Adaptive Duty Cycling MAC Protocols Using Closed-Loop Control for Wireless Sensor Networks

The fundamental design goal of wireless sensor MAC protocols is to minimize unnecessary power consumption of the sensor nodes, because of its stringent resource constraints and ultra-power limitation. In existing MAC protocols in wireless sensor networks (WSNs), duty cycling, in which each node periodically cycles between the active and sleep states, has been introduced to reduce unnecessary energy consumption. Existing MAC schemes, however, use a fixed duty cycling regardless of multi-hop communication and traffic fluctuations. On the other hand, there is a tradeoff between energy efficiency and delay caused by duty cycling mechanism in multi-hop communication and existing MAC approaches only tend to improve energy efficiency with sacrificing data delivery delay. In this paper, we propose two different MAC schemes (ADS-MAC and ELA-MAC) using closed-loop control in order to achieve both energy savings and minimal delay in wireless sensor networks. The two proposed MAC schemes, which are synchronous and asynchronous approaches, respectively, utilize an adaptive timer and a successive preload frame with closed-loop control for adaptive duty cycling. As a result, the analysis and the simulation results show that our schemes outperform existing schemes in terms of energy efficiency and delivery delay

Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks

[EN] In underwater acoustic modem design, pure asynchrony can contribute to improved wake-up coordination, thus avoiding energy-inefficient synchronization mechanisms. Nodes are designed with a pre-receptor and an acoustically adapted Radio Frequency Identification system, which wakes up the node when it receives an external tone. The facts that no synchronism protocol is necessary and that the time between waking up and packet reception is narrow make pure asynchronism highly efficient for energy saving. However, handshaking in the Medium Control Access layer must be adapted to maintain the premise of pure asynchronism. This paper explores different models to carry out this type of adaptation, comparing them via simulation in ns-3. Moreover, because energy saving is highly important to data gathering driven by underwater vehicles, where nodes can spend long periods without connection, this paper is focused on multi-hop topologies. When a vehicle appears in a 3D scenario, it is expected to gather as much information as possible in the minimum amount of time. Vehicle appearance is the event that triggers the gathering process, not only from the nearest nodes but from every node in the 3D volume. Therefore, this paper assumes, as a requirement, a topology of at least three hops. The results show that classic handshaking will perform better than tone reservation because hidden nodes annulate the positive effect of channel reservation. However, in highly dense networks, a combination model with polling will shorten the gathering time.Blanc Clavero, S. (2020). Event-Driven Data Gathering in Pure Asynchronous Multi-Hop Underwater Acoustic Sensor Networks. Sensors. 20(5):1-16. https://doi.org/10.3390/s20051407S116205Roy, A., & Sarma, N. (2018). Effects of Various Factors on Performance of MAC Protocols for Underwater Wireless Sensor Networks. Materials Today: Proceedings, 5(1), 2263-2274. doi:10.1016/j.matpr.2017.09.228Awan, K. M., Shah, P. A., Iqbal, K., Gillani, S., Ahmad, W., & Nam, Y. (2019). Underwater Wireless Sensor Networks: A Review of Recent Issues and Challenges. Wireless Communications and Mobile Computing, 2019, 1-20. doi:10.1155/2019/6470359Rudnick, D. L., Davis, R. E., Eriksen, C. C., Fratantoni, D. M., & Perry, M. J. (2004). Underwater Gliders for Ocean Research. Marine Technology Society Journal, 38(2), 73-84. doi:10.4031/002533204787522703Petritoli, E., & Leccese, F. (2018). High Accuracy Attitude and Navigation System for an Autonomous Underwater Vehicle (AUV). ACTA IMEKO, 7(2), 3. doi:10.21014/acta_imeko.v7i2.535Nam, H. (2018). Data-Gathering Protocol-Based AUV Path-Planning for Long-Duration Cooperation in Underwater Acoustic Sensor Networks. IEEE Sensors Journal, 18(21), 8902-8912. doi:10.1109/jsen.2018.2866837Sun, J., Hu, F., Jin, W., Wang, J., Wang, X., Luo, Y., … Zhang, A. (2020). Model-Aided Localization and Navigation for Underwater Gliders Using Single-Beacon Travel-Time Differences. Sensors, 20(3), 893. doi:10.3390/s20030893Wahid, A., Lee, S., Kim, D., & Lim, K.-S. (2014). MRP: A Localization-Free Multi-Layered Routing Protocol for Underwater Wireless Sensor Networks. Wireless Personal Communications, 77(4), 2997-3012. doi:10.1007/s11277-014-1690-6Sánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2012). An Ultra-Low Power and Flexible Acoustic Modem Design to Develop Energy-Efficient Underwater Sensor Networks. Sensors, 12(6), 6837-6856. doi:10.3390/s120606837Li, S., Qu, W., Liu, C., Qiu, T., & Zhao, Z. (2019). Survey on high reliability wireless communication for underwater sensor networks. Journal of Network and Computer Applications, 148, 102446. doi:10.1016/j.jnca.2019.102446Jiang, S. (2018). State-of-the-Art Medium Access Control (MAC) Protocols for Underwater Acoustic Networks: A Survey Based on a MAC Reference Model. IEEE Communications Surveys & Tutorials, 20(1), 96-131. doi:10.1109/comst.2017.2768802Chirdchoo, N., Soh, W., & Chua, K. C. (2008). RIPT: A Receiver-Initiated Reservation-Based Protocol for Underwater Acoustic Networks. IEEE Journal on Selected Areas in Communications, 26(9), 1744-1753. doi:10.1109/jsac.2008.081213Zenia, N. Z., Aseeri, M., Ahmed, M. R., Chowdhury, Z. I., & Shamim Kaiser, M. (2016). Energy-efficiency and reliability in MAC and routing protocols for underwater wireless sensor network: A survey. Journal of Network and Computer Applications, 71, 72-85. doi:10.1016/j.jnca.2016.06.005Khasawneh, A., Latiff, M. S. B. A., Kaiwartya, O., & Chizari, H. (2017). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks, 24(6), 2061-2075. doi:10.1007/s11276-017-1461-xSánchez, A., Blanc, S., Yuste, P., Perles, A., & Serrano, J. J. (2015). An Acoustic Modem Featuring a Multi-Receiver and Ultra-Low Power. Circuits and Systems, 06(01), 1-12. doi:10.4236/cs.2015.6100

Comparison of CSMA based MAC protocols of wireless sensor networks

Energy conservation has been an important area of interest in Wireless Sensor networks (WSNs). Medium Access Control (MAC) protocols play an important role in energy conservation. In this paper, we describe CSMA based MAC protocols for WSN and analyze the simulation results of these protocols. We implemented S-MAC, T-MAC, B-MAC, B-MAC+, X-MAC, DMAC and Wise-MAC in TOSSIM, a simulator which unlike other simulators simulates the same code running on real hardware. Previous surveys mainly focused on the classification of MAC protocols according to the techniques being used or problem dealt with and presented a theoretical evaluation of protocols. This paper presents the comparative study of CSMA based protocols for WSNs, showing which MAC protocol is suitable in a particular environment and supports the arguments with the simulation results. The comparative study can be used to find the best suited MAC protocol for wireless sensor networks in different environments.Comment: International Journal of AdHoc Network Systems, Volume 2, Number 2, April 201

The ContikiMAC Radio Duty Cycling Protocol

Low-power wireless devices must keep their radio transceivers off as much as possible to reach a low power consumption, but must wake up often enough to be able to receive communication from their neighbors. This report describes the ContikiMAC radio duty cycling mechanism, the default radio duty cycling mechanism in Contiki 2.5, which uses a power efficient wake-up mechanism with a set of timing constraints to allow device to keep their transceivers off. With ContikiMAC, nodes can participate in network communication yet keep their radios turned off for roughly 99% of the time. This report describes the ContikiMAC mechanism, measures the energy consumption of individual ContikiMAC operations, and evaluates the efficiency of the fast sleep and phase-lock optimizations

A Study of Medium Access Control Protocols for Wireless Body Area Networks

The seamless integration of low-power, miniaturised, invasive/non-invasive lightweight sensor nodes have contributed to the development of a proactive and unobtrusive Wireless Body Area Network (WBAN). A WBAN provides long-term health monitoring of a patient without any constraint on his/her normal dailylife activities. This monitoring requires low-power operation of invasive/non-invasive sensor nodes. In other words, a power-efficient Medium Access Control (MAC) protocol is required to satisfy the stringent WBAN requirements including low-power consumption. In this paper, we first outline the WBAN requirements that are important for the design of a low-power MAC protocol. Then we study low-power MAC protocols proposed/investigated for WBAN with emphasis on their strengths and weaknesses. We also review different power-efficient mechanisms for WBAN. In addition, useful suggestions are given to help the MAC designers to develop a low-power MAC protocol that will satisfy the stringent WBAN requirements.Comment: 13 pages, 8 figures, 7 table

EC-CENTRIC: An Energy- and Context-Centric Perspective on IoT Systems and Protocol Design

The radio transceiver of an IoT device is often where most of the energy is consumed. For this reason, most research so far has focused on low power circuit and energy efficient physical layer designs, with the goal of reducing the average energy per information bit required for communication. While these efforts are valuable per se, their actual effectiveness can be partially neutralized by ill-designed network, processing and resource management solutions, which can become a primary factor of performance degradation, in terms of throughput, responsiveness and energy efficiency. The objective of this paper is to describe an energy-centric and context-aware optimization framework that accounts for the energy impact of the fundamental functionalities of an IoT system and that proceeds along three main technical thrusts: 1) balancing signal-dependent processing techniques (compression and feature extraction) and communication tasks; 2) jointly designing channel access and routing protocols to maximize the network lifetime; 3) providing self-adaptability to different operating conditions through the adoption of suitable learning architectures and of flexible/reconfigurable algorithms and protocols. After discussing this framework, we present some preliminary results that validate the effectiveness of our proposed line of action, and show how the use of adaptive signal processing and channel access techniques allows an IoT network to dynamically tune lifetime for signal distortion, according to the requirements dictated by the application