The Social Internet of Things (SIoT) is a modern paradigm of technology characterized by the convergence of the Internet of Things and social networks. Since the interaction of an object with a person or another object is enabled by smart sensors, wireless rechargeable sensor networks (WRSNs) play an important role in advancing SIoT technology. This paper proposes an improved grid-based joint routing and charging algorithm (IGRC) to implement path planning for a mobile charger, aiming to achieve energy balance in WRSNs by providing real-time charging services. The network is divided into multiple uniform square rings in IGRC. The mobile charger first starts from the center of the network and employs the Nearest Neighbor method to visit nodes in the three inner square rings, then moves along the edge of the outer rings and stops at every vertex to charge the nodes in the outer rings. The charging time allocated for each square ring can be accurately calculated based on various energy consumption rates. IGRC ensures that every node can replenish its energy before falling below a critical threshold. Simulation results demonstrate that IGRC outperforms S-CURVES(ad) and GRC in regards to energy balancing and node survival rate.

In a resource-constrained wireless sensor network, energy efficiency is a principle issue for monitoring the movement of continuous objects, such as wild fire and hazardous chemical material. In this paper, a continuous object tracking scheme with two-layer grid model (TGM-COT) is proposed. To address the problem of boundary distortion caused by uneven node distribution, we put forward a novel mechanism for boundary nodes identification. Furthermore, a streamlining mechanism is designed to reduce the amount of uploaded data. Simulation results demonstrate that, without sacrificing additional energy consumption, TGM-COT is able to achieve high tracking accuracy and significantly reduce the communication overhead.

Wireless charging techniques provide a more flexible and promising way to solve the energy constraint problem in industrial wireless rechargeable sensor networks (IWRSNs). Although considerable research has been done on wireless charging algorithms, most of it only focuses on passively replenishing nodes having insufficient energy. In this paper, we propose a grid-based joint routing and charging algorithm for IWRSNs to solve the charging problem in a proactive way. On the one hand, a new routing protocol is designed according to charging characteristics of the charger to achieve local energy balance. On the other hand, different charging times are allocated at different charging points on the basis of energy consumption caused by the routing process to achieve global energy balance. Simulation results verify superiority of our proposed algorithm in solving the balancing energy problem and improving survival rates of nodes.

Traditional Industrial Wireless Sensor Networks (IWSNs) are constrained by limited battery energy. Recent breakthroughs in wireless power transfer have inspired the emergence of Industrial Wireless Rechargeable Sensor Networks (IWRSNs). IWRSNs usually contain one or more mobile chargers which can traverse the network to replenish energy supply for sensor nodes. The essential problem in mobile energy provisioning is to find the optimum path along which the mobile chargers travel to improve charging performance, prolong the battery lifespan of nodes and reduce the charging latency as much as possible. In this paper, we introduce and analyze the impacts of four traveling paths, namely, SCAN, HILBERT, S-CURVES(ad) and Z-curve on energy provisioning for IWRSNs. This evaluation aims to embody effective and essential properties that a superior traveling path should possess. Our simulations show that S-CURVES(ad) outperforms the other traveling paths in the lifetime of nodes and traveling efficiency. And at the same time, it has relatively small charging latency.

Recently underwater acoustic sensor networks (UASNs) have drawn much attention because of their great value in many underwater applications where human operation is hard to carry out. In this paper, we introduce and compare the performance of four localization algorithms in UASNs, namely, distance vector-hop (DV-hop), a new localization algorithm for underwater acoustic sensor networks (NLA), large-scale hierarchical localization (LSHL), and localization scheme for large scale underwater networks (LSLS). The four algorithms are all suitable for large-scale UASNs. We compare the localization algorithms in terms of localization coverage, localization error, and average energy consumption. Besides, we analyze the impacts of the ranging error and the number of anchor nodes on the performance of the localization algorithms. Simulations show that LSHL and LSLS perform much better than DV-hop and NLA in localization coverage, localization error, and average energy consumption. The performance of NLA is similar to that of the DV-hop. The advantage of DV-hop and NLA is that the localization results do not rely on the number of anchor nodes; that is, only a small number of anchor nodes are needed for localization.

Recently, heterogeneous wireless sensor network (HWSN) routing protocols have drawn more and more attention. Various HWSN routing protocols have been proposed to improve the performance of HWSNs. Among these protocols, hierarchical HWSN routing protocols can improve the performance of the network significantly. In this paper, we will evaluate three hierarchical HWSN protocols proposed recently—EDFCM, MCR, and EEPCA—together with two previous classical routing protocols—LEACH and SEP. We mainly focus on the round of the first node dies (also called the stable period) and the number of packets sent to sink, which is an important aspect to evaluate the monitoring ability of a protocol. We conduct a lot of experiments and simulations on Matlab to analyze the performance of the five routing protocols.

Recently Underwater Wireless Sensor Networks have rapidly developed and been widely adopted to meet all kinds of applications, while they are exposed to an open underwater environment which is particularly vulnerable to various attacks, among which Sybil attack is one of the most common and harmful one. In this case, it is urgent to find an effective method to detect the Sybil attack. Our paper puts forward a novel scheme based on state information of nodes to detect the Sybil attack. We implement the feature of our scheme through both by numerical analysis and simulation performance in MATLAB. And the simulation results demonstrate that the detecting accuracy can be up to 94 percent. Our proposed scheme can efficiently detect the Sybil nodes.

With the development of various underwater applications, localization techniques of large-scale Underwater Wireless Sensor Networks (UWSNs) have played a more and more important role in these applications. In this paper, we introduce three localization algorithms for large-scale UWSNs: Node Discovery and Localization Protocol (NDLP), Large-Scale Hierarchical Localization Approach (LSHL) and Localization Scheme for Large Scale underwater networks (LSLS). They are all distributed and range-based localization schemes. Moreover, we compare the localization algorithms in three parameters: localization coverage, localization error and average energy consumption. The simulation results demonstrate that LSLS outperforms LSHL and NDLP in terms of localization coverage. LSHL has lower localization error and energy consumption than LSLS in given conditions. NDLP has higher localization error and energy consumption than LSLS and LSHL, but it performs relatively well when the communication range of nodes is big enough.