Underwater wireless sensor networks are currently seeing broad research in various applications for human benefits. Large numbers of sensor nodes are being deployed in rivers and oceans to monitor the underwater environment. In the paper, we propose an energy-efficient clustering multi-hop routing protocol (EECMR) which can balance the energy consumption of these nodes and increase their network lifetime. The network area is divided into layers with regard to the depth level. The data sensed by the nodes are transmitted to a sink via a multi-hop routing path. The cluster head is selected according to the depth of the node and its residual energy. To transmit data from the node to the sink, the cluster head aggregates the data packet of all cluster members and then forwards them to the upper layer of the sink node. The simulation results show that EECMR is effective in terms of network lifetime and the nodes’ energy consumption.

In recent years, intelligent transportation systems, which provide safety and autonomous services on the road using the Internet and cellular technologies, have become increasingly important. Vehicles are equipped with sensors that can transmit data to other vehicles or infrastructure according to different types of services. In order to ensure robust connectivity for safety services, the transmission among vehicles requires low latency, high reliability, and high packet delivery ratio. With the increased number of vehicles, more frequency resources are needed to establish fast and reliable services. In the area of high vehicle density, the demand of frequency resources is increasing to establish stable connectivity in a short time. However, the amount of frequency resources is limited; the resource allocation scheme (RAS) should effectively assign a resource block to each user to ensure the quality of service. In this paper, we present a comprehensive survey of RASs for the 5G-based vehicular networks known as 5G V2X. We also discuss the challenges and opportunities for resource allocation in modern vehicular networks and present numerous promising future research directions.

A wireless body area sensor network (WBASN) consists of a coordinator and multiple sensors to monitor the biological signals and functions of the human body. This exciting area has motivated new research and standardization processes, especially in the area of WBASN performance and reliability. In scenarios of mobility or overlapped WBASNs, system performance will be significantly degraded because of unstable signal integrity. Hence, it is necessary to consider interference mitigation in the design. This survey presents a comparative review of interference mitigation schemes in WBASNs. Further, we show that current solutions are limited in reaching satisfactory performance, and thus, more advanced solutions should be developed in the future.

Herein, we propose a hybrid multi-channel medium access control (HM-MAC) protocol for wireless body area networks (WBANs) that mitigates inter-WBAN interference significantly. In HM-MAC, a superframe consists of a random access phase and a scheduled access phase. That is, a carrier sensing multiple access with collision avoidance (CSMA/CA) phase and a time division multiple access (TDMA) phase are included in a superframe. The random access phase allows higher-priority users to transmit data packets with low latency and high reliability. The retransmission of data packets is also performed in the random access phase. The periodic data are transmitted in the scheduled phase, resulting in no contention and high reliability. A channel selection algorithm is also proposed to avoid collision between neighboring WBANs. The HM-MAC protocol allows multiple transmissions simultaneously on different channels, resulting in high throughput and low collision. The sensor nodes update idle channels by listening to the beacon signal; consequently, the sensor nodes can change the working channel to reduce inter-WBAN interference. According to our simulation results, HM-MAC achieves a higher packet delivery ratio and higher throughput with lower energy consumption than the conventional scheme in multi-WBAN scenarios. HM-MAC also causes lower end-to-end delays for higher-priority users.

Currently, wireless body area networks (WBANs) are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS) algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.

As wireless body area networks (WBANs) become a key element in electronic healthcare (e-healthcare) systems, the coexistence of multiple mobile WBANs is becoming an issue. The network performance is negatively affected by the unpredictable movement of the human body. In such an environment, inter-WBAN interference can be caused by the overlapping transmission range of nearby WBANs. We propose a link scheduling algorithm with interference prediction (LSIP) for multiple mobile WBANs, which allows multiple mobile WBANs to transmit at the same time without causing inter-WBAN interference. In the LSIP, a superframe includes the contention access phase using carrier sense multiple access with collision avoidance (CSMA/CA) and the scheduled phase using time division multiple access (TDMA) for non-interfering nodes and interfering nodes, respectively. For interference prediction, we define a parameter called interference duration as the duration during which disparate WBANs interfere with each other. The Bayesian model is used to estimate and classify the interference using a signal to interference plus noise ratio (SINR) and the number of neighboring WBANs. The simulation results show that the proposed LSIP algorithm improves the packet delivery ratio and throughput significantly with acceptable delay.