Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Slice Allocation Management Model in 5G Networks for IoT Services with Reliable Low Latency

Version 1 : Received: 22 July 2020 / Approved: 23 July 2020 / Online: 23 July 2020 (08:07:58 CEST)

How to cite: Dighriri, M.; Otebolaku, A.; Alfoudi, A.; Lee, G.M. Slice Allocation Management Model in 5G Networks for IoT Services with Reliable Low Latency. Preprints 2020, 2020070536 (doi: 10.20944/preprints202007.0536.v1). Dighriri, M.; Otebolaku, A.; Alfoudi, A.; Lee, G.M. Slice Allocation Management Model in 5G Networks for IoT Services with Reliable Low Latency. Preprints 2020, 2020070536 (doi: 10.20944/preprints202007.0536.v1).

Abstract

Network slicing is a promising technology for 5G networks in which operators can sell customized services to different tenants at various prices and Quality of Services (QoS) demands. Thus, the latest 4th Generation (4G) and upcoming 5th Generation (5G) mobile technologies are expected to offer massive connectivity and management of high volume of data traffic in the presence of immense interferences from mobile networks of IoT devices. Further, it will face challenges of congestion and overload of data traffic due to the humongous number of IoT devices. Nevertheless, these devices are likely to demand high throughput, low latency, and high level of reliability especially for critical real-time applications such as in Vehicular Communication System (VCS). To address these issues in 5G mobile networks, this paper proposes a Slice Allocation Management (SAM) Model based on the critical services of smart systems such as VCS to satisfy QoS demands. The proposed model aims at providing dedicated slices on the basis of service requirements such as expected throughput and latency for VCS. To ensure such performance and provide data traffic priorities of IoT devices in the uplink of Relay Nodes (RNs) cells in the 5G mobile networks, we have sliced the Radio Access Networks (RAN), along with the assignment of the nearest Mobile Edge Computing (MEC) with isolated slices based on the priorities for each IoT nodes to reduce latency level. The proposed model was simulated and validated using the OPNET simulator. The results obtained demonstrate that SAM Model is able to achieve improvement of end to end delays and uplink throughputs of the networks in high-density networks of IoT devices.

Subject Areas

5G; IoT; SAM Model; Vehicular Communication Systems

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