Adaptive Protocols for Nano-scale Sensor Networksover Composition Varying Channels

Eisa ZarepourSchool of Computer Science and Engineering

University of New South Wales, Sydney, Australia. Email: ezarepour@cse.unsw.edu.au

Abstract—The terahertz band is an unlicensed frequency rangethat is expected to be exploited in the near future for differenttypes of communications, including wireless communication inNano-scale Sensor Networks (NSNs). However, as terahertz bandis the resonance frequency of many molecules, communicationin this band is severely affected by molecular absorption noiseand attenuation. Molecular absorption is highly sensitive to thechannel conditions such as composition of the medium and alsocommunication frequency. In many applications of NSNs such asmonitoring the chemical synthesis and health monitoring systems,the composition of the medium is dynamic over time that leadsto dynamic molecular absorption noise and attenuation. In thiswork, in order to provide high reliable communication for NSNs,we briefly overview different adaptive approaches to overcomethe problem of dynamic molecular absorption in compositionvarying channels.

I. INTRODUCTION

Wireless Nano-scale Sensor Networks (NSNs) [1] introducethe possibility to sense and control physical and chemicalprocesses at the molecule level. The progress trends in NSNssuggests that such bottom-up approach to sense and control,which has not been possible with conventional wireless sensornetworks, has the potential to radically enhance the perfor-mance of many critical applications in medical, industrial,biological [1] and chemical fields [2], [3].

In [2], [4], we have shown how a NSN could be deployedinside a chemical reactor for a bottom-up control of thesynthesis with the ultimate goal of improving the performanceof the reactor. Chemical reactors are built to produce somehigh-value products, but they also generate some low-valuematerials. The performance of a reactor is measured by itsselectivity, which refers to the percentage of high-value prod-ucts in the overall output [5]. By monitoring a reactor at themolecular level and turning off elementary reactions leadingto undesired molecular species, a NSN’s enabled catalyst canpotentially achieve very high selectivity [2], [4].

In most of NSN’s applications, reliability is of great impor-tance to accomplish associated tasks [1], [3]. For example, in[3] we found that the packet loss in the NSN reduces its abilityto monitor and control chemical reactions, which ultimatelyreduces selectivity that has been presented in the Fig 1.a.

Nano-antennas operate on terahertz band that is rangingfrom 0.1 to 10 THz [6]. As terahertz band is the resonance fre-quency of molecules, communication in this band is stronglyaffected by molecular absorption noise and attenuation [6].Molecular absorption is highly sensitive to the composition

of the presented molecules in the channel, temperature andpressure of the medium and also communication frequency.In some environments such as chemical reactors and humanbody cells that NSNs are supposed to be used, these parameterscould be dynamic over time. We call this type of mediums asComposition Varying (CV) channels. In CV mediums, as themolecular absorption noise and attenuation are dynamic overtime, providing a reliable communication is more challenging.In this work, we overview our two approaches to overcomehighly dynamic molecular absorption to establish high reliablecommunication in CV channels. In Section II, an adaptivepower allocation schema for NSNs will be presented. In theSection III, we will briefly discussed the idea of frequencyhopping following by conclusion in Section IV.

II. AN ADAPTIVE POWER ALLOCATION SCHEMA

In CV channels, if the nano-sensor choose a very high powerso that they can overcome the worst possible absorption, thishigh power creates a high interference when the channel isgood. Similarly, the nano-sensor cannot choose a low powerthat is only suitable for good channel condition becausethe nano-sensor will not be able to communicate when thechannel is bad. For autonomous NSNs, which are powered bylimited-capacity nano-batteries or limited-throughput energy-harvesting circuits [1], a better strategy is to adjust the powerover time to maximize the selectivity with a minimal amountof power consumption. In [7], we investigate a NSNs that is

Figure 1. a) Overall selectivity as a function of packet lost probability p. b) Theselectivity achieved by different power allocation policies for a given power budget.

used to improve the selectivity of Fischer-Tropsch Synthesis(FTS) [5] and show that the optimal power allocation strategycan be obtained by formulating the problem as a MarkovDecision Process (MDP). However, the MDP solution requires

the nano-sensors to know the chemical composition of thereactor at any given time, which is not practical. We, therefore,propose an alternative for the nano-sensors to adjust power fol-lowing a rule or heuristic computed offline. We have proposedthree local policies that has been obtained based on the channelapproximation via extensive simulations. By simulating theprocess details, we demonstrate that the proposed heuristicsperform well relative to MDP optimization.

Fig 1.b shows the power-selectivity tradeoff for the constantpower allocation, MDP and the three local policies compareto average selectivity for the uncontrolled FTS. The figureshows that all the five power allocation schemes achieve betterselectivity than the uncontrolled FTS. As expected, the optimalsolution gives the highest selectivity for a given power budgetand outperforms all the other schemes.

III. FREQUENCY HOPING

Different molecules resonate and absorb terahertz at dif-ferent frequency sub-bands. Therefore, for a given speciescomposition in the wireless channel, some sub-channels areaffected less severely than others. It means in CV mediums,a sub-channel which has low noise at one time may becomevery noisy at another time, and vice versa. Fig 2.a plots themolecular absorption coefficient during a FTS for differentfrequencies, as an heat map where the areas with high mediumabsorption coefficient are shown as “hot”. The “hot” areascorrespond to time-frequency regions where the medium hashigh absorption coefficient and communication between nodesin the NSN will be difficult. The figure shows that differentfrequency regions become “hot” at different times.

In [8], we propose frequency hopping as a means to over-come the problem of time-varying noise and attenuation in CVchannels. We formulate the sub-channel selection problem atany given time as an MDP, which allows us not only to opti-mize the communication performance over the entire reactionprocess, but also to control the rate of channel switching byimposing different penalties for hopping because constrainedNSN’s nodes may not be able to switch frequencies rapidly.We show that, compared to conventional non-hopping channelselection, the proposed frequency hopping can significantlyimprove Signal-To-Noise (SNR), capacity and Bit Error Rate(BER) in CV mediums. We propose practically realizableoffline policies that obviate the need for observing the channelstates, yet perform close to the MDP-based optimal solutions.

Fig 2.b shows the SNR that can be obtained via differentchannel selection policies for a power budget of 1 pW and adistance of 1m between the transmitter and the receiver for dif-ferent number of available sub-channels ranging from 2 to 50.As expected, with increasing number of sub-channels, the SNRincreases irrespective of the policy, because the total poweris distributed over a smaller range of frequencies boostingthe signal power. The most important result is that the MDP,improves SNR by around 10dB and 20dB in comparison withBest Channel and Random policy, respectively, irrespective ofthe number of sub channels.

Figure 2. a) Frequency-time variation of molecular absorption coefficient for a FTSchannel b)Achievable SNR via different policies versus number of sub-channels

IV. CONCLUSION

In order to provide high reliable nano-scale communicationin composition varying channels, two approaches have beeninvestigated to overcome the problem of dynamic molecu-lar absorption. First, an optimized adaptive power allocationschema has been proposed. Second, frequency hopping hasbeen utilized as a means to switch between appropriate sub-channels based on composition prediction of the channel at anygiven time slot. The problem has been modelled as an MDPand several heuristics have been developed to approximateoptimal polices.

A more fundamental way to address the dynamic molecularabsorption would be to develop new propagation models thatwould consider the composition as a stochastic variable in themodel that is a worth investigating as a future work.

V. ACKNOWLEDGMENTI would like to thank my supervisor, Professor Mahbub

Hassan and my co-supervisor, Associate Professor Chun TungChou, for their insightful supervisions and supports. I alsothank to Professor Adesoji A. Adesina for his great helps.

REFERENCES

[1] I. F. Akyildiz and J. M. Jornet, “Electromagnetic wireless nanosensornetworks,” Nano Communication Networks, vol. 1, no. 1, pp. 3–19, 2010.

[2] E. Zarepour, A. A. Adesina, M. Hassan, and C. T. Chou, “Nano SensorNetworks for Tailored Operation of Highly Efficient Gas-To-Liquid FuelsCatalysts,” in the proceedings of Australasian Chemical EngineeringConference, Chemeca 2013, Brisbane, Australia, October. 2013.

[3] E. Zarepour, M. Hassan, C. T. Chou, and A. A. Adesina, “Nano-scaleSensor Networks for Chemical Catalysis,” in the proceedings of the 13thIEEE International Conference on Nanotechnology, Beijing, China, 2013.

[4] E. Zarepour, A. A. Adesina, M. Hassan, and C. T. Chou, “An innova-tive approach to improving gas-to-liquid fuels catalysis via nano-sensornetwork modulation,” Industrial & Engineering Chemistry Research, pp.1–37, Mar. 2014.

[5] A. Adesina, “Hydrocarbon synthesis via Fischer-Tropsch reaction: travailsand triumphs,” Applied Catalysis A: General, vol. 138, no. 2, pp. 345–367, May 1996.

[6] J. Jornet and I. Akyildiz, “Channel modeling and capacity analysisfor electromagnetic wireless nanonetworks in the terahertz band,” IEEETransactions on Wireless Communications, vol. 10, no. 10, pp. 3211–3221, 2011.

[7] E. Zarepour, M. Hassan, C. T. Chou, and A. A. Adesina, “PowerOptimization in Nano Sensor Networks for Chemical Reactors,” in theproceedings of ACM International Conference on Nanoscale Computingand Communication, Atlanta, Georgia, USA, 2014.

[8] E. Zarepour, M. Hassan, C. T. Chou, and A. Adesina, “FrequencyHopping Strategies for Improving Terahertz Sensor Network Performanceover Composition Varying Channels,” in The IEEE International Sympo-sium on a World of Wireless, Mobile and Multimedia Networks, WoWMoM2014, Sydney, Australia, June, 2014.