With the large growth of the Internet of Things (IoT), a strong focus has been put on designing and developing energy efficient and high performance protocols. Industrial-type wireless networks require strict and on-time delivery guarantees, such as close to 100% network reliability and ultra low delay. To this aim, standards such as IEEE 802.15.4-TSCH or Wireless HART, aim to guarantee high-level network reliability by keeping nodes time-synchronized and by employing a slow channel hopping pattern to combat noisy environments and external interference. In wireless networks, since all the radio channels are not impacted in a similar manner, blacklisting bad channels may improve performance of the whole wireless infrastructure. In this paper, we perform a thorough experimental study to characterize the radio (for all IEEE 802.15.4 channels) and connectivity among the nodes of an indoor testbed. More precisely, we investigate the locality of these blacklisting techniques and we highlighted: the fact that some channels perform poorly only in a small set of locations, for certain radio links. Our study tends to justify the need for local blacklisting techniques, demanding more control packets, but dealing more efficiently with spectral re-use.

No abstract

Wireless industrial networks require reliable and deterministic communication. Determinism implies that there must be a guarantee that each data packet will be delivered within a bounded delay. Moreover, it must ensure that the potential congestion or interference will not impact the predictable properties of the network. In 2016, IEEE 802.15.4-Time-Slotted Channel Hopping (TSCH) emerged as an alternative Medium Access Control to the industrial standards such as WirelessHART and ISA100.11a. However, TSCH is based on traditional collision detection and retransmission, and can not guarantee reliable delivery within a given time. This article proposes LeapFrog Collaboration (LFC) to provide deterministic and reliable communication over an RPL-based network. LFC is a novel multi-path routing algorithm that takes advantage of route diversity by duplicating the data flow onto an alternate path. Simulations and analytical results demonstrate that LFC significantly outperforms the single-path retransmission-based approach of RPL+TSCH and the state-of-the-art LinkPeek solution.

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

No abstract

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.

In this paper, we explore the role of simulators and testbeds in the development procedure of protocols or applications for Wireless Sensor Networks (WSNs) and Internet of Things (IoT). We investigate the complementarity between simulation and experimentation studies by evaluating latest features available among open testbeds (e.g., energy monitoring, mobility). We show that monitoring tools and control channels of testbeds allow for identification of crucial issues (e.g., energy consumption, link quality) and we identify some opportunities to leverage those real-life obstacles. In this context, we insist on how simulations and experimentations can be efficiently and successfully coupled with each other in order to obtain reproducible scientific results, rather than sole proofs-of-concept. Indeed, we especially highlight the main characteristics of such evaluation tools that allow to run multiple instances of a same experimental setup over stable and finely controlled components of hardware and real-world environment. For our experiments, we used and evaluated the FIT IoT-LAB facility. Our results show that such open platforms, can guarantee a certain stability of hardware and environment components over time, thus, turning the unexpected failures and changing parameters into core experimental parameters and valuable inputs for enhanced performance evaluation.

LoRa networks enable long range communications for Internet of Things (IoT) applications. The current LoRa technology provides a wide range of communication settings whereas many combination settings are orthogonal and, thus, they can be successfully decoded at the gateway when the signals are transmitted simultaneously. Previous simulation results showed that the LoRa network capacity can be improved when multiple communication parameters are applied. In this paper, we model a LoRa network consisting of nodes with different communication settings in terms of bandwidth and spreading factor. We compute the average success probability per configuration as a function of density taking into account both intra and inter-spreading factor collisions. We, also, formulate and solve an optimization problem to maximize the node capacity for a given deployment area and frequency by optimizing the number of nodes having different spreading factor configurations. We present numerical results and we show that solutions close to the optimal can increase the maximum number of nodes by more than 700% compared to case where equal number of users per spreading factor are considered.