Pervasive and Mobile Computing最新文献_第5页

Navigating transient content: PFC caching approach for NDN-based IoT networks 导航瞬时内容：基于 NDN 的物联网网络的 PFC 缓存方法

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-03-24 DOI: 10.1016/j.pmcj.2025.102031

Sumit Kumar , Rajeev Tiwari

{"title":"Navigating transient content: PFC caching approach for NDN-based IoT networks","authors":"Sumit Kumar , Rajeev Tiwari","doi":"10.1016/j.pmcj.2025.102031","DOIUrl":"10.1016/j.pmcj.2025.102031","url":null,"abstract":"<div><div>The emergence of Internet-of-Things (IoT) has revolutionized communication among devices. IoT devices autonomously collect and disseminate contents to end-users via network routers. There is growing interest in integrating IoT communications with Named Data Networking (NDN) architecture to retrieve and distribute content efficiently. The content caching characteristics of NDN are pivotal in improving Quality-of-Service (QoS) for IoT. However, unlike multimedia content traffic, which tends to remain static, IoT-generated content is inherently transient in nature, and each content has a finite lifespan. As a result, without efficient caching solutions for IoT contents, the network efficiency and user experience would be degraded. Existing caching approaches often overlook the importance of IoT content freshness, its access pattern and the position of routers during content placement decisions in the IoT networks. In this paper, a novel Popularity and Freshness-based Caching (PFC) scheme has been proposed that aims to strategically cache popular and fresh IoT contents on routers located close to the end-user devices. In the proposed solution, the popularity of content is determined using the request history queue deployed on all network routers. For efficient caching decisions, the hop count metric favors routers in close proximity to end-users. Rigorous simulations with realistic network parameters are performed on the realistic IoT network topologies. The simulation results demonstrate that the PFC approach outperforms existing state-of-the-art caching approaches (LCE, LCC, Consumer-Driven, Consumer-Cache, etc.) on several performance parameters: cache hit ratio, network delay, hop count, network traffic, and energy consumption. This makes the PFC caching approach well-suited for NDN-based IoT networks by enabling efficient content caching decisions.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102031"},"PeriodicalIF":3.0,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143697403","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

Investment-driven budget allocation and dynamic pricing strategies in edge cache network 边缘缓存网络中投资驱动的预算分配与动态定价策略

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-03-22 DOI: 10.1016/j.pmcj.2025.102040

Quyuan Wang , Pengyang Chen , Jiadi Liu , Ying Wang , Zhiwei Guo

{"title":"Investment-driven budget allocation and dynamic pricing strategies in edge cache network","authors":"Quyuan Wang , Pengyang Chen , Jiadi Liu , Ying Wang , Zhiwei Guo","doi":"10.1016/j.pmcj.2025.102040","DOIUrl":"10.1016/j.pmcj.2025.102040","url":null,"abstract":"<div><div>Edge Caching is an application with great commercial potential in accelerating content acquisition by near-client content caching. To provide high-quality services for customers, it is indispensable for content providers to purchase or rent sufficient wireless channels and cache storage resources from edge suppliers. However, few work has investigated how to allocate limited budget to the appropriate resources in an economically way for caching at a network edge. In this paper, we construct a Fisher cache market to tackle the budget allocation problem and the price adjustment problem in edge caching by using the portfolio approach. In the budget allocation problem, we utilize the Iso-cost line and threshold settings to narrow search space and propose an algorithm termed as Gradient descent based Portfolio Search (GBPS) to acquire an optimal portfolio within a limited search field. With the aid of market supply and demand in micro economic theory, we put forward K-popular Suppliers Price Adjustment algorithm (KSPA) and Elastic Supply and Demand Price Adjustment algorithm (ESDPA) price adjustment algorithms to achieve market equilibrium within a limited budget. Finally, numerical results demonstrate that the proposed algorithms perform better in terms of trading success rate and total payoff by the comparisons of different algorithms.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102040"},"PeriodicalIF":3.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683356","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

EPCM: Efficient privacy-preserving charging matching scheme with data integrity for electric vehicles EPCM：基于数据完整性的电动汽车高效隐私保护充电匹配方案

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-03-22 DOI: 10.1016/j.pmcj.2025.102042

Tingting Jin, Peng Hu, Kaizhong Zuo, Tianjiao Ni, Dong Xie, Zhangyi Shen, Fulong Chen

{"title":"EPCM: Efficient privacy-preserving charging matching scheme with data integrity for electric vehicles","authors":"Tingting Jin, Peng Hu, Kaizhong Zuo, Tianjiao Ni, Dong Xie, Zhangyi Shen, Fulong Chen","doi":"10.1016/j.pmcj.2025.102042","DOIUrl":"10.1016/j.pmcj.2025.102042","url":null,"abstract":"<div><div>Compared to traditional charging stations, the Vehicle-to-Vehicle (V2V) charging mode can expand the coverage of the charging network and is expected to become an important supplementary method for future electric vehicle charging. However, the leakage of location privacy in charging matching has become one of the main concerns of users. To tackle this problem, we propose an efficient privacy preserving charging matching scheme, named EPCM, which ensures data integrity without compromising the location privacy of vehicles. Firstly, we utilize the modified Paillier cryptosystem and identity based batch signature to achieve location privacy and data integrity. Secondly, our scheme operates in a round-by-round manner, ensuring immediate task completion and allowing vehicles to dynamically join or leave. The security proof and analysis indicates that EPCM can achieve security features including confidentiality, location privacy, authentication, and data integrity. Furthermore, by carrying out extensive experiments, the experimental results demonstrate that our scheme performs excellently in terms of computational and communication overhead, as well as total transmission delay.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102042"},"PeriodicalIF":3.0,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683358","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

Load-balancing model using game theory in edge-based IoT network 基于博弈论的边缘物联网负载均衡模型

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-03-16 DOI: 10.1016/j.pmcj.2025.102041

Zaineb Naaz , Gamini Joshi , Vidushi Sharma

引用次数: 0

Bio-inspired recruiting strategies for on-demand connectivity over a multi-layer hybrid CubeSat-UAV networks in emergency scenarios 紧急情况下多层立方体卫星-无人机混合网络按需连接的仿生招聘策略

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-03-10 DOI: 10.1016/j.pmcj.2025.102030

Mauro Tropea , Alex Ramiro Masaquiza Caiza , Floriano De Rango

{"title":"Bio-inspired recruiting strategies for on-demand connectivity over a multi-layer hybrid CubeSat-UAV networks in emergency scenarios","authors":"Mauro Tropea , Alex Ramiro Masaquiza Caiza , Floriano De Rango","doi":"10.1016/j.pmcj.2025.102030","DOIUrl":"10.1016/j.pmcj.2025.102030","url":null,"abstract":"<div><div>In emergency scenarios, the network infrastructure must remain reliable and continuously available to ensure connectivity to people and optimal performance in supporting different types of applications, including real-time services. When terrestrial infrastructure is compromised during emergencies, Flying Ad Hoc Networks (FANETs) can offer a quick and effective solution for re-establishing connectivity in affected areas. The dynamic coverage provided by a swarm of UAVs (Unmanned Aerial Vehicles) during a disaster could be crucial for people inside the affected areas. In high-demand and critical situations, the performance of FANETs may deteriorate due to several factors, including simultaneous user connections, high traffic volumes, limited energy resources of network devices, and interference arising within the same geographic region. To address these challenges, this paper proposes a novel, bio-inspired recruitment algorithm that aims to guarantee good performance of FANETs in energy constrained scenarios by efficiently recruiting UAVs to cover the demand of end users connected to the network. In such a scenario, when additional UAVs cannot be reachable using the on-earth network infrastructure and multi-hop routing, the recruiting can be supported through a multi-layer hybrid architecture that integrates CubeSats to forward recruiting requests to potential UAVs located far from the network. This approach not only enhances the connectivity of end users but also ensures that the network can efficiently be adapted to the demands of users in emergency situations.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102030"},"PeriodicalIF":3.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143610929","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

In-bed gesture recognition to support the communication of people with Aphasia 床上手势识别，以支持失语症患者的交流

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-02-26 DOI: 10.1016/j.pmcj.2025.102029

Ana Patrícia Rocha, Afonso Guimarães, Ilídio C. Oliveira, José Maria Fernandes, Miguel Oliveira e Silva, Samuel Silva, António Teixeira

{"title":"In-bed gesture recognition to support the communication of people with Aphasia","authors":"Ana Patrícia Rocha, Afonso Guimarães, Ilídio C. Oliveira, José Maria Fernandes, Miguel Oliveira e Silva, Samuel Silva, António Teixeira","doi":"10.1016/j.pmcj.2025.102029","DOIUrl":"10.1016/j.pmcj.2025.102029","url":null,"abstract":"<div><div>People with language impairments can have difficulties expressing themselves to others, leading to major limitations to their safety, independence, and quality of life in general. Aphasia is an example of an acquired language impairment that affects many people (around 2 million in the United States), being commonly caused by stroke, but also by other brain injuries. Several augmentative and alternative communication solutions are available to help people with communication difficulties, but they are generally not suitable for all contexts of use (e.g., lying in bed). In the scope of the “APH-ALARM” project, which aimed at developing solutions to support people with Aphasia, we envision a system for the bedroom that enables conveying messages to be sent to a caregiver or relative, for example. Focusing on gesture input, in this contribution, we investigated if smartwatch sensors and machine learning (ML) can be used to recognise arm gestures executed while lying. We explored different factors, namely the feature set, size of the sliding window used for feature extraction, and ML classifier. The results obtained with data gathered from ten subjects are promising, with the best factor combinations for the user-independent solution leading to a mean macro F1 score of 94% or 95%. They demonstrate the potential of using wearables to develop a gesture input modality for the in-bed scenario, which can also potentially be extended to other contexts (e.g., sitting in a bed, chair, or sofa, or standing). This research also provides useful insights that inform future work, including the development and deployment of communication support systems that can benefit not only people with communication difficulties (e.g., more independence), but also those caring for them (e.g., more peace of mind).</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"109 ","pages":"Article 102029"},"PeriodicalIF":3.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143562321","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

A novel middleware for adaptive and efficient split computing for real-time object detection 一种用于实时目标检测的自适应高效分割计算中间件

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-02-22 DOI: 10.1016/j.pmcj.2025.102028

Matteo Mendula , Paolo Bellavista , Marco Levorato , Sharon Ladron de Guevara Contreras

{"title":"A novel middleware for adaptive and efficient split computing for real-time object detection","authors":"Matteo Mendula , Paolo Bellavista , Marco Levorato , Sharon Ladron de Guevara Contreras","doi":"10.1016/j.pmcj.2025.102028","DOIUrl":"10.1016/j.pmcj.2025.102028","url":null,"abstract":"<div><div>Real-world applications requiring real-time responsiveness frequently rely on energy-intensive and compute-heavy neural network algorithms. Strategies include deploying distributed and optimized Deep Neural Networks on mobile devices, which can lead to considerable energy consumption and degraded performance, or offloading larger models to edge servers, which requires low-latency wireless channels. Here we present Furcifer, a novel middleware that autonomously adjusts the computing strategy (i.e., local computing, edge computing, or split computing) based on context conditions. Utilizing container-based services and low-complexity predictors that generalize across environments, Furcifer supports supervised compression as a viable alternative to pure local or remote processing in real-time environments. An extensive set of experiments coversdiverse scenarios, including both stable and highly dynamic channel environments with unpredictable changes in connection quality and load. In moderate-varying scenarios, Furcifer demonstrates significant benefits: achieving a 2x reduction in energy consumption, a 30% higher mean Average Precision score compared to local computing, and a three-fold FPS increase over static offloading. In highly dynamic environments with unreliable connectivity and rapid increases in concurrent clients, Furcifer’s predictive capabilities preserves up to 30% energy, achieving a 16% higher accuracy rate, and completing 80% more frame inferences compared to pure local computing and approaches without trend forecasting, respectively.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"108 ","pages":"Article 102028"},"PeriodicalIF":3.0,"publicationDate":"2025-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487181","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

EncCluster: Scalable functional encryption in federated learning through weight clustering and probabilistic filters EncCluster：通过权重聚类和概率过滤器在联合学习中进行可扩展的功能加密

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-02-21 DOI: 10.1016/j.pmcj.2025.102021

Vasileios Tsouvalas , Samaneh Mohammadi , Ali Balador , Tanir Ozcelebi , Francesco Flammini , Nirvana Meratnia

{"title":"EncCluster: Scalable functional encryption in federated learning through weight clustering and probabilistic filters","authors":"Vasileios Tsouvalas , Samaneh Mohammadi , Ali Balador , Tanir Ozcelebi , Francesco Flammini , Nirvana Meratnia","doi":"10.1016/j.pmcj.2025.102021","DOIUrl":"10.1016/j.pmcj.2025.102021","url":null,"abstract":"<div><div>Federated Learning (FL) enables model training across decentralized devices by communicating solely local model updates to an aggregation server. Although such limited data sharing makes FL more secure than centralized approached, FL remains vulnerable to inference attacks during model update transmissions. Existing secure aggregation approaches rely on differential privacy or cryptographic schemes like Functional Encryption (FE) to safeguard individual client data. However, such strategies can reduce performance or introduce unacceptable computational and communication overheads on clients running on edge devices with limited resources. In this work, we present <span>EncCluster</span>, a novel method that integrates model compression through weight clustering with recent decentralized FE and privacy-enhancing data encoding using probabilistic filters to deliver strong privacy guarantees in FL without affecting model performance or adding unnecessary burdens to clients. We performed a comprehensive evaluation, spanning various datasets and architectures, to demonstrate <span>EncCluster</span> scalability across encryption levels. Our findings reveal that <span>EncCluster</span> significantly reduces communication costs — below even conventional FedAvg — and accelerates encryption by more than four times over all baselines; at the same time, it maintains high model accuracy and enhanced privacy assurances.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"108 ","pages":"Article 102021"},"PeriodicalIF":3.0,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143487182","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

HearDrinking: Drunkenness detection and BACs predictions based on acoustic signal 听觉饮酒：基于声信号的醉酒检测和BACs预测

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-02-10 DOI: 10.1016/j.pmcj.2025.102020

Yuan Wu , Gaorong Zhao , Likairui Zhang , Xinrong Hu , Lei Ding

{"title":"HearDrinking: Drunkenness detection and BACs predictions based on acoustic signal","authors":"Yuan Wu , Gaorong Zhao , Likairui Zhang , Xinrong Hu , Lei Ding","doi":"10.1016/j.pmcj.2025.102020","DOIUrl":"10.1016/j.pmcj.2025.102020","url":null,"abstract":"<div><div>Alcohol poisoning is a severe health concern resulting from excessive drinking and can be life-threatening. By utilizing home monitoring, individuals can quickly determine their blood alcohol content, thus preventing it from reaching hazardous levels. However, most existing systems for drunkenness detection require extra hardware or much effort from the user, making these systems impractical for detecting drunkenness in real life. Motivated by this, we present a device-free, noise-resistant drunkenness detection system named HearDrinking based on smartphone, which utilizes microphone of smartphone to record human’s voice activity, then mine drunkenness related features to yield accurate drunkenness detection. However, using acoustic signal to detect drunkenness is non-trivial since voice activities are prone to be interfered by ambient noise, and extracting fine-grained representations related to drunkenness from voice activities remains unresolved. On one hand, HearDrinking employs a multi-modal fusion method to realize noise-resistant voice activity detection. On the other hand, HearDrinking initially calculates the log-Mel spectrograms from the speech signal. The log-Mel spectrograms contain temporal and spectral information absent in image data. Therefore, conventional convolutions designed for images often have limited effectiveness in extracting features from log-Mel spectrograms. To overcome this limitation, we integrate Omni-dimensional Dynamic Convolution (ODConv) with ShuffleNetV2, creating OD-ShuffleNetV2. ODConv replaces certain conventional convolutions in the ShuffleNetV2 network. Multiple convolution cores are fused based on the log-Mel spectrogram, taking into account multi-dimensional attention, thereby optimizing the network structure. Comprehensive experiments with 15 participants reveal drunkenness detection accuracy of 96.08% and Blood Alcohol Content (BAC) predictions with an average error of 5 mg/dl.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"108 ","pages":"Article 102020"},"PeriodicalIF":3.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395035","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

Climate smart computing: A perspective 气候智能计算：一个视角

IF 3 3区计算机科学

Pervasive and Mobile Computing Pub Date : 2025-02-07 DOI: 10.1016/j.pmcj.2025.102019

Mingzhou Yang, Bharat Jayaprakash, Subhankar Ghosh, Hyeonjung Tari Jung, Matthew Eagon, William F. Northrop, Shashi Shekhar

{"title":"Climate smart computing: A perspective","authors":"Mingzhou Yang, Bharat Jayaprakash, Subhankar Ghosh, Hyeonjung Tari Jung, Matthew Eagon, William F. Northrop, Shashi Shekhar","doi":"10.1016/j.pmcj.2025.102019","DOIUrl":"10.1016/j.pmcj.2025.102019","url":null,"abstract":"<div><div>Climate change is a societal grand challenge and many nations have signed the Paris Agreement (2015) aiming for net-zero emissions. The computing community has an opportunity to contribute significantly to addressing climate change across all its dimensions, including understanding, resilience, mitigation, and adaptation. Traditional computing methods face major challenges. For example, machine learning is overwhelmed due to non-stationarity (e.g., climate change), data paucity (e.g., rare climate events), the high cost of ground truth collection, and the need to observe natural laws (e.g., conservation of mass). This paper shares a perspective on a range of climate-smart computing challenges and opportunities based on multi-decade scholarly activities and acknowledges the broader societal debate on climate solutions. Moreover, it envisions advancements in computing methods specifically designed to tackle the challenges posed by climate change. It calls for a broad array of computer science strategies and innovations to be developed to address the multifaceted challenges of climate change.</div></div>","PeriodicalId":49005,"journal":{"name":"Pervasive and Mobile Computing","volume":"108 ","pages":"Article 102019"},"PeriodicalIF":3.0,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395036","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