Traffic Prioritization in Sensor Networks using Bandwidth Scavenging

Traffic Prioritization in Sensor Networks using Bandwidth Scavenging

Anthony Plummer (Michigan State University, USA), Mahmoud Taghizadeh (Michigan State University, USA) and Subir Biswas (Michigan State University, USA)
DOI: 10.4018/978-1-4666-0017-1.ch012
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This chapter presents a history-based statistical channel access mechanism for enabling traffic prioritization in wireless sensor networks. Prioritized access is realized such that low priority non-real-time sensors can access channel bandwidth that is unused by high priority real-time traffic. The key idea is for the low priority sensor nodes to first observe and statistically model the channel usage pattern by the high priority traffic, then make advantageous probabilistic transmissions so that the non-priority traffic throughput is maximized while protecting the high-priority traffic from disruptions. The chapter details a practical whitespace measurement scheme and presents a channel history based prioritization protocol. The access mechanism is implemented in a TelosB mote-based sensor testbed in which the non-priority motes continually measure the RSSI to infer the channel usage pattern and probabilistically access the channel while different types of traffic are sent by high-priority TelosB motes.
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The concept of a Wireless Sensor Network (WSN) has provided the opportunity for many useful monitoring applications to be developed. A WSN typically consists of many small and low powered communication devices, which can be composed of a few components, including a wireless communication interface, microprocessor, small on-board memory, and sensor interface. The sensor interface allows each device to detect various environment stimuli using different sensor modules. Although these devices are individually low power and low cost, a large number of them together are capable of performing many complex applications. For example in the application of area monitoring, a WSN may measure levels of sound, vibration, atmospheric pressure or temperature within a specified area. With these individual measurements, many applications can be enabled such as battlefield surveillance, animal population monitoring, or health tele-monitoring (Akyildiz, Sankarasubramaniam, & Cayirci, 2002).

With the WSN ability to monitor and report diverse information about an environment, multiple categories of data may be sent over the network. These data types can result from separate data sets generated on a single node with multiple sensor modules or multiple nodes with different sensors types. The latter case creates a heterogeneous WSN where there may be two or more sets of devices with varying capabilities.

Consider a WSN where there are two different sets of sensor devices sharing the same wireless channel. One set supports real time data applications and the other set is used for non-real time applications. Real time applications such as event surveillance typically require constant or variable rate data streams to be sent over the sensor network. Depending on the specific application, the rate of this data can be of the order of a few packets per second to tens of packets per second. The objective is to transport such real time application data packets with minimum delivery delay and packet losses at rates required by the application. Non-real time applications such as environmental monitoring need to measure levels of temperature, moisture and other ambient parameters in a time driven or event driven manner. Such applications typically require lower data rates compared to the real-time data streams and have less stringent packet delay and loss requirements. In this type of network, nodes that support real time applications must coexist with the nodes that are running non-real time application. In other words, devices with different capabilities must share the spectrum resources.

Now, if a network designer wants to ensure that the requirements of the real time traffic network are met in this heterogeneous WSN, a traffic priority structure can be used. In this case, the real time traffic is given priority access to channel over the non-real time traffic. To address this type of traffic prioritization problem in general, some issues that would need to be addressed are:

  • Maintaining a priority structure: Support is needed to facilitate different priority levels for the various sets of network devices

  • Supporting higher priority requirements: Data requirements of the higher priority traffic must be met

  • Limiting the effects of delaying the higher priority traffic: When lower priority traffic has data to send, the impacts on the higher priority traffic must be minimized

  • Supporting different high priority traffic loads: As the high priority traffic changes, the lower priority traffic should adjust its usage of bandwidth accordingly

  • Maximizing the throughput of the lower priority traffic: Lower priority traffic throughput need to be maximized given the available channel bandwidth.

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