**1. Introduction**

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Wireless sensor networks (WSNs) are gaining market traction in numerous industrial segments because they are both cheaper and faster to deploy than their wired counterparts. They also provide incremental value as they are able to extend existing wireless mesh network (WMN) infrastructure to deploy commercial sensory applications on a per-need basis. This establishes a scalable network infrastructure that deploys WSNs in a distributed fashion; sensors gather sensory information from geographically distributed areas and feedback data to centralized controlling stations. These controllers either provide an automatic response based on internal logic or log data for manual response by an operator, if necessary.

There is, however, a need to revolutionize current routing methods to realize next-generation commercial applications for these networks. These innovative routing schemes, which we coin *smart routing*, are based on performance measure and energy optimization, as opposed to traditional routing schemes that typically only minimize energy consumption to prolong network lifetime. Smart routing - the selection of routing nodes that are best able to satisfy both performance and energy conservation requirements given current network conditions is based on cross-layer considerations of the protocol stack. Cross-layer design streamlines communication between layers and provides response based on a more complete view of the stack. These cross-layer factors include the application's requirements, available network routes, transmission channel quality and energy distribution in the network.

The consideration of application performance is complicated by sensors that have critical power constraints. As mentioned, this has typically resulted in the optimization of these networks taking the form of the minimization of energy consumption, or the maximization of network lifetime, as the primary objective [3–6]. However, this typically occurs to the detriment of application performance. Certain studies do strive to reach a maximum delay requirement [7, 8, 10]; however, it is unknown if we can do better as performance is not optimized. Other studies perform rate control in WSNs but do not model the power cost of using a transmission link in terms of the achievable throughput level [5].

©2012 Sheikh and Mahmoud, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ©2012 Sheikh and Mahmoud, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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

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 and require specific engineering attention:


Each of these topics will be covered in this chapter.
