©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The vision of the Internet of Things (IoT) to interconnect and Internet-connect everyday people, objects, and machines poses new challenges in the design of wireless communication networks. The design of medium access control (MAC) protocols has been traditionally an intense area of research due to their high impact on the overall performance of wireless communications. The majority of research activities in this field deal with different variations of protocols somehow based on ALOHA, either with or without listen before talk, i.e., carrier sensing multiple access. These protocols operate well under low traffic loads and low number of simultaneous devices. However, they suffer from congestion as the traffic load and the number of devices increase. For this reason, unless revisited, the MAC layer can become a bottleneck for the success of the IoT. In this paper, we provide an overview of the existing MAC solutions for the IoT, describing current limitations and envisioned challenges for the near future. Motivated by those, we identify a family of simple algorithms based on distributed queueing (DQ), which can operate for an infinite number of devices generating any traffic load and pattern. A description of the DQ mechanism is provided and most relevant existing studies of DQ applied in different scenarios are described in this paper. In addition, we provide a novel performance evaluation of DQ when applied for the IoT. Finally, a description of the very first demo of DQ for its use in the IoT is also included in this paper.Peer ReviewedPostprint (author's final draft

We consider a wireless Machine-to-Machine (M2M) area network where a gateway periodically collects data from a group of end-devices equipped with energy harvesters. While the use of energy harvesters ideally provides infinite lifetime, the unpredictable amount of harvested energy may not guarantee that all data transmissions can be done in due time because of temporary energy shortages. We propose in this paper the Energy Harvesting-aware Reservation Dynamic Frame Slotted-ALOHA (EH-RDFSA) protocol as a solution suitable for managing the access of end-devices that transmit bursts of data packets while taking into account the energy availability. We derive a model based on a discrete-time Markov chain to analyze the evolution of the energy available in an end-device and to evaluate the performance of the network. In particular, we compute the data delivery ratio, which measures the ability of the protocol to successfully transmit data to the gateway without depleting the energy reserves of the end-devices, and the time efficiency, which measures the amount of data that can be transmitted in a given period of time. We have validated the accuracy of the analysis by means of computer-based simulations. Results show that the overall performance is influenced by the energy harvesting rate and the amount of data to transmit from each end-device. Finally, we have compared the performance of EH-RDFSA with that of DFSA and Time Division Multiple Access (TDMA) protocols.

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Recent standardization efforts on low-power wireless communication technologies, including time-slotted channel hopping (TSCH) and DASH7 Alliance Mode (D7AM), are starting to change industrial sensing applications, enabling networks to scale up to thousands of nodes whilst achieving high reliability. Past technologies, such as ZigBee, rooted in IEEE 802.15.4, and ISO 18000-7, rooted in frame-slotted ALOHA (FSA), are based on contention medium access control (MAC) layers and have very poor performance in dense networks, thus preventing the Internet of Things (IoT) paradigm from really taking off. Industrial sensing applications, such as those being deployed in oil refineries, have stringent requirements on data reliability and are being built using new standards. Despite the benefits of these new technologies, industrial shifts are not happening due to the enormous technology development and adoption costs and the fact that new standards are not well-known and completely understood. In this article, we provide a deep analysis of TSCH and D7AM, outlining operational and implementation details with the aim of facilitating the adoption of these technologies to sensor application developers.