Advanced Wireless Networks - 4G Technologies

810 ENERGY-EFFICIENT WIRELESS NETWORKS

a packet received from its previous hop. This is called sleep latency in SMAC, and it increases proportionally with hop length by a slope of schedule length (active period plus sleep period).

(2)A fixed duty cycle does not adapt to the varying traffic rate in sensor network. A fixed duty cycle for the highest traffic load results in significant energy wastage when traffic is low while a duty cycle for low traffic load results in low message data delivery and long queuing delay. Therefore it is desirable to adapt the duty cycle under variant traffic load.

(3)A fixed synchronous duty cycle may increase the possibility of collision. If neighboring nodes turn to active state at the same time, all may contend for the channel, making a collision very likely. There are several possibilities to reduce sleep delay and adjust duty cycle to the traffic load. Those mechanisms are either implicit, in which nodes remain active on overhearing an ongoing transmission or explicit, in which there are direct duty cycle adjusting messages. In adaptive listening, a node that overhears its neighbor’s transmission wakes up for a short period of time at the end of the transmission, so that if it is the next hop of its neighbor, it can receive the message without waiting for its scheduled active time. A node also can keep listening and potentially transmitting as long as it is in an active period. An active period ends when no activation event has occurred for a certain time. The activation time events include reception of any data, the sensing of communication on the radio, the end-of-transmission of a node’s own data packet or acknowledgement, etc.

If the number of buffered packets for an intended receiver exceeds a threshold L, the sender can signal the receiver to remain on for the next slot. A node requested to stay awake sends an acknowledgement to the sender, indicating its willingness to remain awake in the next slot. The sender can then send a packet to the receiver in the following slot. The request is renewed on a slot-by-slot basis.

However, in previous mechanisms (whether explicit or implicit), not all nodes beyond one hop away from the receiver can overhear the data communication, and therefore packet forwarding will stop after a few hops. This data forwarding interruption problem causes sleep latency for packet delivery.

DMAC employs a staggered active/sleep schedule to solve this problem and enable continuous data forwarding on the multihop path. In DMAC, data prediction is used to enable active slot request when multiple children of a node have packets to send in a same sending slot, while the more to send packet is used when nodes on the same level of the data gathering tree with different parents compete for channel access.

20.4.1 Staggered wakeup schedule

For a sensor network application with multiple sources and one sink, the data delivery paths from sources to sink are in a tree structure, a data gathering tree. Flows in the data gathering tree are unidirectional from sensor nodes to sink. There is only one destination, the sink. All nodes except the sink will forward any packets they receive to the next hop. The key insight in designing a MAC for such a tree is that it is feasible to stagger the wake-up scheme so that packets flow continuously from sensor nodes to the sink. DMAC is designed to deliver data along the data gathering tree, aiming at both energy efficiency and low latency.

REFERENCES 811

Figure 20.6 DMAC in a data gathering tree.

In DMAC, the activity schedule of nodes on the multihop path is staggered to wake up sequentially like a chain reaction. Figure 20.6 shows a data gathering tree and the staggered wake-up scheme. An interval is divided into receiving, sending and sleep periods. In receiving state, a node is expected to receive a packet and send an ACK packet back to the sender. In the sending state, a node will try to send a packet to its next hop and receive an ACK packet. In sleep state, nodes will turn off radio to save energy. The receiving and sending periods have the same length of μ, which is enough for one packet transmission and reception. Depending on its depth d in the data gathering tree, a node skews its wake-up scheme dμ ahead from the schedule of the sink. In this structure, data delivery can only be done in one direction towards the root. Intermediate nodes have a sending slot immediately after the receiving slot.

A staggered wake-up schedule has four advantages: (1) since nodes on the path wake up sequentially to forward a packet to next hop, sleep delay is eliminated if there is no packet loss due to channel error or collision; (2) a request for longer active period can be propagated all the way down to the sink, so that all nodes on the multihop path can increase their duty cycle promptly to avoid data stuck in intermediate nodes; (3) since the active periods are now separated, contention is reduced; and (4) only nodes on the multihop path need to increase their duty cycle, while the other nodes can still operate on the basic low duty cycle to save energy. The simulation results for the three different protocols are shown in Figure 20.7. DMAC demonstrates good performance. In the simulation the following parameters were used, as in Lu et al. [43]: Radio bandwidth 100 kbps, radio transmission range 250 m, radio interference range 550 m, packet length 100 bytes, transmit power 0.66 W, receive power 0.395 W and idle power 0.35 W. The sleeping power consumption is set to 0. An MTS (more to send) packet is 3 bytes long. According to the parameters of the radio and packet length, the receiving and sending slot μ is set to 10ms for DMAC and 11 ms for DMAC/MTS. The active period is set to 20 ms for SMAC with adaptive listening. All schemes have the basic duty cycle of 10 %. This means a sleep period of 180 ms for DMAC and SMAC, 198 ms for DMAC/MTS.

REFERENCES 813

[4]J.-C. Cano and D. Kim, Investigating performance of power-aware routing protocols for mobile ad-hoc networks, in International Mobility and Wireless Access Workshop, MobiWac 2002, 12 October 2002, pp. 80–86.

[5]C.-K. Toh, Maximum battery life routing to support ubiquitous mobile computing in

wireless ad hoc networks, IEEE Commun. Mag., vol. 39, no. 6, 2001, pp. 138– 147.

[6]J.-H. Chang and L. Tassiulas, Maximum lifetime routing in wireless sensor networks, IEEE/ACM Trans. Networking, vol. 12, no. 4, 2004, pp. 609–619.

[7]M. Tarique, K.E. Tepe and M. Naserian, Energy saving dynamic source routing for ad hoc wireless networks, in Third Int. Symp. Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WIOPT 2005, 4–6 April 2005, pp. 305–310.

[8]J. Gomez, A.T. Campbell, M. Naghshineh and C. Bisdikian, Power-aware routing in wireless packet networks, in IEEE Int. Workshop on Mobile Multimedia Communications (MoMuC ’99), 15–17 November 1999, pp. 380–383.

[9]Y. Xue and B. Li, A location-aided power-aware routing protocol in mobile ad hoc networks, in IEEE Global Telecommun. Conf., GLOBECOM ’01, vol. 5, 25–29 November 2001, pp. 2837–2841.

[10]A. Avudainayagam, Y. Fang and W. Lou, DEAR: a device and energy aware routing protocol for mobile ad hoc networks, in Proc. MILCOM 2002, vol. 1, 7–10 October 2002, pp. 483–488.

[11]R. Ranjan and A. Saad, Generic architecture for power aware routing in wireless sensor networks, 29th Annual IEEE Int. Conf. Local Computer Networks, 16–18 November 2004, pp. 575–576.

[12]B. Zhang and H.T. Mouftah, Localized power-aware routing for wireless ad hoc networks, in IEEE Int. Conf. Communications, vol. 6, 20–24 June 2004, pp. 3754– 3758.

[13]J. Shen and J. Harms, Position-based routing with a power-aware weighted forwarding function in MANETs, in IEEE Int. Conf. Performance, Computing, and Communications, 2004, pp. 347–355.

[14]A. Safwat, H. Hassanein and H. Moufta, A MAC-based performance study of energyaware routing schemes in wireless ad hoc networks, in IEEE Global Telecommunications Conf., GLOBECOM ’02. vol. 1, 17–21 November 2002, pp. 47–51.

[15]L. De Nardis, G. Giancola and M.-G. Di Benedetto, A position based routing strategy for UWB networks, in IEEE Conf. Ultra Wideband Systems and Technologies, 16–19 November 2003, pp. 200–204.

[16]J. Nie and Z. Zhou, An energy based power-aware routing protocol in ad hoc networks,

IEEE Int. Symp. Communications and Information Technology, ISCIT, vol. 1, 26–29 October 2004, pp. 280–285.

[17]J.-P. Sheu, C.-W. Lai and C.-M. Chao, Power-aware routing for energy conserving and balance in ad hoc networks, in IEEE Int. Conf. Networking, Sensing and Control, vol. 1, 21–23 March 2004, pp. 468–473.

[18]S.-H. Lee, E. Choi and D.-H. Cho, Timer-based broadcasting for power-aware routing in power-controlled wireless ad hoc networks, IEEE Commun. Lett., vol. 9, no. 3, 2005, pp. 222–224.

[19]A. Helmy, Contact-extended zone-based transactions routing for energy-constrained wireless ad hoc networks, IEEE Trans. Vehicular Technol., vol. 54, no. 1, 2005, pp. 307–319.

814 ENERGY-EFFICIENT WIRELESS NETWORKS

[20]M. Maleki, K. Dantu and M. Pedram, Power-aware source routing protocol for mobile ad hoc networks, in Proc. Int. Symp. Low Power Electronics and Design, ISLPED ’02, 2002, pp. 72–75.

[21]R.K. Guha, C.A. Gunter and S. Sarkar, Fair coalitions for power-aware routing in wireless networks, 43rd IEEE Conf. Decision and Control, CDC, vol. 3, 14–17 December 2004, pp. 3271–3276.

[22]L. De Nardis, G. Giancola and M.-G. Di Benedetto, Power-aware design of MAC and routing for UWB networks, in IEEE Global Telecommunications Conf. Workshops, 29 November to 3 December 2004, pp. 235–239.

[23]Q. Li, J. Aslam and D. Rus, Distributed energy-conserving routing protocols, in Proc. 36th Annual Hawaii Int. Conf. System Sciences, 6–9 January 2003, p. 10.

[24]J. Gomez, A.T. Campbell, M. Naghshineh and C. Bisdikian, Conserving transmission power in wireless ad hoc networks, in Ninth Int. Conf. Network Protocols, 11– 14 November 2001, pp. 24–34.

[25]J.-E. Garcia, A. Kallel, K. Kyamakya, K. Jobmann, J.C. Cano and P. Manzoni, A novel DSR-based energy-efficient routing algorithm for mobile ad-hoc networks, IEEE Vehicular Technol. Conf., VTC 2003, vol. 5, 6–9 October, pp. 2849–2854.

[26]N. Gemelli, P. LaMonica, P. Petzke and J. Spina, Capabilities aware routing for dynamic ad hoc networks, Int. Conf. Integration of Knowledge Intensive Multi-Agent Systems, 30 September to 4 October 2003, pp. 585–590.

[27]M. Krunz, A. Muqattash and S.-J. Lee, Transmission power control in wireless ad hoc networks: challenges, solutions and open issues, IEEE Networks, vol. 18, no. 5, 2004, pp. 8–14.

[28]J. Schiller, A. Liers, H. Ritter, R. Winter and T. Voigt, ScatterWeb – low power sensor nodes and energy aware routing, in Proc. 38th Annual Hawaii Int. Conf. System Sciences, 3–6 January 2005, p. 286c.

[29]B. Zhang and H. Mouftah, Adaptive energy-aware routing protocols for wireless ad hoc networks, in First Int. Conf. Quality of Service in Heterogeneous Wired/Wireless Networks, QSHINE, 18–20 October 2004, pp. 252–259.

[30]Y. Zhou, D.I. Laurenson and S. McLaughlin, High survival probability routing in

power-aware mobile ad hoc networks, Electron. Lett., vol. 40, no. 22, 2004, pp. 1424–1426.

[31]S. Agarwal, A. Ahuja, J.P. Singh and R. Shorey, Route-lifetime assessment based routing (RABR) protocol for mobile ad-hoc networks, in IEEE Int. Conf. Commun., ICC, vol. 3, 18–22 June 2000, pp. 1697–1701.

[32]A. Safwat, H. Hassanein and H. Mouftah, Power-aware fair infrastructure formation for wireless mobile ad hoc communications, in IEEE Global Telecommun. Conf., GLOBECOM ’01, vol. 5, 25–29 November 2001, pp. 2832–2836.

[33]S. Guo and O. Yang, An optimal TDMA-based MAC scheduling for the minimum energy multicast in wireless ad hoc networks, IEEE Int. Conf. Mobile Ad-hoc and Sensor Systems, 25–27 October 2004, pp. 552–554.

[34]K. Wang, Y.-L. Xu, G.-L. Chen and Y.-F. Wu, Power-aware on-demand routing protocol for MANET, in Proc. 24th Int. Conf. Distributed Computing Systems Workshops, 23– 24 March 2004, pp. 723–728.

[35]R. Min and A. Chandrakasan, A framework for energy-scalable communication in high-density wireless networks, in Proc. Int. Symp. Low Power Electronics and Design, ISLPED ’02, 2002, pp. 36–41.

REFERENCES 815

[36]D. Shin and J. Kim, Power-aware communication optimization for networks-on-chips with voltage scalable links, in Int. Conf. Hardware/Software Codesign and System Synthesis, CODES + ISSS, 8–10 September 2004, pp. 170–175.

[37]L. Hughes and Y. Zhang, Self-limiting, adaptive protocols for controlled flooding in ad hoc networks, in Proc. Second Annual Conf. Communication Networks and Services Research, 19–21 May 2004, pp. 33–38.

[38]Y. Liu and P.X. Liu, A two-hop energy-efficient mesh protocol for wireless sensor networks, in Proc. of IEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS 2004), vol. 2, 28 September to 2 October 2004, pp. 1786–1791.

[39]A. Safwat, H. Hassanein and H. Mouftah, Energy-efficient infrastructure formation in MANETs, in Proc. IEEE Conf. Local Computer Networks, 14–16 November 2001, pp. 542–549.

[40]G. Dimitroulakos, A. Milidonis, M.D. Galaris, G. Theodoridis, C.E. Gontis and F. Catthoor, Power aware data type refinement on the HIPERLAN/2, in IEEE Int. Conf. Electronics, Circuits and Systems, ICECS, vol. 1, 14–17 December 2003, pp. 216–219.

[41]S. Jayashree, B.S. Manoj and C.S.R. Murthy, Next step in MAC evolution: battery awareness?, in IEEE Global Telecommunications Conf., GLOBECOM ’04, vol. 5, 29 November to 3 December 2004, pp. 2786–2790.

[42]L. Zhao, X. Hong and Q. Liang, Energy-efficient self-organization for wireless sensor networks: a fully distributed approach, in IEEE Global Telecommunications Conf., GLOBECOM ’04, vol. 5, 29 November to 3 December 2004, pp. 2728–2732.

[43]G. Lu, B. Krishnamachari and C.S. Raghavendra, An adaptive energy-efficient and low-latency MAC for data gathering in wireless sensor networks, in Proc. Int. Parallel and Distributed Processing Symp., 26–30 April 2004, p. 224.