Preference-aware Edge Server Placement in the Internet of Things

Yuanyi Chen, Yihao Lin, Zengwei Zheng, Peng Yu, Jiaxing Shen, Minyi Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review


While it is well understood that edge computing can significantly facilitate IoT-related applications by deploying edge servers close to IoT devices, it also faces many challenges with numerous IoT devices connected and interacted. One of the most important issues is how to efficiently deploy edge servers under a certain budget with the explosive growth of data scale and user base. Existing studies for edge server placement fail to consider user’s query preferences since individual users may be interested in events in particular regions and are keen to receive up-to-date data streams that originate in regions of interest. In this paper, we present a preference-aware edge server placement approach that offers better workload distribution in terms of both minimizing query latency and balancing the load of edge servers. To achieve this, we formulate edge server placement with multi-objective optimization as a p-center problem and design two progressive approaches. We firstly propose QIP (Quadratic Integer Programming) for small-scale datasets. Since the p-center problem is an NP-hard problem, we thus propose a heuristic algorithm named TAKG (TAbu search with K-means and Genetic algorithm) for large-scale datasets. To evaluate the utility of the proposed models, we have conducted a comprehensive evaluation on a large dataset that is collected by more than 1,900 IoT devices during 30 days. Experimental results indicate our approaches outperform all baselines significantly in terms of both query latency and load balancing.

Original languageEnglish
JournalIEEE Internet of Things Journal
Publication statusAccepted/In press - 2021


  • Base stations
  • Cloud computing
  • Edge computing
  • Edge server deployment
  • Integer programming
  • Internet of Things
  • Internet of things
  • Multi-objective optimization.
  • Optimization
  • Query latency
  • Servers
  • User preference

ASJC Scopus subject areas

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

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