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Shikhar Sharma 0002

dblp:167/1994-2 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0007-8519-7349ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Edge and fog computing · 50% Network optimization and economics · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Edge and fog computing
mobile edge computing
0.812024
Towards Effective Resource Procurement in MEC: A Resource Re-Selling Framework · IEEE Trans. Serv. Comput. 2024
Network optimization and economics › game theory › dynamic game
stackelberg game
0.812024
Towards Effective Resource Procurement in MEC: A Resource Re-Selling Framework · IEEE Trans. Serv. Comput. 2024
Embedded and real-time systems › real-time scheduling
resource reservation
0.212024
Towards Effective Resource Procurement in MEC: A Resource Re-Selling Framework · IEEE Trans. Serv. Comput. 2024

Methods — techniques the papers use, named apart from their topics

stackelberg game · 1.5game theory · 1.5
YearPublicationVenuePosition
2024 Towards Effective Resource Procurement in MEC: A Resource Re-Selling Framework
abstract
On-demand and resource reservation pricing models, widely used in cloud computing, are currently used in Multi-Access Edge Computing (MEC). Nevertheless the edge's resources are distributed and each server has lower capacity. If too much resources were reserved in advance, on-demand users may not get their jobs served on time, jeopardizing MEC's latency benefits. Concurrently, reservation plan users may possess un-used quota. Therefore, we propose a sharing platform where reservation plan users can re-sell unused resource quota to on-demand users. To investigate the mobile network operator's (MNO‘s) incentive of allowing re-selling, we formulate a 3-stage non-cooperative Stackelberg Game and characterize the optimal strategies of buyers and re-sellers. We show that users’ actions give rise to 4 different outcomes at equilibrium, dependent on the prices and supply levels of the sharing and on-demand pools. Based on the 4 possible outcomes, we characterise the MNO's optimal prices for on-demand users. Numerical results show that having both pools gives the MNO an optimal revenue when the on-demand pool's supply is low, and unexpectedly, when the MNO's commission is low. We develop an interactive prototype, and show that users’ decision distributions in studies on our prototype are similar to that of our decision model.
Marie Siew, Shikhar Sharma 0002, Kun Guo 0002, Desmond W. H. Cai, Wanli Wen, Carlee Joe-Wong, Tony Q. S. Quek
IEEE Trans. Serv. Comput.2