Optimized Provisioning of Edge Computing Resources With Heterogeneous Workload in IoT Networks
| Autor: | Sanaa Sharafeddine, Nouha Kherraf, Ali Ghrayeb, Chadi Assi, Hyame Assem Alameddine |
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| Rok vydání: | 2019 |
| Předmět: |
Computer Networks and Communications
Computer science business.industry Wireless network Distributed computing 020206 networking & telecommunications Workload Cloud computing Provisioning 02 engineering and technology Server 0202 electrical engineering electronic engineering information engineering Enhanced Data Rates for GSM Evolution Electrical and Electronic Engineering business Dimensioning Edge computing |
| Zdroj: | IEEE Transactions on Network and Service Management. 16:459-474 |
| ISSN: | 2373-7379 |
| DOI: | 10.1109/tnsm.2019.2894955 |
| Popis: | The proliferation of smart connected Internet of Things (IoT) devices is bringing tremendous challenges in meeting the performance requirement of their supported real-time applications due to their limited resources in terms of computing, storage, and battery life. In addition, the considerable amount of data they generate brings extra burden to the existing wireless network infrastructure. By enabling distributed computing and storage capabilities at the edge of the network, multi-access edge computing (MEC) serves delay sensitive, computationally intensive applications. Managing the heterogeneity of the workload generated by IoT devices, especially in terms of computing and delay requirements, while being cognizant of the cost to network operators, requires an efficient dimensioning of the MEC-enabled network infrastructure. Hence, in this paper, we study and formulate the problem of MEC resource provisioning and workload assignment for IoT services (RPWA) as a mixed integer program to jointly decide on the number and the location of edge servers and applications to deploy, in addition to the workload assignment. Given its complexity, we propose a decomposition approach to solve it which consists of decomposing RPWA into the delay aware load assignment sub-problem and the mobile edge servers dimensioning sub-problem. We analyze the effectiveness of the proposed algorithm through extensive simulations and highlight valuable performance trends and trade-offs as a function of various system parameters. |
| Databáze: | OpenAIRE |
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