Name
Abstract | ||
|---|---|---|
With IoT-based smart cities, massive heterogeneous IoT devices are running diverse advanced services for unprecedented intelligence and efficiency in various domains of city life. Given the exponentially growing number of IoT devices and the large number of smart city services as well as their different QoS requirements, it has been a big challenge for servers to optimally allocate limited resources to all hosted applications for satisfactory performance. Note that by pushing the computing and storage resources to the proximity of end IoT devices, and deploying applications in distributed edge servers, edge computing technology appears to be a promising solution for this challenge. Toward this, we study in this article how to allocate edge resources for average service response time minimization. Besides the proposed algorithms, extensive numerical results are also presented to validate their efficacy. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MNET.2019.1800221 | IEEE Network |
Keywords | Field | DocType |
Servers,Smart cities,Resource management,Delays,Time factors,Internet of Things,Quality of service | Edge computing,Resource management,Computer science,Server,Quality of service,Response time,Computer network,Minification,Resource allocation,Smart city,Distributed computing | Journal |
Volume | Issue | ISSN |
33 | 2 | 0890-8044 |
Citations | PageRank | References |
5 | 0.40 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Zhao | 1 | 72 | 3.85 |
| Jiadai Wang | 2 | 8 | 0.77 |
| Jiajia Liu | 3 | 1372 | 94.60 |
| Nei Kato | 4 | 3982 | 263.66 |