A novel hybrid medium access control protocol for inter-M2M communications

A scalable medium access control (MAC) protocol is crucial for machine-type devices to access the channel simultaneously in a machine-to-machine (M2M) network. There can be two types of scenarios in an M2M network. First, where the M2M devices communicate with the base station one-by-one, and second, where the M2M devices directly communicate with each other within a group or cluster without any human intervention (Inter-M2M communication). Considering the second type of scenario, the devices can use basic contention or reservation-based MAC protocols. But with such a large number of M2M devices, adaptability, and scalability become bottlenecks. Therefore, in this paper, we propose a novel scalable hybrid-MAC protocol, which combines the benefits of both contention-based and reservation-based medium access schemes. We assume that the contention and reservation portion of M2M devices is a frame structure, which mainly has two parts: contention interval (CI) and data transmission interval (DTI). The devices contend for the channel access during CI. After contention, the successful devices win time-slots and transmit data packets during DTI. In our proposed hybrid-MAC scheme, each M2M device is IEEE 802.11 DCF enabled, and within each time slot during DTI, the devices share data with each other. The analytical and simulation results show that the proposed hybrid-MAC protocol performs better than slotted-ALOHA, p-persistent CSMA, and TDMA in terms of aggregate throughput, average transmission delay, channel utility, and energy consumption.

[1]  Rajeev Tripathi,et al.  A robust hybrid-MAC protocol for M2M communications , 2014, 2014 International Conference on Computer and Communication Technology (ICCCT).

[2]  Tae-Jin Lee,et al.  Enhancement of IEEE 802.11ah MAC for M2M Communications , 2014, IEEE Communications Letters.

[3]  Kwangjae Lim,et al.  Performance evaluation of random access for M2M communication on IEEE 802.16 network , 2012, 2012 14th International Conference on Advanced Communication Technology (ICACT).

[4]  M. Lakshmanan,et al.  AN ADAPTIVE ENERGY EFFICIENT MAC PROTOCOL FOR WIRELESS SENSOR NETWORKS , 2009 .

[5]  Mohsen Guizani,et al.  Home M2M networks: Architectures, standards, and QoS improvement , 2011, IEEE Communications Magazine.

[6]  Jing Wang,et al.  An adaptive medium access control mechanism for cellular based Machine to Machine (M2M) communication , 2010, 2010 IEEE International Conference on Wireless Information Technology and Systems.

[7]  Yu Chen,et al.  Machine-to-Machine Communication in LTE-A , 2010, 2010 IEEE 72nd Vehicular Technology Conference - Fall.

[8]  Enzo Baccarelli,et al.  Distributed and adaptive resource management in Cloud-assisted Cognitive Radio Vehicular Networks with hard reliability guarantees , 2015, Veh. Commun..

[9]  Sajal K. Das,et al.  Performance Evaluation of a Request-TDMA/CDMA Protocol for Wireless Networks , 2001, J. Interconnect. Networks.

[10]  Romano Fantacci,et al.  Proposal of a cognitive based MAC protocol for M2M environments , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[11]  S. Ramanathan,et al.  A unified framework and algorithm for (T/F/C)DMA channel assignment in wireless networks , 1997, Proceedings of INFOCOM '97.

[12]  Tarik Taleb,et al.  Machine type communications in 3GPP networks: potential, challenges, and solutions , 2012, IEEE Communications Magazine.

[13]  Andrzej Duda,et al.  Idle sense: an optimal access method for high throughput and fairness in rate diverse wireless LANs , 2005, SIGCOMM '05.

[14]  Gang Zhou,et al.  Impact of radio irregularity on wireless sensor networks , 2004, MobiSys '04.

[15]  Shengli Xie,et al.  Cognitive machine-to-machine communications: visions and potentials for the smart grid , 2012, IEEE Network.

[16]  Arun Prakash,et al.  Machine-to-Machine (M2M) communications: A survey , 2016, J. Netw. Comput. Appl..

[17]  T.-H. Hsu,et al.  Adaptive time division multiple access-based medium access control protocol for energy conserving and data transmission in wireless sensor networks , 2011, IET Commun..

[18]  Richard J. La,et al.  Fast Adaptive S-ALOHA Scheme for Event-Driven Machine-to-Machine Communications , 2012, 2012 IEEE Vehicular Technology Conference (VTC Fall).

[19]  M. Jacobsson,et al.  Enhanced LTE-Advanced Random-Access Mechanism for Massive Machine-to-Machine ( M 2 M ) Communications , .

[20]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[21]  Biplab Sikdar,et al.  A Survey of MAC Layer Issues and Protocols for Machine-to-Machine Communications , 2015, IEEE Internet of Things Journal.

[22]  Marco Conti,et al.  Optimal capacity of p-persistent CSMA protocols , 2003, IEEE Communications Letters.

[23]  Antonis Kalis,et al.  HYMAC: Hybrid TDMA/FDMA Medium Access Control Protocol for Wireless Sensor Networks , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[24]  Gen-Huey Chen,et al.  Utilization based duty cycle tuning MAC protocol for wireless sensor networks , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[25]  D. Malone,et al.  Modeling the 802.11 Distributed Coordination Function in Nonsaturated Heterogeneous Conditions , 2007, IEEE/ACM Transactions on Networking.

[26]  Azzedine Boukerche,et al.  Performance evaluation of a generalized hybrid TDMA/CDMA protocol for wireless multimedia with QoS adaptations , 2005, Comput. Commun..

[27]  Hsiao-Hwa Chen,et al.  Machine-to-Machine Communications in Ultra-Dense Networks—A Survey , 2017, IEEE Communications Surveys & Tutorials.

[28]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[29]  Jianping Pan,et al.  A hybrid reservation/contention-based MAC for video streaming over wireless networks , 2010, IEEE Journal on Selected Areas in Communications.

[30]  Petar Popovski,et al.  Code-expanded random access for machine-type communications , 2012, 2012 IEEE Globecom Workshops.

[31]  Hamid Aghvami,et al.  A PRMA based MAC protocol for cognitive machine-to-machine communications , 2013, 2013 IEEE International Conference on Communications (ICC).

[32]  Injong Rhee,et al.  Z-MAC: a hybrid MAC for wireless sensor networks , 2005, SenSys '05.

[33]  Jiming Chen,et al.  Design of a Scalable Hybrid MAC Protocol for Heterogeneous M2M Networks , 2014, IEEE Internet of Things Journal.

[34]  Marwan Krunz,et al.  Energy-efficient power/rate control and scheduling in hybrid TDMA/CDMA wireless sensor networks , 2009, Comput. Networks.

[35]  Deborah Estrin,et al.  An energy-efficient MAC protocol for wireless sensor networks , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[36]  Geng Wu,et al.  M2M: From mobile to embedded internet , 2011, IEEE Communications Magazine.

[37]  Deborah Estrin,et al.  Medium access control with coordinated adaptive sleeping for wireless sensor networks , 2004, IEEE/ACM Transactions on Networking.

[38]  Enzo Baccarelli,et al.  Reliable Adaptive Resource Management for Cognitive Cloud Vehicular Networks , 2015, IEEE Transactions on Vehicular Technology.

[39]  David Malone,et al.  Modeling the 802.11 distributed coordination function in non-saturated conditions , 2005, IEEE Communications Letters.

[40]  Chen-Yu Hsu,et al.  An adaptive multichannel protocol for large-scale machine-to-machine (M2M) networks , 2013, 2013 9th International Wireless Communications and Mobile Computing Conference (IWCMC).

[41]  Jesus Alonso-Zarate,et al.  DPCF-M: A Medium Access Control protocol for dense Machine-to-Machine area networks with dynamic gateways , 2013, 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[42]  Anthony Ephremides,et al.  Analysis of a Hybrid Access Scheme for Buffered Users-Probabilistic Time Division , 1982, IEEE Transactions on Software Engineering.