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Extending this concept, one could think of generalizing the concept of action to that of whole behaviors That is, the action selection part of the MDB, instead of producing an action as a result of its processing, could produce or select a behavior controller (in the same sense as in behavior-based robotics) that would be applied until one that offered a better predicted satisfaction was available In this case, instead of testing actions in order to obtain their tness and thus try to decide on the best one, the process would consist in testing behavior based controllers on a simulated world constructed through the world and internal models and assigning them tness values with respect to the predicted satisfaction.

Layer 5: Application, e.g., DNS, HTTP, FTP, SMTP Layer 4: Transport, e.g., TCP, UDP Layer 3: IP (Internet Protocol), e.g., IP v4, IP v6 Layer 2: MAC (media access control), e.g., Ethernet, PPP Layer 1: Physical, e.g., ber, DSL, cable modem

Multicasting reduces the communication costs for applications that send the same data to multiple recipients Instead of sending via multiple unicasts, multicasting minimizes the link bandwidth consumption, sender and router processing, and delivery delay [2] In addition, multicasting provides a simple yet robust communication mechanism whereby a receiver s individual address is unknown or changeable transparently to the source Maintaining group membership information and building optimal multicast trees is challenging even in wired networks However, nodes are increasingly mobile One particularly challenging environment for multicast is a mobile ad hoc network (MANET) A MANET consists of a dynamic collection of nodes with sometimes rapidly changing multihop topologies that are composed of relatively low-bandwidth wireless links There is no assumption of an underlying fixed infrastructure Nodes are free to move arbitrarily Since each node has a limited transmission range, not all messages may reach all the intended hosts.

The TinyOS operating system utilizes a unique software architecture that was designed speci cally for resource-constrained sensor nodes [1]. Primarily based on the concept of wiring together components to create an application, the paradigm strives to use as little memory as possible, while still handling multiple roles in a sensor networking environment. Initially written in standard C, the project has since moved to a custom language, nesC. This Network Embedded Systems C uses C-like syntax, but adds some new features to support the structure and execution model of a TinyOS application. We will discuss nesC and the component design further, but rst let us consider the execution model. 6.6.1 Execution Model

To provide communication through the whole network, a source-to-destination path could pass through several intermediate neighbor nodes Unlike typical wireline routing protocols, ad hoc routing protocols must address a diverse range of issues [3] The network topology can change randomly and rapidly, at unpredictable times Since wireless links generally have lower capacity, congestion is typically the norm rather than the exception The majority of nodes will rely on batteries, thus routing protocols must limit the amount of control information that is passed between nodes The goal of MANETs is to extend mobility into the realm of autonomous, mobile, wireless domains, where a set of nodes form the network routing infrastructure in an ad hoc fashion The majority of applications for the MANET technology are in areas where rapid deployment and dynamic reconfiguration are necessary and the wireline network is not available [3].

friendly and accessible environments Random sensor distribution is generally considered in remote or inhospitable areas, or when a fast deployment of a large amount of sensors is desirable We will consider only random placement in this chapter An example of deterministic placement is considered in ref [45], where the authors proposed path exposure (the likelihood of detecting a target traversing the region using a given path) as the measure of goodness of the sensors that are deployed to perform collaborative target detection A centralized algorithm for placing sensors at selected locations to minimize path exposure is described in ref [45] In most articles in the literature, all sensing radii are equal, while a few articles consider coverage with different sensing radii We will consider only the case of equal sensing radii at each node, since there is limited research done for the case of adjustable ranges [46,47].