Emerging IoT applications are transitioning from battery-powered to grid-powered nodes. DRP, a contention-based data dissemination protocol, was developed for these applications. Traditional contention-based protocols resolve collisions through control packet exchanges, significantly reducing goodput. DRP mitigates this issue by employing a distributed delay timer mechanism that assigns transmission-start delays based on the average link quality between a sender and its children, prioritizing highly connected nodes for early transmission. However, our in-field experiments reveal that DRP is unable to accommodate real-world link quality fluctuations, leading to overlapping transmissions from multiple senders. This overlap triggers CSMA’s random back-off delays, ultimately degrading the goodput performance. To address these shortcomings, we first conduct a theoretical analysis that characterizes the design requirements induced by real-world link quality fluctuations and DRP’s passive acknowledgments. Guided by this analysis, we design EDRP, which integrates two novel components: (i) Link-Quality Aware CSMA (LQ-CSMA) and (ii) a Machine Learning-based Block Size Selection (ML-BSS) algorithm for rateless codes. LQ-CSMA dynamically restricts the back-off delay range based on real-time link quality estimates, ensuring that nodes with stronger connectivity experience shorter delays. ML-BSS algorithm predicts future link quality conditions and optimally adjusts the block size for rateless coding, reducing overhead and enhancing goodput. In-field evaluations of EDRP demonstrate an average goodput improvement of 39.43% than the competing protocols.

As the number of wireless devices supporting multiple communication interfaces increases, the connection redundancy is being considered for efficient bandwidth utilization and QoS improvement. Accordingly, network technologies must adapt to emerging multi-interface devices to improve network performance. Multipath TCP (MPTCP) is default multipath transport protocol desired for networks with multi-interface devices and has achieved success in computer networks. However, it has not been well studied for wireless networks, especially for carrier sense multiple access (CSMA) based wireless networks, which present great challenges to round trip time (RTT) computation and multipath scheduling. This paper introduces MPTCP techniques for heterogeneous WiFi and 5G networks. We first model a proposed 5-state congestion control algorithm and WiFi CSMA function. We then present an innovative RTT computation method and a novel loss-ware multipath scheduling mechanism. We evaluated the proposed MPTCP techniques under varying network configurations. Our MPTCP can significantly outperform conventional MPTCP.

This paper explores the transformative potential of the IoT paradigm in promoting smart agriculture. Key challenges lie in how to connect agriculture sensors to remote cloud servers in the absence of feasible communication infrastructure and the unreliable wireless links in rural areas. To address these issues, we propose an innovative two-tier smart agriculture architecture: an Unmanned Aerial Vehicle (UAV) aided agriculture network model, which leverages UAVs as intermediaries to collect and route data from agriculture sensors to cloud servers. This novel architecture leads to two particular problems, i.e., data packet scheduling in the first-tier networks and multi-hop routing in the second-tier UAV mesh network. To that end, we present formal Markov decision process (MDP) based problem formulations for both tiers, with a primary focus on the more challenging multi-hop routing problem in the second-tier network. This problem is approached as a multi-agent reinforcement learning (MARL) framework, for which we introduce a novel distributed algorithm - Focus Coordination: attention-guided Multi-Agent Deep Deterministic Policy Gradient (FC-MADDPG). This algorithm reduces communication overhead and mitigates the risks associated with single-node failures. We evaluated the performance of the proposed FC-MADDPG algorithm, demonstrating its efficacy in enhancing data transmission reliability and efficiency.

Sub-1 GHz (920 MHz) frequency bands for LPWAN (Low Power Wide Area Network) wireless communications systems are attracting attention from various IoT applications. Environmental and infrastructure monitoring systems, such as smart meter, ground inclinometer, and bridge sensor, are widely deployed. AsLPWAN systems operating on Sub-1 GHz bands can provide long distance communications,, a large number of network devices can connect to networks. Although these networks can be configured in a star configuration for a relatively small area, the mesh configuration has been emerging recently. IEEE 802.15.4g-FSK PHY/OFDM PHY is a typical PHY technology in mesh networks for the purpose of transferring IoT application data over a wider area. To distribute the same data such as firmware to LPWAN devices during network operation, improving distribution efficiency becomes critical. On the one hand, using broadcast transmission, the delivery confirmation cannot be performed. On the other hand, unicast transmission is very time consuming if the number of IoT devices is large. Therefore, we proposed a novel firmware distribution method using erasure code for large scale IoT networks. Our ns-3 simulations demonstrate that the proposed method can improve the distribution efficiency by up to 1.8 times compared to conventional methods and achieve higher spectrum efficiency for IEEE 802.15.4g-OFDM PHY.

With the advent of 5G and beyond communication technologies, the consumer IoT devices are evolving from current generation to next generation. Next generation IoT devices can support multiple communication interfaces and perform more functions. Accordingly, IoT network technologies must adapt to the emerging multi-link devices to improve network performance. Multipath TCP (MPTCP) is desired for networks with multi-link devices and has achieved success in computer networks. However, MPTCP has not been well studied for wireless networks. To that end, this paper presents MPTCP techniques for heterogeneous wireless IoT networks consisting of IEEE 802.15.4 nodes and 5G nodes. We propose a path builder, an adaptive congestion controller and an innovative path scheduler. We evaluated our MPTCP techniques under varying network configurations. Compared with conventional MPTCP, the proposed MPTCP can significantly reduce the number of packet transmissions, shorten packet delivery time, improve network throughput and packet delivery rate.

Sub-1 GHz Wireless Communications of LPWAN (Low Power Wide Area Network) are attracting attention in IoT applications. In addition to battery-powered devices, the number of grid-powered and solar-powered sensor devices using LPWAN are also rapidly increasing for various IoT applications. We aim to improve reliability and efficiency of IEEE 802.15.4 CSMA/CA mechanism in the network consisting of devices without power constraint. We propose Suspendable Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) algorithms for IEEE 802.15.4 to mitigate packet loss by channel access failure while maintaining compatibility with conventional IEEE 802.15.4 CSMA/CA. We have performed extensive simulations to valid the Suspendable CSMA/CA mechanism. Simulation results show that the proposed Suspendable CSMA/CA improves Packet Delivery Rate (PDR) by 9.7 points (89.9 % to 99.6 %) compared to the conventional IEEE 802.15.4g CSMA/CA and therefore, can lead higher spectrum efficiency for IoT applications operate in the limited Sub-l G Hz wireless bandwidth. The proposed Suspendable CSMA/CA mechanism has been also approved and adopted for the next IEEE 802.15.4 amendment by IEEE 802.15 Working Group.

With the advent of 5G and beyond communication technologies, the consumer IoT devices are evolving from current generation to next generation. The next generation IoT devices are capable of supporting multiple communication modes and performing more functions. During the migration phase, it is impractical to completely remove the deployed current generation devices. Accordingly, the next generation IoT networks will consist of the mixed current and next generation devices. To that end, how to efficiently route diverse data in next generation IoT networks needs to be addressed. This paper presents a two-topology routing architecture for next generation IoT networks, one topology for regular data delivery and another topology for priority data delivery. The priority routes are discovered to minimize route overlap. We evaluated our route discovery algorithms under varying network configurations. Compared with standard RPL baseline, the proposed routing algorithms can simultaneously reduce route overlap, route transmission time and route length.

The software distribution in advanced IoT networks is inevitable. However, distributing software in multi-hop wireless networks consumes enormous communication bandwidth and can also suffer from reliability challenge. This paper proposes an innovative dynamic relay point (DRP) protocol to reduce the number of software packet transmissions. It also introduces a network condition based rateless coding scheme to improve the packet transmission reliability. The NS3 simulator is employed for performance evaluation. The proposed DRP protocol outperforms multi-point relay (MPR) baseline by reducing the software packet transmissions and improving the effective throughput.

With the explosive proliferation of wireless devices, our lives are improved by various applications supported by heterogeneous wireless technologies, such as WiFi and ZigBee. However, the coexistence of WiFi and ZigBee also results in the degradation of the network performance, which cannot be avoided if the WiFi devices are even unaware of the ambient ZigBee devices. To better accommodate the heterogeneous wireless devices, this paper presents X-Disco, the first cross-technology neighbor discovery mechanism, for a WiFi device to detect ZigBee neighbors, without modification to hardware or firmware. With the help of the recently proposed cross-technology communication, X-Disco enables a commodity WiFi device to trigger responses, containing ZigBee neighbor information, from the ambient ZigBee coordinators (including routers). Through exploring the WiFi PHY-layer information accessible by WiFi driver, X-Disco decodes the responded ZigBee messages and obtains the ZigBee neighbor information. To improve X-Disco's reliability, we also propose ZigBee neighbor validation and interruption mitigation to exclude hidden node terminals and mitigate the interference caused by the ambient WiFi traffic respectively. The evaluation of X-Disco is performed on the commodity devices (TP-Link WDR 4300 WiFi router, TelosB motes) and USRP B210. The results demonstrate X-Disco successfully detects nine ZigBee neighbors within 70ms in the office.

Motivated by an increasing interest in wireless networking in mission-critical applications, and a recent amendment of the time slotted channel hopping to IEEE 802.15.4, the multichannel delay sensitive scheduling is investigated in the many-to-one network, which is also known as the convergecast network. In such a network, each node has data to be transmitted to a gateway through multi-hop communications. As a realistic setting, packet release time at each node is not assumed to be uniform. Under this assumption, the goal of this work is to design a scheduling scheme that minimizes the schedule length and maximum end-to-end delay, in which the former is essential for repetitive data acquisition, whereas the later improves the freshness of the acquired data. To achieve the scheduling goal, the problem is formulated as a multi-objective integer programming. To obtain a feasible solution and gain an insight into the problem, a lower bound on the schedule length is derived. Based on that, a new scheduling scheme is designed to minimize the two objectives simultaneously. Link level simulations verify the performance improvement of the proposed scheme over the existing schemes.

IEEE 802.11ah and IEEE 802.15.4g are two wireless technologies designed for outdoor IoT applications. Both technologies have communication range up to 1000 meters. Therefore, 802.11ah network and 802.15.4g network are likely to coexist. Our simulation results show that using standard defined coexistence mechanisms, 802.11ah network can severely interfere with 802.15.4g network and lead to significant packet loss in 802.15.4g network. As a result, additional coexistence control mechanisms are needed. Due to asymmetrical features such as modulation scheme and frame structure, 802.11ah devices and 802.15.4g devices cannot perform automatic cooperation. Thus, self-coexistence control techniques are preferred. This paper proposes learning based self-coexistence control techniques for 802.11ah devices to mitigate the interference impact of 802.11ah network on 802.15.4g network. We first present a α-Fairness based energy detection clear channel assessment (ED-CCA) method that enables 802.11ah devices to detect more ongoing 802.15.4g packet transmissions. We then introduce a Q-Learning based backoff mechanism for 802.11ah devices to avoid interfering with 802.15.4g packet transmission process. The proposed coexistence techniques can achieve fair spectrum sharing between 802.11ah network and 802.15.4g network.

Vehicle-to-Pedestrian (V2P) communication using wireless LAN (Local Area Network) has issues. Fast Device Discovery is one of them. In this paper, we proposed two novel methods to solve this issue. The methods are Collective Scanning and Collective Scanning + Extension Receiving. Collective Scanning improves the scanning time by a vehicle which operates in one channel receives responses from all pedestrians which operate in available channels. Collective Scanning + Extension Receiving, is an extension method of Collective Scanning, improves the scanning time and prevents the detection leakage of pedestrians by a vehicle that extends waiting of responses depending on the number of responses from pedestrians. We evaluated two proposal methods compared with conventional Active Scanning of IEEE 802.11 about the scanning time and the detection rate of pedestrians using Network Simulator-3 (NS-3). In the result, by Collective Scanning, the scanning time improved 24.51 millisecond (ms) from 114.74 ms with the same detection rate in the environment that has one vehicle and within 50 pedestrians when comparing with Active Scanning of IEEE 802.11. By Collective Scanning + Extension Receiving, the scanning time improved 42.52 ms from 114.65 ms with the same detection rate in the environment that has one vehicle and more than 50 pedestrians when comparing with Active Scanning of IEEE 802.11.