Pervasive and Mobile Computing最新文献_第6页

Inferring in-air gestures in complex indoor environment with less supervision 在监管较少的情况下推断复杂室内环境中的空中手势

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-03-08 DOI: 10.1016/j.pmcj.2024.101904

Zhongkai Deng , Qizhen Zhou , Jianchun Xing , Qiliang Yang , Yin Chen , Hu Zhang , Zhaoyi Chen , Deyu Deng , Yixin Mo , Bowei Feng

{"title":"Inferring in-air gestures in complex indoor environment with less supervision","authors":"Zhongkai Deng , Qizhen Zhou , Jianchun Xing , Qiliang Yang , Yin Chen , Hu Zhang , Zhaoyi Chen , Deyu Deng , Yixin Mo , Bowei Feng","doi":"10.1016/j.pmcj.2024.101904","DOIUrl":"10.1016/j.pmcj.2024.101904","url":null,"abstract":"<div><p>People have high demands for comfort and technology in indoor environments. Gestures, as a natural and friendly human computer interaction (HCI) method, have received widespread attention and have been the subject of many research studies. Traditional approaches are based on wearable devices and cameras, which can be cumbersome to operate and infringe upon users’ privacy. Millimeter-wave (mmWave) radar avoids these problems by detecting gestures in a noninvasive manner. However, it encounters practical challenges in complex indoor environments, such as dynamic disturbance from surroundings, variable usage conditions and diverse gesture patterns, which conventionally require considerable manual effort to address. In this paper, we attempt to minimize human supervision and propose a noninvasive gesture recognition method named RaGe that involves a commercial mmWave indoor radar. First, a parameter optimization framework considering gesture prior constraints is proposed for radar configuration, which functions to weaken the disturbance from surroundings. Second, we alleviate data shortages in variable usage conditions and achieve low-cost data augmentation by applying affine transformations. Third, we combine deformable convolution operations with an unsupervised attention mechanism, thus exploring the intrinsic features involved in diverse gesture patterns. Experimental results show that RaGe is able to recognize 7 gestures with 99.3% accuracy and less human supervision, surpassing the state-of-the-art methods in comparative experiments.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"100 ","pages":"Article 101904"},"PeriodicalIF":4.3,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140105443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An evaluation of heart rate monitoring with in-ear microphones under motion 对运动状态下使用耳内麦克风进行心率监测的评估

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-03-07 DOI: 10.1016/j.pmcj.2024.101913

Kayla-Jade Butkow , Ting Dang , Andrea Ferlini , Dong Ma , Yang Liu , Cecilia Mascolo

{"title":"An evaluation of heart rate monitoring with in-ear microphones under motion","authors":"Kayla-Jade Butkow , Ting Dang , Andrea Ferlini , Dong Ma , Yang Liu , Cecilia Mascolo","doi":"10.1016/j.pmcj.2024.101913","DOIUrl":"10.1016/j.pmcj.2024.101913","url":null,"abstract":"<div><p>With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate detection systems. Heart rate is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable heart rate monitoring with wearable devices has therefore gained increasing attention in recent years. Existing heart rate detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time <em>in-ear audio-based motion-resilient</em> heart rate monitoring. We first collected heart rate-induced sounds in the ear canal using an in-ear microphone under seven stationary activities and two full-body motion activities (i.e., walking, and running). Then, we devised a novel deep learning based motion artefact (MA) mitigation framework to denoise the in-ear audio signals, followed by a heart rate estimation algorithm to extract heart rate. With data collected from 15 subjects over nine activities, we demonstrate that hEARt, our end-to-end approach, achieves a mean absolute error (MAE) of 1.88 ± 2.89 BPM, 6.83 ± 5.05 BPM, and 13.19 ± 11.37 BPM for stationary, walking, and running, respectively, opening the door to a new non-invasive and affordable heart rate monitoring with useable performance for daily activities. Not only does hEARt outperform previous in-ear heart rate monitoring work, but it outperforms reported in-ear PPG performance.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"100 ","pages":"Article 101913"},"PeriodicalIF":4.3,"publicationDate":"2024-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1574119224000397/pdfft?md5=1d87af00a83a5ca4188bd2b75b510b82&pid=1-s2.0-S1574119224000397-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140105447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Role of IoT technologies in big data management systems: A review and Smart Grid case study 物联网技术在大数据管理系统中的作用：综述与智能电网案例研究

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-29 DOI: 10.1016/j.pmcj.2024.101905

A.R. Al-Ali , Ragini Gupta , Imran Zualkernan , Sajal K. Das

{"title":"Role of IoT technologies in big data management systems: A review and Smart Grid case study","authors":"A.R. Al-Ali , Ragini Gupta , Imran Zualkernan , Sajal K. Das","doi":"10.1016/j.pmcj.2024.101905","DOIUrl":"https://doi.org/10.1016/j.pmcj.2024.101905","url":null,"abstract":"<div><p>Empowered by Internet of Things (IoT) and cloud computing platforms, the concept of smart cities is making a transition from conceptual models to development and implementation phases. Multiple smart city initiatives and services such as Smart Grid and Smart Meters have emerged that have led to the accumulation of massive amounts of energy big data. Big data is typically characterized by five distinct features namely, volume, velocity, variety, veracity, and value. To gain insights and to monetize big data, data has to be collected, stored, processed, analyzed, mined, and visualized. This paper identifies the primary layers of a big data architecture with start-of-the-art communication, storage, and processing technologies that can be utilized to gain meaningful insights and intelligence from big data. In addition, this paper gives an in-depth overview for research and development who intend to explore the various techniques and technologies that can be implemented for harnessing big data value utilizing the recent big data specific processing and visualization tools. Finally, a use case model utilizing the above mentioned technologies for Smart Grid is presented to demonstrate the energy big data road map from generation to monetization. Our key findings highlight the significance of selecting the appropriate big data tools and technologies for each layer of big data architecture, detailing their advantages and disadvantages. We pinpoint the critical shortcomings of existing works, particularly the lack of a unified framework that effectively integrates these layers for smart city applications. This gap presents both a challenge and an opportunity for future research, suggesting a need for more holistic and interoperable solutions in big data management and utilization.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"100 ","pages":"Article 101905"},"PeriodicalIF":4.3,"publicationDate":"2024-02-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140030431","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LICAPA: Lightweight collective attestation for physical attacks detection in highly dynamic networks LICAPA：在高动态网络中检测物理攻击的轻量级集体认证

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-21 DOI: 10.1016/j.pmcj.2024.101903

Ziyu Wang , Cong Sun

{"title":"LICAPA: Lightweight collective attestation for physical attacks detection in highly dynamic networks","authors":"Ziyu Wang , Cong Sun","doi":"10.1016/j.pmcj.2024.101903","DOIUrl":"10.1016/j.pmcj.2024.101903","url":null,"abstract":"<div><p>UAVs or vehicular networks have been extensively used in different domains. Such a system network consists of various heterogeneous and mobile devices operating autonomously and cooperatively to provide flexible services. However, ensuring devices’ runtime integrity has always been critical to such highly dynamic and disruptive networks. Collective attestation is a popular technique in ensuring service integrity on remote devices. However, the physical attacks pose significant threats to the enforcement of the runtime integrity, and the existing detection approaches raise a considerable number of false positives, which impede the robustness of the network. We propose LICAPA, a collective attestation framework for detecting physical attacks with high accuracy. LICAPA can detect a device under physical attack with the timestamps signed by other recently-attested devices. Such a proof-from-others mechanism provides more knowledge about the compromised device for physical attack detection. It reduces the potential false positives compared with the state-of-the-art approaches. LICAPA provides a physical-adversary-tolerant runtime device joining mechanism and a new attestation report aggregation scheme to reduce the storage and communication cost of the device. On the prototype implementation of the trust anchor, we evaluate LICAPA’s computational costs. The simulation results demonstrate LICAPA’s low communication cost and long resistance time against false detection on physical attack. LICAPA reduces the overall swarm attestation cost by over 20% compared with SALAD (<em>Secure and Lightweight Attestation of Highly Dynamic and Disruptive Networks</em>) and PASTA (<em>Practical Attestation Protocol for Autonomous Embedded Systems</em>).</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"99 ","pages":"Article 101903"},"PeriodicalIF":4.3,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1574119224000294/pdfft?md5=16eb6fb6c8f2a44387364de5b0970a87&pid=1-s2.0-S1574119224000294-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139920781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient and secure heterogeneous online/offline signcryption for wireless body area network 无线体域网络的高效安全异构在线/离线签名加密

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-10 DOI: 10.1016/j.pmcj.2024.101893

Huihui Zhu, Chunhua Jin, Yongliang Xu, Guanhua Chen, Liqing Chen

{"title":"Efficient and secure heterogeneous online/offline signcryption for wireless body area network","authors":"Huihui Zhu, Chunhua Jin, Yongliang Xu, Guanhua Chen, Liqing Chen","doi":"10.1016/j.pmcj.2024.101893","DOIUrl":"10.1016/j.pmcj.2024.101893","url":null,"abstract":"<div><p>As a special Internet of Things (IoT) application, the wireless body area network (WBAN) has gained widespread attention by medical institutions. However, existing schemes for WBAN data transmission lack heterogeneity support across certificateless cryptosystem (CLC) and public key infrastructure (PKI), resulting in issues like key escrow or complicated certificate management. In addition, for performance reasons, conventional signcryption protocols are unsuitable for WBAN applications. To address these gaps and enable secure and efficient sensitive data transmission from WBAN sensors to hospital servers, we design a heterogeneous online/offline signcryption scheme. Our scheme enables patients’ sensors implanted or worn to encrypt sensitive data in CLC and send it to the hospital server in PKI system. The CLC avoids key escrow issue while the PKI increases scalability. We minimize the online computational cost of WBAN sensors by dividing signcryption into offline and online phases, with time-consuming operations in the offline phase. Furthermore, we formally prove the security of our scheme and evaluate its performance. Results show our scheme has advantages in supporting heterogeneity across CLC and PKI with low computational costs, making it uniquely suitable for the protection of data privacy in WBAN applications compared to existing protocols.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"99 ","pages":"Article 101893"},"PeriodicalIF":4.3,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139893128","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PSO based Amorphous algorithm to reduce localization error in Wireless Sensor Network 基于 PSO 的 Amourphous 算法减少无线传感器网络中的定位误差

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-10 DOI: 10.1016/j.pmcj.2024.101890

Pujasuman Tripathy, P.M. Khilar

{"title":"PSO based Amorphous algorithm to reduce localization error in Wireless Sensor Network","authors":"Pujasuman Tripathy, P.M. Khilar","doi":"10.1016/j.pmcj.2024.101890","DOIUrl":"10.1016/j.pmcj.2024.101890","url":null,"abstract":"<div><p>In recent years, localizing or identifying the position of unknown sensor nodes has become an essential problem in Wireless Sensor Networks (WSN). The improvement in localization accuracy leads to obtaining the exact location of the dumb node. Among all localization algorithms, Amorphous localization is highly suggested for usage in many application domains due to its simplicity, viability, low cost, and zero additional hardware requirements. Position estimation of the dumb node in the Amorphous algorithm considers three different practical scenarios, such as the position of dumb nodes falling within the range of anchor nodes, the position of the dumb node being in the opposite direction of the anchor node, and the position of the dumb node not within the range of anchor node. However, the localization error generated by the Amorphous algorithm is high. To address the limitations of Amorphous algorithm we have proposed a PSO based Amorphous algorithm. The proposed work reduces the average hop size of anchor nodes and reduces the localization error. The simulation results demonstrate that, in comparison to other existing Amorphous algorithms, the proposed PSO based Amorphous localization algorithm produced a superior performance in terms of MAE, MSE and RMSE.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"100 ","pages":"Article 101890"},"PeriodicalIF":4.3,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139822193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

TODO: Task Offloading Decision Optimizer for the efficient provision of offloading schemes TODO：任务卸载决策优化器，用于有效提供卸载方案

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-10 DOI: 10.1016/j.pmcj.2024.101892

Shilin Chen , Xingwang Wang , Yafeng Sun

{"title":"TODO: Task Offloading Decision Optimizer for the efficient provision of offloading schemes","authors":"Shilin Chen , Xingwang Wang , Yafeng Sun","doi":"10.1016/j.pmcj.2024.101892","DOIUrl":"10.1016/j.pmcj.2024.101892","url":null,"abstract":"<div><p>As the volume of data stored on local devices increases, users turn to edge devices to help with processing tasks. Developing offloading schemes is challenging due to the varying configurations of edge devices and user preferences. While traditional methods provide schemes for offloading in various scenarios, they face unavoidable challenges, including the requirement to manage device workloads in real-time, significant computational costs, and the difficulty of balancing multi-objectives in offloading schemes. To solve these problems, we propose the Task Offloading Decision Optimizer, which offers efficient multi-objective offloading schemes that consider real-time device workload and user preference. The proposed offloading scheme contains three goals: reducing task execution time, decreasing device energy consumption, and lowering rental costs. It comprises two essential parts: Scheme Maker and Scheme Assistor. Scheme Maker utilizes deep reinforcement learning, optimizes the internal architecture, and enhances the performance of the operation. It optimizes buffer storage to generate dependable multi-objective offloading schemes considering real-time environmental conditions. Scheme Assistor utilizes the data in the Scheme Maker buffer to enhance efficiency by reducing computational costs. Extensive experiments have proved that the proposed framework efficiently provides offloading schemes considering the real-time conditions of the devices and the users, and it offers offloading schemes that enhance task completion rate by 50%. Compared to the baseline, the task execution time is reduced by 12%, and the device energy consumption is reduced by 11.1%.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"99 ","pages":"Article 101892"},"PeriodicalIF":4.3,"publicationDate":"2024-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139812680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reinforcement learning-based load balancing for heavy traffic Internet of Things 基于强化学习的大流量物联网负载均衡

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-08 DOI: 10.1016/j.pmcj.2024.101891

Jianjun Lei, Jie Liu

{"title":"Reinforcement learning-based load balancing for heavy traffic Internet of Things","authors":"Jianjun Lei, Jie Liu","doi":"10.1016/j.pmcj.2024.101891","DOIUrl":"https://doi.org/10.1016/j.pmcj.2024.101891","url":null,"abstract":"<div><p>Aiming to large-scale data transmission requirements of resource-constrained IoT (Internet of Things) devices, the routing protocol for low power lossy network (RPL) is expected to handle the load imbalance and high energy consumption in heavy traffic scenarios. This paper proposes a novel <strong>R</strong>PL routing optimization <strong>A</strong>lgorithm based on deep <strong>R</strong>einforcement <strong>L</strong>earning (referred to as RARL), which employs the centralized training and decentralized execution architecture. Hence, the RARL can provide the intelligent parent selection policy for all nodes while improving the training efficiency of deep reinforcement learning (DRL) model. Furthermore, we integrate a new local observation into the RARL by exploiting multiple routing metrics and design a comprehensive reward function for enhancing the load-balance and energy efficiency. Meanwhile, we also optimize the Trickle timer mechanism for adaptively controlling the delivery of DIO messages, which further improves the interaction efficiency with environment of DRL model. Extensive simulation experiments are conducted to evaluate the effectiveness of RARL under various scenarios. Compared with some existing methods, the simulation results demonstrate the significant performance of RARL in terms of network lifetime, queue loss ratio, and packet reception ratio.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"99 ","pages":"Article 101891"},"PeriodicalIF":4.3,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139748870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel IoT trust model leveraging fully distributed behavioral fingerprinting and secure delegation 利用全分布式行为指纹和安全授权的新型物联网信任模型

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-08 DOI: 10.1016/j.pmcj.2024.101889

Marco Arazzi , Serena Nicolazzo , Antonino Nocera

{"title":"A novel IoT trust model leveraging fully distributed behavioral fingerprinting and secure delegation","authors":"Marco Arazzi , Serena Nicolazzo , Antonino Nocera","doi":"10.1016/j.pmcj.2024.101889","DOIUrl":"https://doi.org/10.1016/j.pmcj.2024.101889","url":null,"abstract":"<div><p>The pervasiveness and high number of Internet of Things (IoT) applications in people’s daily lives make this context a very critical attack surface for cyber threats. The high heterogeneity of involved entities, both in terms of hardware and software characteristics, does not allow the definition of uniform, global, and efficient security solutions. Therefore, researchers have started to investigate novel mechanisms, in which a super node (a gateway, a hub, or a router) analyzes the interactions of the target node with other peers in the network, to detect possible anomalies. The most recent of these strategies base such an analysis on the modeling of the fingerprint of a node behavior in an IoT; nevertheless, existing solutions do not cope with the fully distributed nature of the referring scenario.</p><p>In this paper, we try to provide a contribution in this setting, by designing a novel and fully distributed trust model exploiting point-to-point devices’ behavioral fingerprints, a distributed consensus mechanism, and Blockchain technology. In our solution we tackle the non-trivial issue of equipping smart things with a secure mechanism to evaluate, also through their neighbors, the trustworthiness of an object in the network before interacting with it. Beyond the detailed description of our framework, we also illustrate the security model associated with it and the tests carried out to evaluate its correctness and performance.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"99 ","pages":"Article 101889"},"PeriodicalIF":4.3,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1574119224000154/pdfft?md5=e7b2906244cfb05dbee063203a65f60e&pid=1-s2.0-S1574119224000154-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139738296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization of mobility sampling in dynamic networks using predictive wavelet analysis 利用预测小波分析优化动态网络中的移动采样

IF 4.3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2024-02-01 DOI: 10.1016/j.pmcj.2024.101887

Peppino Fazio , Miralem Mehic , Floriano De Rango , Mauro Tropea , Miroslav Voznak

{"title":"Optimization of mobility sampling in dynamic networks using predictive wavelet analysis","authors":"Peppino Fazio , Miralem Mehic , Floriano De Rango , Mauro Tropea , Miroslav Voznak","doi":"10.1016/j.pmcj.2024.101887","DOIUrl":"10.1016/j.pmcj.2024.101887","url":null,"abstract":"<div><p>In the last decade, the investigation of mobility features has gained enormous significance in many scenarios as a result of the significant diffusion and deployment of mobile devices covered by high-speed technologies (e.g., 5G). Many contributions in the literature have attempted to discover mobility properties, but most studies are based on the time features of the mobility process. No study has yet considered the effects of setting a proper sampling frequency (generally set to 1 s), in order to avoid information loss. Following our previous works, we propose a novel predictive spectral approach for mobility sampling based on the concept of a predictive wavelet. With this method, the choice of sampling frequency is governed by the current spectral components of the mobility process and derived from an analysis of future, predicted components. To assess whether our proposal may yield a helpful method, we conducted several simulation campaigns to test sampling accuracy and obtained results that confirmed our expectations.</p></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"98 ","pages":"Article 101887"},"PeriodicalIF":4.3,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1574119224000130/pdfft?md5=4ee4cc1275b8ee0647dbfa8fed17e7b2&pid=1-s2.0-S1574119224000130-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139669507","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0