IoT connectivity solutions: Media access control layer and network topology


Media access control layer and network topology

For IoT applications, the main characteristics of the media access layer control (MAC) that need to be considered are multiple access, synchronization, and network topology.

Multiple Access. Looking back at decades of successful cellular system deployment, one can safely conclude that TDMA is a good fit for the IoT. TDMA is suited for low-power operation with a decent number of devices, as it allows for optimal scheduling of inactive periods. Hence, TDMA is selected for multiple access in the MAC layer.

Synchronization. In IoT applications, there are potentially a very large number of power-sensitive devices with moderate throughput requirements. In such a configuration, it is essential to maintain a reasonably consistent time base across the entire network and potentially across different networks. Given that throughput is not the most critical requirement, it is suitable to follow a beacon-enabled approach, with a flexible beacon period to accommodate different types of services.

Network topology. Mobile networks using a cellular topology have efficiently been servicing a large number of devices with a high level of security and reliability, e.g., 5,000+ per base station for LTE in urban areas. This typology is based on a star topology in each cell, while the cells are connected in a hierarchical tree in the network backhaul. This approach is regarded suitable for the IoT and is therefore selected.

The network layer and interface to applications

The network layer (NWK) and the interface to applications are less fundamental as far as power-efficiency and reliability is concerned. In addition, there is more variation in the field of IoT applications. Nevertheless, it is widely acknowledged that IoT applications need to support the Internet Protocol (IP), whether it is IPv4 or IPv6. In addition, the User Datagram Protocol (UDP) and Constrained Application Protocol (CoAP) could provide the relevant trade-off between flexibility and implementation-complexity on resource-constrained devices.

Furthermore, the IoT will represent an immense security challenge, and it is likely that state-of-the-art security features will become necessary. As of today, we can assume 128 bits Advanced Encryption Standard (AES) for encryption and Diffie-Hellman (DH), or the Elliptic Curve Diffie-Hellman (ECDH) variants, can become the baseline for securing communication.

Internet of Things wireless connectivity option analysis: Z-Wave Pros and Cons


As another asynchronous wireless networking protocol, Z-Wave is designed for home automation and remote control applications. Z-Wave originated from the Danish startup Zen-SYS and was acquired by Sigma Designs in 2008. The Z-Wave Alliance was formed in 2005. Unlike most competing technologies as discussed so far, Z-Wave operates in the sub-GHz bands: 868.42 MHz in Europe, 908.42 MHz in the US, 916 MHz in Israel, 919.82 MHz in Hong-Kong, 921.42 MHz in Australia and New Zealand. The use of sub-GHz bands brings improved range, reliability, and less interference in the Z-Wave network. Nevertheless, there are a few issues worth mentioning when applying Z-Wave for the IoT.

Z-Wave offers limited data rates and mediocre spectrum efficiency due to Manchester GFSK coding (invented in 1948) which doubles the used spectrum for limited coding gain. Originally offering a low data rate of 9.6 kbps, Z-Wave has been upgraded to 100 kbps in the latest version. The Z-Wave network is limited to 232 nodes, yet manufacturers recommend no more than 30 to 50 nodes in practical deployments. Moreover, Z-Wave makes use of relays, such as wall-mounted light switches, to forward packets when devices are out-of-range.

Z-Wave uses a Source Routing Algorithm (SRA), meaning that the message initiator has to embed the routing information into the packet. This implies overhead as the route occupies space meant for the actual data payload. More importantly, this means that the initiator needs to be aware of the network topology. The network topology therefore needs to be maintained and distributed to the nodes that may initiate messages. This is a complex task and is typically not manageable by an end device constrained in computing power, code size, battery capacity, and cost. Z-Wave defines different device types with different capabilities and protocol stack sizes:

  • Controllers: have a full and largest protocol stack as they can initiate messages. The master controller, the Static Update Controller, (SUC), maintains the network topology and handles network management.
  • Mobile controllers: can support request for neighbor rediscovery from moving nodes by implementing the portable controller protocol stack.
  • Routing Slaves: depend on SUCs for network topology and can initiate messages to a restricted set of nodes.
  • Slaves: have the smallest protocol stack, can only reply to requests, and cannot initiate messages.

When using multiple controllers in the same network, only the master (SUC) can be used for network maintenance. Whenever a Z-Wave device is added or removed from the network, the network topology of the master controller has to be replicated manually to the secondary controllers. This process makes network maintenance cumbersome.

The Source Routing Algorithm, along with the network topology management, also makes it very difficult to handle mobility. There is some support for nodes to request for neighbors’ rediscovery, however, this is a complicated and power-consuming process. Taken together this does not provide anything near seamless support for mobility. In addition, Z-Wave also has security flaws, as can be seen from reports of successful attacks on Z-Wave devices.

Overall, Z-Wave has been quite successful thanks to the trade-offs it provides. Z-Wave is a lot simpler than ZigBee, yet it provides a sufficient set of basic functions for simple deployments in home or small commercial spaces. Z-Wave has a good market share for the smart home and smart building by proving the benefits of sub-GHz communication. Nevertheless, its limitations as outlined above prevent it from becoming a future-proof technology for upcoming IoT applications.