Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge Computing
Paper presented at EICS '22: https://dl.acm.org/doi/10.1145/3532210 The "Software as a Service" (SaaS) model of cloud computing popularized online multiuser collaborative software. Two famous examples of this class of software are Office 365 from Microsoft and Google Workspace. Cloud technology removes the need to install and update the software on end users' computers and provides the necessary underlying infrastructure for online collaboration. However, to provide a good end-user experience, cloud services require an infrastructure able to scale up to the task and allow low-latency interactions with a variety of users worldwide. This is a limiting factor for actors that do not possess such infrastructure. Unlike cloud computing which forgets the computational and interactional capabilities of end users' devices, the edge computing paradigm promises to exploit them as much as possible. To investigate the potential of edge computing over cloud computing, this paper presents a method for engineering interactive collaborative software supported by edge devices for the replacement of cloud computing resources. Our method is able to handle user interface aspects such as connection, execution, migration, and disconnection differently depending on the available technology. We exemplify our approach by developing a distributed Pictionary game deployed in two scenarios: a nonshared scenario where each participant interacts only with their own device and a shared scenario where participants also share a common device, including a TV. After a theoretical comparative study of edge vs. cloud computing, an experiment compares the two implementations to determine their effect on the end user's perceived experience and latency vs. real latency
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Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge Computing
- 1. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) Engineering the Transition of Interactive Collaborative Software from Cloud Computing to Edge Computing Guillaume Ortegat, Donatien Grolaux, Etienne Rivière, Jean Vanderdonckt
- 2. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Cloud computing ● Exchange message only with the server ● State managed by the server
- 3. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Cloud computing: Cloud Latency and Model Limitation Bandwidth hardware limitation Unexploited ressources No device adaptation No user situation adaptation
- 4. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Edge computing ● Migrate the hosting task on the user device ● Peer-to-peer communication between devices ● Small cloud server
- 5. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Traffic controller Server part User Client part User Client part Disconnection mechanism Drawing mechanism Connection mechanism Guessing mechanism Client part Cloud computing Overall structure Components structure Edge computing User Client part Server part User Client part Drawing mechanism Hosting mechanism Guessing mechanism Disconnection mechanism Connection mechanism Client part
- 6. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Transition from Cloud to Edge computing ● Modified mechanisms : connection, drawing, guessing, disconnection ● Added mechanism : migration of the hosting part
- 7. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Application example: distributed Pictionary User role Display role Drawing role
- 8. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) User 1 User 2 User 3 User 1 User 2 User 3 User 1 User 3 Non-shared scenario
- 9. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) ● Vidéo scénario séparé Tablet Shared Used by User 2 TV shared User 1 User 2 User 3 Tablet Shared Used by User 1 User 1 User 2 User 3 Shared scenario
- 10. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Evaluation 2 groups of 5 people Game configurations 8 2 30.3 years Daily All except one Cloud 0 ms Cloud 80 ms Cloud 300 ms Edge Shared scenario S0 S80 S300 SE Non-shared scenario N0 N80 N300 NE Protocol 1. Consent form 2. Acclimatation 3. Playing all the configurations 4. Answer questions after each game
- 11. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 0 100 200 300 400 500 600 Shared - Edge (SE) Non-shared - Edge (NE) Non-shared - Cloud 300 (N300) Non-shared - Cloud 80 (N80) Shared - Cloud 300 (S300) Non-shared - Cloud 0 (N0) Shared - Cloud 0 (S0) Shared - Cloud 80 (S80) 138.42 60.86 64.14 439.13 117.01 12.25 30.11 Latency measured [msec] Real latency ✱✱✱✱ ✱✱ ✱✱✱✱ 1 2 3 4 5 6 7 Shared - Edge (SE) Non-shared - Edge (NE) Non-shared - Cloud 300 (N300) Non-shared - Cloud 80 (N80) Shared - Cloud 300 (S300) Non-shared - Cloud 0 (N0) Shared - Cloud 0 (S0) Shared - Cloud 80 (S80) 5.90 5.56 4.90 4.90 4.67 4.30 4.22 3.40 Rating scale [1..7] Condition [Code] ✱ Perceived latency Condition [Code] Perceived latency Real latency **** ** **** **** ****
- 12. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Informal User Comments Many players have difficulty seeing the difference between game configurations Players did not notice the server was shut down during a game Some players express fun to play and aim the victory
- 13. ACM EICS ‘22 (Sophia Antipolis, June 21-24, 2022) 18 Conclusion • Low latency • Server failure tolerant • Level of service equivalent to cloud • Take advantage of edge device • Adaptation of each application requires a specific architecture • Librairies presents few shortcomings