# Research Challenges for the Internet of Things: What Role Can OR Play?
## 3 How can OR Support the Future IoT?
### IoT Scalability Studied Using Simulation  
The first key challenge according to [PERSON] [6] is scalability. The IoT will have billions or even trillions of devices connected and these must be managed, maintained, operated and supported using appropriate addressing conventions, protocols, and power. Existing approaches to these challenges may well be inadequate and fail to scale for the anticipated huge number and range of IoT objects.  
A simple visualization can show how IoT networks can rapidly become extremely complex. Figure 2 shows three IoT networks composed of equal numbers of sensors and actuators where all nodes are connected to each other. The number of connections grows rapidly from only 6 for a 4-node network, 120 for a 16-node network to 2016 for a 64-node network, since the number of connections for such an N-node network is trivially \(N\times(N-1)/2\).  
To assess scalability, discrete-event Simulation can be applied. As shown, IoT networks can become so complex that traditional analytic methods will not be tractable. Discrete-event simulation enables a hypothetical system to be studied under a wide variety of conditions and provide averaged results from running the same scenario over many replications. [PERSON] et al. [51] and [PERSON] et al. [87; 88] have developed simulation systems for the IoT. [PERSON] model, for example, addresses scalability using a multi-level simulation approach where both coarse and fine grained models are combined.  
[PERSON] and [PERSON] [52] identified 36 such systems in 2012 for WSNs and classified them into eight types: (a) emulators; (b) topology simulators; (c) environment and wireless simulators; (d) network and application level simulators; (e) cross level simulators, then a series of simulators based on specific software; (f) NS-32 based simulators; (g) OMNeT++ simulators; and (h) Ptolemy II based simulators. Many of these could be applied to address IoT issues such as scalability including type (b) topology simulators such as Atarraya [53] that enables comparison of performance and efficiency of different network topologies, type (c) environment and wireless simulators such as the Wireless Sensor Network Localization Simulator that can determine the location of sensor nodes in different sized networks and type (d) network simulators such as Sensor Security Simulator that can evaluate security in large sensor networks and SIDnet-SWANS that can model network behavior at different levels of granularity.  
Discrete-event simulation is readily applicable to studying problems such as traffic flow through an IoT network of nodes. Events would include transmission of packets from one node (perhaps triggered by a sensor) and their reception and processing at other nodes. With many expected wireless nodes, issues such as propagation modelling may also be required [89]. Packet arrival and transmission times would be determined by sampling from appropriate probability distributions. Simulation of the system would show how it performs as a function of number of nodes.  
Figure 2: Scaling in IoT networks with: (a) 4 nodes; (b) 16 nodes; and (c) 64 nodes (red circles represents sensors; black circles actuators) (These images were created using the D3 javascript library ([https://d3 js.org/](https://d3 js.org/)). One of the authors ([PERSON]) is experimenting with the use of D3 for simulation of the IoT).