliographical references (pages 58-59). In recent times, Multi-access edge computing (MEC) has been introduced to assist cloud servers by bringing the computation closer to the edge. This is a well-known replacement to deal with the strict latency faced by users while retrieving contents from long-distance data centers. To cope up with this latency while simultaneously improving users’ QOS poses a limitation which can be handled through caching at edge nodes. However, where to cache and what to cache so that a higher cache hit rate is achieved also poses another significant issue which is addressed in this research. In this paper we have approached the problem of dynamic caching along with the selection of edge node that leads to better cache hit rate. We have also proposed the use of UAVs as aerial Base Station(BS) to assist in peak hours where a ground base station is not enough to support the surge in user requests.It also elaborates the optimal relocation of UAVs to e↵ectively support user mobility, which then caters a cluster of users by the K-means clustering algorithm. In addition, to maximize the cache hit ratio we have proposed a cooperative deep reinforcement learning algorithm which ensured a global increase in cache hit ratio and also an ecient allocation of storage. We have shown simulations on UAV reallocation based on user mobility patterns and also achieved higher global cache hit ratio using our proposed multi-agent actor-critic algorithm. In this paper, emphasis was given on how to cache and where to cache based on the cooperation of UAV and GBS which open doors for further research. Sadman Araf Adittya Soukarjya Saha Salman Ibne Eunus B. Computer Science 2021-10-19T09:57:44Z 2021-10-19T09:57:44Z 2020 2020-12 Thesis ID 17101354 ID 17101148 ID 17101051 http://hdl.handle.net/10361/15469 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 59 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Unmanned aerial vehicle(UAV) Cooperative Edge Caching signal-tonoise ratio multi-agent deep deterministic policy gradient K-means clustering Reinforcement learning
spellingShingle	Unmanned aerial vehicle(UAV) Cooperative Edge Caching signal-tonoise ratio multi-agent deep deterministic policy gradient K-means clustering Reinforcement learning Araf, Sadman Saha, Adittya Soukarjya Eunus, Salman Ibne UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.
author2	Kazi, Sadia Hamid
author_facet	Kazi, Sadia Hamid Araf, Sadman Saha, Adittya Soukarjya Eunus, Salman Ibne
format	Thesis
author	Araf, Sadman Saha, Adittya Soukarjya Eunus, Salman Ibne
author_sort	Araf, Sadman
title	UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
title_short	UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
title_full	UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
title_fullStr	UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
title_full_unstemmed	UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning
title_sort	uav assisted cooperative caching on network edge using multi agent actor critic reinforcement learning
publisher	Brac University
publishDate	2021
url	http://hdl.handle.net/10361/15469
work_keys_str_mv	AT arafsadman uavassistedcooperativecachingonnetworkedgeusingmultiagentactorcriticreinforcementlearning AT sahaadittyasoukarjya uavassistedcooperativecachingonnetworkedgeusingmultiagentactorcriticreinforcementlearning AT eunussalmanibne uavassistedcooperativecachingonnetworkedgeusingmultiagentactorcriticreinforcementlearning
_version_	1814308070635864064

UAV assisted cooperative caching on network edge using multi agent Actor critic reinforcement learning

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