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\Large{\textbf{References Demo}}
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\section{Introduction}
For disaster management, uncertainty handling is the main key problem. But, in
Joint Service deployment and Requests Allocation~(JSR) domain, research work
mainly uses the approaches such as deterministic optimization \cite{hardtoshare,
multicell, bandwidth}, Lyapunov optimization \cite{dataintensive}, stochastic
optimization, replication of services to achieve high reliability, and forecasting of
user requests using machine learning without considering uncertainty. In
deterministic optimization \cite{edgeuav}, request demand is known before the
run. However, in online optimization, time is divided into slots and performs
optimization per slot basis, which does not consider uncertain demand. Even if
we used any probability distribution to model demand, it does not provide the
correct model/pattern to define the uncertain data \cite{edgeuncertainty}. Using
a replication approach to achieve high availability also incurs extra resource cost
\cite{robust}. Using the forecasting method also, we can not predict the impact
of uncertain events on the requests, which may lead to under-provisioning/over
provisioning resources to process the required tasks \cite{rsome}.
\section{Experiment Setup and Performance Parameters}
To demonstrate the efficiency of the proposed approaches, we will simulate the
scenario for an urban site affected by any natural calamity \cite{oilindustry}. To
implement optimization models, we will use the IBM Cplex Optimizer tool
\cite{cplex}.
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ref.bib
@ARTICLE{oilindustry,
author={Ngoenriang, Napat and Turner, Stephen John and Niyato, Dusit and
Supittayapornpong, Sucha}, journal={IEEE Internet of Things Journal},
title={Joint UAV-Placement and Data Delivery in Aerial Inspection under
Uncertainties}, year={2021}, volume={}, number={}, pages={1-1},
doi={10.1109/JIOT.2021.3113713}}
@ARTICLE{uavservice,
author={Qu, Yuben and Dai, Haipeng and Wang, Haichao and Dong, Chao and
Wu, Fan and Guo, Song and Wu, Qihui}, journal={IEEE Journal on Selected
Areas in Communications}, title={Service Provisioning for UAV-Enabled
Mobile Edge Computing}, year={2021}, volume={39}, number={11},
pages={3287-3305}, doi={10.1109/JSAC.2021.3088660}}
@misc{cplex,
author = {IBM}, title = {IBM CPLEX Optimizer},
howpublished = "\url{https://www.ibm.com/in-en/analytics/cplex-optimizer}",
year = {2021}, note = "[Online; accessed 3-Feb-2022]"}
@misc{rsome,
author = {NSU}, title = {RSOME},
howpublished = "\url{https://xiongpengnus.github.io/rsome/}",
year = {2021}, note = "[Online; accessed 3-Feb-2022]"}
@INPROCEEDINGS{hardtoshare,
author={He, Ting and Khamfroush, Hana and Wang, Shiqiang and La Porta,
Tom and Stein, Sebastian}, booktitle={IEEE 38th International Conference on
Distributed Computing Systems (ICDCS)}, title={It's Hard to Share: Joint
Service Placement and Request Scheduling in Edge Clouds with Sharable and
Non-Sharable Resources}, year={2018}, volume={}, number={}, pages={365-375},
doi={10.1109/ICDCS.2018.00044}}
@INPROCEEDINGS{multicell,
author={Poularakis, Konstantinos and Llorca, Jaime and Tulino, Antonia M.
and Taylor, Ian and Tassiulas, Leandros}, booktitle={IEEE Conference on
Computer Communications (INFOCOM)}, title={Joint Service Placement and
Request Routing in Multi-cell Mobile Edge Computing Networks},
year={2019}, volume={}, number={}, pages={10-18},
doi={10.1109/INFOCOM.2019.8737385}}
@ARTICLE{bandwidth,
author={Poularakis, Konstantinos and Llorca, Jaime and Tulino, Antonia M.
and Taylor, Ian}, journal={IEEE/ACM Transactions on Networking},
title={Service Placement and Request Routing in MEC Networks With Storage,
Computation, and Communication Constraints}, year={2020}, volume={28},
number={3}, pages={1047-1060}, doi={10.1109/TNET.2020.2980175}}
@INPROCEEDINGS{dataintensive,
author={Farhadi, Vajiheh and Mehmeti, Fidan and He, Ting and Porta, Tom
La and Khamfroush, Hana and Wang, Shiqiang and Chan, Kevin S},
booktitle={IEEE Conference on Computer Communications(INFOCOM)},
title={Service Placement and Request Scheduling for Data-intensive
Applications in Edge Clouds}, year={2019}, volume={}, number={},
pages={1279-1287}, doi={10.1109/INFOCOM.2019.8737368}}
@article{edgeuncertainty,
author = {Xu, Xiaolong and Cao, Hao and Geng, Qingfan and Liu, Xihua and
Dai, Fei and Wang, Chuanjian}, title = {Dynamic resource provisioning for
workflow scheduling under uncertainty in edge computing environment},
journal = {Concurrency and Computation: Practice and Experience}, volume =
{n/a}, number = {n/a}, pages = {e5674},
doi = {https://doi.org/10.1002/cpe.5674}}
@ARTICLE{edgeuav, author={Qu, Yuben and Dai, Haipeng and Wang,
Haichao and Dong, Chao and Wu, Fan and Guo, Song and Wu, Qihui},
journal={IEEE Journal on Selected Areas in Communications}, title={Service
Provisioning for UAV-Enabled Mobile Edge Computing}, year={2021},
volume={39}, number={11}, pages={3287-3305},
doi={10.1109/JSAC.2021.3088660}}
@ARTICLE{robust, author={Li, Bo and He, Qiang and Cui, Guangming and
Xia, Xiaoyu and Chen, Feifei and Jin, Hai and Yang, Yun}, journal={IEEE
Transactions on Services Computing}, title={READ: Robustness-oriented
Edge Application Deployment in Edge Computing Environment},
year={2020}, volume={}, number={}, pages={1-1},
doi={10.1109/TSC.2020.3015316}}
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