As a novel cyber-physical-social network paradigm, the internet of things(IoT) provides a powerful tool to monitor the hazardous fields of interest. Due to the uneven random deployment, sensor energy depletion and external attacks, the emergence of coverage holes would remarkably degrade the network performance and quality of service(QoS). For overcoming the drawbacks resulting from the coverage holes, this work focuses on how to locally detect coverage holes by exploiting onehop neighboring sensors’ cooperation based on the novel confident information coverage model(CIC), which is formulated as the Localized Confident Information Coverage Hole Detection(LCICHD) problem. For handling the CICHD problem, we devise a family of heuristic CIC holes detection schemes including the LCHD, LCHDRL, Random and RandomRL. Both the LCHD and LCHDRL schemes locally determine coverage status of each subregion and take the sensor communication ability into consideration. While the LCHDRL considers not only the sensor remaining energy but also the residual lifetime during the CIC hole detection. After acquiring the coverage status of each partitioned local subregion, the coverage hole boundary will be extracted by image processing techniques. For comparison, both the Random and RandomRL schemes arbitrarily select sensors within the sensing field to detect CIC holes, and the RandomRL scheme takes the sensors’ residual lifetime into consideration during the hole detection process. Experimental simulations show that the proposed schemes can efficiently detect the emerged coverage holes including the locations and the number, and the LCHDRL algorithm is more practical and efficient compared to the other three peer solutions.

The promising Industrial Internet of Things (IIoT) consisting of heterogeneous resource-restricted IoT nodes recently has attracted great attention from both academia and industry communities. However, the battery-powered, computing and communication resource-constrained and randomly uneven distributed features of the IoT nodes pose several great tough hurdles including the quality of services of real-time processing, energy efficiency, network lifetime and coverage holes to the IIoT-based industrial applications. To deal with these challenges, based on the emerging edge computing paradigm and the novel confident information coverage (CIC) model, this paper investigates how to relocate redundant IoT edge nodes to provide timely confident information coverage service in an offloading-assisted energy-balanced manner while extending the network lifetime, which is called as the CIC-based IoT edge node Relocation (CICENR) problem. To effectively handle the CICENR problem, we propose an offloading-assisted energy-balanced IoT edge node relocation approach (CIC-OAEBA) and the other CIC-based Direct Replacement Approach (CIC-DRA). Specially, the CIC-OAEBA adopts the Grid-Quorum strategy to quickly detect the redundant IoT edge nodes by offloading the communication-intensive and computing-intensive tasks from grid header nodes to peer IoT edge nodes, and make full use of the cascaded movement strategy to move the nearest redundant IoT edge nodes to the requesting CIC hole locations. Experimental results indicate the proposed approaches remarkably outperform other peer methods in terms of response time, energy efficiency, and especially the network lifetime and coverage performance.

The promising Internet of Things (IoT) provides a powerful platform for practical smart applications. The limited resources of the IoT nodes as well as the emerged coverage holes pose a great challenge on the Quality of Service (QoS) of the IoT. Mobile Edge Computing (MEC), which can improve IoT nodes energy consumption efficiency and optimize the utilization effectiveness of the limited resources, provides a novel view for coping with the challenge. Based on the MEC, this paper focuses on how to solve the problem of dispatch of mobile edge nodes for confident information coverage holes repairing (shorted as DMEN-CICHR) with the goal of maximizing the network lifetime and guaranteeing the network connectivity. To deal with the DMEN-CICHR problem, we develop an energy-balanced and obstacle-adaptive mobile edge node dispatch algorithm called EBOADMEN-CICHR, which restricts the mobile edge nodes from moving too long distance by setting a bound for each CIC hole and repeatedly updating the bound by a competition mechanism. To guarantee the network connectivity, the EBOADMEN-CICHR recursively performs breadth first search (BFS) on a constructed undirected graph to find all disconnected subgraphs and then dispatches some mobile edge nodes to connect those disconnected subgraphs until the whole network is connected. A number of experiments emulating the realistic scenarios in radiological pollution monitoring in uranium tailings are executed to verify the effectiveness of the proposed EBOADMEN-CICHR solution. Experimental results show the EBOADMEN-CICHR can perform better than other peer methods in term of higher energy efficiency and longer network lifetime.

Network lifetime and coverage are the key evaluation metrics of Wireless Sensor Networks (WSNs). Aiming at network lifetime, Hierarchical Clustering-task Scheduling Policy (HCSP) breaks the traditional clustering framework, but it doesnt fully consider the network coverage problem. We propose a Hierarchical Clustering Node Collaborative Scheduling (HCNCS) protocol that optimizes HCSP to extend the network lifetime and improves the coverage performance of WSNs by nodes collaborative sensing. According to the deployment location, HCNCS classifies nodes into Node Collaborative Sensing Disks(NCSDs), which as units for data sensing and transmission. Nodes are rotated in WSNs to balance the energy consumption and through collaborative sensing to improve the coverage of NCSDs. In addition, HCNCS constrains the number of clusters by NCSDs classification based on K-means to reduce the communication energy consumption of clustering. Based on the HCNCS, this paper further proposes an Enhanced Hierarchical Clustering Node Collaborative Scheduling (EHCNCS) protocol. Compared with HCNCS, EHCNCS selects NCSDs according to Node Collaborative Scheduling (NCS) algorithm after clustering, which improves the coverage capability of NCSDs at the cost of increasing a small amount of the communication energy consumption. EHCNCS also rotates Cluster Heads (CHs) by the CH rotation candidate table to balance network energy consumption. The extensive simulations show that HCNCS has an obvious advantage over HCSP in terms of network lifetime and network coverage. Compared with HCNCS, EHCNCS significantly prolongs the network lifetime of WSNs at the expense of a bit of coverage performance.