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86th IEEE Vehicular Technology Conference (VTC-Fall)

作者： Chou, Shih-Fan Yen, Hsiu-Wen Chen, Yen-Ju Pang, Ai-Chun Ho, Ting-Wu Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei Taiwan Natl Taiwan Univ Grad Inst Networking & Multimedia Taipei Taiwan Acad Sinica Res Ctr Informat Technol Innovat Taipei Taiwan ITRI Informat & Communicat Res Lab Hsinchu Taiwan

ISBN: (纸本)9781509059355

The rapid growth in multimedia services and diverse mobile technologies have recently brought about sudden surges in traffic demands. To keep up with this trend, small cells are considered as a promising solution to supplement macrocell coverage and enhance network capacity in next generation cellular networks. However, the isotropic characteristics of conventional omni-directional antennas installed in small cells reveal a trade-off between coverage and power consumption. Boosted power levels allow for larger coverage areas while resulting in serious interference among cells. On the other hand, although weak power emissions can mitigate interference, coverage holes may appear instead. To overcome the physical limitations, a beamforming technique called switched multi-element antenna (SMEA) is introduced in this work, which is capable of shaping kinds of radiation patterns toward desired users. We propose an efficient radiation pattern selection scheme using SMEA, with the objective of maximizing the total number of served users within the coverage ranges of small cells. We then construct a series of simulations to evaluate the performance of our proposed scheme. Compared with a uniform power control scheme using omnidirectional antenna and a distributed pattern selection scheme using SMEA, simulation results show that our proposed scheme can significantly enhance coverage and deal with the trade-off issue as well.

关键词： small cell switched multi-element antenna coverage maximization cellular networks

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Centralized Algorithms for Redundant coverage maximization in Wireless Visual Sensor Networks

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IEEE LATIN AMERICA TRANSACTIONS 2016年第7期14卷 3378-3384页

作者： da Silva, T. F. Costa, D. G. Univ Estadual Feira de Santana PGCA Feira de Santana Brazil

Visual sensors can be used to retrieve still images or video streams in a large set of monitoring applications, providing valuable information of the monitored environment. In fact, camera-enabled sensors are directional and the viewed area depends on their orientations. As the positions and orientations of the embedded cameras may not be optimal after deployment, the area viewed by sensors may be adjusted using some optimization algorithm. Although the problem of coverage optimization has been addressed by some research works, coverage maximization arises as a challenging problem where the number of camera views over a set of targets has to be maximized for higher availability and increased number of viewed perspectives of targets. This paper proposes centralized algorithms to compute orientations of rotatable cameras to achieve maximized coverage in wireless visual sensor networks, bringing significant results to this research area.

关键词： Wireless Visual Sensors Networks Redundant Visual coverage coverage maximization

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Environment Learning-Based coverage maximization With Connectivity Constraints in Mobile Sensor Networks

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IEEE SENSORS JOURNAL 2016年第10期16卷 3958-3971页

作者： Duc Van Le Oh, Hoon Yoon, Seokhoon Univ Ulsan Dept Elect & Comp Engn Ulsan 44610 South Korea Natl Univ Singapore Dept Comp Sci Singapore 119077 Singapore

This paper takes into consideration the problems related to monitoring a phenomenon of interest in an unknown and open environment using multiple mobile sensor (MS) nodes. We propose an environment learning-based phenomenon monitoring system that iteratively learns about the environment and relocates MS nodes to optimal positions, where MS nodes can attain a high weighted sensing coverage and maintain network connectivity. In this paper, finding optimal positions for MS nodes is defined as the connectivity-constrained coverage maximization problem. An integer linear programming optimization formulation is proposed to find the solution. We also propose three heuristics algorithms to efficiently solve the connectivity-constrained coverage maximization problem. Simulation results show that the proposed algorithms outperform other approaches in terms of the weighted coverage efficiency and energy efficiency.

关键词： Connectivity maintenance coverage maximization environment learning mobile sensor network phenomenon monitoring

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MMSCM: A multiple mobile sinks coverage maximization based hierarchical routing protocol for mobile wireless sensor networks

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IET COMMUNICATIONS 2023年第10期17卷 1228-1242页

作者： Liu, Chun Guo, Liping Hubei Univ Technol Coll Comp Sci Wuhan Peoples R China Hubei Univ Technol Coll Comp Sci Wuhan 430000 Peoples R China

Mobile wireless sensor network (MWSN) adapts to the requirements of mobility of civil and military network devices and has received a lot of attention. Designing an efficient, low-energy, and fault-tolerant routing protocol for the frequently changing topology of highly mobile MWSNs is challenging. Most routing protocols today only support the movement of sensor nodes or only sink. This paper proposes a Multiple Mobile Sinks coverage maximization based hierarchical routing protocol for mobile wireless sensor networks (MMSCM), which allows sensor nodes and sinks to move simultaneously. The MMSCM divides the monitoring area into virtual grids and deploys a movable sink in each grid cell. Sink selects the appropriate next hop for each cluster head in the area to build an optimal routing forest and collects data from all routing tree root nodes at a uniform speed along the specified path with maximum coverage. Simulation results show that, compared with current advanced routing algorithms, the MMSCM protocol can better solve the network delay problem and improve data throughput while extending the network life cycle, which is more suitable for time-sensitive application scenarios.

关键词： coverage maximization hierarchical routing mobile sensor nodes mobile sink WSN

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Privacy Preserving Participant Recruitment for coverage maximization in Location Aware Mobile Crowdsensing

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2022年第9期21卷 3250-3262页

作者： Li, Liang Shi, Dian Zhang, Xinyue Hou, Ronghui Yue, Hao Li, Hui Pan, Miao Xidian Univ Sch Cyber Engn Xian 710071 Shaanxi Peoples R China Chinese Acad Sci Inst Comp Technol State Key Lab Comp Architecture Beijing 100080 Peoples R China Univ Houston Dept Elect & Comp Engn Houston TX 77204 USA San Francisco State Univ Dept Comp Sci San Francisco CA 94132 USA

Mobile crowdsensing has emerged as a promising paradigm where location-based sensing tasks are outsourced to mobile participants carrying sensor-equipped devices. A critical issue of crowdsensing is to guarantee the sensing coverage by appropriately recruiting participants, which requires participants' precise locations and thus raises privacy concerns. In this paper, we are motivated to develop a privacy preserving participant recruitment scheme for mobile crowdsensing, which maximizes the spatial coverage of the sensing range while protecting participants' location privacy against an untrusted crowdsensing platform. Briefly, we propose a utility-assured location obfuscation mechanism operated in a hexagonal grid system, which the participants can follow to locally perturb their locations with personalized privacy demands. Given the obfuscated locations, we efficiently solve a coverage-maximized participant recruitment problem with the budget constraint by using a deterministic rounding algorithm. Considering the existence of biased sensing data incurred by location obfuscation, we further develop a fault-aware crowdsensing framework to improve the robustness of the recruitment strategy, where a constant-approximation algorithm is applied to select participants against any number of unqualified sensing results. Extensive simulations on real-world location datasets and Uber's geospatial indexing system validate the efficacy of our location obfuscation mechanism and participant recruitment schemes in mobile crowdsensing systems.

关键词： Privacy Crowdsensing Sensors Recruitment Task analysis Differential privacy Robustness Mobile crowdsensing location differential privacy coverage maximization approximation algorithm

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A Molecular Force-Based Deployment Algorithm for Flight coverage maximization of Multi-Rotor UAV

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2019年第3-4期95卷 1063-1078页

作者： Wang, Xi Tan, Guanzheng Liu, Xiya Zhao, Zhixiang Cent South Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China

This paper presents a molecular force-based deployment algorithm of charging stations according to the principle of intermolecular forces in physics to expand the flight coverage of electric-powered multi-rotor Unmanned Aerial Vehicles (UAV). With the help of this algorithm, a multi-rotor UAV can reach anywhere in the specific area by charging at the charging station several times. In this algorithm, a number of equal circles are used to cover the specific area (in a two-dimensional plane), and the center of each circle denotes a charging station. The radius of these circles is equal to the radius of action of the UAV. The number of the circles is set by the users. Under the combined effect of three virtual forces, the centers of the circles, called nodes, keep moving within the specific area, and multiple iterations are performed to adjust the location of each node. Finally, a proper deployment scheme for the charging stations is generated, which can achieve the working area maximization of the UAV by a certain number of charging stations. Simulation experiments were executed, and the results under different conditions show that the proposed algorithm can meet the expected requirements and has an advantage over three other algorithms in terms of coverage ratio. The experiment results also indicate that in the case of dense node density, the proposed algorithm has a better coverage performance than the case of sparse node density. The experimental data are available at . The codes will be published later.

关键词： Molecular force UVA coverage maximization Node deployment

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MCCM: An Approach for Connectivity and coverage maximization

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FUTURE INTERNET 2020年第2期12卷 19-19页

作者： Ghaddar, Alia Bou Hatoum, Monah Fadlallah, Ghassan Mcheick, Hamid Int Univ Beirut Dept Comp Sci Beirut 146404 Lebanon Lebanese Univ Dept Comp Sci Rafic Hariri Educ Campus Beirut 146404 Lebanon Univ Quebec Chicoutimi Dept Comp Sci Chicoutimi PQ G7H 2B1 Canada

The internet of Things (IoT) has attracted significant attention in many applications in both academic and industrial areas. In IoT, each object can have the capabilities of sensing, identifying, networking and processing to communicate with ubiquitous objects and services. Often this paradigm (IoT) using Wireless Sensor Networks must cover large area of interest (AoI) with huge number of devices. As these devices might be battery powered and randomly deployed, their long-term availability and connectivity for area coverage is very important, in particular in harsh environments. Moreover, a poor distribution of devices may lead to coverage holes and degradation to the quality of service. In this paper, we propose an approach for self-organization and coverage maximization. We present a distributed algorithm for "Maintaining Connectivity and coverage maximization" called MCCM. The algorithm operates on different movable devices in homogeneous and heterogeneous distribution. It does not require high computational complexity. The main goal is to keep the movement of devices as minimal as possible to save energy. Another goal is to reduce the overlapping areas covered by different devices to increase the coverage while maintaining connectivity. Simulation results show that the proposed algorithm can achieve higher coverage and lower nodes' movement over existing algorithms in the state of the art.

关键词： coverage maximization connectivity wireless sensor networks (WSNs) heterogeneous devices Internet of Things (IoT)

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CMHWN: coverage maximization of Heterogeneous Wireless Network 16

CMHWN: Coverage Maximization of Heterogeneous Wireless Netwo...

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16th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA)

作者： Mcheick, Hamid Hatoum, Monah Shouki Bou Ghaddar, Alia Univ Quebec Chicoutimi Dept Comp Sci Chicoutimi PQ Canada Lebanese Univ Dept Comp Sci Hadat Lebanon Int Univ Beirut Dept Comp Sci Beirut Lebanon

ISBN: (纸本)9781728150529

Two of the main challenges in wireless sensor networks (WSNs) are connectivity and coverage. Connectivity keeps different nodes in the network linked and to exchange data. coverage affects the efficiency of the operating sensors used in the network. This paper proposes a novel resilient incremental algorithm that improves the coverage of randomly distributed mobile devices within a heterogeneous or homogeneous environment. This algorithm guarantees connectivity by ensuring at least 2-connected neighbors for any device in the network. Results showed up to 89% coverage improvement in a heterogeneous environment and up to 99% coverage improvement in a homogeneous environment.

关键词： Internet of Things Heterogeneous and homogeneous environments coverage maximization Connectivity Wireless Sensor Network

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Area coverage maximization of Multi UAVs Using Multi-Agent Reinforcement Learning 3

Area Coverage Maximization of Multi UAVs Using Multi-Agent R...

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3rd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)

作者： Wijaya, Glenn B. Tamba, Tua A. Parahyangan Catholic Univ Dept Elect Engn Bandung Indonesia

ISBN: (纸本)9798350307573;9798350307566

A method to maximize the total coverage of multiple unmanned aerial vehicles (UAVs) which monitor a bounded space is presented. The goal of all UAVs is to maximize their individual coverage while minimize possible coverage overlaps among them. This goal is achieved using a multi-agent reinforcement learning (MARL) method which is embedded with a coordination strategy that allows several UAVs to negotiate their actions to avoid possible overlaps between their coverage. Simulation results are shown to illustrate the developed MARL scheme's performance.

关键词： Multi-UAV systems coverage maximization reinforcement learning

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Self-Tuning Sectorization: Deep Reinforcement Learning Meets Broadcast Beam Optimization

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2020年第6期19卷 4038-4053页

作者： Shafin, Rubayet Chen, Hao Nam, Young-Han Hur, Sooyoung Park, Jeongho Zhang, Jianzhong Reed, Jeffrey H. Liu, Lingjia Samsung Res Amer Plano TX 75023 USA Virginia Tech Bradley Dept Elect & Comp Engn Wireless VT Blacksburg VA 24061 USA Samsung Res Amer Stand & 5G Mobil Innovat Lab Plano TX 75023 USA Mavenir Richardson TX USA Samsung Elect Air Technol Lab Suwon 443742 South Korea

Beamforming in multiple input multiple output (MIMO) systems is one of the key technologies for modern wireless communication. Creating appropriate sector-specific broadcast beams are essential for enhancing the coverage of cellular network and for improving the broadcast operation for control signals. However, in order to maximize the coverage, patterns for broadcast beams need to be adapted based on the users' distribution and movement over time. In this work, we present self-tuning sectorization: a deep reinforcement learning framework to optimize MIMO broadcast beams autonomously and dynamically based on users' distribution in the network. Taking directly UE measurement results as input, deep reinforcement learning agent can track and predict the UE distribution pattern and come up with the best broadcast beams for each cell. Extensive simulation results show that the introduced framework can achieve the optimal coverage, and converge to the oracle solution for both single sector and multiple sectors environment, and for both periodic and Markov mobility patterns.

关键词： MIMO communication Cellular networks Antenna arrays Azimuth Wireless communication Interference MIMO sectorization broadcast beams coverage maximization self-organizing networks deep reinforcement learning

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