Cloud Based Smart City Services for Industrial Internet of Things in Software-Defined Networking
- Authors
- Babbar, Himanshi; Rani, Shalli; Singh, Aman; Abd-Elnaby, Mohammed; Choi, Bong Jun
- Issue Date
- Aug-2021
- Publisher
- MDPI
- Keywords
- software defined networking; industrial internet of things (IIoT); cloud; smart cities; POX; QoS metrics
- Citation
- SUSTAINABILITY, v.13, no.16
- Journal Title
- SUSTAINABILITY
- Volume
- 13
- Number
- 16
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/41607
- DOI
- 10.3390/su13168910
- ISSN
- 2071-1050
- Abstract
- The network session constraints for Industrial Internet of Things (IIoT) applications are different and challenging. These constraints necessitates a high level of reconfigurability, so that the system can assess the impact of an event and adjust the network effectively. Software Defined Networking (SDN) in contrast to existing networks segregates the control and data plane to support network configuration which is programmable with smart cities requirement that shows the highest impact on the system but faces the problem of reliability. To address this issue, the SDN-IIoT based load balancing algorithm is proposed in this article and it is not application specific.Quality of service (QoS) aware architecture i.e., SDN-IIoT load balancing scheme is proposed and it deals with load on the servers. Huge load on the servers, makes them vulnerable to halt the system and hence leads to faults which creates the reliability problem for real time applications. In this article, load is migrated from one server to another server, if load on one server is more than threshold value. Load distribution has made the proposed scheme more reliable than already existing schemes. Further, the topology used for the implementation has been designed using POX controller and the results has been evaluated using Mininet emulator with its support in python programming. Lastly, the performance is evaluated based on the various Quality of Service (QoS) metrics; data transmission, response time and CPU utilization which shows that the proposed algorithm has shown 10% improvement over the existing LBBSRT, Random, Round-robin, Heuristic algorithms.
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