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coverage optimization for Directional Sensor Networks: A Novel Sensor Redeployment Scheme

IEEE INTERNET OF THINGS JOURNAL 2023年第2期10卷 1461-1475页

作者： Cai, Xuelian Wang, Luqiao Hui, Yilong Chen, Yue Yue, Wenwei Wang, Hui Zhang, Yao Cheng, Nan Li, Changle Xidian Univ Res Inst Smart Transportat State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Northwestern Polytech Univ Dept Comp Sci Xian 710072 Peoples R China

The ever-growing Internet of Things (IoT) provides a powerful means for complex and changeable environmental monitoring. Directional sensor networks (DSNs), as a typical architecture of IoT, can efficiently facilitate various digital and intelligent IoT applications. In the DSNs, due to the asymmetry in coverage focus and diversity in detection angle of the directional IoT sensors, how to enhance the coverage performance with the limited sensors becomes a new challenge. To this end, we develop a novel sensor redeployment scheme based on the minimum exposure path (MEP) to optimize the coverage performance of the DSNs. Specifically, we first propose a minimum exposure path searching algorithm based on the particle swarm optimization (MEP-PSO) algorithm with the target of obtaining the MEP in the DSNs. With this algorithm, the traditional MEP problem can be analyzed and simplified by conducting the grid discretization and building the weighted undirected graph. Then, an MEP-based coverage optimization (MEP-CO) algorithm is proposed to determine the optimal deployment locations and the dispatch sensors so that the IoT sensors can be dynamically redeployed to achieve the coverage optimization. After that, we derive the formula for the coverage upper bound (CUB) and develop a CUB algorithm to provide a benchmark for evaluating the effectiveness of different coverage optimization algorithms. Simulation results demonstrate that the proposed coverage optimization scheme can significantly promote the minimum exposure value (MEV) and coverage ratio of the monitoring area compared with the existing algorithms.

关键词： coverage optimization directional sensor networks (DSNs) Internet of Things (IoT) minimum exposure path (MEP)

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coverage optimization and Spatial Load Balancing by Robotic Sensor Networks

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2010年第3期55卷 749-754页

作者： Cortes, Jorge Univ Calif San Diego Dept Mech & Aerosp Engn La Jolla CA 92093 USA

This technical note studies robotic sensor networks performing static coverage optimization with area constraints. Given a density function describing the probability of events happening and a performance function measuring the cost to service a location, the objective is to position sensors in the environment so as to minimize the expected servicing cost. Moreover, because of load balancing considerations, the area of the region assigned to each robot is constrained to be a pre-specified amount. We characterize the optimal configurations as center generalized Voronoi configurations. The generalized Voronoi partition depends on a set of weights, one per robot, assigned to the network. We design a Jacobi iterative algorithm to find the weight assignment whose corresponding generalized Voronoi partition satisfies the area constraints. This algorithm is distributed over the generalized Delaunay graph. We also design the "move-to-center-and-compute-weight" strategy to steer the robotic network towards the set of center generalized Voronoi configurations while monotonically optimizing coverage.

关键词： coverage optimization generalized Voronoi partitions robotic sensor networks servicing problems space partitioning

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coverage optimization and Simulation of Wireless Sensor Networks Based on Particle Swarm optimization

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INTERNATIONAL JOURNAL OF WIRELESS INFORMATION NETWORKS 2020年第2期27卷 307-316页

作者： Zhang, Ye Xinxiang Univ Sch Elect & Mech Engn Xinxiang 453000 Henan Peoples R China

As a new type of measurement and control network, wireless sensor networks (WSNs) technology has the characteristics of diversity and wide practicability. Based on the characteristics of WSNs, wireless sensor networks are widely used in military and civil industries. However, due to the frequent changes in the basic topology of wireless sensor networks and the relatively small number of corresponding network nodes, the efficiency of the nodes is the reason for its further development. Therefore, the node distribution strategy and the corresponding network coverage optimization strategy of wireless sensor networks are of great significance to achieve energy saving and network life extension. In order to solve the above WSNs problems, this paper will analyze and simulate the coverage optimization of wireless sensor networks based on Improved Particle Swarm optimization algorithm. Firstly, this paper will analyze the structure characteristics of wireless sensor networks, complete the WSNs network coverage model and get the corresponding functions. Then this paper innovatively proposes "external dispersion method" to solve the problem of local area overlap in WSNs network coverage. At the same time, it innovatively proposes "free-particle swarm optimization" to solve the local convergence of conventional particle swarm optimization. At the end of this paper, simulation experiments are carried out to compare the optimal particle swarm optimization algorithm with the traditional particle swarm optimization algorithm. The experiments show that the proposed algorithm has obvious advantages in convergence and coverage.

关键词： Wireless sensor networks coverage optimization External decentralization Stochastic particle swarm optimization coverage optimization model

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coverage optimization in DSL Networks by Low-Complexity Discrete Spectrum Balancing

Coverage Optimization in DSL Networks by Low-Complexity Disc...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Wolkerstorfer, Martin Nordstrom, Tomas FTW Telecommun Res Ctr Vienna Donau City Str 1 A-1220 Vienna Austria

ISBN: (纸本)9781424492688

Spectrum balancing is an established optimization approach in multi-carrier digital subscriber line (DSL) systems. It has previously been applied to very different performance objectives such as sum-rate, min-rate, or fairness maximization and sum-power minimization. In this work we study the maximization of the service coverage, which will be defined as the number of DSL lines which can be granted an operator-specified high-bandwidth service. The proposed algorithm is based on a previously described mathematical decomposition framework. We extend this framework for our new problem and enhance its scalability by various low-complexity heuristics. Simulations demonstrate the applicability of our algorithm for DSL networks of realistic sizes. More precisely, our results obtained in thousand 25 user near-far DSL scenarios show an average gain in service coverage of more than 13% compared to state-of-the-art sumrate maximizing spectrum balancing algorithms.

关键词： Complexity theory DSL DSL lines DSL networks Heuristic algorithms Mathematical model optimization Resource management Search problems coverage optimization digital subscriber lines low-complexity discrete spectrum balancing mathematical decomposition framework multicarrier digital subscriber line systems operator-specified high-bandwidth service optimisation service coverage

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coverage optimization of Field Observation Instrument Networking Based on an Improved ABC Algorithm 8th

Coverage Optimization of Field Observation Instrument Networ...

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8th International Conference on Pioneering Computer Scientists, Engineers and Educators (ICPCSEE)

作者： Deng, Xingyue Huo, Jiuyuan Wu, Ling Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Peoples R China Lanzhou Ruizhiyuan Informat Technol Co LTD Lanzhou 730070 Peoples R China

ISBN: (纸本)9789811952098;9789811952081

The severe conditions of cold and arid areas seriously affect the progress of data collection and analysis for field observation instruments. Therefore, this study adopted the modified artificial bee colony (ABC) algorithm to optimize the coverage of nodes and designed an energy-efficient node coverage optimization method. In the coverage optimization, the coverage rate and the number of working nodes are considered comprehensively, and the fitness value calculation is improved. The experimental results reveal that the modified ABC algorithm has better coverage optimization performance than the original ABC algorithm, genetic algorithm (GA), and particle swarm optimization (PSO) algorithm.

关键词： Field observation instrument networking Wireless sensor network ABC algorithm coverage optimization

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coverage optimization for DVB-T2 SFNs Using ITU-R P. 1546 and ITU-R P. 1812 10

Coverage Optimization for DVB-T2 SFNs Using ITU-R P. 1546 an...

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10th IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Anedda, M. Anedda, A. Murroni, M. Univ Cagliari Dept Elect & Elect Engn I-09123 Cagliari Italy

ISBN: (纸本)9781479958665

In this paper, two available propagation prediction methods for point-to-area terrestrial services in the VHF-UHF bands are compared: ITU-R P.1546 and ITU-R P.1812. This work allows evaluating the path-specific propagation prediction method that best approximates effective and real radio-wave propagation in single frequency networks (SFN) for digital video broadcasting (DVB). Multipath interference (MPI) minimization at receiver antenna is obtained through the static delay adjustment, antenna gain, elevation orientation and azimuth. MPI minimization and thus, coverage optimization have been reached using the heuristic genetic algorithm (GA). Simulation results show that the methods compared provide different propagation prediction performances according to different geography of territory. The proposed approach has been validated for DVB-T2 SFN transmitters network planning in Sardinia island (Italy), Basque Country (Spain) and Flanders (Belgium).

关键词： ITU-R DVB-T2 OFDM receivers SFNs genetic algorithm coverage optimization

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coverage optimization for Minimization of Drive Tests in LTE with Extended RLF Reporting

Coverage Optimization for Minimization of Drive Tests in LTE...

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21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Puttonen, Jani Turkka, Jussi Alanen, Olli Kurjenniemi, Janne Magister Solut Ltd Jyvaskyla 40700 Finland

ISBN: (纸本)9781424480166

In this article we have studied the coverage optimization for 3G Long Term Evolution (LTE) according to Minimization of Drive Tests (MDT) work item description in Third Generation Partnership Project (3GPP). Target for the MDT work item is to define a set of measurements and measurement reporting procedures, so that operators are able to collect measurement data from users and thereby reducing need for manual drive tests. The main focus of MDT is coverage optimization. We propose an extended Radio Link Failure (RLF) reporting for both coverage and mobility optimization use cases for MDT. In this paper the MDT studies and especially the benefits of extended RLF reporting and classification are analyzed by means of dynamic system level simulations. The RLFs are classified into three categories based on the content in extended RLF reports: coverage, handover parameterization and interference problem. It can be concluded that the coverage as well as other problems may be identified with quite high probability with only a minimal standardization effort.

关键词： 3G Long Term Evolution 3G mobile communication 3G partnership project LTE Long Term Evolution MDT coverage optimization extended RLF reporting failure analysis minimization of drive test mobility optimization optimisation probability probability radio link failure radio links

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coverage optimization for Dense Deployment Small Cell Based on Ant Colony Algorithm 80

Coverage Optimization for Dense Deployment Small Cell Based ...

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80th IEEE Vehicular Technology Conference (VTC Fall)

作者： Han, Rui Feng, Chunyan Xia, Hailun Wu, Yaguang Beijing Univ Posts & Telecommun Beijing Key Lab Network Syst Architecture & Conve Beijing 100088 Peoples R China

ISBN: (纸本)9781479944491

Dense deployment of small cell in heterogeneous networks (HetNet) is considered as a promising way to cope with the exponential growth in mobile traffic demand. In such scenario, coverage optimization is a challenge due to the unplanned deployment and plug-and-play feature of small cell. In this paper, the coverage performance of the network is analyzed under different deployment density of small cells. Then the coverage problem is modeled as a cost function which includes the inappropriate coverage ratio of the network. After that, the ant colony algorithm (ACA) is applied to find the optimal pilot Tx power of each small cell through the minimization of the cost function. Finally, compared to the fixed coverage scheme, the proposed algorithm can not only reduce the ratio of coverage hole but also the proportion of coverage overlap as well.

关键词： coverage optimization small cell networks ant colony algorithm

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coverage optimization for Femtocell Clusters using Modified Particle Swarm optimization

Coverage Optimization for Femtocell Clusters using Modified ...

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IEEE International Conference on Communications (ICC)

作者： Huang, Liang Zhou, Yiqing Hu, Jinlong Han, Xue Shi, Jinlin Chinese Acad Sci Inst Comp Technol Wireless Commun Technol Res Ctr Beijing 100190 Peoples R China

ISBN: (纸本)9781457720536

coverage optimization is a main challenge for femtocell clusters which are considered to be a promising solution to provide seamless cellular coverage for large indoor areas. Although particle swarm optimization (PSO) can be employed to solve the coverage optimization of femtocell clusters, it reduces to single particle swarm optimization (SPSO) when only one femtocell cluster is considered and can only find the local optimum solution. In this paper, a modified PSO (MPSO) algorithm is proposed, which employs a heuristic power control scheme to guide the algorithm to search for the global optimum solution. Simulation results show that MPSO significantly outperforms SPSO and fixed power scheme with low complexity. Moreover, MPSO can converge rapidly and is suitable for online coverage optimization.

关键词： Femtocell Femtocell Cluster coverage optimization Particle Swarm optimization

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coverage optimization of Mobile Sensor Networks Based Improved Beetle Antennae Search Algorithm 4

Coverage Optimization of Mobile Sensor Networks Based Improv...

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4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS)

作者： Liu, Huanxiao Song, Dapeng Wang, Jun Yang, Xiaofei Liu, Wei Ye, Hui Zhenjiang Vocat Tech Coll Sch Informat Engn Zhenjiang Jiangsu Peoples R China Jiangsu Univ Sci & Tech Sch Elect & Informat Zhenjiang Jiangsu Peoples R China

ISBN: (纸本)9781728162072

In order to effectively improve the coverage ratio of the mobile sensor networks, an optimization method based the Improved Beetle Antennae Search (IBAS) algorithm is proposed. The beetle can use the left and right "tentacle" to smell and search for food. Firstly, in the search phase, improved search step length and random direction function are introduced into the algorithm to balance the global and local exploration capability, which can effectively avoid falling into the local optimum. Secondly, the detection strategy based on the current optimal value is adopted to improve the coverage ratio and evenness ratio of mobile sensor network. Finally, simulation experiment and discussion are made. The results show that, compared with other algorithms, our algorithm not only can improve the coverage ratio, but also make the node coverage distribution more evenness.

关键词： Mobile Sensor Network coverage optimization Beetle Antenna Search Intelligent Algorithm

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