The so-called Industrial Internet of Things (IIoT) is expected to transform our world, and in depth modernize very different domains such as manufacturing, energy, agriculture, construction industry, and other industrial sectors. The need for low power radio networks first led to low duty cycle approaches where nodes turn off their radio chipset most of the time to save energy. The medium access control (MAC) has thus been largely investigated over the last fifteen years. Unfortunately, classical contention access methods use a random access and are unable to provide guarantees. In the meantime, some dedicated standards have emerged (e.g. IEEE 802.15.4-2006, IEEE 802.15.4-2015), combining Time Division Multiple Access (TDMA) with slow channel hopping in order to enable reliability and energy efficiency. Slow channel hopping allows each node to use different channels for a frame and its possible retransmissions with a low-cost hardware. To provide high-reliability, these protocols rely on a common schedule in order to prevent simultaneously interfering transmissions. In this context, we clearly observe a strong growth of the number of proposals in the last years, denoting a strong interest of the research community for deterministic slow channel hopping scheduling for the IIoT. We categorize here the numerous existing solutions according to their objectives (e.g. high-reliability, mobility support) and approaches. We also identify some open challenges, expected to attract much attention over the next few years.

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We consider the problem of running RPL on top of the ieee 802.15.4 MAC layer-the two layers operate over two different structures, a directed acyclic graph in the case of RPL and a cluster-tree for ieee 802.15.4. We propose to adapt the cluster-tree of ieee 802.15.4 so that it can efficiently work coupled with rpl. Nodes in our modified cluster-tree can associate with several parent nodes by taking advantage of an adequate organization of superframes at the MAC layer. Building on this modified MAC layer, we define an opportunistic forwarding scheme that extends rpl with the possibility of forwarding packets over multiple paths. Instead of always using a preferred parent, a node opportunistically forwards packets through other parents as long as their routes towards the sink are better. We take advantage of the opportunistic forwarding to support higherpriority delay-sensitive alarms that need to arrive in sink before a given deadline along with low-intensity monitoring data considered as best-effort. We compare our opportunistic version of RPL to its basic version through detailed simulations in terms of packet delivery ratio, incurred delay, and overhead.

Efficient routing is needed in order to ensure a long lifetime of the Wireless Sensor Networks. Several routing metrics have been proposed to be used, however, energy efficient routing is still an open problem. In this paper, we propose a novel metric to prolong the lifetime of the network: the Expected Lifetime (ELT). ELT estimates the lifetime of a node by taking into account its residual energy, the link reliability to its neighbors and the quantity of traffic to forward. Therefore, we will be able to reduce the energy consumption, while keeping low packet losses and capturing the variations of the link quality. We apply this metric to RPL, the emerging routing protocol for low-power and lossy networks and show the lifetime gains of the network. Because we estimate ELT through passive measurements we provide here a detailed methodology to efficiently implement it with RPL.

International audienceTime Slotted Channel Hopping (TSCH) is among the proposed Medium Access Control (MAC) layer protocols of the IEEE 802.15.4-2015 standard for low-power wireless communications in Internet of Things (IoT). TSCH aims to guarantee high network reliability by exploiting channel hopping and keeping the nodes time-synchronized at the MAC layer. In this paper, we focus on the traffic isolation issue, where several clients and applications may cohabit under the same wireless infrastructure without impacting each other. To this end, we present an autonomous version of 6TiSCH where each device uses only local information to select their timeslots. Moreover, we exploit 6TiSCH tracks to guarantee flow isolation, defining the concept of shared (best-effort) and dedicated (isolated) tracks. Our thorough experimental performance evaluation campaign, conducted over the open and large scale FIT IoT-LAB testbed (by employing the OpenWSN), highlight the interest of this solution to provide reliability and low delay while not relying on any centralized component

Abstract-The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is one of the emerging routing standards for multihop Wireless Sensor Networks (WSN). RPL is based on the construction of a Destination-Oriented Directed Acyclic Graph (DODAG), which offers a loop-free topology to route data packets. While several routing metrics have been proposed in the literature, it is unclear how they perform with RPL. In this paper, we analyze the impact of different PHY and MAC metrics on the stability and efficiency of RPL. We highlight the fact that realistic conditions lead to instabilities and oscillations in the routing structure. While minimizing the hop length leads to a stable but poor routing structure, more sophisticated link metrics such as ETX reflect more clearly the radio link quality but increase the number of DODAG reconfigurations. We also provided a detailed methodology to measure the DODAG stability and to implement efficiently each routing metric with RPL.

Envisioned communication densities in Internet of Things (IoT) applications are increasing continuously. Because these wireless devices are often battery powered, we need specific energy efficient (low-power) solutions. Moreover, these smart objects use low-cost hardware with possibly weak links, leading to a lossy network. Once deployed, these Low-power Lossy Networks (LLNs) are intended to collect the expected measurements, handle transient faults and topology changes, etc. Consequently, validation and verification during the protocol development are a matter of prime importance. A large range of theoretical or practical tools are available for performance evaluation. A theoretical analysis may demonstrate that the performance guarantees are respected, while simulations or experiments aim on estimating the behaviour of a set of protocols within real-world scenarios. In this article, we review the various parameters that should be taken into account during such a performance evaluation. Our primary purpose is to provide a tutorial that specifies guidelines for conducting performance evaluation campaigns of network protocols in LLNs. We detail the general approach adopted in order to evaluate the performance of layer 2 and 3 protocols in LLNs. Furthermore, we also specify the methodology that should be adopted during the performance evaluation, while reviewing the numerous models and tools that are available to the research community.

The devices composing Wireless Sensor Networks (WSN) are very limited in terms of memory, processing power and battery. RPL has emerged as the de facto routing standard in low-power and lossy networks. While most of the proposals focus on minimizing the global energy consumption, we aim here at designing an energy-balancing routing protocol: each node should efficiently consume the same quantity of energy to improve the network lifetime. To this end, we exploit an Expected Lifetime metric, denoting the residual time of the nodes (time until the node will run out of energy). We propose mechanisms to detect the energy-bottleneck nodes and to spread the traffic load uniformly among them. While RPL constructs a Destination-Oriented Directed Acyclic Graph (DODAG) structure, it only implements single path. We propose here to exploit its natural multipath structure. This multipath approach helps reducing the number of DODAG reconstructions that leads to instabilities and convergence problems. Simulations highlight we improve both the routing reliability and the network lifetime.