Scheduling Adjustment of Mac Protocols on Cross Layer for Sensornets
A number of recent advances in MAC protocols for wireless sensor networks have been proposed to decrease idle listening. Low-Power-Listening (LPL) protocols transmit data packets for the inter-listening interval, for this reason, allowing sensor nodes to sleep for long periods of time between channel probes. The inter-listening interval as well as the particular type of LPL protocol ought to well match the network conditions. Some LPL protocols break communication between the sender and the receiver after the data packet has been successfully received. In this study, a novel variable rate based time frame scheduling scheme is proposed to further reduce collisions and improve energy saving in wireless sensor networks. During this pre-schedule slot, each node knows exactly the schedule of other neighbor nodes. Multi-rate and power scaling are adopted to achieve further energy saving by employing an acceptable rate rather than the maximum rate. Data rate is dynamically adjusted according to the traffic load of sending nodes in an energy efficient data rate to retrench energy. Compared with Z-MAC, performance in the present study proves to have better ability of local framing pre-schedule and multi-rate achieves better energy efficiency. Our results show that using the improved method of the MAC schedule provides up the enhancement of lifetime for different traffic scenarios.
January 28, 2010; Accepted: March 08, 2010;
Published: June 10, 2010
Applications of Wireless Sensor Networks (WSNs, which we call sensornets hereafter) are becoming increasingly complex and they require the network to keep a satisfying level of operation for extended periods of time. Therefore, sensornets cannot but make the best possible use of their initial energy resources, specifically by continually suiting protocols to the changing conditions in the network. Both protocol-specific and cross-layer schemes have provided a plethora of energy reducing techniques. Particularly, there are several protocols that focus on reducing energy at the data link/MAC layer, which constitutes the scope of this study, In this study, we investigated how to efficiently improve the energy-conserving ability in sleep mode for as long as possible. The idea presented in this study discusses switching between MAC schedules to adopt the most energy-efficient pattern of packet transmissions and receptions. Since, different areas of the network undergo different traffic loads, the MAC protocol should exploit the schedule most economically for the local situations.
In new sensornets platforms, a simple observation was made that idle listening,
far from being negligible, was a main source of energy consumption. The LPL
and Preamble Sampling (PS) MAC protocols were introduced as a result. In his
taxonomy of MAC protocols, Langendoen identifies LPL and PS protocols as two
branches of random access MAC protocols, with the only difference that LPL MAC
protocols need not know anything about their neighbors and their wake-up schedules.
Both types of MAC protocols, including B-MAC (Polastre et
al., 2004), WiseMAC (El-Hoiydi and Decotignie, 2004)
, SyncWUF (Shi and Stromberg, 2007) and X-MAC (Buettner
et al., 2006), use the insight behind Aloha with PS (El-Hoiydi,
2002): the sending node occupies the medium for long intervals to signal
its imminent packet transmission. Receiving nodes are thus allowed to sleep
for at most the duration of this preamble and are required to hold awake while
they sense a busy medium until the packet transfer is accompished. In this study,
we consider only the LPL branch of the Langendoen taxonomy (although many of
our results can be transposed to other MAC protocols) and we define (LPL) MAC
schedule as the pattern of packet transmissions occurring within the interval.
Researchers are forced to abandon B-MAC and a few other LPL protocols because
of radios changes: Although, it paved the way to new MAC protocols, B-MAC, which
uses a variable-length preamble to signal the impending packet transmission,
can no longer be implemented as proposed on the new IEEE 802.15.4 compliant
platforms since this standard has a fixed preamble length of only a few bytes.
After the introduction of new radios, researchers introduced new LPL and PS
protocols: X-MAC , C-MAC (Liu et al., 2007),
WiseMAC, CSMA-MPS (Mahlknecht and Bock, 2004) and SpeckMac
(Wong and Arvind, 2006) are among the most popular contributions.
These protocols are based on repeating either the data packet itself (SpeckMAC
and CSMA-MPS), or an advertisement packet (X-MAC/C-MAC), in place of a long
A large number of more sophisticated mobility models for WSNs research have
been presented (Le Boudec and Vojnovic, 2005; Jardosh
et al., 2005; Carlson et al., 2004).
The most widely adopted models of such kind are based on random individual movement,
the simplest of which, the random walk mobility model (similar to Brownian motion),
is adopted to represent pure random movements of the entities of a system (Einstein,
1956). Environment monitoring and battle field surveillance require the
sensor nodes to be operated in low power to extend life time (Le
Boudec and Vojnovic, 2005). Taking the inborn nature of wireless sensor
network into consideration, we should first pay attention to energy efficiency
and then the high throughput, low latency and fairness (Chatzigiannakis
et al., 2005; Calì et al., 2000).
The smooth operation and energy efficiency of any wireless sensor network depends,
to a large extent, on the effectiveness of Medium Access Control (MAC) layers
responsibility. In this paper, an MAC layer approach is adopted to achieve energy
Wireless channel accessing schemes can be classified into two broad categories
by tradition: contention-based and reservation-based (Wu
and Biswas, 2005). A commonly-used MAC paradigm in wireless networks is
CSMA (Carrier Sense Multiple Access), which is a contention-based medium access.
It gains high popularity due to its simplicity and robustness. It does not require
much infrastructure support (Rhee et al., 2005).
Collision can occur in any two hop neighbors. RTS/CTS can alleviate the hidden
terminal problem, but it incurs high overhead (Woo and Culler,
2001; Polastre et al., 2004). The proposed
Z-MAC (Rhee et al., 2005) that combined CSMA
and TDMA. In the low level, CSMA is generally adopted; while in the high contention
level, a TDMA hint is desired to enhance contention resolution. However, there
is no multi-rate functionality in Z-MAC.
In this study, multi-rate functionality is introduced into Z-MAC to reduce
contention and collision. Since, each node knows its schedule and neighbors
schedules, it can smartly sleep to achieve further energy saving. Simultaneously,
we also have finished the relative earlier research study (Gao
et al., 2009, 2010; Wei
and Wang, 2009; Wei et al., 2007a, b,
Aloha with PS is one of the first channel-probing schemes proposed for sensornets
(El-Hoiydi, 2002). As a consequence, El-Hoiydi introduced
WiseMAC. We show that explicit scheduling between nodes is unnecessary because
it can be achieved implicitly with X-MAC, C-MAC, or MX-MAC. B-MAC with LPL is
the first MAC protocol to introduce LPL schedules for recent radios (with WiseMAC
being the first for PS MAC protocols). Authours thoroughly compare B-MAC to
S-MAC and T-MAC (Van Dam and Langendoen, 2003). The
802.11 family MAC provides multi-rate functionalities, but energy consumption
is very high in these MAC. They are not suitable to wireless sensor works. S-MAC
(Wei et al., 2002) is a low power contention
based MAC protocol. The B-MAC allows application to implement its own MAC through
a well defined interface. It also adopts LPL (Low Power Listening) and CCA (Clear
Channel Assessment) to achieve higher throughput and energy efficiency. The
Z-MAC is based on B-MAC, uses CSMA as the baseline MAC scheme, but uses a TDMA
schedule as a hint to enhance contention resolution. In Z-MAC, a time slot assignment
is performed at the time of deployment. Higher overhead is incurred at the beginning.
Its design philosophy is that high initial overhead is amortized over a long
period of network operation, eventually compensated by improved throughput and
Most studies have been dedicated to the task of adapting MAC protocols to conditions
in the local neighborhood of a node. Watteyne et al. propose several variants
of one-hop MAC, which is a receiver-based cross-layer routing and MAC protocol.
Additionally, MiX-MAC considers schedules for broadcast packets. In El-Hoiydi
(2002) and Van Dam and Langendoen (2003) propose
to improve S-MAC by a novel adaptive active/sleep duty cycle. Pham and Jha introduce
MS-MAC, an S-MAC-based protocol that adapts S-MACs listening, sleeping
and synchronization cycles to anticipated node movements.
In this study, based on Z-MAC, we establish the past body of work, utilizing the idea of adapting to network different situations and specifically focusing on pre-schedule about LPL MAC protocols, which have proven quite energy efficient for the practical sensornets applications. We use a novel multi-rate solution to reduce contention by trying to limit the transmission confined in the owner slot. This approach greatly reduces contention and hence reduces energy consumption.
CROSS LAYER DESIGN SCENARIOS
The concept of cross layer design is not new in the networking area. In the
early study (Jardosh et al., 2005), (Tseng
et al., 2004) , cross layer design has been proved to be effective
in networks. Cross layer design principles have greater importance in ad hoc
networks because of the unique features of these environments. Different layers
are more likely to adopt the same information in decision making, for example,
the link and channel states, locations of the nodes, neighbor list and topology
information of the network are frequently adopted by both the routing and the
MAC layers in decision making. In addition, different layers (especially routing
layer and MAC layer) need to cooperate closely to meet the requirements of the
applications in a fast changing wireless environment. This goal can be better
achieved when the routing layer shares the MAC-layer information such as channel
condition, neighbor information, etc.
Cross-layer design allows interaction between any layers. A layer can interact
with layers in the protocol stack. The study by Chatzigiannakis
et al. (2005) discussed the positive effects of cross layer information
sharing on the mobile device. It also proposed a framework to realize efficient
cross layer information sharing.
Normally, the signal processing applications (such as DSC: Distributed Source
Coding) running on the sensor nodes will sample data from the environment. The
sampled data is to be transmitted to a sink node many hops afar. The DSP data
is submitted to the application adaptation component; with corresponding end
to end rate requirements and destination nodes indication (the default
destination is the sink node, keeping this as a variable parameter for the flexibility).
The application adaptation component pushes the data in the queue of the FIFO
management component. It also gives end-to-end rate hint to routing component.
The routing component will pack the data into TOS_Msg format in the FIFO management
component without the memory copy and find next hop neighbour in the local database
component. Then routing selection and rate parameters are passed to MAC component.
MAC component will pack data into MAC frame format (again, without memory copy).
And then it will calculate the transmit power according to the channel condition
and data rate and then set data rate and supply power to physical layer. After
that, the physical layer will start data transmission, sending data from FIFO
to radio. This process is shown in Fig. 1.
|| Diagram of components in the framework
CROSS LAYER CONTROL
The multi-rate MAC component is based on T-MAC. It adopts T-MAC to perform
the Media Access Control functionality and node sleep/wakeup. We add multi-rate
functionality into the MAC component. The multi-rate in MAC component is achieved
by dynamically adjusting:
MAC scenario description:
When the routing component calls the command of sending packets to MAC component,
the data packets have already been well packed in advance in sending FIFO (the
data packets stored in FIFO have their headers in TOS_Msg format). The MAC component
then packs MAC header and CRC tail to the TOS_Msg, of course, without memory
copy. After that, it chooses a proper modulation scheme according to the data
rate and sets transmit radio power based on the modulation scheme and channel
lost between sender and receiver. Then it starts radio for data transmission.
When a packet is captured by the physical layer, it will be stored in the FIFO
after header and tail processing.
To evaluate the effectiveness of the Local Framing Pre-schedule, we simulated
this functionality in MATLAB and compared it with original Z-MAC. The test benchmark
adopted in this simulation is the same as Fig. 1. Node 0 sends
data to node 1 and node 4 sends data to node 5. Data sent by these nodes has
variable length to test the performance under different traffic loads. The experimental
parameters are presented in Table 1.
The experimental parameters are the same as adopted in Z-MAC and B-MAC. Traffic
data lengths adopted in simulation are: 413 bytes, 836 bytes, 1278 bytes, 1689
bytes, 2206 bytes and 2538 bytes, respectively. The total energy consumptions
are acquired and compared. The research by Schurgers et
al. (2001) has proposed that, to maintain the same receiving signal
strength, the transmitting power is proportional to the symbol rate and the
modulation constellation size:
Normally, multi-rate is achieved by modulation scaling by keeping symbol rate
the same, while scaling the constellation size. In order to keep the same receiver
SNR, the transmit current should be proportional to a power of two of the transmission
rate. Based on parameters of B-MAC, the transmit current for data rate 19.2
kbps is 20 mA and if Eq. 1 is used, we can get scaled transmit
current of multiple rates in Table 2. Both the original Z-MAC
and Z-MAC with pre-schedule scheme transmit data at a full rate. The total energy
consumption in one round is presented and compared in Fig. 2.
||Experimental parameters in simulation
||Data rate lookup table adopted in simulation
|| Total energy consumption
The total energy consumption increases with the increase of the traffic amount.
The heavier the traffic, the higher total energy consumption. Z-MAC has already
achieved excellent energy saving, even without pre-schedule scheme which has
already been proved in (Tseng et al., 2004).
By introducing a pre-schedule scheme, total energy consumption is reduced by
eliminating unnecessary low power listening. The pre-schedule scheme works well
under relatively low traffic level. While in high traffic level, the difference
between pre-schedule and no pre-schedule becomes little. This is because the
unnecessary low power listening drops under higher traffic level.
By introducing multi-rate, a node can choose a slow rate instead of full rate to transmit data as long as the buffered data can be successfully transmitted in a round. Transmitting data at high rate will cause more energy consumption, while this multi-rate approach achieves considerable energy saving. The multi-rate scheme works well especially in high traffic scenarios.
CONCLUSION AND FUTURE WORK
In this study, a novel multi-rate local framing pre-schedule scheme based on Z-MAC is proposed to further reduce energy consumption although, Z-MAC achieved excellent energy conservation, the local framing pre-schedule scheme gracefully reduced unnecessary low power listening. The local framing pre-schedule scheme further improves energy saving. Multi-rate solution gives multiple choices in transmission because power transmission is related to the data rate in modulation scaling and transmitting data at the low rate achieves lower energy consumption; therefore, as long as a node can finish its data transmission in a round, choosing a lower rate is better than transmitting at full rate in terms of energy saving. This can achieve better performance, especially in high traffic level. In future, we plan to raise the number of parameters and metrics to switch MAC schedules. We also plan to explore further node synchronization for special node deployment cases. This will require developing cross-layer routing protocols and applications enable to utilize the MAC schedules.
We would like to thank Ang Gao for helpful discussions and insightful comments. He reviewed the draft of the paper and made further modifications that improved the quality of the study. Bin Zhou devoted herself to designing some graphs and other art works in this study. We also thank the anonymous reviewers for their insightful and valuable hints.
Buettner, M., G.V. Yee, E. Anderson and R. Han, 2006. X-MAC: A short preamble MAC protocol for duty-cycled wireless sensor networks. Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, October 31-November 3, 2006, Boulder, Colorado, USA., pp: 430-430.
Cali, F., M. Conti and E. Gregori, 2000. Dynamic tuning of the IEEE 802.11 protocol to achieve a theoretical throughput limit. IEEE/ACM Trans. Network., 8: 785-799.
CrossRef | Direct Link |
Carlson, E., C. Bettstetter, H. Karl, C. Prehofer and A. Wolisz, 2004. Distributed maintenance of resource reservation paths in multihop 802.11 networks. Proceedings of the IEEE 60th Conference on Vehicular Technology VTC2004-Fall, Sept. 26-29, Berlin, Germany, pp: 2994-2998.
Chatzigiannakis, I., A. Kinalis and S. Nikoletseas, 2005. Power conservation schemes for energy efficient data propagation in heterogeneous wireless sensor networks. Proceedings of the 38th Annual Symposium on Simulation, April 04-06, Washington, DC, USA., pp: 60-71.
Einstein, A., 1956. Investigations on the Theory of the Brownian Movement. 1st Edn., Dover Publications, USA., ISBN-10: 0486603040.
El-Hoiydi, A. and J.D. Decotignie, 2004. WiseMAC: an ultra low power MAC protocol for the downlink of infrastructure wireless sensor networks. Proceedings of the Ninth IEEE Symposium on Computers and Communications, June 28-July 01, Alexandria, Egypt, pp: 18-31.
El-Hoiydi, A., 2002. Aloha with preamble sampling for sporadic traffic in ad hoc wireless sensor networks. Proceedings of the IEEE International Conference on Communications, Volume 5, April 28-May 2, 2002, Centre Suisse Electronique et de Microtechnique SA., Neuchatel, pp: 3418-3423.
Gao, A., W. Wei and X. Xiao, 2010. Multiple hash Sub-chains: Authentication for the hierarchical sensor networks. Inform. Technol. J., 9: 740-748.
Gao, A., W. Wei, Z. Wang and Y. Wenyao, 2009. A hierarchical authentication scheme for the different radio ranges sensor networks. Proceedings of the 7th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, Aug. 29-31, Vancouver, Canada, pp: 494-501.
Jardosh, A.P., E.M. Belding-Royer, K.C. Almeroth and S. Suri, 2005. Real world environment models for mobile Ad hoc Networks. Proceedings of the IEEE Journal on Special Areas in Communications - Special Issue on Wireless Ad hoc Networks, Mar. 23, University of California at Santa Barbara, pp: 1-21.
Le Boudec, J.Y. and M. Vojnovic, 2005. Perfect simulation and stationarity of a class of mobility models. Proceedings of IEEE INFOCOM`05, Mar. 13-17, Miami - FL, USA., pp: 72-79.
Liu, S., K.W. Fan and P. Sinha, 2007. CMAC: An energy efficient MAC layer protocol using convergent packet forwarding for wireless sensor networks. Proceedings of the IEEE International Conference on Sensor and Ad Hoc Communications and Network, (SECON `07), The Ohio State University, pp: 1-10.
Mahlknecht, S. and M. Bock, 2004. CSMA-MPS: A minimum preamble sampling MAC protocol for low power wireless sensor networks. Proceedings of the IEEE International Workshop on Factory Communication Systems, September 22-24, 2004, Vienna University of Technology, Vienna, Austria, pp: 73-80.
Polastre, J., J. Hill and D. Culler, 2004. Versatile low power media access for wireless sensor networks. Proceedings of the 2nd international conference on Embedded Networked Sensor Systems, Nov. 03-05, Baltimore, MD, USA., pp: 95-107.
Rhee, I., A. Warrier, M. Aia and J. Min, 2005. Z-MAC: A hybrid MAC for wireless sensor networks. Proceedings of the 3rd International Conference on Embedded Networked Sensor Systems, Nov. 02-04, San Diego, California, USA, pp: 90-101.
Schurgers, C., O. Aberthorne and M.B. Srivastava, 2001. Modulation scaling for energy aware communication systems. Proceedings of the 2001 International Symposium on Low Power Electronics and Design, August 6-7, 2001, Huntington Beach, California, United States, pp: 96-99.
Shi, X. and G. Stromberg, 2007. SyncWUF: An ultra low-power MAC protocol for wireless sensor networks. IEEE Trans. Mobile Comput., 6: 115-125.
CrossRef | Direct Link |
Tseng, H.W., S.H. Yang, P.Y. Chuang, E.H.K. Wu and G.H. Chen, 2004. An energy consumption analytic model for a wireless sensor MAC protocol. Proceedings of the IEEE 60th Conference on Vehicular Technology, Sept. 26-29, Los Angeles, CA, USA., pp: 4533-4537.
Van Dam, T. and K. Langendoen, 2003. An adaptive energy efficient MAC protocol for wireless sensor networks. Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, Nov. 05-07, Los Angeles, California, USA., pp: 171-180.
Wei, W., S. Qi, Y. Qi, W. Wang and M. Xi, 2007. Allotropy programming paradigm for ubiquitous computing environment. Proceedings of the IEEE Computer Society International Conference on Convergence Information Technology, Nov. 21-23, IEEE Computer Society, Washington, DC, USA., pp: 514-521.
Wei, W., X. Wang, B. Zhou, A. Gao and H. Xin, 2009. Diverse-rate based dual energy aware efficiency task scheduling scheme in WSNs. Proceedings of the 1st International Symposium Computer Network Multimedia Technology, Dec. 09, Wuhan, China, pp: 580-583.
Wei, W., Y. Qi, S. Qi, D. Hou, W. Wang, M. Xi and Q. Yao, 2007. Energy efficient multi-rate based time slot pre-schedule scheme in WSNs for ubiquitous environment. Proceedings of the IEEE Computer Society Asia-Pacific Services Computing Conference, Dec. 11-14, IEEE Computer Society, Washington, DC. USA., pp: 75-80.
Wei, W., Y. Qi, W. Wang, R. Li, Y. Shi, Y. Gu and A. Chen, 2008. Variant rate based cross layer time frame scheduling in wireless sensor networks. Proceedings of the 7th Annual Wireless Telecommunications Symposium, April 24-26, IEEE Communication Society, Cal Poly Pomona, California, USA., pp: 62-68.
Wei, W., Y. Qi, X. He, W. Wang, R. Li and H. He, 2008. Improving the survivability of WSNs with biological characters based on rejuvenation technology. Proceedings of the 2008 IEEE Asia-Pacific Services Computing Conference, Dec. 9-12, IEEE Computer Society Washington, DC., USA., pp: 644-649.
Wei, Y., J. Heidemann and D. Estrin, 2002. An energy-efficient MAC protocol for wireless sensor networks. Proceedings of the IEEE Infocom, June 2002, New York, NY, USA, pp: 1567-1576.
Wong, K.J. and D. Arvind, 2006. SpeckMAC: Low-power decentra-lised MAC protocol for low data rate transmissions in specknets. Proceedings of the 2nd International Workshop on Multi-Hop Ad Hoc Network: From Theory to Reality, May 26-26, Florence, Italy, pp: 71-78.
Woo, A. and D.E. Culler, 2001. A transmission control scheme for media access in sensor networks. Proceedings of the ACM International Conference on Mobile Computing and Networking, July 2001, ACM, Rome, Italy, pp: 221-235.
Wu, T. and S. Biswas, 2005. A self-reorganizing slot allocation protocol for multi-cluster sensor networks. Proceedings of the 4th International Symposium on Information Processing in Sensor Networks, April 15, Michigan State Univ., East Lansing, MI, USA., pp: 309-316.