University of Virginia1 TMMAC: An Energy Efficient Multi- Channel MAC Protocol for Ad Hoc Networks Jingbin Zhang †, Gang Zhou †, Chengdu Huang ‡, Sang H. Son †, John A. Stankovic † † Department of Computer Science, University of Virginia ‡ Department of Computer Science, University of Illinois

University of Virginia2 Motivation  TMMAC: A TDMA based multi-channel MAC protocol using a single half duplex radio transceiver.  Why Multi-channel?  Increase the bandwidth  Most IEEE devices can switch channels dynamically.  Why a single radio transceiver?  Using multiple radio transceivers increases both the cost and energy consumption  Most IEEE devices use a single half-duplex radio transceiver  Why TDMA?  Increase the life time of the mobile devices  Improve the throughput

University of Virginia3 Contribution  Novel multi-channel MAC  Energy efficient: 74% less per packet energy  High throughput: 113% higher throughput  Supporting broadcast efficiently.  Accurate analytical model.  Dynamic ATIM window adjustment scheme.

University of Virginia4 Outline  State of the Art  TMMAC Design  Analytical Model  Dynamic ATIM Window Adjustment  Performance Evaluation  Conclusion

University of Virginia5 State of the Art (1)  Special hardware support:  Multiple radio transceivers: [Wu et al. 2000] [Raniwala et al. 2005] [Adya et al. 2004]  Busy tone: [Deng et al. 1998]  FHSS: [Tang et al. 1999] [Tyamaloukas et al. 2000]

University of Virginia6 State of the Art (2)  Single radio transceiver:  Frequency negotiation: [So et al. 2004] [Fitzek et al. 2003] [Li et al. 2003] [Jain et al. 2001]…  Random number generators: [Bahl et al. 2004]:  MMAC [So et al. 2004]  Time synchronization  Beacon interval: ATIM window + Communication window  ATIM window: Frequency negotiation  Communication window: Data transmission DCF

University of Virginia7 TMMAC Design: Overview  Similar to PSM & MMAC:  Time synchronization, Beacon interval (ATIM window + Communication window)  Different from MMAC:  Communication window is divided into time slots  Both the frequency and the time are negotiated in the ATIM window  ATIM window is dynamically adjusted

University of Virginia8 TMMAC Design: Example (1)  Assumption: Two channels; The communication window contains 5 time slots DABC Channel Usage Bitmaps (CUBs) At the start of an ATIM windowSuppose node B has two packets to be sent to node C in this beacon interval. Combined CUBs Channel Allocation Bitmaps (CABs) ATIM packet OR ATIM-ACK packetATIM-RES packet E Slot 2Rec. in channel 1 Slot 4Rec. in channel 2 Slot 2Send in channel 1 Slot 4Send in channel 2

University of Virginia9 TMMAC Design: Example (2) DABC E Slot 2Rec. in channel 1 Slot 4Rec. in channel 2 Slot 2Send in channel 1 Slot 4Send in channel 2 Suppose node E has two packets to be sent to node D in this beacon interval. ATIM packet OR Slot 2Rec. in channel 1 Slot 3Rec. in channel ATIM-ACK packet Slot 2Send in channel 1 Slot 3Send in channel 2 ATIM-RES packet CABs

University of Virginia10 TMMAC Design: Example (3) DABC E Slot 2Rec. in channel 1 Slot 4Rec. in channel 2 Slot 2Send in channel 1 Slot 4Send in channel 2 Suppose node C has one packets to broadcast to its neighbors in this beacon interval Slot 1Rec. in channel 1 Slot 3Rec. in channel 2 ATIM-BRD packet Slot 2Send in channel 1 Slot 3Send in channel CABs Slot 2Rec. in channel 1 Slot 4Rec. in channel 2 Slot 5Send in channel Slot 2Send in channel 1 Slot 4Send in channel 2 Slot 5Rec. in Channel 2 Slot 2Rec. in channel 1 Slot 3Rec. in channel 2 Slot 5Rec. in channel 2

University of Virginia11 Analytical Model  Analyze the saturation throughput of TMMAC in wireless LANs.  Built upon [Bianchi 2000], which is used to analyze the saturated throughput of  Validated through simulations in GloMoSim.

University of Virginia12 Impact of Time Synchronization Error 2% at maximum 18% to 31%

University of Virginia13 Motivation  There is no fixed optimal ATIM window size when the network is saturated.  A smaller ATIM window is preferred when the network is not saturated.  The dynamic ATIM window scheme used in PSM is not applicable. [Jung et al. 2002] Dynamic ATIM Window Adjustment

University of Virginia14 Rules for Dynamic ATIM Window Adjustment (1)  A finite set of ATIM window sizes are used: {ATIM 1, …, ATIM i, ATIM i+1, …, ATIM m } and ATIM i+1 -ATIM i =l slot  The default channel is never used for data communication in the time slots before ATIM m.  The ATIM window size for the next beacon interval is piggybacked in the ATIM control packets.  Node A wants to send the packet to node B  A knows B’s ATIM window size  A does not know B’s ATIM window size Dynamic ATIM Window Adjustment

University of Virginia15 Rules for Dynamic ATIM Window Adjustment (2)  Decide whether the network is saturated.  If the network is saturated  If the communication window is fully used  decrease the ATIM window size by one level  If not  Increase the ATIM window size by one level  If the network is not saturated, decrease the ATIM window size by one level Dynamic ATIM Window Adjustment >? Saturation threshold

University of Virginia16 Simulation Settings Number of channels3 Bit rate2Mbps Packet size512 bytes Channel switch delay80us Time synchronization error0.1ms Beacon interval100ms Network size1000m by 1000m Node number200 Application layerCBR Routing layerGF MAC layerTMMAC, MMAC, Communication Range250m Carrier sense range500m Performance Evaluation

University of Virginia17 Evaluation Metrics  Aggregated Throughput  Total throughput of all the nodes in the network  Per packet energy  The value of total energy consumed by the whole network divided by the total number of data packets successfully transmitted. Performance Evaluation

University of Virginia18 Evaluation of Dynamic ATIM Window Adjustment (1) Performance Evaluation Traffic pattern

University of Virginia19 Evaluation of Dynamic ATIM Window Adjustment (2) Performance Evaluation Traffic pattern

University of Virginia20 Performance vs. System Loads (1)  Aggregate throughput vs. packet arrival rate 113% more aggregated throughput Performance Evaluation

University of Virginia21 Performance vs. System Loads (2)  Per packet energy vs. packet arrival rate 74% less per packet energy Performance Evaluation

University of Virginia22 Performance vs. System Loads (3)  Aggregate throughput vs. packet arrival rate (6 channels) 84% more aggregated throughput Performance Evaluation

University of Virginia23 Conclusion  TMMAC exploits the advantage of both multiple channels and TDMA in an efficient way.  TMMAC achieves high communication throughput and low energy consumption.  113% higher communication throughput  74% less per packet energy

University of Virginia24 Publication  Jingbin Zhang, Gang Zhou, Sang H. Son, John A. Stankovic, Kamin Whitehouse, "Performance Analysis of Group Based Detection for Sparse Wireless Sensor Networks," in Submission.  Jingbin Zhang, Gang Zhou, Chengdu Huang, Sang H. Son, John A. Stankovic, "TMMAC: An Energy Efficient Multi-Channel MAC Protocol for Ad Hoc Networks," 2007 IEEE International Conference on Communications (IEEE ICC'07), Glasgow, Scotland,  Jingbin Zhang, Ting Yan, John A. Stankovic, Sang H. Son, "Thunder: Towards Practical, Zero Cost Acoustic Localization for Outdoor Wireless Sensor Networks," ACM SIGMOBILE Mobile Computing and Communications Review (ACM MC2R), Special Issue on Localization Technologies and Algorithms,  Jingbin Zhang, Ting Yan, Sang H. Son, "Deployment Strategies for Differentiated Detection in Wireless Sensor Networks," Third Annual IEEE International Conference on Sensor Mesh and Ad Hoc Communications and Networks (IEEE SECON'06), Reston, VA,  Shan Lin, Jingbin Zhang, Gang Zhou, Lin Gu, Tian He, John A. Stankovic, "ATPC: Adaptive Transmission Power Control for Wireless Sensor Networks," 4th ACM International Conference on Embedded Networked Sensor Systems (ACM SenSys'06), Boulder, Colorado,  Jingbin Zhang, Gang Zhou, Sang H. Son, John A. Stankovic, "Ears on the Ground: An Acoustic Streaming Service in Wireless Sensor Networks," Fifth IEEE/ACM International Conference on Information Processing in Sensor Networks (IEEE/ACM IPSN'06, Demo Abstract), Nashville, TN,  Arsalan Avatoii, Jingbin Zhang, Sang H. Son, "Group-Based Event Detection in Undersea Sensor Networks," Second International Workshop on Networked Sensing Systems (INSS'05), San Diego, California, 2005.

University of Virginia25 Questions?