2024
Conference article  Open Access

Optimizing resource allocation in the edge: a minimum weighted vertex cover approach

Makris A., Maragkoudakis E., Kontopoulos I., Theodoropoulos T., Korontanis I., Carlini E., Mordacchini M., Dazzi P., Varvarigou T.

Cloud computing  Application placement  Proactive image placement  Optimization problem  Edge computing 

The transition from Cloud Computing to a Cloud-Edge continuum introduces novel opportunities and challenges for data-intensive and interactive Next Generation applications. Strategies that were effective in the Cloud environment now necessitate reconsideration to adapt to the Edge's distributed, dynamic, and heterogeneous ecosystem. Proactively planning the placement of application images becomes crucial to minimize image transfer time, align with the dynamic nature of the system, and meet the strict demands of applications. In this regard, this paper proposes an empirical experimental analysis, by comparing the results of different placement strategies and various network topologies. In particular, we model the problem of proactive placement of application images as a Minimum Weighted Vertex Cover problem. Our results demonstrate that the Greedy approach seems to offer the optimal tradeoff with respect to the number of allocated images and execution time.

Publisher: ACM


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BibTeX entry
@inproceedings{oai:iris.cnr.it:20.500.14243/499522,
	title = {Optimizing resource allocation in the edge: a minimum weighted vertex cover approach},
	author = {Makris A. and Maragkoudakis E. and Kontopoulos I. and Theodoropoulos T. and Korontanis I. and Carlini E. and Mordacchini M. and Dazzi P. and Varvarigou T.},
	publisher = {ACM},
	doi = {10.1145/3659994.3660316},
	year = {2024}
}

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Cloud for Holography and Cross Reality


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