Critique #2 Ø M. Sha, G. Hackmann and C. Lu, Real-world Empirical Studies on Multi- Channel Reliability and Spectrum Usage for Home-Area Sensor Networks, IEEE Transactions on Network and Service Management, 10(1): 56-69, March 2013. Ø Due on 2/13 (Tuesday) 1
Characterizing Wireless in Homes Chenyang Lu Cyber-Physical Systems Laboratory
Home Area Network Ø Smart energy: meters, thermostats, home appliances Ø Smart health: collect vital signs, measure sleep, detecting falls Ø Need reliable and power-efficient Home Area Networks (HANs) 3
Wireless Home Area Networks Ø Advantages q Do not require wired infrastructure. q Easily and inexpensively retrofit existing homes. q Energy efficiency Ø Reliability challenges q Unpredictable environment q Crowded 2.4 GHz ISM band 4
Channels in the 2.4 GHz ISM Band 5
Empirical Studies in Homes Ø 2.4Hz spectrum study of existing wireless signals Ø IEEE 802.15.4 link reliability in all 16 channels 6
Spectrum Usage Traces Ø Collected from the 2.4 GHz spectrum in six apartments and an office 7
Methodology Ø Spectrum usage between 2.400 GHz and 2.495 GHz Ø Wi-Spy 2.4x spectrum analyzer q Sweep across the 2.4 GHz spectrum q Sampling period: 40 ms q Signal strength reading on each of 254 discrete frequencies Ø Traces over 7 days in 6 apartments and Bryan Hall q Normal daily activities q 15,120,000 readings for each of the 254 frequencies q 2.5 GB of data per location Ø Signal strength readings à binary values based on a threshold q 0: idle channel; 1: busy channel. 8
Questions 1. Is there a channel free in all apartments? 2. Does spectrum usage change over time? 3. Do homes have similar spectrum usage patterns as offices? 4. Is 802.11 the dominant interferer in homes? 9
Is there a channel free in all homes? Ø No, due to diverse spectrum usage patterns in homes Channel Occupancy Rate 10
Does spectrum usage change? Daily standard deviation Hourly standard deviation Spectrum occupancy exhibits considerable variability over time. 5-minute standard deviation 11
Is Wi-Fi the dominant interferer? 12
Is Wi-Fi dominating the spectrum? 13
Is Wi-Fi dominating the spectrum? Ø While Wi-Fi is a major source of interference, others can be non-negligible contributors to spectrum occupancy. 14
Empirical Studies in Homes Ø 2.4GHz spectrum study of existing wireless signals Ø IEEE 802.15.4 link reliability in all 16 channels 15
Methodology Ø Platform q Tmote Sky and TelosB motes q IEEE 802.15.4 compliant Chipcon CC2420 radio q 16 channels (11-26) in 5 MHz steps q TinyOS 2.1 using default CSMA/CA MAC layer Ø Packet Reception Rate (PRR) of all 802.15.4 channels q 10 apartments, 24 hours per apartment q A node broadcast 100 packets per channel to multiple receivers, cycling through all 16 channels in 5 minutes q Receivers recorded the PRRs in onboard Flash 16
Questions 1. Is there a persistently reliable channel? 2. If a good channel cannot be found, are retransmissions sufficient to deal with packet loss? 3. If no single channel is reliable, can we exploit channel diversity to achieve reliability? 4. Do channel conditions exhibit cyclic behavior over time? 5. Is reliability strongly correlated among different channels? 17
Is there a persistently reliable channel? Ø Link reliability varies among apartments and links. Different apartments Different links within a same apartment 18
Is there a persistently reliable channel? Ø No, because of temporal variability. Lowest PRR observed on each link s most reliable channel 19
Is retransmission sufficient? Ø No, due to burstiness of transmission failures. 20
Is channel hopping effective? Ø Yes! 21
How often needs a link switch channel? Ø Only a small number of channel hops per day. Number of channel hops required under an optimal schedule (one link selected randomly per apartment) 22
Can hopping be scheduled statically? Ø Channel conditions are not cyclic à channel-hopping decisions must be made dynamically. Pearson product-moment correlation coefficient 23
How should new channels be selected? Ø Reliability is correlated among adjacent channels. Ø A link should hop far away from a failing channel. Conditional probability of channel failure Correlation of channel reliability 24
Spectrum Analysis: Observations 1. There is no common idle channel across different homes. 2. Spectrum occupancy in homes exhibits variability over time, whether looking at timescales of days, hours, or minutes.. 3. While Wi-Fi is a major source of interference in homes, other interferers cannot be ignored. 25
802.15.4 Link Study: Observations 1. Link reliability varies greatly from channel to channel. 2. There is not always a single persistently reliable channel. 3. Retransmissions are insufficient due to bursty transmission failures. 4. Channel hopping can improve long-term link reliability. q Only a few channel hops per day can maintain reliable links. q Channel conditions are not cyclic à channel-hopping decisions must be made dynamically. q Reliability is correlated across adjacent channels à a link should move far away from a failing channel. 26
ARCH: Adaptive and Robust Channel Hopping Ø Receiver-oriented protocol q Insight: links have different channel conditions within a home. q Different receivers may have different channels. Ø Monitor channel condition q Maintain a sliding window of ETX values of incoming links q Mark channel unreliable if ETX values exceed threshold Ø Select a new channel q Insight: strong correlation of link failures in adjacent channels. q Probabilistically chooses a new channel q The further away a channel is from the current channel, the more likely it will be chosen. Ø Upon selecting a new channel, nodes notify neighbors of this change. Neighbors update their neighbor tables. 27
Paper Ø M. Sha, G. Hackmann and C. Lu, Real-world Empirical Studies on Multi-Channel Reliability and Spectrum Usage for Home-Area Sensor Networks, IEEE Transactions on Network and Service Management, 10(1): 56-69, March 2013. Ø M. Sha, G. Hackmann and C. Lu, ARCH: Practical Channel Hopping for Reliable Home-Area Sensor Networks, IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'11), April 2011. 28