Farah AIT SALAHT; Frédéric Desprez; Adrien Lebre
An Overview of Service Placement Problem in Fog and Edge Computing Journal Article
In: Acm Computing Surveys, vol. 53, no. 3, pp. 1-35, 2020.
@article{ait_salaht_2680,
title = {An Overview of Service Placement Problem in Fog and Edge Computing},
author = {Farah AIT SALAHT and Frédéric Desprez and Adrien Lebre},
url = {https://doi.org/10.1145/3391196},
year = {2020},
date = {2020-06-01},
journal = {Acm Computing Surveys},
volume = {53},
number = {3},
pages = {1-35},
abstract = {To support the large and various applications generated by the Internet of Things (IoT), Fog Computing was introduced to complement the Cloud Computing and offer Cloud-like services at the edge of the network with low latency and real-time responses. Large-scale, geographical distribution, and heterogeneity of edge computational nodes make service placement in such infrastructure a challenging issue. Diversity of user expectations and IoT devices characteristics also complicate the deployment problem. This article presents a survey of current research conducted on Service Placement Problem (SPP) in the Fog/Edge Computing. Based on a new classification scheme, a categorization of current proposals is given and identified issues and challenges are discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Farah AIT SALAHT; Mehdi Kandi; Hind Castel-Taleb; Emmanuel Hyon
Analysis of Performance and Energy Consumption in the Cloud Proceedings Article
In: Computer Performance Engineering, Berlin, Germany, 2017, ISBN: 978-3-319-66583-2.
@inproceedings{ait_salaht_2681,
title = {Analysis of Performance and Energy Consumption in the Cloud},
author = {Farah AIT SALAHT and Mehdi Kandi and Hind Castel-Taleb and Emmanuel Hyon},
url = {https://doi.org/10.1007/978-3-319-66583-2_13},
issn = {978-3-319-66583-2},
year = {2017},
date = {2017-08-01},
booktitle = {Computer Performance Engineering},
address = {Berlin, Germany},
abstract = {We analyze here a cloud system represented by hysteresis multi server queueing system. It is characterized by forward and backward thresholds for activation and deactivation of block of servers representing a set of VMs (Virtual Machines). The system is represented by a complex Markov Chain which is difficult to analyse when the size of the system is huge. We propose both analytical and numerical mathematical methods for deriving the steady-state probability distribution. We compute then performance and energy consumption measures and we define an overall cost taking into account both aspects. We compare the proposed methods with respect to the computation time and we analyse the impact of some parameters on the behaviour of the system.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
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