Wireless Sensor and Actor Networks (WSAN)





Research Projects 

Project Description
WSANs Communication Architecture

After sensors in the sensor/actor field detect a phenomenon, they either transmit their readings to the resource-rich actor nodes which can process all incoming data and initiate appropriate actions, or route data back to the sink which issues action commands to actors. We call the former case as Automated Architecture due to the nonexistence of central controller (human interaction) while we call the latter one as Semi-Automated Architecture since the sink (central controller) collects data and coordinates the acting process. These two architectures are given in Figure 6. (a) and (b). Depending on the types of applications, one of these architectures may be used. The advantage of Automated Architecture is that the information sensed is conveyed quickly from sensors to actors, since they are close to each other. Moreover, since event information is only transmitted locally through sensor nodes, only sensors around the event area are involved in the communication process which results in energy and bandwidth savings in WSANs.


         Figure 6. (a) Automated and (b) Semi-Automated Architecture.

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Effective Sensor-Actor Coordination

The main communication paradigm in WSANs is based on the sensor-actor coordination. Appropriate actions corresponding with the sensed phenomenon cannot be performed unless event information is transmitted from sensors to actors. The most important characteristic of sensor-actor communication is to provide low communication delay due to the proximity of sensors and actors. However, since the role of sink does not involve collecting the sensor data and coordinating the activities of the nodes, sensor and actor nodes should locally coordinate with each other so as to provide efficient transmission of sensor readings. In WSANs, for sensor-actor coordination there is a need to develop protocols which are able to provide real-time services with given delay bounds, according to application constraints and ensure an energy efficient communication among sensors and actors.

In addition to these requirements of the sensor-actor communication, there is a question such that which actor nodes will be informed about the event as a result of sensor-actor communication. One of the possibilities is that sensor readings may be sent only to one actor node, as shown in Figure 7. Then, here one of the main challenges is to determine that single actor node to which sensors will send the information. The selection of that actor node among all of the actors requires the coordination of all sensor nodes in the event area. This selection can be done based on the distance of actors to the event area, total energy consumption of sensor nodes, total event transmission time, or the action ranges and current capabilities of actor nodes.


         Figure 7. Single-Actor.

In WSANs, instead of only one actor, multiple actors can also receive the information about the sensed phenomenon as shown in Figure 8. In this case, sensors only need to coordinate with sensors within some neighborhood so as to divide themselves into clusters each of which selects one different actor to transmit the data. These clusters may be constructed in such a way that the event transmission time is minimized, since low latency between sensing and acting is required in WSANs or in such a way that the event features are transmitted through the minimum energy paths, since sensors have scarce energy resources. Moreover, in order for actors receiving event information to coordinate with each other and perform required actions, clusters and corresponding actors may also be selected so that the action regions of those actors can cover the entire event area and those actors form a connected communication graph where there is an edge between any two actors that can directly communicate with each other.


         Figure 8. Multi-Actor

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Effective Actor-Actor Coordination

In WSANs actors can communicate with each other in addition to communicating with sensors. Since there are few number of actor nodes and the power capacities of these nodes are higher than sensor nodes, actor-actor communication is similar to the communication in wireless ad-hoc networks. Actor-actor communication can occur in the cases where the actor receiving sensor data may not act on the event area due to small action range or insufficient energy, where one actor may not be sufficient to perform the required action, thus other nearby actors should be triggered, where multiple actors receive the same event information and there is an action threshold, hence these actors should ``talk'' to each other so as to decide which one of them performs the action and where multiple events occur simultaneously, thus actor should communicate with each other to perform task allocation.

All of the above situations which indicate the necessity of actor-actor coordination converge on the following question: "Which actor(s) should execute which actions?". One of the axes to answer this question can be that Whatever the number of actors receiving sensor data via sensor-actor coordination is, only one actor performs the action. If multiple actors receive data packets from sensors, they need to negotiate with each other and coordinate locally to select the most appropriate actor for that event. However, if one actor is informed about the event features at the end of sensor-actor communication, then there occurs a question such that whether this actor takes decision in an isolated fashion and thus initiates action by itself or it first communicates with other actors to find "best" actor for that event. In the latter case, that actor publishes the announcement message to other actors. After it receives responses from other actors, it selects one of the available actors and lets it perform the action.

On the other hand, instead of only one actor, tasks can be performed by multiple actors. In this case, the additional challenge is to decide what the optimal number of appropriate actors is. Furthermore, whatever the number of actors receiving the sensor data is, actors need to coordinate with each other so as to decide on the number of required actors for that event. Then, there is a need for another decision process to select the most fit actors among the capable actors available for that task.

Moreover, in WSANs, while actors can take a decision on the action in a distributed way as explained above, the decision process can also be performed in a centralized way. The centralized approach provides action decisions to be taken in an organized way since the decision is taken at only one actor node which may be equipped with more powerful communication facilities. Hence, actors in the event area do not deal with data processing and local communication with each other, which may provide them to consume less power. However, the drawbacks of centralized approach are that it may be high communication delay if the decision unit is far away from the event area and it will be difficult for the central unit to update the new locations of actors in the network when the actors are mobile.

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WSANs Protocol Architecture

In order to deal with the challenges of sensor-actor and actor-actor coordinations, a protocol stack of sensor and actor nodes is consisted of three planes, namely Management Plane, Coordination Plane and Communication Plane, as shown in Figure 9. Communication plane involves application, transport, routing, MAC and Physical layers. It enables the information exchange among the nodes of the network and produces a change in the state of the network. Data received by a node at the communication plane should be submitted to the coordination plane which decides how the node should act on the data. Moreover, the coordination plane provides nodes to be modeled as a social entity, i.e., in terms of the coordination and negotiation techniques it possesses. Management plane is responsible for monitoring and controlling a sensor/actor node so that it operates properly. It can also provide information needed by the coordination layer to make decisions.


         Figure 9. WSAN Protocol Stack.

The functions performed by the management layer can be categorized into the following three areas: (i) Power Management Plane manages how a node uses its power. For example, when the power level of a sensor node is low, this plane informs the coordination plane about this situation. Then, the coordination plane may decide not to participate in routing messages. This decision is submitted to the communication plane which provides a node to broadcast this information to its neighbors. Although power management plane is more important for resource-limited sensor nodes than for resource-rich actor nodes, this plane is also necessary in actor nodes since some actions may require high power capacity and thus before taking action decisions the current power level of an actor node should be submitted to the coordination plane in order to determine the eligibility of a node for that action. Moreover, power management plane informs the coordination plane in case of low power situation so that if the actor is mobile, it goes to the appropriate station and replenish its battery.(ii) Mobility Management Plane detects and registers the movements of nodes so that network connectivity is always maintained.(iii) Fault Management Plane refers to the detection and resolution of node problems.

Coordination plane determines how a node behaves according to the data received from communication plane and management plane. After sensing an event, sensors communicate their readings with each other. At each sensor node these exchanged data are submitted to the coordination plane to make decisions. By this way, sensors are able to coordinate among themselves on a higher-level sensing task.The existence of coordination plane may be much more critical for actors than for sensors, in the case of distributed decision (DD) actors have to collaborate with each other in order to perform appropriate actions. When an event occurs, the common goal of all actors is to provide required action on that event. Thus, social abilities, i.e., sophisticated coordination and negotiation abilities, are necessary in WSANs to ensure coherent behavior of the community of actors. These required social abilities of an actor are defined in the coordination plane. Specifically, what coordination layer does in actor-actor coordination is to make decisions about which actors act on the event area and whether to have those actors act concurrently or, if sequentially, then in what order.

Although it is possible to communicate without coordinating, coordination cannot be achieved without communication. Therefore, the communication plane which provides the exchange and sharing of information and link relation between nodes is one of the important planes in the architecture of sensor and actor nodes. Communication plane receives commands from the coordination plane (about the decision of how the node will behave) and then according to that information provides communication with other nodes by using the developed communication protocols. Similarly, when communication plane of a node receives data from other nodes, it submits the information to the coordination plane which makes decisions about that information. Specifically, the communication plane deals with the construction of physical channels, the access of the node into the medium (MAC), the selection of routing paths through which the node transmits its data and the transport of packets from one node to another node.

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Transport Layer

Since in WSANs sensor-actor and actor-actor communications occur one after the other, they influence each other. For instance, when the transport protocol for sensor-actor communication detects low reliability, transport protocol for actor-actor communication regulates the traffic between actors so that the actor receiving low reliable event information can inform the other nearby actors about this situation as soon as possible. Thus, in WSANs there is a need for unified transport protocol which works well both for sensor-actor communication and actor-actor communication. This unified transport protocol should involve the characteristics of both sensor-actor and actor-actor transport protocols.

Sensor-actor communication allows sensor nodes to transmit their data to actor nodes so that appropriate actions corresponding with the sensed phenomenon can be initiated. In order for an actor node to initiate right actions, sensor readings have to reliably arrive at the actor. However, there is no such a requirement that every individual report has to reach the actor with perfect accuracy, because some of the sensor readings are highly correlated with each other and thus actor generally acts according to the collective information provided by sensor nodes instead of responding every sensor information separately. Hence, the important point is whether the actor node can detect the event reliably, that is, know about the exact type, location, intensity, etc. of the event or not. Then, the actor node will take decisions and act according to current reliability level.In addition to the reliability, in WSANs transport protocols must support the real-time issues since timing constraints may be very important depending on the application. Thus, a major requirement for WSANs is to aggregate and disseminate information not only in a reliable manner, but also within a time frame that allows the actors to take necessary actions. Therefore, the transport protocol developed for sensor-actor communication should integrate the real-time properties into the reliability issue.

As in sensor-actor communication, transport protocols for actor-actor communication should support both reliable and timely transfer of data. However, reliability requirement of actor-actor communication is different from that of sensor-actor communication: in actor-actor communication instead of event reliability, there is a need for em conventional reliability, that is, reliable transmission of every message between actors. The reason for conventional reliability is that actors communicate coordination messages which contain details about the events and the according tasks and thus, in order to avoid wrong actions every message transmitted between actors should be totaly reliable. Moreover, as stated above another function of transport layer for actor-actor communication is to control end-to-end transmission delay so that the task completion time is minimized and the real-time restrictions are not violated.

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Routing Layer

In WSANs there are both multiple sensors and multiple actors which can communicate with each other. When sensors detect an event, there is no specific actor to which a message will be sent. This uncertainty occurring due to the existence of multiple actors causes challenges in terms of the routing issues. Moreover, another challenging problem which routing protocols should deal with in WSANs is to provide reliable event transmission as well as end-to-end real-time guarantees.

Since there are multiple actors, the problem of selecting an actor node is faced. Each source, a sensor which detects an event, should select an actor node and establish a path toward it. The selection can be made on the basis of local information such as its own available energy, the available energy of the neighboring sensors, or on the basis of metrics related to the distance from the actors. Moreover, for each node there is a need to determine the optimum mode of communication, i.e., single-hop or multi-hop. For multi-hop routing, there will be multiple possible paths between the source and the selected actor node. Thus, there is a need to develop a routing protocol which provides path selection, data delivery and path maintenance. Furthermore, to be responsive to actors joining and leaving dynamically and to avoid unpredictable congestion and holes in the network, the routing protocol must be self-organizing and adaptive. Moreover, WSANs have timing constraints in the form of end-to-end deadlines. Thus, developed routing protocol should support real-time communication by considering that data in a system may have different deadlines due to different validity intervals. Therefore, routing protocol should also consider the issue of prioritization and provide data with small delay bound to arrive at the actor on time.

For actor-actor communication, the use of flooding algorithms usually may not be efficient since flooding causes all resource-constrained sensors to receive multiple copies of the same packet which are irrelevant to them. Actually, routing protocols developed for ad-hoc networks such as DSR, AODV, OLSR can be used for actor-actor communication as long as communication overhead occurring at sensor nodes due to actor-actor communication is low. In addition, in order to provide timely actions and adaptability to different applications, ad-hoc routing protocols should be improved to get unified routing protocol which considers real-time restrictions and supports all types of decision processes as well as all types of task types

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Medium Access Control

In WSANs large number of sensor nodes and relatively small number of actor nodes coexist. Thus, in order to effectively transmit the event information from large number of sensors to actors there is a need for MAC protocol which organizes the data communication between sensors and actors. Moreover, in some applications (i.e., distributed robotics) actors may be mobile. As they move, they may leave the transmission regions of some sensors and enter the other sensors' region; or maybe they will be totaly disconnected from the network. Therefore, another function of MAC protocol in WSANs is to maintain network connectivity between sensors and mobile actors. Furthermore, as discussed before, the timely detection, processing, and delivery of information are indispensable requirements in a sensor/actor network application. Hence, as the base of the communication stack, the MAC layer should support real-time guarantees or QoS features.

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Current WSN and WSAN protocol designs are largely based on a layered approach. Thus, transport, routing and MAC issues discussed above are designed and operated independently. However, the suboptimality and inflexibility of this paradigm result in poor performance for WSANs, due to constraints of low energy consumption and low latency.

For an actor node to initiate right actions, event information should be transmitted reliably from sensors to actors as stated before. In WSANs, one of the main factors which causes low event reliability is network congestion. In the case of high congestion, MAC layer reacts locally by exponential back-off, while transport layer reacts by lowering the transmission rates of sensors. However, normally these two layers act independently from each other which causes inefficiencies due to the duplication of functions. By cross-layering approach, each protocol shares its data with other protocols, which avoids those inefficiencies. For example, in WSANs when congestion is high, first of all MAC layer reacts to the congestion. If this response is not sufficient, MAC layer informs the routing layer about this congestion. Then, routing layer lets coordination plane know the situation. As a result, coordination plane and routing layer provide data traffic to be rerouted through another appropriate actor node. On the other hand, if alternate actors and routes do not exist, the optimization can use transport protocol mechanisms to freeze traffic transmissions.

Another example of the cross-layering design in WSANs is the optimization of the size of the packets transmitted from sensors to actors. In order to provide a unified packet structure that incorporates the functionalities of each protocol in the protocol stack, routing, MAC and physical layers should be investigated together. The energy efficiency of the WSAN depends on the energy required to transmit a packet and the reliability of the network. From the routing layer point of view, reliability of the packet depends on the distance of the node generating the packet in terms of the number of hops to the actor. Intuitively, it is better to send smaller sized packets from the nodes far away from the actor. Hence, in order to provide energy efficiency, the information about an event may be transmitted to the actor using small sized packets while the relay nodes aggregate the packets due to being closer to the actor.

On the other hand, the size of the packet determines the number of packets needed to be sent to inform an event to the actor. Then, from the MAC layer point of view the number of packets translates into the number of contention attempts the node needs to perform. Decreased packet size in effect leads to increased collision probability and thus high energy consumption at the MAC layer. Lastly, from the physical layer point of view, as the coding rate increases, communication will be more reliable. Increased rate translates into sending more bits for useful information. However, a sensor node consumes energy based on the number of bits it sends for a transmission, i.e., packet size. Hence, packet size optimization also affects the bit level energy consumption. As a result, a useful model and an energy efficiency metric that accommodates all these factors is needed for optimization of packet sizes in WSANs.In addition to the coding rate, power control strategies at the physical layer affect the functionality of higher level protocols.

The basic ideas of cross-layering optimization stated above are also valid for actor-actor communication.

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Research Challenges
  • For sensor-actor coordination, clustering algorithms which provide timely transmission of sensor readings and better utilization of the existing energy resources as well as which work well both for single-actor (SA) and multi-actor (MA) cases need to be developed.
  • For actor-actor coordination, there is a need to provide a unified framework that can be exploited by different applications to always select the best networking paradigm available according to the events sensed and to the operation to be performed, so as to provide efficient actor-actor communication.
  • There is a need for an analytic framework in order to characterize the three planes, that is, management, coordination and communication planes.
  • Sophisticated distributed coordination algorithms need to be developed for effective sensing and acting tasks.
  • Leveraging a cross layer approach can provide much more effective sensing, data transmission, and acting in WSANs. Several cross-layer integration issues among the communication layers should be investigated in order to improve the overall efficiency of WSANs.
  • There is a need for real-time communication protocols for both sensor-actor and actor-actor coordinations in WSANs.

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