Energy-efficient and robust-time synchronization is crucial for industrial Internet of things (IIoT). Some energy-efficient time synchronization schemes that achieve high accuracy have been proposed recently. However, some unsynchronized nodes namely isolated nodes exist in the schemes. To deal with the problem, this paper presents R-Sync, a robust time synchronization scheme for IIoT. We use a pulling timer to pull isolated nodes into synchronized networks whose initial value is set according to level of spanning tree. Then, another timer is set up to select backbone node and its initial value is related to the distance to parent node. Moreover, we do experiments based on simulation tool NS-2 and testbed based on wireless hardware nodes. The experimental results show that our approach makes all the nodes get synchronized and gets the better performance in terms of accuracy and energy consumption, compared with three existing time synchronization algorithms TPSN, GPA, STETS.

We analyze the power-saving operation in Third-Generation Partnership Project (3GPP) Long-Term Evolution Advanced (LTE Advanced) wireless networks. Typically, it is an exhausting and complicated job to numerically analyze the performance of power-saving operations since it is necessary to carefully consider every possible probability, make probability-generating functions, and differentiate these functions. Instead, we develop a totally new approach toward simple but accurate derivations. For this purpose, we divide the time period for the steady-state power-saving operation into several independent parts. Then, we analyze the power-saving operation in each part and thereafter combine the results into an aggregate result. The new approach enables us to avoid sophisticated steps while we reach an accurate analytical model. The equations are validated through comparison with simulation results.

In this paper, we study the network of unmanned aerial vehicles (UAVs) which acts as a relay between a base station and remotely deployed Internet of Things devices. UAVs have received much attention for connecting remotely located networks/objects, but there is a lack of study on multi-hop relay transmission schemes over UAV networks. It is particularly challenging because of the their high mobility and limited resources, to name a few. In this regard, we propose an energy-efficient, cooperative multi-hop relay scheme for UAVs. We formulate the optimal multi-hop transmission scheduling problem to minimizes the power consumption of UAVs without violating the given time constraint. We convert the initial formulation into a low-complex iterative algorithm, making it suitable for an online scheduling. Also, we propose a buffer prediction and correction scheme to initiate the multi-hop transmission scheduling without having the perfect buffered data information. Evaluation results show that the proposed scheme can energy-efficiently schedule the multi-hop transmissions over dynamic UAVs without violating the time constraints.

Channel asymmetry and high fluctuation of channel conditions are two salient characteristics of wireless channels in mobile environments. Therefore, when using IEEE 802.11 devices in mobile environments such as vehicular networks, it is critical to have an effective rate adaptation scheme that can deal with these issues. In this paper, we propose a practical rate adaptation scheme called RAM (rate adaptation in mobile environments) and implement it in the Madwifi device driver. RAM uses a receiver-based approach to handle channel asymmetry and a conservative SNR prediction algorithm to deal with high channel fluctuation. More importantly, RAM allows the receiver to convey the feedback information in a creative manner via ACK transmission rate variation, which does not require changes to the device firmware and hence is implementable at the device driver level. The effectiveness of RAM is demonstrated through experimental evaluation in indoor static and mobile environments and outdoor vehicular environments, as well as simulation study based on SNR traces collected from the experiments.

Wireless sensor networks are increasingly being employed for potentially hazardous and critical applications such as monitoring the gas concentration levels in a battle held. In such sensitive applications, it is vital to monitor closely the transient phenomenon and take requisite preventive and corrective actions, if necessary. In such scenarios, due to the presence of adversaries who intend to disrupt the functioning of the system, it becomes imperative to shield our system from false data injection attacks. We propose a novel secure statistical scheme, called SSTF to effectively monitor the transient phenomenon while being immune to false data injection attacks. For achieving our goals, we require the sensors to do a lightweight computation and report a simple statistical digest in addition to the current sensed reading. SSTF is a two-tier system consisting of a statistical inter-sensor testing framework, which is the kernel of our scheme, employed atop an enhanced version of a well-known existing security scheme. We present detailed theoretical analysis and in- depth simulations to show the effectiveness of SSTF.