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Wireless image sensor networks (WISNs) collect surveillance images, resulting in copious quantities of data requiring processing and transmission within the network. To reduce and balance energy expenditure during in-network image data processing and transmission, this study introduces an energy-saving strategy based on image super-resolution for WISNs assisted by cloud. The strategy constructs an image data processing and transmission system for WISNs, leveraging cloud infrastructure. By utilizing image quality feedback, the adaptive adjustment of image node sensing resolution is facilitated, minimizing image data transmission volume while ensuring high-quality super-resolution reconstructed image. The establishment of low-overhead, multipath transmission routes enables image nodes to transmit data in blocks, contingent upon neighboring transmission node statuses, thereby equalizing energy consumption for image data transmission. Cloud servers are employed to reconstruct high-resolution images and provide users with surveillance images that satisfy quality requisites. Empirical findings demonstrate that the proposed approach extends the lifetime of WISNs, furnishes users with superior-quality surveillance images, and markedly enhances network monitoring efficacy. [ABSTRACT FROM AUTHOR]

Employing mobile elements is an efficient solution to the performance improvement of wireless sensor networks (WSNs). We propose an efficient data gathering mechanism for disconnected WSNs with rendezvous points (DGM-RPs). The mobile sink traverses the entire network and stops only at the rendezvous points (RPs) while gathers the data from sensors in every disconnected segment. In this paper, mobile sinks perform the task of edge computing and alleviate the load of upper cloud. We measure the shape of disconnected segments, layering them by use of the convex hull, and then design the travelling path of the mobile sink to minimize the travel latency to visit all disconnected segments. At least one RPs will be selected in a segment firstly, and then, on this basis, we consider the distribution density of sensor nodes and the location of the RPs already exist to adding new RPs, which make good use of the margin to reducing the energy consumption and prolong the network lifetime. [ABSTRACT FROM AUTHOR]

Load balancing is of great significance to extend the longevity of wireless sensor networks, due to the inherent imbalanced energy overhead in such networks. However, existing solutions cannot balance the load distribution in partially disconnected wireless sensor networks. For example, if a network is partitioned into several segments with different area sizes, some areas have much more traffic load than other areas. In this article, we propose a load-balanced routing scheme, which aims to balance energy consumption within each segment and among different segments. First, we adopt unequal transmission distances to build initial routing for intrasegment load balancing. Second, we adopt the genetic algorithm to build extra routing between different segments for intersegment load balancing. The unique character of our work is twofold. On one hand, we investigate partitioned wireless sensor networks where there are several isolated segments. On the other hand, we pursue load balancing from a global perspective rather than from a local one. Some simulations verify the effectiveness and the advantages of our scheme in terms of extra deployment cost, system longevity, and load balancing degree. [ABSTRACT FROM AUTHOR]

The target nodes are k-covered by the sensor nodes; there will be a lot of redundant data forcing the phenomenon of congestion which lowers the network communication capability and coverage and accelerates network energy consumption. Therefore, this paper proposes an energy-efficient coverage control with multinodes redundancy verification (ECMRV). The algorithm constructs the coverage network model by using the positional relationship among the sensor nodes, and the proof procedure of the sector coverage expected value of the monitoring area also has been provided. On the aspect of the energy consumption, this paper gives the proportion of energy conversion functions between the working sensor nodes and the neighboring sensor nodes. And by using the function proportional to schedule the sensor nodes with low energy, we achieve the energy balance of the whole network and the optimization of the network resources. Finally, the simulation experiments indicate that this algorithm can not only improve the quality of network coverage, but completely inhibit the rapid energy consumption of the sensor nodes as well; as a result, the network lifetime extends, which has verified availability and stability of the algorithm in the paper. [ABSTRACT FROM AUTHOR]

In the process of fulfilling k-coverage over target nodes, a large quantity of redundant data may be produced, which will cause network congestion, reduce communication efficiency, impair coverage quality, and exhaust network energy quickly. To solve this problem, the paper proposes an Energy-Efficient k-Coverage Algorithm (EEKCA), which attempts to construct a network coverage model by utilizing the relative positions of nodes. Through analyzing the model, the coverage expectations for nodes in the monitored area and the minimum number of nodes required for full coverage are computed. As for power consumption, the paper presents an energy shifting function between working nodes and neighboring nodes, by use of which the scheduling for low-energy node is completed, balancing the energy consumption over the entire network and optimizing network resources. Finally, simulation results suggest that the proposed algorithm not only can improve the coverage quality of network but also can prevent the rapid depletion of node energy, thus achieving the goal of extending network lifetime. [ABSTRACT FROM AUTHOR]

In the process of the wireless sensor network research, the issue on the energy consumption and coverage is an essential and critical one. According to the characteristic of the sensor nodes, it is homogeneous, and we proposed the k-degree coverage algorithm based on optimization nodes deployment. First, the algorithm gives the solving procedure of the maximum seamless coverage ratio, when the three-node joint coverage has been provided. Second, when the sensor nodes are covering the monitoring area, the algorithm gives the solving procedure of the expected coverage quality and the judgment methods of the coverage ratio, when the nodes are compared with the nearby ones. And when there is redundancy coverage in the given monitoring area, we have given the solving procedure of any sensor nodes that exist in the redundant nodes coverage. Finally, using the simulation experiment, the results of the coverage algorithm based on optimization nodes deployment are compared with other algorithms in terms of the coverage quality and the network lifetime, the performance indexes have enhanced to 13.36% and 12.92% on average. Thus, the effectiveness and viability of the coverage algorithm based on optimization nodes deployment have been proved. [ABSTRACT FROM AUTHOR]