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Electricity is an indispensable resource in daily life. While it brings great convenience to people, it also brings some safety hazards, especially in the event of power failure, which may cause significant harm. Therefore, monitoring and warning of power faults are very important. Traditional power grounding fault monitoring and warning systems have problems such as untimely monitoring, inaccurate warning, and high error rates in fault location. In order to solve the above problems, this paper uses wireless networks to construct a power grounding fault monitoring and early warning system. The wireless network collected fault data based on the complexity of power grounding fault data, and used threshold monitoring method to analyze the collected data. The wireless network was used to construct a prediction model to monitor grounding faults. Through experiments, it can be found that the accuracy of the wireless network-based power fault monitoring system for predicting grounding faults was over 92.57%, and the average warning accuracy of 20 experiments was 93.856%. This paper studied a wireless network-based algorithm for monitoring and warning of power grounding faults, which can effectively improve the monitoring and warning capabilities of power systems, and reduce the risk of power equipment faults and the probability of power accidents.

Mobile Backbone Wireless Networks (MBWN) [10] are wireless networks in which the base stations are mobile. Our strategy is the following: mobile nodes are dynamically grouped into clusters of bounded radius. In the very large wireless networks we deal with we deal with, several hundreds of clusters may be generated. Clustering makes use of a two dimensional Euclidean version of the Antipole Tree data structure [5]. This very effective structure was originally designed for finite sets of points in an arbitrary metric space to support efficient range searching. It requires only a linear number of pair-wise distance calculations among nodes. Mobile Base Stations occupy an approximate centroid of the clusters and are moved according to a fast practical bipartite matching algorithm which tries to minimize both total and maximum distance. We show that the best known computational geometry algorithms [1] become infeasible for our application when a high number of mobile base stations is required. On the other hand our proposed 8% average error solution requires O(k log k) running time instead of the approximatively O(k²) exact algorithm [1]. Communication among nodes is realized by a Clusterhead Gateway Switching Routing (CGSR) protocol [15] where the mobile base stations are organized in a suitable network. Other efficient clustering algorithms [11, 17] may be used instead of the Antipole Tree. However the nice hierarchical structure of the Antipole Tree makes it applicable to other types of mobile wireless (Ad-Hoc) and wired networks but this will be subject of future work.

This paper deals with an important problem of mobile communication. The objective is to place k base stations of equal range on the boundary of a convex polygonal region P such that each point inside P is covered by at least one base station. We name this problem as region-cover(k) problem. A simplified form of this problem is the vertex-cover(k) problem, where the objective is to communicate with only the vertices of P instead of covering the entire polygon. We first present efficient algorithms for vertex-cover(2) and region-cover(2) problems, where the base stations are to be installed on a pair of specified edges. The time complexity of these algorithms are O(n log n) and O(n²) respectively, where n is the number of vertices in the polygon P. Next, we consider the case where k ≥ 3. We first concentrate on a restricted version of the vertex-cover(k) and region-cover(k) problems, where all the k base stations are to be installed on the same edge of P. Our proposed algorithm for the restricted vertex-cover(k) problem produces optimum result in O(min(n²,nk log n)) time, whereas the algorithm for the restricted region-cover(k) problem produces an (1 + ∊)-factor approximation result in time. Finally, we propose efficient heuristic algorithm for the unrestricted version of the region-cover(k) problem for k ≥ 3. Experimental results demonstrate that our proposed algorithm runs fast and produces near optimum solutions.

We propose a model of dynamically evolving random networks and give an analytical result of the cover time of the simple random walk algorithm on a dynamic random symmetric planar point graph. Our dynamic network model considers random node distribution and random node mobility. We analyze the cover time of the parallel random walk algorithm on a complete network and show by numerical data that k parallel random walks reduce the cover time by almost a factor of k. We present simulation results for four random walk algorithms on random asymmetric planar point graphs. These algorithms include the simple random walk algorithm, the intelligent random walk algorithm, the parallel random walk algorithm, and the parallel intelligent random walk algorithm. Our random network model considers random node distribution and random battery transmission power. Performance measures include normalized cover time, probability distribution of the length of random walks, and load distribution.

Many real-world networks are essentially heterogeneous, where the nodes have different abilities to gain connections. Such networks are difficult to be embedded into low-dimensional Euclidean space if we ignore the heterogeneity and treat all the nodes equally. In this paper, based on a newly defined heterogeneous distance and a generalized network distance under the constraints of network and triangle inequalities, respectively, we propose a new heterogeneous multidimensional scaling method (HMDS) to embed different networks into proper Euclidean spaces. We find that HMDS behaves much better than the traditional multidimensional scaling method (MDS) in embedding different artificial and real-world networks into Euclidean spaces. Besides, we also propose a method to estimate the appropriate dimensions of Euclidean spaces for different networks, and find that the estimated dimensions are quite close to the real dimensions for those geometrical networks under study. These methods thus can help to better understand the evolution of real-world networks, and have practical importance in network visualization, community detection, link prediction and localization of wireless sensors.

For the impact of the bitrate change of video streaming services according to the available bandwidth on user satisfaction, in this paper, we propose a spatial and temporal feature-based reduced reference (RR) quality assessment for rate-varying videos in wireless networks called STRQAW. First, simulating the orientation selectivity mechanism of the human visual system (HVS), the histogram of the orientation selectivity-based visual pattern in each frame is extracted as the spatial feature. The histogram similarity between the rate-varying video and the original video is computed as the spatial metric. Second, we extract the temporal variation of the DCT coefficients of the consecutive frame differences as the temporal feature. The temporal variation similarity between the rate-varying video and the original video is calculated as the temporal metric. Finally, we take into account the recency effect and assess the overall quality by combining the temporal and spatial metric. The experimental results using the Laboratory for Image and Video Engineering (LIVE) mobile video quality assessment (VQA) database show that STRQAW is consistent with the subjective assessment results, which means it reflects human subjective feelings well and it provides an evaluation for adjusting compression-coding rates in real time. STRQAW can be used to guide video application providers and network operators working towards satisfying end-user experiences.

In this paper, the bifurcation analysis software, DDE-BIFTOOL, is employed to analyze the Hopf bifurcation of the wireless network congestion model with state-dependent round trip delay. Hopf bifurcations are investigated for the four typical work conditions. The corresponding stable and unstable bifurcating periodic solutions are quantitatively and qualitatively verified by nonlinear simulation software, WinPP, respectively, which agree with those of DDE-BIFTOOL very well. The results imply that the channel loss probabilities $P_{ul}$ and $P_{dl}$ can play a more important role than the speed of the network, i.e. the related link bandwidth $C$. For larger $P_{ul}$ and $P_{dl}$ in Cases 3 and 4, the smaller $T_p$ and $K$ can induce Hopf bifurcation. This will result in the loss of stability and performance degradation. So $P_{ul}$ and $P_{dl}$ should be set smaller to avoid congestion, providing a sound theoretical basis and instructions for the congestion control of the wireless network.

One of the fundamental issues in sensor networks is the coverage problem, which reflect-show well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the servicearea of the sensor network is covered by at least α sensors, where ff is a given parameter andthe sensing regions of sensors are modeled by balls (not necessarily of the same radius). This problem in a 2D space is solved in [10] with an efficient polynomial-time algorithm (in termsof the number of sensors). In this paper, we show that tackling this problem in a 3D space is still feasible within polynomial time. Further, the proposed solution can be easily translated intoan efficient polynomial-time distributed protocol. We demonstrate an application of the derived result by proposing an energy-conserving scheduling protocol.

This work investigates distributed transmission scheduling in wireless networks. Due to interference constraints, “neighboring links” cannot be simultaneously activated, otherwise transmissions will fail. Here, we consider any binary model of interference. We use the model described by Bui et al. in [L. X. Bui, S. Sanghavi and R. Srikant, Distributed link scheduling with constant overhead, IEEE/ACM Trans. Netw.17(5) (2009) 1467–1480; S. Sanghavi, L. Bui and R. Srikant, Distributed link scheduling with constant overhead, in Proc. ACM Sigmetrics (San Diego, CA, USA, 2007), pp. 313–324.]. We assume that time is slotted and during each slot there are two phases: one control phase in which a link scheduling algorithm determines a set of non-interfering links to be activated, and a data phase in which data is sent through these links. We assume random arrivals on each link during each slot, so that a queue is associated to each link. Since nodes do not have a global knowledge of the queues sizes, our aim (like in [L. X. Bui, S. Sanghavi and R. Srikant, Distributed link scheduling with constant overhead, IEEE/ACM Trans. Netw.17(5) (2009) 1467–1480; S. Sanghavi, L. Bui and R. Srikant, Distributed link scheduling with constant overhead, in Proc. ACM Sigmetrics (San Diego, CA, USA, 2007), pp. 313–324.]) is to design a distributed link scheduling algorithm. To be efficient, the control phase should be as short as possible; this is done by exchanging control messages during a constant number of mini-slots (constant overhead). In this paper, we design the first fully distributed local algorithm with the following properties: it works for any arbitrary binary interference model; it has a constant overhead (independent of the size of the network and the values of the queues), and it does not require any knowledge of the queue-lengths. We prove that this algorithm gives a maximal set of active links, where for any non-active link there exists at least one active link in its interference set. We also establish sufficient conditions for stability under general Markovian assumptions. Finally, the performance of our algorithm (throughput, stability) is investigated and compared via simulations to that of previously proposed schemes.

Indoor localization for livestock is important as it facilitates effective monitoring and management of animals within confined spaces, such as barns or stables. By accurately tracking the position of individual animals, farmers and livestock managers can gain valuable insights into their behavior, health, and welfare. This information enables the early detection of potential issues, such as diseases or injuries, allowing for prompt intervention and treatment. While GPS sensors offer global position estimation, they are limited to outdoor environments and inherently exhibit inaccuracies of several meters. In indoor spaces, alternative sensors like lasers and cameras can estimate positions, but they necessitate maps and substantial computational resources to process complex algorithms. Presently, Wireless Networks (WN) are extensively accessible in indoor environments, providing efficient global localization with relatively low cost and computing demands. This paper presents a novel approach to estimate the location of cows in a given area using Deep Neural Networks (DNNs) applied to LQI data. This method aims to improve the efficiency of livestock management, particularly in large-scale farming operations, by enabling precise tracking and monitoring of individual animals. Our proposed model leverages data from wireless sensor networks (WSNs) and demonstrates promising results in terms of accuracy and computational efficiency. This study contributes to the ongoing research in smart agriculture and the application of advanced technologies in the livestock industry.

Cyber security is the term used to describe the processes and technologies designed to protect computers, networks, data and programs from unauthorized access, damage or attack. Many businesses pay lots of attention to security concerns. For these reasons this research has been undertaken. Ad-hoc networks are crucial enablers of next-generation communications. Such networks can be formed and reconfigured dynamically and they can be mobile, standalone or internetworked with other networks. Mobile Ad-hoc Networks (MANETs) are established by a group of autonomous nodes that communicate with each other by establishing a multi-hop radio network and maintaining connectivity in an infrastructure-less manner. The security of the connections between devices and networks is crucial. The important challenges of supporting multimedia applications in an ad-hoc network are the security issues. In this chapter, a new and efficient media-aware security framework will be designed for facilitating various multimedia applications in ad-hoc networks over the Internet.

Existing work on demand-driven-based wireless environments has largely focused on energy-efficient caching strategies. While these schemes minimize the number of uplink requests (and hence conserve energy), they are still not adequate as clients must continue to monitor the broadcast for data that is not found in the cache or has been invalidated. Other work on disseminating data via periodic broadcasting of the data file has developed techniques that organize data to allow clients to selectively tune to the desired portion of the broadcast. Such schemes, unfortunately, cannot be applied to demand-driven-based context because demand-driven data cannot be predetermined. In this paper, we study the issue of selective tuning in a demand-driven-based environment. We propose and study three strategies that allow clients to repeatedly toggle between doze mode and active mode until the desired objects are obtained. One of the strategies is stateful-based in the sense that the server is aware of the schedule of doze-off/awake time determined by the clients. The other two strategies are stateless-based approaches where the clients' schedules of doze-off/awake time depend on cues broadcast by the server. We conducted a performance study and our results demonstrate that the proposed schemes are energy efficient without sacrificing on the average access times of object retrievals. Furthermore, our results show that none of the algorithms is superior in all cases.

This paper describes a wireless spectral sensing network (WSSN) applied in mushroom workshops, which is capable of measuring the near infrared spectrum and the environmental parameters. With the sensing ability of chemical compositions, the WSSN can be used to provide scientific guidance for mushroom cultivation. As the network's core unit, the spectral sensing node uses, uniquely, a new monolithically integrated multichannel spectral sensor (MCSS). A multichannel integrated narrow-band filter array, an uncooled InGaAs detector array and a readout circuit are integrated into the MCSS. Benefiting from the monolithic design of MCSS, the size and complexity of the spectral sensing node is reduced. A field programmable gate array (FPGA) is used to control the whole measurement process and wireless communication. The discussion in this paper focuses on the design and performance of the spectral sensing node.

Safety message transmission is a key issue in wireless networking as it concerns people's lives. The Enhanced Distributed Channel Access (EDCA) mechanism defined in IEEE 802.11e is used in a variety of networks as Medium Access Control (MAC) protocol which concerns the transmission of safety messages. However, due to the random nature of the default parameters of Contention Window (CW) in EDCA, safety messages would be deprived of their chance to access the channel due to low-priority traffic when the two collide. In addition, the priority classification in EDCA is universal and it is not perfectly appropriate for specific applications in some emergency scenarios. To address the above issues, this paper proposes a mechanism called Absolute EDCA (AEDCA). The word “absolute” refers to the guaranteed absolute priority status of safety messages. To ensure fast access and transactions while providing reliable service, the scheme adopts a reclassified priority category. Based on the new priority classification, an AEDCA algorithm to avoid the randomness of backoff's influence on high-priority traffic is proposed. Meanwhile, in order to accommodate and implement the algorithm, a CW parameter adjustment strategy is designed. Simulation results illustrate that the AEDCA scheme can provide more reliable transmission of safety messages and achieve better performance in terms of packet delivery ratio, delay and throughput.

The minimum Steiner tree problem has wide application background, such as transportation system, communication network, pipeline design and VISL, etc. It is unfortunately that the computational complexity of the problem is NP-hard. People are common to find some special problems to consider. Since the complexity of the Steiner tree problem, the almost of papers are relate to the object of small data problem, i.e., the number of involved objects is small. Those conclusions are useful to the theoretical research from which some algorithms are originated. For the practical problems, there are large number of objects are need to be considered. How to find the more optimal approximate algorithm is the reason of paper. We want to find the more optimal approximate approach by the analysis of the different cases.