Traffic Load Balancing among Brokers at the IoT Application Layer

Xiang Sun, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

At the Internet of Things (IoT) application layer, a physical phenomenon, which is sensed by a server (i.e., an IoT device), is defined as an IoT resource. In this paper, we propose to cache popular IoT resources in brokers, which are considered as the application layer middleware nodes. Caching popular resources in the brokers is to move the traffic loads (for delivering the up-To-date contents of the resources) from the servers (which host these popular resources) to the brokers, thus reducing the energy consumption of the servers. However, many brokers may be geographically distributed in the network and caching popular resources in nearby brokers may result in unbalanced traffic loads among the brokers, and may thus dramatically increase the average delay of the brokers in delivering the contents of their cached popular resources to clients. To reduce the average delay among the brokers, we propose to re-cache/re-Allocate the popular resources from heavily loaded brokers into lightly loaded brokers in order to balance the traffic loads among brokers. We formulate the popular resource re-caching problem as an optimization problem, which is proven to be NP-hard. We design the latency aware popular resource re-caching (LEARN) algorithm to efficiently solve the problem, and demonstrate the performance of LEARN via simulations.

Original languageEnglish (US)
Pages (from-to)489-502
Number of pages14
JournalIEEE Transactions on Network and Service Management
Volume15
Issue number1
DOIs
StatePublished - Mar 2018

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Keywords

  • CoAP
  • CoAP Pub/Sub
  • Internet of Things
  • broker
  • popularity
  • resource caching

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