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This section aims to describe the determination of duty cycle and idle listening minimisation in several existing MAC protocols for WSNs. Duty cycle is defined as a ratio of waking up duration to the total interval which includes sleeping. The waking up period includes the durations required for listening, receiving and transmitting. Traditional networks such as ad-hoc wireless networks and wireless local area networks (WLANs) require high throughput or efficient bandwidth

utilisation. Nodes in such networks have to be in the active mode most of the time for data transmissions. Minimising idle listening to conserve power is not therefore the main goal. Determination of duty cycle in the schedule-based MAC approach is inherently simpler than the contention-based where it is sometimes not clear when the radio can be switched off. In the schedule-based schemes, the key issue is time synchronisation and timing. If the overhead for those can be kept low, then an efficient scheme should be possible.

As WSNs are application specific, duty cycle and idle listening minimisation requirements are dependent upon applications. High duty cycle is essential in event-based applications such as an intrusion detection system. The sensors deployed to detect the events have to be in an active mode more frequently. In order to achieve the high throughput during a short period of time, the sensors may have to be active most of the time and idle listening minimisation may not be the main goal. Environmental monitoring WSNs consist of sensors which may report their readings every minute or hour [MPS+02, TPS+05]. For example, the work described in [PHC04] was designed to achieve a 1% duty cycle which is required in [MPS+02]. A sensor should be switched to sleep mode if it has no data to transmit or receive. Most of the reviewed approaches are inspired by the multi-hop where each sensor is responsible for routing [PHC04, YHE03, DL03, ROG03, EEDP04, LKR07, JBT03]. It is therefore necessary to listen to the signals from its neighbours. The authors of [YHE03] quote some results from previous studies which state that idle listening consumes a significant amount of power especially when the listening period is long. It is recommended that the sensors must avoid idle listening by periodically being switched to sleep mode but delay may become another key concern [Haa04].

In the contention-based approach, listening is required for carrier sensing or orchestrating between nodes. Carrier sensing is performed prior to transmission to avoid collisions. Additional listening is required in [PHC04] to guarantee reliable data reception. If no packet is received within a predefined timeout, the sensors are switched back to sleep mode. Preamble length must be at least as long as the sampling period. This scheme puts the high cost to the receiver as it has to listen and receive the preamble longer. It was designed for the low duty cycle WSNs. Each sensor periodically exchanges its schedule with its neighbours in [YHE03]. Neighbour discovery is thus important and synchronisation between sensors is desired. Each sensor has to maintain a table which stores the schedules of its neighbours. This scheme aims to decrease the carrier sensing interval but additional resources are required. Moreover, Request To Send (RTS) and Clear To Send (CTS) are exchanged prior to data transmissions. It suits the periodic-based applications as several message exchanges are performed. This work was enhanced to support the heavy traffic systems where communication delay becomes important by allowing the overhearing nodes to wake up for a short period at the end of transmissions. This lets the neighbours forward data to the listening nodes immediately. Both [YHE03] and [PHC04] have been widely used in the periodic-

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based WSNs. This dissertation also develops a schedule-based protocol for this application category. This will be used in a comparative study which is discussed later in this dissertation. The authors of [DL03] demonstrate the minor impacts of collision, protocol overhead and overhearing on energy consumption compared to idle listening. Idle listening is reduced by transmitting all messages in burst. The durations between bursts are variable. In order to determine the length of the active period, an interval variable is used to specify the minimal amount of idle listening per frame. The sensors will be switched to sleep mode if no event is detected within such an interval. Buffer capacity is used to determine an upper bound of maximal time frame as messages between active periods have to be buffered. This work suggests the interval to be 1.5 times the combination of contention duration, RTS length and turn-around time. Asymmetric communication in a unidirectional communication pattern, such as sensor-to-sink, may cause an early sleeping problem as a node may go into a sleep mode when its neighbours still have messages to send. An additional frame is used to let another node know that there is a message for it and also that the medium is currently used by the other nodes. Furthermore, a sensor with a full buffer may require to send out data instead of receiving. Therefore, it immediately sends its own RTS to another node instead of replying with the CTS.

A hardware-software codesign platform has been proposed for a single-channel contention protocol based upon nonpersistent CSMA [EEDP04]. This scheme mitigates the idle listening by combining nonpersistent CSMA with preamble sampling. In nonpersistent CSMA, a node has to wait for a random duration prior to transmission after a free medium has been detected. The preamble sampling is conducted to check for activities in the channel such as transmissions by means of received signal strength. A wake-up preamble signal prior to data transmission helps to avoid overemitting. The length of a wake-up preamble is decreased by learning from the sampling schedule of direct neighbours. Each sensor updates its sampling schedule during every data exchange by piggybacking the remaining time until the next sampling. Additional information is included in the acknowledgement. This concept may not be efficient if there are many neighbours as each sensor has to keep and maintain a table where the schedules are stored.

Three side effects of low duty cycle have been observed in [LKR07]. Firstly, latency is increased as the sender may have to wait until the receiver wakes up. Secondly, a fixed duty cycle may lead to an inefficient data delivery. For example, a duty cycle for the highest traffic load results in a significant energy waste. However, a duty cycle for a low traffic load results in low throughput and a long queuing delay. Finally, a fixed synchronous duty cycle may increase the possibility of a collision. DMAC is built based upon the time-slot concept. It solves such problems by assigning an offset to the active/sleep schedule of each sensor. The offset is related to the depth on the tree which is assumed to remain unchanged. The idea is to sequentially wake the nodes up like a chain reaction. The packets can be thus continuously forwarded to their destinations. Both receiving and

sending durations have the same length which is enough for one packet transmission and reception.

The determination of the duty cycle is simpler in the schedule-based approach as the communications can be scheduled in advance. The sensors wake up by periodically switching their radios on for control receptions and data transmissions. Control and data can be sent in the same or separate communication channel. A time slot is allocated to each of the sensors for transmissions and they switch the radios off and turn to sleep mode whilst the others are sending. Idle listening can be minimised as sensors are in sleep mode most of the time. However, a high duty cycle is difficult to achieve in the schedule-based approach. For a set of fixed sensors, each of them has to wait until the others finish their transmissions. Throughput observed at the base station may be reduced as some sensors are not able to send a specific number of packets within a period of time. However, the contention-based approach can support the systems which require heavy traffic as the sensors send at anytime the medium is free. The schedule-based supports power conservation via idle listening minimisation.