Wireless medium access control (MAC) and routing protocols are fundamental building blocks of the Internet of Things (IoT). As new IoT networking standards are being proposed and different existing solutions patched, evaluating the end-to-end performance of the network becomes challenging. Specific solutions designed to be beneficial, when stacked may have detrimental effects on the overall network performance. In this paper, an analysis of MAC and routing protocols for IoT is provided with focus on the IEEE 802.15.4 MAC and the IETF RPL standards. It is shown that existing routing metrics do not account for the complex interactions between MAC and routing, and thus novel metrics are proposed. This enables a protocol selection mechanism for selecting the routing option and adapting the MAC parameters, given specific performance constraints. Extensive analytical and experimental results show that the behavior of the MAC protocol can hurt the performance of the routing protocol and vice versa, unless these two are carefully optimized together by the proposed method.
The importance of a mathematical modeling of MAC protocols related to sensor networking has been advocated in recent literature @cite_19 Park_TON -- @cite_16 . The critical effect of MAC parameters on the performance has been shown and discussed in @cite_19 for IEEE 802.15.4 networks. @cite_11 , a Markov chain model is used to design a distributed adaptive algorithm for minimizing the power consumption of single hop star networks using the IEEE 802.15.4 MAC, while guaranteeing a given successful packet reception probability and delay constraints. @cite_16 , an automatic MAC protocol selection mechanism is proposed. The main idea of this approach is to provide a mathematical analysis of various MAC protocols, including the IEEE 802.15.4 MAC, and to choose the optimal MAC protocol and adapt its parameters for the selected modality, topology, and packet generation rate. In particular the designed mechanism takes into account the corresponding physical layer technology and hardware, while satisfying constraints for energy, reliability, and delay. The value of the aforementioned approaches is that the algorithms do not require any modification of the IEEE 802.15.4 standard to be applied. However, their application is limited to single-hop networks.
@cite_19 @cite_16 @cite_11
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The recent IEEE 802.15.4 standard defines a low rate wireless personal area network which can be used to implement sensor networks. In particular, the beacon enabled mode with slotted CSMA-CA contention resolution mechanism appears suitable for deployment in simple hierarchical sensor clusters. However, a detailed analysis of the operation of the MAC layer according to the 802.15.4 standard reveals a number of issues which may potentially become performance bottlenecks and thus lead to serious performance degradation. we analyze those issues and their impact, and suggest modifications of the coordinator function that allow the network to handle higher traffic loads and thus offer much improved performance to its clients. We present a novel approach for Medium Access Control (MAC) protocol design based on protocol engine. Current way of designing MAC protocols for a specific application is based on two steps: First the application specifications (such as network topology and packet generation rate), the requirements for energy consumption, delay and reliability, and the resource constraints from the underlying physical layer (such as energy consumption and data rate) are specified, and then the protocol that satisfies all these constraints is designed. Main drawback of this procedure is that we have to restart the design process for each possible application, which may be a waste of time and efforts. The goal of a MAC protocol engine is to provide a library of protocols together with their analysis such that for each new application the optimal protocol is chosen automatically among its library with optimal parameters. We illustrate the MAC engine idea by including an original analysis of IEEE 802.15.4 unslotted random access and Time Division Multiple Access (TDMA) protocols, and implementing these protocols in the software framework called SPINE, which runs on top of TinyOS and is designed for health care applications. Then we validate the analysis and demonstrate how the protocol engine chooses the optimal protocol under different application scenarios via an experimental implementation. Distributed processing through ad hoc and sensor networks is having a major impact on scale and applications of computing. The creation of new cyber-physical services based on wireless sensor devices relies heavily on how well communication protocols can be adapted and optimized to meet quality constraints under limited energy resources. The IEEE 802.15.4 medium access control protocol for wireless sensor networks can support energy efficient, reliable, and timely packet transmission by a parallel and distributed tuning of the medium access control parameters. Such a tuning is difficult, because simple and accurate models of the influence of these parameters on the probability of successful packet transmission, packet delay, and energy consumption are not available. Moreover, it is not clear how to adapt the parameters to the changes of the network and traffic regimes by algorithms that can run on resource-constrained devices. In this paper, a Markov chain is proposed to model these relations by simple expressions without giving up the accuracy. In contrast to previous work, the presence of limited number of retransmissions, acknowledgments, unsaturated traffic, packet size, and packet copying delay due to hardware limitations is accounted for. The model is then used to derive a distributed adaptive algorithm for minimizing the power consumption while guaranteeing a given successful packet reception probability and delay constraints in the packet transmission. The algorithm does not require any modification of the IEEE 802.15.4 medium access control and can be easily implemented on network devices. The algorithm has been experimentally implemented and evaluated on a testbed with off-the-shelf wireless sensor devices. Experimental results show that the analysis is accurate, that the proposed algorithm satisfies reliability and delay constraints, and that the approach reduces the energy consumption of the network under both stationary and transient conditions. Specifically, even if the number of devices and traffic configuration change sharply, the proposed parallel and distributed algorithm allows the system to operate close to its optimal state by estimating the busy channel and channel access probabilities. Furthermore, results indicate that the protocol reacts promptly to errors in the estimation of the number of devices and in the traffic load that can appear due to device mobility. It is also shown that the effect of imperfect channel and carrier sensing on system performance heavily depends on the traffic load and limited range of the protocol parameters.