Industrial Internet of Things applications need strict Quality of Service guarantees, including when they use wireless networks. While existing standardization efforts, such as Deterministic Networks (IETF) and Time-Sensitive Networking (TSN), have focused mainly on wired networks, more recent activities address wireless networks, like the Reliable and Available Wireless (RAW) Working Group of the IETF. Duplicating packets over multiple paths can improve availability and reliability, but this can potentially result in more out-of-order packets. Existing reordering algorithms, including two recently standardized by the IETF, are not always well suited to wireless networks. As a result, guaranteeing a bounded end-to-end latency and/or maximum consecutive packet losses is still particularly challenging. We propose a novel packet reordering algorithm for deterministic networking that includes wireless segments to achieve lower end-to-end latency while providing high end-to-end reliability. We simulate a 6TiSCH wireless network to compare its performance with the existing ones. Furthermore, we also extend existing Network Calculus bounds on the reordering timer to obtain path-dependent values that can reduce the average latency. We also introduce a probabilistic model to compute the reordering ratio when there are no retransmissions that fits the simulation results.

Ensuring both reliable and low-latency communications over 4G or 5G Radio Access Network (RAN) is a key feature for services such as smart power grids and the metaverse. However, the lack of appropriate security mechanisms at the lower-layer protocols of the RAN–a heritage from 4G networks–opens up vulnerabilities that can be exploited to conduct stealthy Reduction-of-Quality attacks against the latency guarantees. This paper presents an empirical assessment of a proposed time-delay attack that leverages overshadowing to exploit the reliability mechanisms of the Radio Link Control (RLC) in Acknowledged Mode. By injecting falsified RLC Negative Acknowledgements, an attacker can maliciously trigger retransmissions at the victim User Equipment (UE), degrading the uplink latency of application flows. Extensive experimental evaluations on open-source and commercial off-the-shelf UEs demonstrate the attack’s effectiveness in increasing latency, network load, and buffer occupancy. The attack impact is quantified by varying the bitrate representing different applications and the number of injected negative acknowledgments controlling the attack intensity. This work studies a realistic threat against the latency quality of service in 4G/5G RANs and highlights the urgent need to revisit protocol security at the lower-RAN layers for 5G (and beyond) networks.

More and more devices connect to the network leading to the emergence of Internet of Things (IoT). One of the most popular use cases is the Industrial IoT (IIoT), in which ultra-high end-to-end network reliability and low latency are the main requirements. In order to fulfill these features, the Institute of Electrical and Electronics Engineers (IEEE) has published the 802.15.4-2015 standard and in particular, its Time Slotted Channel Hopping (TSCH) mode more specifically. Furthermore, to enable transmission of Internet Protocol version 6 (IPv6) packets, the IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) adaptation layer was introduced in RFC 4944 standard, which defines three functions, fragmentation, reassembly and fragment forwarding. However, RFC 4944 does not cope well with lossy links since it requires reception of all fragments in order to reassemble the original IPv6 packet. In order to improve network reliability, Forward Error Correction (FEC) techniques were proposed that enable recovery of lost fragments using redundancy. In this paper, we thoroughly present the state of the art approaches that use FEC techniques. We then introduce our proposal, namely E-XORFEC, which deploys the ability of recovering different fragments based on redundancy factors. Finally, we implement the considered methods in the 6TiSCH simulator, evaluate their performance and finally show that our proposed method outperforms all of them.

The devices of Internet of Things (IoT) networks can be deployed for extended period of time in inaccessible locations. After their deployment, new features, bug fixes, or changes in the client needs can require an update of the node's behavior, and this update has to be transmitted over the radio medium. Proposals have been made in the literature to apply the Software Defined Network (SDN) paradigm to wireless sensor networks but they focus on the packet forwarding layer of the stack. In this work, we propose to extend the programmability to the whole stack with a fully programmable device architecture able to handle the runtime programming of every protocol on any hardware. We detail the use of extended finite-state machines (XFSM) on which the architecture is based and their conversion to compact executable bytecode that can be sent over radio. Simulations demonstrate that this architecture can reproduce a protocol from the literature and enable interoperability between programmable nodes and legacy nodes.

Battery Management System (BMS) is a critical part of Electric Vehicles (EVs). The introduction of a wireless communication and networking inside the BMS in order to replace the traditional wired bus brings multiple benefits. As it is a critical application, the network has stringent requirements such as high reliability, low energy consumption, and bounded latency. In this paper, we propose a network architecture based on an enhanced version of the IEEE Std 802.15.4 Time Slotted Channel Hopping (TSCH) Medium Access Control (MAC) mode running over the physical layer of Bluetooth Low Energy (BLE). To orchestrate the data transmissions, we present a reliable and predictable schedule based on the Low Latency Deterministic Network (LLDN) Group Acknowledgement (GACK) method which dynamically manages the retransmissions. We implement a WBMS for the Renault Zoe battery pack to demonstrate that our proposed architecture achieves 100% of network reliability with bounded latency, and low energy consumption.

One of the most critical parts of Electric Vehicles (EVs) is the Battery Management System (BMS). Replacing the traditional wired bus of the BMS by a wireless network brings several benefits. Since it is a critical application, the wireless network has to meet strict requirements such as low energy consumption, bounded latency, and high reliability. In this paper, we propose an enhanced version of the IEEE Std 802.15.4 Time Slotted Channel Hopping (TSCH) Medium Access Control (MAC) mode running over the physical layer of Bluetooth Low Energy (BLE). To coordinate the data plane, we introduce a reliable and predictable schedule based on the Low Latency Deterministic Network (LLDN) Group Acknowledgement (GACK) method to dynamically manage the retransmissions. To validate our proposal, we implement a Wireless BMS (WBMS) network for the Renault Zoe battery pack. After conducting several experiments, we demonstrate that our proposed architecture outperforms a traditional retransmission based strategy and achieve 100% of network reliability with bounded latency, and low energy consumption.

Context: Internet-of-Things (IoT) systems are increasingly deployed in the real world, but their security lags behind the state of the art of non-IoT systems. Moving target defense (MTD) is a cyberdefense paradigm, successfully implemented in conventional systems, that could improve IoT security. Objective: Identify and synthesize existing MTD techniques for IoT and validate the feasibility of MTD as a cybersecurity paradigm suitable for IoT systems. Method: We use a systematic literature review method to search and analyze existing MTD for IoT techniques up to July 2020. We evaluated the existing techniques in terms of security foundations and real-world deployability using the evidence they provide. We define and use entropy-related metrics to categorize them. This is the first MTD survey to use Shannon's entropy metric empirically. Results: Thirty-two distinct MTD for IoT techniques exist: 54% are Network-layer-based, 50% present strong evidence about their real-world deployment, and 64% have weak security foundations. Conclusion: MTD for IoT is a feasible cyberdefense approach. A variety of proposals exist, with evidence about their implementation and evaluation. Nevertheless, the MTD for IoT state of the art is still immature: the security foundations of most existing proposals are weak. Novel techniques should prioritize providing convincing security foundations and real-world deployment evidence.

Deterministic networking allows carrying data flows with low data-loss rates and with bounded latency. A typical use-case is the convergence of Operational Technology (OT) with Information Technology (IT), also known as the Industrial Internet. Wireless networks operate on a shared communication medium where the potential external interference along with multi-path fading impact data packet delivery. By employing diversity in the time, frequency and spatial domains, wireless technologies with scheduled transmissions, such as IEEE Std 802.15.4-2015 Time Slot Channel Hopping (TSCH), can mitigate those effects and provide Reliable and Available Wireless (RAW) communications that approach determinism. Nevertheless, a radio link operating in the ISM band still needs to handle collisions and possibly re-transmission. Therefore, It takes redundant links and paths to provide both the high availability and the near consistent reliability that industrial applications require. In this paper, we present the Packet Automatic Repeat reQuest (ARQ), Replication and Elimination (RE), and Overhearing (PAREO) functions to further increase the Quality of Service (QoS) in industrial networks, even when implemented on top of best-effort traffic in a shared network. The results show that PAREO provides up to approximately 6 times lower Packet Error Rate (PER) and up to approximately 10% higher energy consumption than the default RPL implementation with 7 retransmissions, while keeping jitter and latency as low as default RPL with 1 retransmission.

With the growth of the Internet of Things appliances in industrial environments, known as Industry 4.0, wireless multihop network solutions have been attracting more attention in the past years. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the de facto protocol for Low-power and Lossy Networks specially designed for industrial use-cases. However, the default operation of RPL does not provide a high level of network reliability and low jitter performance. The use of IEEE Std 802.15.4-2015 Time Slot Channel Hopping (TSCH) at the Medium Access Control layer can mitigate the effects of external interference by re-transmitting over different radio frequency. Still, this standard does not support possible link failures or node over-the-air programming. In this paper, we propose the use of multiple disjoint paths to enforce reliability and availability when both RPL and TSCH standards are used. Indeed, we propose and compare two approaches based on the principle of replication: i) packet replication at the source node only, and ii) packet replication at the source node and scattering if two replicas merge. We implemented these two algorithms in Contiki OS and evaluated their trade-offs over the simulated network environment provided by COOJA. Finally, we compare these solutions against the state-of-the-art Packet Automatic Repeat reQuest (ARQ), Replication and Elimination (RE), and Overhearing (PAREO) technique that proposes a braided multipath pattern.

The Battery Management System (BMS) of an Electric Vehicle (EV) is a system designed to ensure safe operation of the battery pack, and reporting its state to other systems. It is a complex and distributed system. In today’s BMS implementations, the communication is performed through wire buses. In this paper, we study the opportunity to use IEEE Std 802.15.4 Time Slotted Channel Hopping (TSCH), a standardized Internet of Things (IoT) approach. We first describe the real- world experiments we did to measure the link quality at Medium Access Control (MAC) layer for wireless nodes placed inside an EV battery pack. Then, we propose a topology management and TSCH scheduling strategy using Linear Programming, based on the results obtained in the experiments.

IEEE Std 802.15.4-2015 Time Slotted Channel Hopping (TSCH) is the de facto Medium Access Control (MAC) mechanism for industrial applications. It renders communications more resilient to interference by spreading them over the time (time slotted) and the frequency (channel hopping) domains. The 6TiSCH architecture bases itself on this new MAC layer to enable high reliability communication in Wireless Sensor Networks (WSNs). In particular, it manages the construction of a distributed communication schedule that continuously adapts to changes in the network. In this paper, we first provide a thorough description of the 6TiSCH architecture, the 6TiSCH Operation Sublayer (6top), and the Minimal Scheduling Function (MSF). We then study its behavior and reactivity from low to high traffic rates by employing the python-based 6TiSCH simulator. Our performance evaluation results demonstrate that the convergence pattern of MSF is the root cause of the majority of packet losses observed in the network. We also show that MSF is subject to over-provisioning of the network resources, especially in the case of varying traffic load.

The Internet of Things (IoT) is more and more present in fundamental aspects of our societies and personal life. Billions of objects now have access to the Internet. This networking capability allows for new beneficial services and applications. However, it is also the entry-point for a wide variety of cyber-attacks that target these devices. The security measures present in real IoT systems lag behind those of the standard Internet. Security is sometimes completely absent. Moving Target Defense (MTD) is a 10-year-old cyber-defense paradigm. It proposes to randomize components of a system. Reasonably, an attacker will have a higher cost attacking an MTD-version of a system compared with a static-version of it. Even if MTD has been successfully applied to standard systems, its deployment for IoT is still lacking. In this paper, we propose a generic MTD framework suitable for IoT systems: IANVS (pronounced Janus). Our framework has a modular design. Its components can be adapted according to the specific constraints and requirements of a particular IoT system. We use it to instantiate two concrete MTD strategies. One that targets the UDP port numbers (port-hopping), and another a CoAP resource URI. We implement our proposal on real hardware using Pycom LoPy4 nodes. We expose the nodes to a remote Denial-of-Service attack and evaluate the effectiveness of the IANVS-based port-hopping MTD proposal.

This paper describes our work on a flexible centralized controller for scheduling wireless networks. The context of this work encompasses wireless networks within the wider Internet of Things (IoT) field and in particular addresses the requirements and limitations within the narrower Industrial Internet of Things (IIoT) sub-field. The overall aim of this work is to produce wireless networking solutions for industrial applications. The challenges include providing high reliability and low latency guarantees, comparable to existing wired solutions, within a noisy wireless medium and using generally computationally- and energy-restrained network nodes. We describe the development of a centralized controller for Wireless Industrial Networks, currently aimed at IEEE Std 802.15.4-2015 Time Slotted Channel Hopping protocol. Our controller takes a high-level network-centric problem description as input, translates it to a low-level representation and uses that to retrieve a solution from a Satisfiability Modulo Theories (SMT) solver, translating the solution back to a higher-level network-centric representation. The advantages of our solution are the ability to gain the added flexibility, higher ease of deployment, and lower deployment cost offered by wireless networks by generating configurable and flexible schedules for these applications.

The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is the de facto routing protocol for Low Power and Lossy Networks (LLNs). It is a proactive and link-layer agnostic routing protocol standardized as RFC 6550 by the Internet Engineering Task Force (IETF). Based on the distance-vector technique, RPL builds a Destination Oriented Directed Acyclic Graph (DODAG) topology. To establish and maintain the routes, RPL uses DODAG Information Object (DIO) control packets, that are transmitted in broadcast, for RPL nodes to propagate the DODAG related information, while its transmission frequency depends on Trickle timer algorithm, i.e., the less stable the network the more DIOs are transmitted. Thus, when a new node intends to join the RPL DODAG, it listens for a DIO message from nearby nodes, which may take a very long time if the network is in a stable state. Therefore, RFC 6550 is equipped with the DODAG Informational Solicitation (DIS) message to solicit DIOs from nearby RPL nodes, similar to the Router Solicitation in IPv6 Neighbor Discovery. However, the solicitation procedure is not the most efficient one, since it resets the Trickle timers in the nodes that receive the DIS message and, thus, they transmit an unnecessarily large number of DIOs that congest the network and consume energy in the nodes. In this paper, we propose to augment RFC 6550, the RPL routing protocol, with additional DIS flags and options that allow a RPL node to better control how the nearby RPL nodes will respond to its solicitation for DIOs. Our performance evaluation in Contiki-NG & COOJA demonstrates that we can reduce the control packets in the network by up to 45.5%.

The Industrial Internet of Things (IIoT) is expected to be a key enabler for the Industry 4.0. However, networked control automation often requires high reliability and bounded latency to react properly. Thus, modern wireless protocols for industrial networks, such as IEEE 802.15.4-2015 time-slotted channel hopping (TSCH), rely on a strict schedule of the transmissions to avoid collisions and to make the end-to-end traffic deterministic. Unfortunately, guaranteeing a bounded end-to-end latency is particularly challenging since transmissions have to be temporally chained. Even worse, potential degradation of the link quality may result in reconstructing the whole TSCH schedule along the path. In this article, we propose the low-latency distributed scheduling function (LDSF) that relies on the organization of the slotframe in smaller parts, called blocks. Each transmitter selects the right set of blocks, depending on its hop distance from the border router, so that retransmission opportunities are automatically scheduled. To save energy, a node can still turn off its radio as soon as its packet is correctly acknowledged. Our mathematical analysis as well as our simulation evaluation show the efficiency of the proposed LDSF algorithm compared to three state-of-the-art scheduling functions (SFs): 1) the minimal SF (MSF); 2) low-latency SF (LLSF); and 3) stratum.

LoRa is a popular low-rate, low-power wide area network technology providing long range wireless access over unlicensed sub-GHz frequency bands to the Internet of Things (IoT). It has been used in many applications ranging from smart building to smart agriculture. LoRa is a patented modulation, but preliminary reverse-engineering efforts documented parts of it. In this paper, we first present the LoRa modulation architecture. We then tackle with channel coding, whitening and interleaving with reverse-engineering in mind. Based on these early developments, we derive closed-form expressions of the different stages of the LoRa transceiver which, in turn, allows us to assess the performance of LoRa under known channels using simulations.

Industrial applications require more and more low-power operation and high-reliability (close to 100%). Since traditional low-power radio technologies are sensitive to external interference, many recent standards implement frequency hopping schemes. For instance, IEEE 802.15.4-2015 time slotted channel hopping (TSCH) relies on a deterministic schedule of data transmissions combined with a pseudo-random frequency hopping scheme to improve the reliability. Unfortunately, specific radio channels keep on increasing the average number of retransmissions. Using a subset of the best radio channels (whitelisting) helps to improve the reliability, but may create collisions when used improperly. We here investigate the most accurate techniques to use only the best radio channels while still providing deterministic performance. We propose to group the links per timeslot, allocating them either to the same whitelist or even appropriately reordering them to avoid collisions. Finally, we evaluate the performance of the different whitelisting schemes using an experimental dataset from FIT IoT-LAB platform, proving the relevance of such approach to improve the reliability.

The IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) networks suffer considerably from the high interference caused by the presence of nearby external devices, such as from the presence of IEEE 802.11b/g/n Access Points. Frequency hopping and blacklisting of radio channels that temporarily or consistently present bad performance are the two main approaches to cope with interference and increase the chances of successful packet delivery. However, the blacklisting of a number of channels and the scheduling of transmissions so that two or more neighboring links do not use the same frequency at the same time is a challenging problem, since in IEEE 802.15.4 TSCH many parallel transmissions may occur. Blacklisting algorithms may be applied either locally or globally in IEEE 802.15.4 networks. In this paper, we first present the weaknesses of a localized blacklisting solution presented in the literature for multi-hop networks, and we propose a new distributed solution to overcome these issues. Both analytical and simulation evaluation under heavy interference show the superiority of the proposed scheme. In particular, the packet delivery ratio is improved while achieving minimum delay.

The Industrial Internet of Things (IIoT) faces multiple challenges to achieve high reliability, low-latency and low power consumption. The IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol aims to address these issues by using frequency hopping to improve the transmission quality when coping with low-quality channels. However, an optimized transmission system should also try to favor the use of high-quality channels, which are unknown a priori. Hence reinforcement learning algorithms could be useful.

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 cannot guarantee reliable delivery within a given time. This paper proposes LeapFrog Collaboration (LFC) to provide deterministic and reliable communication over a routing protocol (RPL) based network. LFC is a novel multipath 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.

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.

Recent standardization activities bring high Quality of Service (QoS) and predictability to Internet of Things (IoT), which are “going industrial”. Critical applications such as industrial process control, smart grid or vehicle automation require deterministic transmissions with properties such as on-time data deliveries and end-to-end reliability close to 100%. Traditional radio technologies based on collision detection and retransmission introduce unpredictable delays, and can not ensure reliable delivery within a narrowly bounded time. This paper proposes to exploit spatial diversity and packet redundancy to compensate for the inherently lossy wireless medium. We introduce “Leapfrog Collaboration”, a communication mechanism which takes advantage of communication overhearing, and in which parallel transmissions over two paths are scheduled. Promiscuous listening between the paths enables nodes to possibly overhear transmissions on the other. We evaluate the delay and jitter of the communication by simulation using Contiki OS and show that Leapfrog Collaboration outperforms the default retransmission-based approach of IEEE802.15.4-TSCH by up to 28% and 54%, respectively, while providing high network reliability.

Advance clustering techniques have been widely used in Wireless Sensor Networks (WSNs) since they can potentially reduce latency, improve scheduling, decrease end-to-end delay and optimise energy consumption within a dense network topology. In this paper, we present a novel clustering algorithm for high density IEEE 802.15.4-2015 Time-Slotted Channel Hopping (TSCH). In particular, the proposed methodology merges a variety of solutions into an integrated clustering design. Assuming an homogeneous network distribution, the proposed configuration deploys a hierarchical down-top approach of equally numbered sub-groups, in which the formation of the separate sub-groups is adapted to the network density and the node selection metric is based on the link quality indicator. The presented algorithm is implemented in Contiki Operating System (OS) and several test vectors have been designed in order to evaluate the performance of the proposed algorithm in a COOJA simulation environment. Performance results demonstrate the capability of the clustering structure since compared to the default scheme it significantly improves the energy efficiency up to 35%, packet drops more than 40% as well the packet retransmission rate. Last but not least, the outcome of this study indicates a major increase in the network lifetime, i.e., up to 50%.

Industrial applications require more and more low-power operations, low-delay, deterministic communications as well as end-to-end reliability close to 100%. However, traditional radio technologies are sensitive to external interference, which degrades the reliability and introduces unpredictable delays due to collision detection and retransmissions. Therefore, recent standardization efforts focus on slow channel hopping strategies to provide strict Quality of Service (QoS) for the Industrial Internet of Things (IIoT). By keeping nodes time-synchronized and by employing a channel hopping approach, IEEE 802.15.4-TSCH (Time-Slotted Channel Hoping) aims at providing high-level network reliability. However, some radio channels still suffer from high external interference and need to be blacklisted. Since the interference pattern is rather dynamic, unpredictable and highly localized, we here propose heuristics to decide which channels to blacklist. To avoid deafness, the transmitter and the receiver must also agree on a consistent blacklist. Furthermore, since the external interference may be time-dependent as well, we also propose mechanisms to decide when a channel has to be blacklisted or on the contrary recovered. Our thorough experimental evaluation based on OpenWSN and FIT IoT-LAB highlight the relevance of this approach: with a localized blacklisting strategy, we increase by 20% packet delivery rate for the worst links.

With the ubiquity of sensing technologies in our personal spaces, the protection of our privacy and the confidentiality of sensitive data becomes a major concern. In this letter, we focus on wearable embedded systems that communicate data periodically over the wireless medium. In this context, we demonstrate that private information about the physical activity levels of the wearer can leak to an eavesdropper through the physical layer. Indeed, we show that the physical activity levels strongly correlate with changes in the wireless channel that can be captured by measuring the signal strength of the eavesdropped frames. We practically validate this correlation in several scenarios in a real residential environment, using data collected by our prototype wearable accelerometer-based sensor. Finally, we propose a privacy enhancement algorithm that mitigates the leakage of this private information.

The emergence of microgeneration systems steadily increases, and it raises concerns regarding their impact on the power grid. It is, therefore, crucial to efficiently integrate them into future smart grid architectures, as there is not any standard way to monitor production units. Moreover, current data collection systems are simple and do not consider their impact on local area networks. This paper presents a set of proposed mechanisms that reduces the monitoring traffic, while offering management flexibility on large-scale systems. This study is illustrated with measurements performed on a small grid, and it shows that, for monitoring a photovoltaic production, both 1-min and 1-s intervals provide the same production estimation, while significantly decreasing the associated traffic. It can be reduced even more by aggregating several measurements during a given period before sending them and by using specific mechanisms to ensure reliability. This experiment also helps authors identify best practices for monitoring different equipment based on their behaviors.

Recent boom of mobile applications has become an essential class of mobile Internet of Things (IoT), whereby large amounts of sensed data are collected and shared by mobile sensing devices for observing phenomena such as traffic or the environmental. Currently, most of the proposed Medium Access Control (MAC) protocols mainly focus on static networks. However, mobile sensor nodes may pose many communication challenges during the design and development of a MAC protocol. These difficulties first require an efficient connection establishment between a mobile and static node, and then an efficient data packet transmissions. In this study, we propose MobIQ, an advanced mobility-handling MAC scheme for low-power MAC protocols, which achieves for efficient neighbour(hood) discovery and low-delay communication. Our thorough performance evaluation, conducted on top of Contiki OS, shows that MobIQ outperforms state-of-the-art solutions such as MoX-MAC, MOBINET and ME-ContikiMAC, in terms of significantly reducing delay, contention to the medium and energy consumption.

Time 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.

The IEEE 802.15.4-2015 standard defines a number of Medium Access Control (MAC) layer protocols for low-power wireless communications in the IoT. Originally defined in the IEEE 802.15.4e amendment, TSCH (Time Slotted Channel Hopping) is among the proposed mechanisms. TSCH is a scheme aiming to guarantee network reliability by keeping nodes time-synchronised at the MAC layer. In order to ensure successful communication between a sender and a receiver, the latter starts listening shortly before the expected time of a MAC layer frame's arrival. The offset between the time a node starts listening and the estimated time of frame arrival is called guard time and it aims to reduce the probability of missed frames due to clock drift. In this poster, we investigate the effect of the guard time duration on energy consumption. We identify that, when using the 6tisch minimal schedule, the most significant cause of energy consumption is idle listening during guard time. Therefore, the energy-efficiency of TSCH can be significantly improved by guard time optimisation. Our performance evaluation results, conducted using the Contiki operating system, show that an efficient configuration of guard time may reduce energy consumption by up to 30%, without compromising network reliability.

This demonstration aims at observing in an interactive manner the impact of modification of preamble and sampling periods at the low-power family of MAC protocols, and thus, illustrating in real-time the energy consumption and delay performance of each node accordingly. To do so, we implemented the ability for users to generate traffic at some remote nodes that are involved in two distinct deployed topologies. Those deployed networks operate with either a statically configured network, by employing X-MAC on top of the Contiki OS, or T-AAD, a lightweight traffic auto-adaptive protocol that allows live and automatic modifications of duty-cycle configurations.

In traditional routing protocols designed for Wireless Sensor Networks, each sensor node is related to one or more neighbors that will forward its readings up to the sink. This technique performs well for static topologies with homogeneous configurations, but usually fails to cope with network dynamics such as mobility and node failures. Opportunistic routing is an approach to address this particular problem. In this context, the data packets are addressed to a set of potential forwarders and then forwarded by the neighbor that first acknowledges the message. Yet, several former studies demonstrated that in some cases, a single packet may be forwarded by multiple neighbors simultaneously. This situation leads to packet duplication and consequently to increased channel occupancy and energy consumption in the network. In this paper, we study to what extent the previously reported phenomenon depends on both the topology density and the nodes MAC configuration. We then introduce a mechanism that handles the potential deafness in the network through heterogeneous configuration among the nodes in the network. We do so through local, dynamic and automatic MAC parameters adaptation, in order to reduce unnecessary traffic, channel occupancy and energy consumption due to packet duplication in opportunistic networks. Finally, we provide both theoretical analysis and experimental campaign to detail the benefits of our approach.

Validation of protocols and mechanisms is an essential step to the development of object networks in critical domains. Most papers still provide evaluation either obtained through theoretical analysis or simulations campaigns. Yet, simulators and formal models fail to precisely reproduce the unique specificities of the deployment environments those networks have to evolve in. Also, by putting no limits to code complexity and execution, those tools prevent users to apprehend the actual limits of WSN nodes and to propose realistic communication protocols and applications. In this paper, we highlight to what extent the addition of experimentations can significantly improve the value of performance evaluation campaigns. Along with the recent tendency to have algorithmic and protocol proposals facing real environments, it is questionable whether the so obtained results should be considered as scientific or empirical ones. In the former case, reproducibility, stability over time, topology management to cite a few, are a must have for testbeds and real deployments that are used. In the latter, the results should be viewed as a proof-of-concept only, far from independent of the used hardware and encountered conditions at the experimentation time but still critical from the development cycle standpoint. Through some experiments over the IoT-LAB testbed, we aim at demonstrating to what extent some of the simulation setup and conditions from reality could be emulated. We also provide insight on how to obtain the best out of it in a quick and efficient manner. We show that such testbeds would satisfy many expectations (e.g. scientific tool and proof-of-concept validator), thus minding and bridging some of the gaps between theory and practice in WSN. To this end, we here give an overview of available simulation tools, and guidelines on how to transpose simulation setups to the open large-scale IoT-LAB platform.