Abstract
Already available WiFi direct and upcoming 5G Device-to-Device (D2D) communication mechanisms are paving the way for the development of Mobile Ad-hoc Networks (MANET) applications. This trend involves the cooperation of nearby mobile nodes in charge of dispatching messages. In addition, the consolidation of the Fog paradigm enables innovative scenarios characterized by the interaction of MANET and Edge nodes. For instance, tourists visiting a city form a MANET to share pictures while the municipality provides Internet connectivity via Edge devices. However, it is required to address specific issues stemming from the collaborative nature of D2D communication, ranging from limited node capabilities providing multi-hop networks to unreliable connectivity due to node mobility. This paper presents the Reliable and Dynamic Routing Technique (RaDRT) solution, adopting the Software Defined Networking (SDN) approach to regulate routing of traffic flows in such Edge-MANET environments. To this purpose, RaDRT originally exploits the joint combination of three primary guidelines: 1) SDN to monitor/manage the state of the mobile network also considering different Quality of Service (QoS) requirements of concurrently running applications, 2) dynamic management of service priority to tune if and how packets are forwarded in a fine-grained per-flow differentiated manner, and 3) joined mobile/fixed solution to maximize the overall QoS also evaluating path reliability based on node mobility. This paper presents the Reliable and Dynamic Routing Technique (RaDRT) solution, adopting the Software Defined Networking (SDN) approach to regulate routing of traffic flows in such Edge-MANET environments. To this purpose, RaDRT originally exploits the joint combination of three primary guidelines: 1) SDN to monitor/manage the state of the mobile network also considering different Quality of Service (QoS) requirements of concurrently running applications, 2) dynamic management of service priority to tune if and how packets are forwarded in a fine-grained per-flow differentiated manner, and 3) joined mobile/fixed solution to maximize the overall QoS also evaluating path reliability based on node mobility.
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