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1 MOBMAC - An Energy Efficient and low latency MAC for Mobile Wireless Sensor Networks Proceedings of the 2005 Systems Communications (ICW ’ 05)
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2 Introduction (1/3) As it is reported in [6] and based on our literature search, we have not found any other MAC protocols to support mobility except the MS-MAC [6] MS-MAC proposes an improvement to SMAC to create more suitable MAC for mobile scenarios However, MS-MAC fails to address the problem of frame loses resulting from the communication signal experiencing mobility induced effects such as Doppler Shifts
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3 Introduction (2/3) These frame losses result in a large number of retransmissions Minimizing these retransmissions will improve the energy efficiency of the system
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4 Introduction (3/3) NS2 fails to consider bit errors due to low SNR and the Doppler shifts This results in a high Packet Reception Rate (PRR), which is contradictory to the characteristics of real world wireless systems In conditions where the transmitting nodes or the receiving nodes are mobile, the communication signal experiences a Doppler Shift This Doppler Shift causes the signal to undergo frequency distortion and results in bit errors
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5 MOBMAC (1/2) uses an adaptive frame size predictor uses an Extended Kalman Filter as detailed in [8][9] to predict an optimal frame size for each transmission A smaller frame size is predicted when the signal characteristics are poor (i.e. when the signal is Doppler shifted) and larger frame sizes are predicted when the quality of the channel improves (i.e. when the nodes are stationary)
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6 MOBMAC (2/2) By transmitting a small frame size in a bad channel, there are two advantages: (1) smaller frames need lower transmission power compared to larger frames so their loss is less costly (2) the probability of occurrence of error in a smaller frame is less than that of a large frame Nevertheless, this leads to reduced bandwidth, which is undesirable for time critical applications. Thus, the system must be capable of adaptively varying the frame size based on the signal characteristics
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7 Physical layer modifications in NS2 (1/5) The current implementation in ns-2 does not consider the Signal to Noise ratio (SNR) and relative velocity between the communicating nodes while processing the incoming frame takes into consideration of the SNR and the relative velocity between communicating nodes in order to arrive at a bit error rate We have modeled the physical layer characteristics based on the mica-2 sensors [10]
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8 Physical layer modifications in NS2 (2/5) The Doppler shift, which is one of the parameters in the simulation, is calculated using the radio frequency and the relative velocity as The system is simulated using Matlab [12] based on the mica-2 parameters This yields the BER of the system at different SNR and various relative velocities
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9 Physical layer modifications in NS2 (3/5) calculates the receiver strength based on the two-ray ground propagation model double Pr = Pr_TwoRay(&txinfo, &rxinfo, this); The SNR (in dB) of the signal is calculated from the received signal double Pr_dB=10 0*log10(Pr); double SNR=Pr_dB-m_nNoiseFloor; Where the noise floor “ m_nNoiseFloor ” can be set from the script file ===> bind("noisefloor_", &m_nNoiseFloor);
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10 Physical layer modifications in NS2 (4/5) Then the relative velocity between the nodes is calculated by using the position of communicating nodes and their speed The SNR and relative velocity are fed as arguments in to a lookup function to obtain the BER of that signal double BER=m_oDataMatrix Lookup(SNR,RelSpeed);
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11 Physical layer modifications in NS2 (5/5) This BER is used in the calculation of the Packet Error Rate (PER) The Probability of error free reception of the frame as given in [13] when using Manchester coding is f equals the length of the frame and l is the length of the preamble The probability of erroneous frame is
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12 Simulation Result (1/3) It shows more energy consumption in conditions where the signal undergoes Doppler shift or has a low SNR due to frame losses
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13 Simulation Result (2/3) In mobile scenarios, MOBMAC improves energy efficiency and reduces latency when compared to the SMAC
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14 Simulation Result (3/3)
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