A Bilevel Programming Framework for Joint Edge Resource Management and Pricing

Tarannum Nisha, Duong Tung Nguyen, Vijay K. Bhargava

Research output: Contribution to journalArticlepeer-review

Abstract

The emerging edge computing paradigm promises to provide low-latency and ubiquitous computation to numerous mobile and Internet of Things (IoT) devices at the network edge. How to efficiently allocate geographically distributed heterogeneous edge resources to a variety of services is a challenging task. While this problem has been studied extensively in recent years, most of the previous work has largely ignored the preferences of the services when making edge resource allocation decisions. To this end, this paper introduces a novel bilevel optimization model, which explicitly takes the service preferences into consideration, to study the interaction between an EC platform and multiple services. The platform manages a set of edge nodes (ENs) and acts as the leader while the services are the followers. Given the service placement and resource pricing decisions of the leader, each service decides how to optimally divide its workload to different ENs. The proposed framework not only maximizes the profit of the platform but also minimizes the cost of every service. When there is a single EN, we derive a simple analytic solution for the underlying problem. For the general case with multiple ENs and multiple services, we present a Karush-Kuhn-Tucker-based solution and a duality-based solution, combining with a series of linearizations, to solve the bilevel problem. Extensive numerical results are shown to illustrate the efficacy of the proposed model.

Original languageEnglish (US)
JournalIEEE Internet of Things Journal
DOIs
StateAccepted/In press - 2022
Externally publishedYes

Keywords

  • bilevel programming
  • Cloud computing
  • cloud/edge economics.
  • Costs
  • Delays
  • edge computing
  • Edge resource management
  • Indexes
  • Internet of Things
  • Pricing
  • Resource management
  • workload allocation

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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