A Novel Routing Scheme for Creating Opportunistic Context-Virtual Networks in IoT Scenarios

Abstract

The massive amount of traffic required by the emerging Internet of Things (IoT) paradigm can be supported by the imminent arrival of 5G next-generation networks. However, the limited capacity of resources in IoT nodes, e.g., battery lifetime or buffer space, opens a challenge to be taken into account when proposing new routing solutions on IoT scenarios with intermittent connectivity. In this paper, we propose the concept of Opportunistic Context-Virtual Networks (OCVNs). The novelty of this approach is to create virtual groups of nodes that share interests in common for routing purposes. Therefore, only the nodes that are interested in the content of the messages that are flowing throughout the network are used as relaying nodes, providing their own resources for the sake of the communication. By leveraging the use of store-carry-and-forward mechanisms, a novel routing algorithm is proposed and evaluated over two realistic scenarios. Experimental results reveal that our solution outperforms other well-known opportunistic routing algorithms in terms of delivery probability and overhead ratio, while resource usage of relaying nodes is significantly reduced.

Keywords: Internet of Things; contextual information; opportunistic networks; routing algorithms.

Figure 1

Example of the situational context.

Figure 2

Example of three Opportunistic Context-Virtual Networks (OCVNs) in a seven-node environment.

Figure 3

Behavior of the defined Situational and Adaptive Context-Aware Routing (SACAR) algorithms. IR, In Range; HC, Historical Contacts.

Figure 4

Resource consumption of SACAR algorithms.

Figure 5

Storage required for the SACAR algorithms.

Figure 6

Smart office scenario.

Figure 7

Mall scenario.

Figure 8

Average delivery probability ($d_{\mathrm{prob}}$) vs. the frequency of messages generation ($\omega$): smart office scenario. DDR, Direct Delivery Routing; ER, Epidemic Routing; MPR, MaxProp Routing; PR, ProPHET Routing; SWR, Spray and Wait Routing; GSaR, Geographic-Based Spray-and-Relay.

Figure 9

Overhead ratio ($\theta$) vs. frequency of message generation ($\omega$): smart office scenario.

Figure 10

Average latency ($\tau$) vs. frequency of message generation ($\omega$): smart office scenario.

Figure 11

Average number of hops ($\gamma$) vs. frequency of message generation ($\omega$): smart office scenario.

Figure 12

Average delivery probability ($d_{\mathrm{prob}}$) vs. frequency of message generation ($\omega$): mall.

Figure 13

Average buffer time ($\delta$) vs. frequency of messages generation ($\omega$): mall.