**2. Network architecture**

Wireless mesh networks (WMNs) are the architectural enabler for wireless sensor networks (WSNs). As mentioned, WMNs provide the opportunity to deploy WSNs in an incremental fashion to execute sensory applications at multiple locations of interest on a per-need basis; WMNs also provide an alternative to carrying Internet Protocol (IP) traffic in rural or hostile environments where access to fibre may not be available. This provides feedback of sensory data from a WSN to a centralized controlling station over a long haul through a mesh node that is assigned to govern a sensor cluster.

These specially-assigned mesh nodes, called *cluster-heads*, are selected based on proximity, or deployed to extend the network, to the sensory location(s) of interest. Cluster-heads provide a bridge to the mesh network and may assume supervisory control of their subordinate sensors, which are typically limited in their resources and computational capabilities. To perform these functions, cluster-heads are equipped with the additional resources to handle the traffic load, although they likely carry multiple types of traffic, only one of which may be sensory. A WMN enabling a WSN is presented in Figure 1.

**Figure 1.** A Wireless Mesh Network Enabling a Wireless Sensor Network

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190 Wireless Sensor Networks – Technology and Protocols Cross-Layer Design for Smart Routing in

Next-generation sensor networks require performance optimization by considering both the potential performance that can be achieved and the corresponding impact on a node's energy

With that said, the dependencies of next-generation applications on various performance and energy factors vary. Many of these applications are critical and require immediate response such as those for physical security, industrial processes and infrastructure monitoring; however, those for temperature control and ambient light measurement, for example, are less critical and are able to conserve energy at the expense of less performance-heavy resource allocation. Hence, the aim is to create a flexible cross-layer platform for distributed WSNs that considers the *criticality* of the resource allocation for next-generation applications.

This chapter covers the main research areas that arise in designing smart routing protocols

• **Network Architecture** - determining the optimal configuration of the distributed architecture and the deployment of WSNs at areas of interest to extend the WMN; • **Optimization Metrics** - identifying cross-layer performance and energy factors that impact resource allocation: application requirements, available routes, channel quality, battery life, physical (PHY) layer considerations (transmit power, operating channel and

• **Criticality** - defining the dependency of commercial applications on performance and

• **Route Selection** - selecting the route with the optimal trade-off between performance and

• **Coexistence** - providing connectivity between heterogeneous communication interfaces to bridge sensor and mesh technologies such as Bluetooth and WiMax, respectively; and, • **Energy Harvesting** - quantifying the impact of replenishing energy reserves from kinetic,

Wireless mesh networks (WMNs) are the architectural enabler for wireless sensor networks (WSNs). As mentioned, WMNs provide the opportunity to deploy WSNs in an incremental fashion to execute sensory applications at multiple locations of interest on a per-need basis; WMNs also provide an alternative to carrying Internet Protocol (IP) traffic in rural or hostile environments where access to fibre may not be available. This provides feedback of sensory data from a WSN to a centralized controlling station over a long haul through a mesh node

These specially-assigned mesh nodes, called *cluster-heads*, are selected based on proximity, or deployed to extend the network, to the sensory location(s) of interest. Cluster-heads provide a bridge to the mesh network and may assume supervisory control of their subordinate sensors, which are typically limited in their resources and computational capabilities. To perform these functions, cluster-heads are equipped with the additional resources to handle the traffic load,

bandwidth), and the energy efficiency of the wireless communication protocol;

energy conservation for a given application criticality;

solar or heat energy on resource allocation.

Each of these topics will be covered in this chapter.

that is assigned to govern a sensor cluster.

capacity. This enables nodes to make more informed resource allocation decisions.

and require specific engineering attention:

energy considerations;

**2. Network architecture**

We design a network architecture to analyze the impact of smart routing on resource allocation for WSN applications with varying requirements. This architecture, presented in Figure 2, consists of multiple sensor clusters and an overlay WMN that spans roughly a one kilometer area. In this network, one sensor cluster is formed of high-bandwidth Ultrawideband (UWB) sensors that are suited to data intensive applications such as video monitoring; UWB is a high-speed alternative to Zigbee for sensor networks with low power consumption but is inherently short range [2]. A second sensor cluster of Zigbee sensors is deployed to execute a low bandwidth application such as temperature monitoring. The WMN uses WiMax mesh technology to connect these geographically distributed clusters to the central controlling stations. This station is responsible for communicating with an outside controller or processing center, or is the processing center itself.

**Figure 2.** A Distributed Wireless Mesh Network of Zigbee and UWB Sensor Clusters

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The communication technologies chosen are presented as a single scenario but typically depend on the range of communication required, node density and required bandwidth requirements of the applications of interest.

In terms of node interaction, cluster-heads perform supervisory control of sensors and optimize resource allocations for sensors that they govern. Sensors correspondingly inform their cluster-heads of the state of their resources periodically.

Ideally, mesh nodes, including cluster-heads, are organized in a hexagonal topology for maximum connectivity [1]. These mesh nodes are placed at the center of their clusters around which sensors are typically positioned randomly. However, while we would ideally like to maintain a hexagonal topology of mesh nodes, this may not always be practical because the organization of mesh nodes depends highly on the sensory locations of interest. For example, if a sensor cluster is deployed to monitor stresses on bridge infrastructure, or the military is interested in monitoring certain high security areas, it will likely not be possible to deploy a mesh node at an ideal location. It is important to note that, in networks for which a hexagonal mesh topology is not possible, network planners must be aware of potential single points of failure. In these cases, load balancing or redundancy should be explored to ensure that mesh nodes are not overburdened.

In this analysis, neither sensor nodes nor mesh nodes are wired to power sources. This allows us to explore a general architecture and expands the number of environments in which, and applications for which, the system can be deployed. In reality, certain mesh nodes may be connected to power sources if the locations in which the mesh nodes are deployed have power sources readily available. Another option is energy harvesting to replenish energy reserves over time, which we will cover later in this chapter.
