Drop in the price of hardware fuelled by manufacturing process improvements has resulted in a noticeable upward cycle of research in the field of networks that not only sense the data but also provide automated reaction to specific situations known as Wireless Sensor and Actuator Networks (WSAN).
“Smart environments” are the next step in the evolutionary development in intelligent systems automation related to utilities, construction, industry, home and transportation. The “smart environment” is defined as one that is “able to acquire and apply knowledge about the environment and its inhabitants in order to improve their experience in that environment”.
The WSN, which are in the heart of the “smart environments” consist of densely deployed micro-sensor nodes that continuously observe certain physical phenomenon. The existing abundance of WSN applications can be divided into two major groups based on the nature of the supported applications: WSN for monitoring and WSN for event detection/tracking. A major common feature is that both exploit the collective effort of nodes which have computing, transmitting and sensing capabilities. From the user point of view the main objective of WSN is to reliably detect or collect, and estimate event features based on the collective information provided by all sensor nodes. From the engineering design point of view, the main challenge for achieving this objective is posed by the severe energy and processing constraints of the low-end wireless sensor nodes. The collaborative sensing notion of WSN, which is achieved by the networked deployment of sensor nodes, can potentially be used towards overcoming the characteristic challenge of WSN, i.e., resource constraints. To this end, there has been a significant amount of research effort to develop suitable networking protocols in order to achieve communication with maximum energy efficiency. Because of the strict demands of WSN as compared to wired networks and Ad- Hoc networks, the design goals of such system are different from the traditional approaches.
The suitability of one of the foundations of networking, the OSI layered protocol architecture, is coming under close scrutiny from the research community. It is repeatedly argued that although layered architectures have served well for wired networks, they are not particularly suitable for wireless sensor networks. That is why the notion for a different approach, called cross-layer design, has come into existence. Generally speaking, cross-layer design refers to protocol design done by actively exploiting the dependence between protocol layers to obtain performance gains. This is unlike layering, where the protocols at the different layers are designed independently.
Cross-layer design stands as the most promising alternative to inefficient traditional layered protocol architectures allowing designers to take into consideration different factors like the scarce energy and processing resources of WSNs, joint optimization and design of networking layers and last but not least overall performance evaluation.
To understand the concept of the cross-layer design and CLD frameworks, first the definition of layered frameworks should be elaborated. A layered architecture, like the seven-layer open systems interconnect, divides the overall networking task into layers and defines a hierarchy of services to be provided by the individual layers. The services at the layers are realized by designing protocols for the different layers. The architecture restricts direct communication between nonadjacent layers; communication between adjacent layers is limited to procedure calls and responses. Alternatively, protocols can be designed by violating the reference architecture, for example, by allowing direct active information exchange between protocols at nonadjacent layers or sharing variables between layers. Such violation of the layered architecture is what is known as the most popular definition of cross-layer design with respect to the reference architecture.
Cross-layer design allows active communication between different layers which ultimately can result in significant performance gains. Some of the new trends in wireless networking such as cooperative communication and networking, opportunistic transmission and real system performance evaluation are discussed in light of QoS support for multihop sensor networks. The interaction between protocols at different layers is examined from the point of view of different system parameters controlled at distinct layers. For instance, it is argued that power control and modulation adaptation in the physical layer can affect the overall system topology, while scheduling and channel management in the MAC layer will affect the space/time reuse in the whole network. A general framework illustrated below shows the interaction ideas and point out that all controls can have a multiple impact. (1) illustrates the fact that assignment of channels to certain network interfaces changes the interference between neighboring channels.
Future “smart environments” will not only collect information from the environment but will also “acquire and apply knowledge about the environment to improve the users’ experience”. Thus not only sensing nodes will be required but also “acting” nodes, known as “actuators”. While the sensor nodes are very low-power, low-cost sensing devices with very limited communication and processing capabilities the actor nodes are more resource rich nodes, equipped with better communication abilities (more processing power, larger transmission range) and longer battery life. These networks are known as Wireless sensor and actuator networks -WSAN illustrated below.
WSAN have two unique features, which clearly differentiate them from WSNs: real time requirement and coordination. The real time requirement comes from the fact that WSAN are expected to immediately respond to a certain event. The coordination requirement has two aspects: one provides transmission of the event features from the sensors to the actor nodes while the other is related to the coordination among the actor nodes themselves and the optimization of their actions. A protocol model for WSAN that is three dimensional and inherently cross-layered is illustrated below;
It consists of three planes: communication plane, management plane and coordination plane. The communication plane is responsible for realizing the communication between the nodes. The data received by a node at the communication plane is submitted to the coordination plane to decide how the node should react to this data. The management plane in turn is responsible for monitoring the operation of the network and controlling the sensor and actor nodes. Important issues as mobility management, power management and fault tolerance are handled by the management plane. The coordination plane is more related to the actor nodes as they have to collaborate very efficiently with each other in order to perform a certain task, working sequentially or concurrently. It is stated that the realization of WSANs will need to satisfy more severe constraints and specific requirements introduced by the coexistence of sensor and actor nodes.
In summary cross-layer Design is the new unconventional protocol design approach that has been suggested to meet the challenges and restrictions posed by the newly emerging networks like WSN and WSAN. These networks are based on small but intelligent devices (smart sensor nodes) that can sense the environment, collect data and transfer data, if necessary react to a specific event.
