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Reliability, timeliness and load reduction at the edge for cloud gaming

Franco, Antonio LU ; Fitzgerald, Emma LU ; Landfeldt, Björn LU and Körner, Ulf LU (2020) 38th IEEE International Performance Computing and Communications Conference, IPPCCC 2019
Abstract
In this paper we study reliability, timeliness and load reduction in an hybrid Mobile Edge Computing (MEC)/Cloud game streaming infrastructure. In our scenario, a user plays a game streamed by the producer to their handheld device -- or User Equipment (UE). The UE communicates user actions to the edge/cloud via the mobile communication infrastructure; the object is to retrieve the latest game status, of which the most important information is the rendered frame. Particularly, we study reliability through replication in a number of MEC-servers, timeliness through Age of Information (AoI) and load reduction by leveraging the X2 interface at the edge, in order to abort useless frame rendering computations. We translate it as a scenario where... (More)
In this paper we study reliability, timeliness and load reduction in an hybrid Mobile Edge Computing (MEC)/Cloud game streaming infrastructure. In our scenario, a user plays a game streamed by the producer to their handheld device -- or User Equipment (UE). The UE communicates user actions to the edge/cloud via the mobile communication infrastructure; the object is to retrieve the latest game status, of which the most important information is the rendered frame. Particularly, we study reliability through replication in a number of MEC-servers, timeliness through Age of Information (AoI) and load reduction by leveraging the X2 interface at the edge, in order to abort useless frame rendering computations. We translate it as a scenario where a sink -- representing the UE -- is interested in the freshest possible update from distributed nodes. Each node sends updates following a Last Come First Served (LCFS) policy with preemption. We consider two scenarios; the first is $n$ parallel LCFS systems sending updates, and the second adds a feedback loop aimed at decreasing the number of jobs sent per second by the nodes, thus decreasing the load per node. We analyze the number of jobs sent per second and average peak Age of Information at the sink, showing that the second scheme achieves a significantly lower rate of jobs compared with the first, while maintaining constant AoI, thus reducing the load at the edge. We also find that using the feedback loop, we achieve the maximum saving in transmitted jobs per second when the average arrival rate per system is equal to the inverse of the average busy time in every node. (Less)
Abstract (Swedish)
In this paper we study reliability, timeliness and load reduction in an hybrid Mobile Edge Computing (MEC)/Cloud game streaming infrastructure. In our scenario, a user plays a game streamed by the producer to their handheld device – or User Equipment (UE). The UE communicates user actions to the edge/cloud via the mobile communication infrastructure; the object is to retrieve the latest game status, of which the most important information is the rendered frame. Particularly, we study reliability through replication in a number of MEC- servers, timeliness through Age of Information (AoI) and load reduction by leveraging the X2 interface at the edge, in order to abort useless frame rendering computations. We translate it as a scenario where... (More)
In this paper we study reliability, timeliness and load reduction in an hybrid Mobile Edge Computing (MEC)/Cloud game streaming infrastructure. In our scenario, a user plays a game streamed by the producer to their handheld device – or User Equipment (UE). The UE communicates user actions to the edge/cloud via the mobile communication infrastructure; the object is to retrieve the latest game status, of which the most important information is the rendered frame. Particularly, we study reliability through replication in a number of MEC- servers, timeliness through Age of Information (AoI) and load reduction by leveraging the X2 interface at the edge, in order to abort useless frame rendering computations. We translate it as a scenario where a sink – representing the UE – is interested in the freshest possible update from distributed nodes. Each node sends updates following a Last Come First Served (LCFS) policy with preemption. We consider two scenarios; the first is n parallel LCFS systems sending updates, and the second adds a feedback loop aimed at decreasing the number of jobs sent per second by the nodes, thus decreasing the load per node. We analyze the number of jobs sent per second and average peak Age of Information at the sink, showing that the second scheme achieves a significantly lower rate of jobs compared with the first, while maintaining constant AoI, thus reducing the load at the edge. We also find that using the feedback loop, we achieve the maximum saving in transmitted jobs per second when the average arrival rate per system is equal to the inverse of the average busy time in every node. (Less)
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author
; ; and
organization
alternative title
Tillförlitlighet, latensvärden och lastreduktion vig nätverkets rand för spel i molnet
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
epub
subject
host publication
International Performance Computing and Communications Conference
pages
8 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
38th IEEE International Performance Computing and Communications Conference, IPPCCC 2019
conference location
London, United Kingdom
conference dates
2019-10-29 - 2019-10-31
external identifiers
  • scopus:85079101713
ISBN
978-1-7281-1025-7
DOI
10.1109/IPCCC47392.2019.8958728
language
English
LU publication?
yes
id
6044fec7-349a-4250-b96e-fe3e44c7c4b8
date added to LUP
2019-09-02 10:02:36
date last changed
2020-08-02 06:53:07
@inproceedings{6044fec7-349a-4250-b96e-fe3e44c7c4b8,
  abstract     = {In this paper we study reliability, timeliness and load reduction in an hybrid Mobile Edge Computing (MEC)/Cloud game streaming infrastructure. In our scenario, a user plays a game streamed by the producer to their handheld device -- or User Equipment (UE). The UE communicates user actions to the edge/cloud via the mobile communication infrastructure; the object is to retrieve the latest game status, of which the most important information is the rendered frame. Particularly, we study reliability through replication in a number of MEC-servers, timeliness through Age of Information (AoI) and load reduction by leveraging the X2 interface at the edge, in order to abort useless frame rendering computations. We translate it as a scenario where a sink -- representing the UE -- is interested in the freshest possible update from distributed nodes. Each node sends updates following a Last Come First Served (LCFS) policy with preemption. We consider two scenarios; the first is $n$ parallel LCFS systems sending updates, and the second adds a feedback loop aimed at decreasing the number of jobs sent per second by the nodes, thus decreasing the load per node. We analyze the number of jobs sent per second and average peak Age of Information at the sink, showing that the second scheme achieves a significantly lower rate of jobs compared with the first, while maintaining constant AoI, thus reducing the load at the edge. We also find that using the feedback loop, we achieve the maximum saving in transmitted jobs per second when the average arrival rate per system is equal to the inverse of the average busy time in every node.},
  author       = {Franco, Antonio and Fitzgerald, Emma and Landfeldt, Björn and Körner, Ulf},
  booktitle    = {International Performance Computing and Communications Conference},
  isbn         = {978-1-7281-1025-7},
  language     = {eng},
  month        = {01},
  publisher    = {IEEE - Institute of Electrical and Electronics Engineers Inc.},
  title        = {Reliability, timeliness and load reduction at the edge for cloud gaming},
  url          = {https://lup.lub.lu.se/search/ws/files/69041804/paper.pdf},
  doi          = {10.1109/IPCCC47392.2019.8958728},
  year         = {2020},
}