## 1 Introduction  
Present-day large-scale industrial monitoring and control systems may typically consist of thousands of sensors, controllers and actuators. In order to carry out their assigned tasks, it is essential for the devices to communicate. In the past, this communication was performed over point-to-point wired systems. Such systems, however, involved a huge amount of wiring which in turn introduced a large number of physical points of failure, such as connectors and wire harnesses, resulting in a highly unreliable system. These drawbacks resulted in the replacement of point-to-point systems using industrial computer networks known as _fieldbuses_. Over the past few decades, the industry has developed a myriad of fieldbus protocols (e.g., Foundation Fieldbus H1, ControlNet, PROFIBUS, CAN, _etc._). Compared to traditional point-to-point systems, fieldbuses allow higher reliability and visibility and also enable capabilities, such as distributed control, diagnostics, safety, and device interoperability [1]. However, industrial processes are rapidly increasing in complexity in terms of factors such as scale, quality, inter-dependencies, and time and cost constraints. For example, globalization has led to companies opening up their manufacturing plants in not just one, but multiple geographic locations. Yet, in order to maximize the utilization of these distributed resources and optimize global operation, it is essential for companies to have a _detailed_ outlook of the various operational characteristics of every single piece of equipment within every industrial plant. This could possibly require both static and moving parts of a piece of machinery to be monitored. In other words, accurate, fine-grained, large-scale, remote monitoring is an essential requirement [2]. Similarly, the view of increasing complexity also holds when considering applications which go beyond monitoring but also require _control_. Control operations have traditionally been carried out at the point of sensing, but more complex applications are now requiring distributed sensing and control. For example, in order to optimize overall energy usage, an industrial plant might require several pieces of machinery located in different parts of the plant to change their operational characteristics. This would require distributed sensing, control and subsequently actuation. While existing industrial networking technologies are sufficient for performing localized monitoring and control, the distributed nature of upcoming industrial applications requires a paradigm shift from present-day strategies. The focus needs to shift from localized operations to a distributed approach where new benefits and synergies are discovered from the interconnection and communication of individual systems. Wireless technologies have the potential to play a key role in industrial monitoring and control systems, as they have certain key advantages over conventional wired networks. In addition to extensively reducing bulk and installation costs, the unobtrusiveness of the technology allows it to be deployed easily in areas which simply cannot be monitored using wired solutions (e.g., in moving parts) [3]. Modifications of the network topology (in terms of the addition or reorganization of nodes) can also be easily performed without incurring additional costs for wiring. With increased scalability, wireless sensor networks can also run collaborative algorithms (e.g., for vibration monitoring applications) to improve the robustness of the overall system. Wireless systems also require less maintenance, since unlike their wired counterparts, they are not prone to damage due to corrosion or wear and tear. Thus, this unique combination of increased scalability and robustness through usingdistributed mechanisms makes wireless technologies an invaluable option for developing future industrial applications that require fine-grained, flexible, robust, low-cost and low-maintenance monitoring and control.