Modern vehicles increasingly rely on distributed computing platforms that exchange large volumes of sensor and control data with strict timing requirements. Ensuring that this traffic meets its deadlines over Ethernet-based in-vehicle networks requires Time-Sensitive Networking (TSN) and, in particular, effective configuration of the Time-Aware Shaper (TAS). However, generating and updating TAS schedules that remain valid as traffic patterns evolve is an NP-hard problem that traditional optimization or heuristic methods address only partially. This paper introduces a Deep Reinforcement Learning (DRL) scheduler that learns to configure TAS schedules directly from network state while preserving standard compliance through analytical validation. The proposed DRL scheduler encodes the scenario (network topology and workload) of the in-vehicle network using a Graph Neural Network (GNN) and learns scheduling policies that balance deadline satisfaction, latency, and resource utilization. Evaluation on a comprehensive benchmark shows that the proposed approach consistently outperforms state-of-the-art heuristics and a topology-specific DRL baseline, achieving higher success rate and lower delay while maintaining efficient bandwidth use. Once trained, it can adapt to new traffic scenarios within milliseconds, demonstrating the potential of the DRL-based scheduler as a foundation for adaptive and reliable communication in next-generation software-defined vehicles.

As vehicles develop into software-defined platforms with powerful automated driving capabilities and driver support systems, their in-vehicle networks become significantly more complicated. A key technique for ensuring deterministic, low-latency connectivity for crucial data traffic in such settings is Time-Sensitive Networking (TSN), and specifically the Time-Aware Shaper (TAS). However, current TAS scheduling techniques have difficulty adjusting schedules to dynamically shifting traffic patterns and changing operating conditions. This paper presents an adaptive scheduler using Deep Reinforcement Learning (DRL), which aims to meet strict deadlines, reducing latency and providing near-ideal resource usage. Experimental results for different vehicle scenarios show that our DRL-based scheduler performs better in terms of success rate, low latency, and overall network performance than state-of-the-art heuristic algorithms such as earliest deadline first (EDF) scheduling.

In-vehicle networks (IVNs) are rapidly evolving to support increasingly complex automotive applications, demanding higher bandwidth and deterministic timing bounds. Time-Sensitive Networking (TSN) has emerged as a promising Ethernet-based technology that addresses these stringent requirements. However, evaluating TSN-based IVN strategies remains a challenge due to the lack of standardized benchmarks and simulation tools. This paper introduces INSIM, a modular simulation platform specifically designed for TSN-based IVNs, providing an intuitive graphical interface, an extensible plug-in architecture, and integrated benchmarking features. INSIM integrates analytical performance models and discrete-event simulations (as plug-ins), enhancing the workflow for engineers by refining topology design, adjusting parameters, conducting simulations, and assessing performance, while providing researchers with a flexible platform to plug in, analyze, and compare custom network resource managers or analytical performance models.

This paper introduces a novel approach for a system-wide performance evaluation of Zigbee networks, in the context of large-scale lighting applications. It allows a comprehensive assessment of Zigbee networks through quantitative measurement of three key performance indicators: Reliability, Robustness, and Responsiveness. It proposes a systematic framework that injects different traffic scenarios into the network to get performance scores for each node in the network for every scenario. These scores are then passed through weighted scoring algorithms to obtain a network-level score for each performance indicator. Weighting factors are computed through the Analytic Hierarchy Process (AHP) that prioritizes multiple criteria based on merit. The framework has been deployed and tested in real-life lighting systems, considering two luminaire network topologies: open-space and corridor layouts. The results show the use of the framework for overall acceptance testing as well as identifying low-performing nodes. Thus, this paper presents a distinctive methodology and a testbed to qualitatively monitor the performance of any Zigbee network deployed for lighting solutions based on user needs.

The Bluetooth Mesh (BM) standard was released in 2017 to expand the application of the Bluetooth Low Energy (BLE) technology for larger-scale multi-hop Internet-of-Things (IoT) networks. To implement multi-hop data delivery, BM defines a relay feature for BLE nodes using a controlled flooding algorithm for data dissemination. By default, the relay nodes persistently scan the advertising channels to receive packets from their neighbors and broadcast. However, it has a big impact on the energy consumption and lifetime of the relay nodes, especially when they have limited energy resources. On the other hand, any constant and homogeneous setting of a duty cycle for relay nodes across the network leads to inefficient performance since the nodes can be in different spatial and temporal conditions. This paper proposes a run-time adaptive duty-cycling mechanism for relay nodes to reduce unnecessary energy consumption and yet collaboratively make a reliable end-to-end data delivery. Each relay node independently decides about its suitable duty cycle based on its local conditions. The proposed method is evaluated using a publicly available BM simulator, showing a significant reduction in energy consumption (up to 57% in the conducted experiments) while preserving the packet delivery performance of the network.

Bluetooth Mesh (BM) is one of the promising networking technologies for Internet-of-Things (IoT) networks released by Bluetooth SIG in 2017. BM provides a protocol for multi-hop scalable networking of IoT devices over the widely-used Bluetooth Low Energy (BLE) technology. However, the capabilities and limits of this technology are not fully studied to determine the IoT applications for which this technology can be used. One of the barriers towards this is the lack of a suitable BM network simulator for performance investigations under various conditions and settings. This paper presents a full-fledged open-source event-driven simulator (BMSim) for the performance evaluation of BM networks. The accuracy of the developed simulator is verified by real experiments. Also, BMSim is used to perform a comprehensive investigation of the performance of the BM protocol in various network conditions and configuration settings. The impact of several configuration parameters on the BM network performance is studied. Since the simulator is capable of simulating dynamic networks and run-time configurations, a BM network with node mobility is also investigated. The results reveal the importance and necessity of proper BM parameter configuration mechanisms to achieve the required quality-of-service and network efficiency.

To achieve strict reliability goals with lower redundancy cost, Time-Sensitive Software-Defined Networking (TSSDN) enables run-time recovery for future in-vehicle networks. While the recovery mechanisms rely on network planning to establish reliability guarantees, existing network planning solutions are not suitable for TSSDN due to its domain-specific scheduling and reliability concerns. The sparse solution space and expensive reliability verification further complicate the problem. We propose NPTSN, a TSSDN planning solution based on deep Reinforcement Learning (RL). It represents the domain-specific concerns with the RL environment and constructs solutions with an intelligent network generator. The network generator iteratively proposes TSSDN solutions based on a failure analysis and trains a decision-making neural network using a modified actor-critic algorithm. Extensive performance evaluations show that NPTSN guarantees reliability for more test cases and shortens the decision trajectory compared to state-of-the-art solutions. It reduces the network cost by up to 6.8x in the performed experiments.

The IEEE 802.15.4 time-slotted channel hopping (TSCH) is widely used as a reliable, low-power, and low-cost communication technology for many industrial Internet of Things (IoT) networks. In many applications, Quality-of-Service (QoS) requirements are different for heterogeneous nodes, necessitating nonequal parameter settings per node. This results in a very large configuration space making space exploration complex and time consuming. Moreover, network state and QoS requirements may change over time. Thus, run-time configuration mechanisms are needed for making decisions about proper node settings to consistently satisfy diverse and dynamic QoS requirements. In this article, we propose a run-time decentralized self-optimization framework based on deep reinforcement learning (DRL) for parameter configuration of a multihop TSCH network. DRL adopts neural networks as approximate functions to speed up the process of converging to QoS-satisfying configurations. Simulation results show that our proposed framework enables the network to use the right configuration settings according to the diverse QoS demands of different nodes. Moreover, it is shown that the convergence time of the learning framework is in the order of a few minutes which is acceptable for many IoT applications.

Escalation in the use of Internet of Things (IoT) devices gives rise to the number of networks operating in the license-free 2.4-GHz frequency band. This prepares the ground for networks to experience interference from coexisting networks and thus performance degradation. Time-slotted channel hopping (TSCH), as an operational medium access mode of the IEEE 802.15.4 technology, was introduced to ensure the reliability of IoT networks when they undergo coexistence. It uses frequency hopping as a protective strategy against long-term packet losses due to interference. However, when several independent TSCH networks coexist, they are prone to interfere with one another. In extreme scenarios, coexisting TSCH networks may block links of one another for an extended duration of time, leading to application failure. In this article, we propose a novel technique called time hopping to secure the reliability of coexisting TSCH networks. The developed technique synchronously and periodically alters the timing of nodes within a TSCH network to avoid coexisting TSCH networks from getting stuck in extreme coexistence scenarios and long-term continuous collisions. We evaluate the effectiveness of the proposed technique through extensive simulations. The results clearly show that the proposed time hopping technique substantially improves the worst case internetwork collision ratio, with as much as 50% improvement in some tested scenarios. The implementation of the technique is very simple, with almost no communication or computation overhead for the constrained wireless nodes; it is done and tested on real nodes for proof of concept.

In the automotive domain, Ethernet Audio Video Bridging (AVB) provides service guarantees for real-time traffic. Its configuration synthesis requires routing the flows and allocating the bandwidth for Credit Based Shaping (CBS). Current approaches typically employ deadline-oblivious bandwidth allocation and rely on routing to establish deadline guarantees. But the worst-case delay of AVB flows requires complex analysis. Thus, routing integrated with the delay analysis either supports limited Stream Reservation (SR) classes or suffers significant timing overhead. To enable efficient run-time flow setup, we propose SynAVB, a tool to synthesize the configuration of Ethernet AVB, which establishes deadline awareness in bandwidth allocation. SynAVB supports an arbitrary number of SR classes and processes them one by one. For the flows in an SR class, it first performs a deadline-oblivious routing based on Mixed Integer Linear Programming (MILP) to guarantee the necessary bandwidth required by the flows. Then, a deadline-aware slope allocation algorithm computes the bandwidth required on every link to satisfy the deadline of all flows. Our experiment demonstrates that, given the same routes, the deadline-aware bandwidth allocation results in fewer flows violating the deadline compared with other allocation strategies. Moreover, SynAVB can guarantee the deadline of more flows while its run-time is up to 14.3x faster than the state-of-the-art approaches.

Time-Sensitive Networking (TSN) is a promising solution for the next generation in-vehicle networks. To enable innovations in adaptability, there is a strong trend to integrate TSN with Software-Defined Networking (SDN). Software-defined TSN requires fast routing algorithms that guarantee the Worst-Case End-to-End Delay (WCED) of the Audio Video Bridging (AVB) flows. However, current AVB flow routing algorithms execute WCED analysis for an exponential amount of route candidates, which is not feasible at run-time. Current WCED analysis of the AVB flows depends on the specific flow setup of other traffic classes. When high-priority flows change, low-priority flows must be adjusted as well to maintain deadline guarantees. In this paper, we propose a per-class flow management scheme to enable run-time routing of the AVB flows. Our composable analysis computes a formal WCED bound of the AVB flows. It does not rely on the flow setup of other traffic classes. So, the WCED and routes can be computed for each traffic class independently and in parallel. Based on the analysis, we develop a fast heuristic algorithm to incrementally route the AVB flows with guaranteed deadlines. Our experiments demonstrate that, compared to the existing solutions, the composable analysis is 2.6x faster. The cost is that the WCED bound can be up to 31% higher. When given a similar run-time as existing solutions, the proposed routing algorithm can set up 1.6x more flows. The average time to set up one flow is within 0.14s.

The energy efficiency of an Internet of Things (IoT) receiver can be improved by introducing an adjustable tradeoff between signal quality and energy consumption. In good channel conditions, the receiver can be set to consume less energy per bit, without compromising signal quality in bad channel conditions. We propose a system-level receiver design that enables adequate configuration and combination of signal quality and energy tradeoffs in multiple receiver components. Co-design of all components is essential. We identify the most energy-efficient configurations in our system-level design under different channel conditions. With those configurations, the proposed receiver outperforms a state-of-the-art adjustable receiver with only an adjustable analog front end by several tens of percent in energy per successfully received bit and by$2\times $in energy-sensitivity configuration range. To show the efficacy of the proposed approach, we integrate a model of the proposed design into the OMNeT++ simulator and show the benefits on an environmental monitoring scenario. In this scenario, we report up to$6\times $energy savings for the entire transceiver compared to the conventional transceiver design without adjustable receiver.

In this work, a design of an IEEE 802.15.4 con-formant O-QPSK demodulator is proposed, which is capable of trading off receiver sensitivity for power savings. Such design can be used to meet rigid energy and power constraints for many applications in the Internet-of-Things (IoT) context. In a Body Area Network (BAN), for example, the circuits need to operate with extremely limited energy sources, while still meeting the network performance requirements. This challenge can be addressed by the paradigm of adequate computing, which trades off excessive quality of service for power or energy using approximation techniques. Three different, adjustable approximation techniques are integrated into the demodulation to trade off effective signal quantization bit-width, filtering performance, and sampling frequency for power. Such approximations impact incoming signal sensitivity of the demodulator. For detailed trade-off analysis, the proposed design is implemented in a commercial 40-nm CMOS technology to estimate power and in Python to estimate sensitivity. Simulation results show up to 64% power savings by sacrificing $\tilde 7$ dB sensitivity.

The IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) is a widely used standard technology for industrial Wireless Sensor Networks (WSNs). The applications of such networks have diverse Quality-of-Service (QoS) demands that should be satisfied. Optimal configuration of the network parameters based on their QoS requirements and run-time adaptation to continuously meet the QoS requirements given all network dynamics is a great challenge for large-scale networks. The configuration space is very large for large-scale networks resulting in space exploration to be complex and extremely time-consuming. Moreover, such space exploration needs to be performed multiple times at design-time to give insight into the worst and best case performance of the mechanisms and network topology. Yet, it is needed for the run-time reconfiguration upon changes in the network. To address the stated challenges, we propose a fast and accurate enough algorithm based on Pareto algebra to extract a subset of Pareto configurations for large TSCH networks in a very short time. A proper configuration can be then picked from this set. Having such a fast optimization algorithm, the network can react to the changes in the link quality, routing topology, and reconfigure itself optimally at an appropriate time. The performance of the proposed technique is extensively evaluated, and compared with other approaches such as basic incremental Pareto analysis, and genetic algorithm, showing its superior execution time and quality of configurations in terms of accuracy and diversity.

The introduction of Bluetooth Low Energy (BLE) in 2010 provided constrained devices with a wireless point-to-point communication standard. It facilitates the creation of piconets and reducing product development time and cost. It is until 2017 that the Bluetooth special interest group releases the Mesh Profile allowing a multi-hop interconnection through BLE's advertisements. Being a relatively new technology, this paper aims to experimentally evaluate its performance and investigate the limits of the technology in terms of data delivery capacity in monitoring applications. Several experiments are performed by deploying a number of BLE nodes in an office environment, making a multi-hop network. The performance of the network in terms of packet delivery to a base station is measured in each experiment. Moreover, experiments including mobile nodes are carried out under the multi-hop setup to test the behaviour of the protocol when some nodes move around. The experimental results show that the relay nodes impose critical limitations for message delivery in multi-hop networks, limiting the usage of the BLM technology for many monitoring applications.

To handle the rigid power and energy constraints in the Digital BaseBand (DBB) of Wireless Sensor Networks (WSN)s, we introduce approximate computing as a new power reduction method. The Received Signal Strength Indicator (RSSI) computation is a key element in DBB processing. We evaluate the trade-off in RSSI computation between Quality-of-Service (QoS) and power consumption through circuit-level approximation. RSSI elements are approximated in such a way that error propagation is minimized. In an industrial 40-nm CMOS technology, substantial energy savings up to 24% are achieved for every successfully transferred bit in DBB processing in a low- power listening WSN scenario.

The IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol has received considerable attention in many industrial applications. However, analytical models for fast performance estimation of TSCH-based networks by considering the interaction between Medium Access Control (MAC) and Physical (PHY) layers is an open problem. In this paper, we propose a stochastic model for performance analysis of TSCH-based networks including dedicated and shared links with non-ideal wireless link properties. The proposed model is scalable and is able to evaluate the MAC performance of a large-scale network quickly. The developed model is verified by simulations and real-world experiments. The results confirm the accuracy of the proposed model for large-scale networks with orders of magnitude faster execution compared to the existing model in the literature. This confirms the speed and scalability of the model, which makes it a perfect tool for network design and optimization.

Narrowband Internet of Things (NB-IoT) is a new Low Power Wide Area Network (LPWAN) technology released by the Third Generation Partnership Project (3GPP). The primary goals of NB-IoT are enhanced coverage, low cost, and long battery life. In order to enhance coverage, NB-IoT has new features, such as increasing transmission repetitions, decreasing bandwidth, and adapting the Modulation and Coding Scheme (MCS). In this paper, we present an implementation of these three features of NB-IoT in NS-3, an end-to-end network simulator. Using the developed simulation framework, the influence of the coverage enhancement features on network reliability and latency is evaluated. Furthermore, we propose a hybrid link adaptation strategy based on all three features, which tries to achieve optimal latency and coverage. To achieve this, we formulate and solve an optimization problem that finds the optimal value of repetitions, bandwidth and MCS such that the latency is minimum and the reliability is maintained. Based on the hybrid link adaption strategy, a new scheduler is implemented and evaluated in the NS-3 simulator. Through numerical results we show that the hybrid link adaptation method achieves lower latency and higher coverage than any of the coverage enhancement techniques. We also show that the proposed optimization method achieves the same performance as the exhaustive search method but with lower complexity.

Time-Slotted Channel Hopping (TSCH), as an operational mode of the IEEE 802.15.4 standard, is a promising medium access mechanism for industrial Wireless Sensor Networks (WSNs). However, efficient performance of such networks depends on the medium access scheduling scheme, which is not specified by the standard. This paper proposes a low-latency distributed scheduler, called LaDiS, for multi-hop tree-based TSCH networks. The main objective is to provide low end-to-end data latency in convergecast WSNs with very low communication overhead. The schedule of each node is determined by its parent based on the available local information about the routing structure and traffic requirement of that node. At the same time, LaDiS provides proper opportunity for data aggregation by relaying nodes in a multi-hop network leading to reduced traffic. The performance of the proposed scheduler as well as the existing distributed TSCH schedulers is extensively evaluated in various setups. The results show that LaDiS considerably outperforms others in terms of data latency in the networks under consideration in this work. LaDiS is implemented and integrated in the Contiki operating system.

Wireless Body Area Networks (WBANs) have made their way into many smart and ubiquitous healthcare and wellness applications. A low-power, efficient, and reliable communication protocol is of paramount importance for the success of WBANs in satisfying the requirements of the health applications. The IEEE 802.15.4 standard is always one of the main options due to its efficiency and low-complexity. However, it suffers from the impact of other wireless technologies using the same frequency band such as WiFi and Bluetooth. Time Slotted Channel Hoping (TSCH) is an operational mode of the IEEE 802.15.4e standard, which is originally developed for reliable industrial wireless networks. TSCH has Time Division Multiple Access (TDMA) and frequency hopping features, which increase the network robustness against effects such as noise, interference, and multi-path fading. This paper proposes to exploit TSCH for communications in WBANs, and studies its performance. The features of TSCH like power efficiency, TDMA-based operation, and heterogeneity support fit very well with the requirements of many health monitoring applications. The performance of the TSCH standard for WBAN communications is investigated through real-world experiments in various conditions. The results show that TSCH outperforms the basic IEEE 802.15.4 standard in terms of communication reliability against interferences from coexisting wireless devices.

Wireless sensor networks (WSNs) are considered as a promising solution in intravehicle networking to reduce wiring and production costs. This application requires reliable and real-time data delivery, while the network is very dense. The time-slotted channel hopping (TSCH) mode of the IEEE 802.15.4 standard provides a reliable solution for low-power networks through guaranteed medium access and channel diversity. However, satisfying the stringent requirements of in-vehicle networks is challenging and demands for special consideration in network formation and TSCH scheduling. This paper targets convergecast in dense in-vehicle WSNs, in which all nodes can potentially directly reach the sink node. A cross-layer low-latency topology management and TSCH scheduling (LLTT) technique is proposed that provides a very high timeslot utilization for the TSCH schedule and minimizes communication latency. It first picks a topology for the network that increases the potential of parallel TSCH communications. Then, by using an optimized graph isomorphism algorithm, it extracts a proper match in the physical connectivity graph of the network for the selected topology. This network topology is used by a lightweight TSCH schedule generator to provide low data delivery latency. Two techniques, namely grouped retransmission and periodic aggregation, are exploited to increase the performance of the TSCH communications. The experimental results show that LLTT reduces the end-to-end communication latency compared to other approaches, while keeping the communications reliable by using dedicated links and grouped retransmissions.

The Bluetooth Low Energy (BLE) and Time Slotted Channel Hopping (TSCH) mode of the IEEE 802.15.4 are two of the most widely used technology standards for Wireless Sensor Networks (WSNs). In many applications, both technologies need to be used in the same environment to fulfill application requirements. However, since they share the same 2.4 GHz ISM band, such networks may suffer from cross-technology interference, which decreases the reliability of the network. To solve this problem, we propose a cooperative coexistence solution for BLE and TSCH networks in which joint time-slot and channel hopping synchronization are performed. The proposed solution uses a scheduling matrix to model the resource usage of the networks. Following this, the overlaps in this matrix are eliminated by rescheduling the transmissions of the networks. The proposed solution does not require any protocol change. The performance of the proposed cooperative coexistence mechanism is evaluated using experiments with real wireless devices. The results of those show that our proposed solution considerably decreases Packet Error Rate (PER); an improvement of up to 45% PER is observed.

The IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) protocol defines two types of timeslots for communications, namely dedicated and shared timeslots. An upper layer in the protocol stack uses these timeslots to design a communication schedule for the network links, based on the required bandwidth for each link. Considering a network with time-varying data traffic generation by each node, the bandwidth requirements are changing over time for each link. This leads to poor efficiency of a predefined schedule when there is no data traffic for the dedicated timeslots, or there is too much data traffic injected to the shared timeslots. In this paper, we propose a new type of timeslot, called hybrid timeslot. A hybrid timeslot acts as a dedicated timeslot for a specific link, when there are packets available to be transmitted on that link. Otherwise, it acts as a shared timeslot that can be accessed by other links, using a contention-based mechanism. The hybrid timeslot has backward compatibility with the TSCH protocol and is functional with a few adaptations in the parameter setup of the TSCH protocol. Experimental and simulation results show that for heterogeneous networks using hybrid timeslots improves communication latency without reliability penalty.

Time-Slotted Channel Hopping (TSCH) is considered as one of the most reliable MAC solutions for low- power wireless networking. In order to establish time-slotted communications, this technique requires all nodes to remain synchronized. The synchronization is continuously done through normal communications to compensate the clock drift between different nodes. In this paper, we present a detailed look into the behavior of the IEEE 802.15.4 PHY and MAC in terms of the synchronization task. We show that the relation between timeslot offsets provided by the standard leads to different synchronization error margins for positive and negative relative clock drifts. This is due to the time required for detection of ongoing transmissions at receivers. This may lead to the situation that two nodes are able to communicate in only one direction. Depending on which node is the source node, the available margin to compensate the relative clock drift is different. Accordingly, we provide new values for timeslot offsets to compensate positive and negative relative clock drifts equally. Simulation results confirm that the standard offsets reduce the performance of TSCH due to asymmetric synchronization error handling. The results also show that this negative effect is mitigated by using the new offsets provided in this paper.

IEEE 802.15.4 Time-Slotted Channel Hopping (TSCH) aims to improve communication reliability in Wireless Sensor Networks (WSNs) by reducing the impact of the medium access contention, multipath fading, and blocking of wireless links. While TSCH outperforms single-channel communications, cross-technology interference on the license-free ISM bands may affect the performance of TSCH-based WSNs. For applications such as in-vehicle networks for which interference is dynamic over time, it leads to non-guaranteed reliability of the communications over time. This article proposes an Enhanced version of the TSCH protocol together with a Distributed Channel Sensing technique (ETSCH+DCS) that dynamically detects good quality channels to be used for communication. The quality of channels is extracted using a combination of a central and a distributed channel-quality estimation technique. The central technique uses Non-Intrusive Channel-quality Estimation (NICE) technique that proactively performs energy detections in the idle part of each timeslot at the coordinator of the network. NICE enables ETSCH to follow dynamic interference, while it does not reduce throughput of the network. The distributed channel quality estimation technique is executed by all the nodes in the network, based on their communication history, to detect interference sources that are hidden from the coordinator. We did two sets of lab experiments with controlled interferers and a number of simulations using real-world interference datasets to evaluate ETSCH. Experimental and simulation results show that ETSCH improves reliability of network communications, compared to basic TSCH and the state-of-the-art solution. In some experimental scenarios NICE itself has been able to increase the average packet reception ratio by 22% and shorten the length of burst packet losses by half, compared to the plain TSCH protocol. Further experiments show that DCS can reduce the effect of hidden interference (which is not detectable by NICE) on the packet reception ratio of the affected links by 50%.

Wireless sensor networks have entered into our lives, and are expected to be even more widespread in the near future. Bluetooth Low Energy (BLE) and IEEE 802.15.4 are two low-power wireless standards that are widely used in sensor network applications. They share the same unlicensed 2.4 GHz ISM spectrum. To be able to employ both technologies in the same environment in a heterogeneous network, the creation of a proper coexistence mechanism is imperative. In this paper, we propose and develop a cooperative mechanism for the coexistence of co-located IEEE 802.15.4 and BLE networks in the time domain. This mechanism tries to avoid overlap of communications in these networks in order to decrease the chance of Cross-Technology Interference (CTI) and thus packet drops. The proposed mechanism does not impose any protocol change. The performance of the proposed mechanism is evaluated by using real hardware devices. The experimental results show that the overall packet reception ratio improves up to 12%.

The rapid growth of the Internet-of-Things (IoT) has led to a proliferation of low-power wireless technologies. A major challenge in designing an IoT network is to achieve coexistence between different wireless technologies sharing the unlicensed 2.4 GHz ISM spectrum. Although there is significant literature on coexistence between IEEE 802.15.4 and IEEE 802.11, the coexistence of Bluetooth Low Energy (BLE) with other technologies remains understudied. In this work, we examine coexistence between IEEE 802.15.4, BLE and IEEE 802.11, which are widely used in residential and industrial wireless applications. We perform a mathematical analysis of the effect of cross-technology interference on the reliability of the affected wireless network in the physical (PHY) layer. We also set up and perform PHY layer experiments to verify the analytical results. Finally, we extend the study to the Medium Access Control (MAC) layer. Our findings show that, even though the MAC layer mechanisms of IEEE 802.15.4 and BLE improve reliability, cooperative solutions are required to achieve coexistence.

Wireless in-vehicle networks are considered as a flexible and cost-efficient solution for the new generation of cars. One of the candidate wireless technologies for these wireless sensor networks is the IEEE 802.15.4 standard which operates in the 2.4 GHz ISM band. This is while the number of wireless devices that operate in this band is ever increasing. This broad usage of the same RF band may cause considerable performance degradation of wireless networks due to interference. There is some work on the coexistence of the IEEE 802.15.4 protocol and other standard technologies such as IEEE 802.11 (Wi-Fi) and IEEE 802.15.1 (Bluetooth), but none of it considers the highly dynamic conditions of in-vehicle networks. In this paper, we investigate the interference behavior in in-vehicle environments using real-world experiments. We consider different scenarios and measure the interference on all the 16 channels of IEEE 802.15.4 in the 2.4 GHz band.The measurement data set is available to the public. This real-world data set can be used for realistic and accurate network simulation. To study the effect of interference on in-vehicle networks, we use this data set to evaluate the performance of an IEEE 802.15.4e TSCH link. The simulation results show that the packet error rate for some interference scenarios is considerably high and dynamic over time. This shows the value of the data set and reveals the importance of using adaptive interference mitigation techniques to improve the reliability of wireless in-vehicle networks.

Cross-technology interference on the license-free ISM bands has a major negative effect on the performance of Wireless Sensor Networks (WSNs). Channel hopping has been adopted in the Time-Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4e to eliminate blocking of wireless links caused by external interference on some frequency channels. This paper proposes an Enhanced version of the TSCH protocol (ETSCH) which restricts the used channels for hopping to the channels that are measured to be of good quality. The quality of channels is extracted using a new Non-Intrusive Channel-quality Estimation (NICE) technique by performing energy detections in selected idle periods every timeslot. NICE enables ETSCH to follow dynamic interference well, while it does not reduce throughput of the network. It also does not change the protocol, and does not require non-standard hardware. ETSCH uses a small Enhanced Beacon hopping Sequence List (EBSL) to broadcast periodic Enhanced Beacons (EB) in the network to synchronize nodes at the start of timeslots. Experimental results show that ETSCH improves reliability of network communication, compared to basic TSCH and a more advanced mechanism ATSCH. It provides higher packet reception ratios and reduces the maximum length of burst packet losses.

Node mobility is a key feature of using Wireless Sensor Networks (WSNs) in many sensory applications, such as healthcare. The Medium Access Control (MAC) protocol should properly support the mobility in the network. In particular, mobility is complicated for contention-free protocols like Time Division Multiple Access (TDMA). An efficient access to the shared medium is scheduled based on the node's local neighborhood. This neighborhood may vary over time due to node movement or other dynamics. In scenarios including body-area networking, for instance, some clusters of nodes move together, creating further challenges but also opportunities. This article presents a MAC protocol, MCMAC, that provides efficient support for cluster mobility in TDMA-based MAC protocols in WSNs. The proposed protocol exploits a hybrid contention-free and contention-based communication approach to support cluster mobility. This relieves the protocol from rescheduling demand due to frequent node movements. Moreover, we propose a listening scheduling mechanism to avoid idle listening to mobile nodes that leads to a considerable energy saving for sensor nodes. The protocol is validated by performing several experiments in a real-world large-scale deployment including several mobile clusters. The protocol is also evaluated by extensive simulation of networks with various scales and configurations.

Sensor nodes in many Wireless Body Area Network (WBAN) architectures are supposed to deliver sensed data to a gateway node on the body. To satisfy the data delivery requirements, the network needs to adapt itself to the changes in connection status of the body nodes to the gateway. As a prerequisite, Link Quality Estimation (LQE) needs to be done to detect the connection status of the nodes. The quality of links in WBANs is highly time-varying. The LQE technique should be agile to react fast to such link quality dynamics while avoiding frequent fluctuations to reduce the network adaptation overhead. In this paper, we present an empirical study on using different LQE methods for detecting the connection status of body nodes to the gateway in WBANs. A set of experiments using 16 wireless motes deployed on a body are performed to log the behavior of the wireless links. We explore the trade-offs made by each LQE method in terms of agility, stability, and reliability in detecting connection changes by analyzing the experimental data. Moreover, different LQE methods are used in an adaptive multi-hop WBAN mechanism, as a case study, and their impact on the Quality-of-Services (QoS) are investigated.

In recent years, vehicular ad-hoc networks (VANETs) have received increasing interests because of their promising solutions in many urban applications. VANETs are distinguished from other kinds of ad-hoc networks, such as Mobile Ad-hoc Networks (MANETs), by high mobility and reduced communications. The topology of the network is highly time-varying due to high mobility of wireless nodes, and also joining and leaving nodes. This makes it challenging to find and maintain efficient and reliable data forwarding routes between different nodes in the network. On the other hand, equipment such as positioning systems usually exist in current vehicles which can be used to improve the efficiency of packet dissemination. This paper proposes TIGeR, a new Traffic-aware Intersection-based Geographical Routing protocol. Nodes that are at intersections make routing decision to forward packets based on both the local vehicular traffic information of different roads and the road's angle with respect to the direct vector toward the destination. Local vehicular traffic information is considered as a sign of network connectivity in a road. Simulation results show that TIGeR improves the packet delivery ratio, especially in sparse networks.

Adaptation of the network architecture through on-demand data forwarding is an efficient mechanism to provide robustness against long outages in WBANs. We developed an experimental testbed that provides online observation of the network behavior for different data propagation approaches in WBANs. The demonstration shows how different approaches deal with special challenges in WBANs such as low quality of wireless links, topology variations due to posture changes, and mobility. Moreover, sensor nodes can be configured online to investigate how different protocols react in various situations.

Practical experience reveals the characteristic properties of Wireless Body Area Networks (WBANs), signifying the need for a well-designed communication protocol. High mobility, stringent resource constraints, and low and time-variant quality of wireless links are some of the challenging issues in WBANs. Typical applications further have varying Quality-of-Service requirements and demand reliable and fast data transmission at low energy cost. This paper proposes a simple, robust, and optimized protocol for data propagation in WBANs. A hybrid design approach is proposed that automatically adapts the network topology according to the connectivity status of the network. An on-demand data forwarding mechanism combined with an epidemic data propagation strategy realize a proper data delivery and robustness while minimizing the idle listening and unnecessary data forwarding. Several experiments using wireless sensor nodes deployed on a body reveal how this protocol can automatically adapt the network in different situations. The results confirm the robustness and improved behavior of this protocol in comparison with existing fixed protocol architectures.

The inherently unreliable communication infrastructure compel WSN protocols to employ error control mechanisms. Traditionally, error control is achieved by a retransmission scheme using acknowledgment mechanisms. WSN architectures are severely resource constrained and the additional energy expense of transmitting error control messages can seriously degrade network lifetime. In this paper, we analyze performance of error control schemes for the case of point-to-multipoint communication. An explicit acknowledgment mechanism may provide for reliable communication, but has two major drawbacks: 1) the over head is significant for small data messages, and 2) in case of asymmetrical communication links, multi-hop dissemination of acknowledgments is required. As an alternative to such explicit acknowledgment schemes we propose the use of probabilistic acknowledgments. In this probabilistic scheme, a sender estimates the probability that a message has been successfully delivered, based on information about the quality of the radio channel. A message is then retransmitted until the probability of successful delivery reaches a defined threshold value. Network capacity available for error control can be distributed prudently among all information items to be disseminated, possibly taking into account different application requirements. We formulate are transmission control strategy which results in minimal latency and maximal message delivery ratio.

In many applications of Wireless Sensor Networks (WSNs), heterogeneity is a common property in terms of different sensor types and different circumstances like node location, link quality, and local node density. In many applications, there are several different sensor types with entirely different Quality-of-Service (QoS) requirements. The requirements may also vary over time according to the application scenario and also due to network dynamics. Different requirements appeal different approaches while forwarding sensed data through a multi-hop communication network. This paper proposes a dynamic priority assignment strategy to be used for data routing in heterogeneous WSNs aiming to fairly propagate information according to its importance and requirements. To cope with heterogeneity and dynamics, nodes in the routing path dynamically compute priorities for individual data items according to the attached QoS requirements. We apply the proposed strategy for a healthcare monitoring application scenario which consists of an ambient network and several mobile clusters of nodes in the form of Wireless Body Area Networks (WBANs). The nodes have very different requirements and WBANs show a high mobility in the network with more stringent demands. The results show a large improvement in the achieved QoS for more demanding information.

Wireless sensor networks (WSNs) are developing into a promising solution for many applications, for example in healthcare. In many scenarios, there is some form of node mobility. The medium access control (MAC) mechanisms should support the expected kind of mobility in the network. Mobility is particularly complicating for contention free MAC protocols like TDMA-based protocols, because they dedicate unique slots to every node in a neighborhood. In scenarios such as body-area networking, some clusters of nodes move together, creating further challenges and opportunities. This paper proposes MCMAC (Mobile Cluster MAC), a TDMA-based MAC protocol to support mobile clusters in WSNs. The proposed protocol does not need adaptation time after movement of clusters. Several optimization mechanisms are proposed to decrease power consumption. Simulation results show that the optimizations decrease power consumption of nodes around 70% without increasing latency of data transmission compared to the non-optimized version.

In this paper, we present optimized methodology for Intra-task voltage scheduling. Our proposed method gets data flow and control flow of application that represents coloration between different parts of the application at the early stage of design using UML-RT model and decides to schedule processor's voltage. By applying this technique on JPEG encoder system experimental results show reduction in energy consumption by 18-54 % over common Intra-DVS algorithm.

Model checking thoroughly verifies the design correctness with respect to a specification. When the verification process succeeds, we can only postulate the correctness of the design relative to the given specification. How far can we affirm the verified design implements all the behavior of the desired system? With this regard we need to estimate the completeness of the properties by using some coverage metrics. In this paper, we have proposed a new metric called assignment coverage and an optimized method to overcome the intensive computations required for the multiple transformations among the abstract layers in the verification tool. The proposed coverage computation method provides adequate information to complete the set of properties. Finally, we have applied the proposed metric to some verification benchmark to reveal the effectiveness of this metric in finding undetected coverage holes.