EdgeMORE: Improving Resource Allocation with Multiple Options from Tenants
Andrea Araldo, Alessandro Di Stefano, Antonella Di Stefano

TL;DR
EdgeMORE is a resource allocation strategy for edge computing that leverages service adaptability, allowing services to declare multiple configurations to optimize resource use and maximize network operator utility.
Contribution
The paper introduces EdgeMORE, a novel ILP-based method enabling edge services to declare multiple adaptable configurations for improved resource allocation.
Findings
EdgeMORE significantly increases network utility in simulations.
Service adaptability enhances resource utilization efficiency.
Compared to fixed configurations, EdgeMORE achieves better resource management.
Abstract
Under the paradigm of Edge Computing (EC), a Network Operator (NO) deploys computational resources at the network edge and let third-party Service Providers (SPs) run on top of them, as tenants. Besides the clear advantages for SPs and final users thanks to the vicinity of computation nodes, a NO aims to allocate edge resources in order to increase its own utility, including bandwidth saving, operational cost reduction, QoE for its users, etc. However, while the number of third-party services competing for edge resources is expected to dramatically grow, the resources deployed cannot increase accordingly, due to physical limitations. Therefore, smart strategies are needed to fully exploit the potential of EC, despite its constrains. To this aim, we propose to leverage service adaptability, a dimension that has mainly been neglected so far: each service can adapt to the amount of…
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Taxonomy
TopicsIoT and Edge/Fog Computing · Cloud Computing and Resource Management · Age of Information Optimization
