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| 2. |
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| 3. |
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| 4. |
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| 5. |
- Hu, Xiping, et al.
(author)
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SAfeDJ : A crowd-cloud codesign approach to situation-aware music delivery for drivers
- 2015
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In: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP). - : Association for Computing Machinery (ACM). - 1551-6857 .- 1551-6865. ; 12:1s, s. 21:1-24
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Journal article (peer-reviewed)abstract
- Driving is an integral part of our everyday lives, but it is also a time when people are uniquely vulnerable. Previous research has demonstrated that not only does listening to suitable music while driving not impair driving performance, but it could lead to an improved mood and a more relaxed body state, which could improve driving performance and promote safe driving significantly. In this article, we propose SAfeDJ, a smartphone-based situation-aware music recommendation system, which is designed to turn driving into a safe and enjoyable experience. SAfeDJ aims at helping drivers to diminish fatigue and negative emotion. Its design is based on novel interactive methods, which enable in-car smartphones to orchestrate multiple sources of sensing data and the drivers' social context, in collaboration with cloud computing to form a seamless crowdsensing solution. This solution enables different smartphones to collaboratively recommend preferable music to drivers according to each driver's specific situations in an automated and intelligent manner. Practical experiments of SAfeDJ have proved its effectiveness in music-mood analysis, and mood-fatigue detections of drivers with reasonable computation and communication overheads on smartphones. Also, our user studies have demonstrated that SAfeDJ helps to decrease fatigue degree and negative mood degree of drivers by 49.09% and 36.35%, respectively, compared to traditional smartphone-based music player under similar driving situations.
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| 6. |
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| 8. |
- Sathyamoorthy, Peramanathan, et al.
(author)
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Profiling energy efficiency and data communications for mobile Internet of Things
- 2017
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In: Wireless Communications & Mobile Computing. - : Hindawi Limited. - 1530-8669 .- 1530-8677. ; 17
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Journal article (peer-reviewed)abstract
- This paper proposes a novel power management solution for resource-constrained devices in the context of Internet of Things (IoT). We focus on smartphones in the IoT, as they are getting increasingly popular and equipped with strong sensing capabilities. Smartphones have complex and asynchronous power consumption incurred by heterogeneous components including their on-board sensors. Their interaction with the cloud allows them to offload computation tasks and access remote data storage. In this work, we aim at monitoring the power consumption behaviours of the smartphones, profiling both individual applications and the system as a whole, to make better decisions in power management. We design a cloud orchestration architecture as an epic predictor of behaviours of smart devices by extracting their application characteristics and resource utilization. We design and implement this architecture to perform energy profiling and data analysis on massive data logs. This cloud orchestration architecture coordinates a number of cloud-based services and supports dynamic workflows between service components, which can reduce energy consumption in the energy profiling process itself. Experimental results showed that small portion of applications dominate the energy consumption of smartphones. Heuristic profiling can effectively reduce energy consumption in data logging and communications without scarifying the accuracy of power monitoring.
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| 9. |
- Tu, Wei, et al.
(author)
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A Survey on Mobile Sensing Based Mood-Fatigue Detection for Drivers
- 2016
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In: SMART CITY 360. - Cham : SPRINGER INT PUBLISHING AG. - 9783319336817 - 9783319336800 ; , s. 3-15
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Conference paper (peer-reviewed)abstract
- The rapid development of the Internet of Things (IoT) has provided innovative solutions to reduce traffic accidents caused by fatigue driving. When drivers are in bad mood or tired, their vigilance level decreases, which may prolong the reaction time to emergency situation and lead to serious accidents. With the help of mobile sensing and mood-fatigue detection, drivers' moodfatigue status can be detected while driving, and then appropriate measures can be taken to eliminate the fatigue or negative mood to increase the level of vigilance. This paper presents the basic concepts and current solutions of moodfatigue detection and some common solutions like mobile sensing and cloud computing techniques. After that, we introduce some emerging platforms which designed to promote safe driving. Finally, we summarize the major challenges in mood-fatigue detection of drivers, and outline the future research directions.
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| 10. |
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| 11. |
- Zhou, Li, et al.
(author)
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Green Small Cell Planning in Smart Cities under Dynamic Traffic Demand
- 2015
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In: 2015 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS). - 9781467371315 ; , s. 618-623
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Conference paper (peer-reviewed)abstract
- In smart cities, cellular network plays a crucial role to support connectivity anywhere and anytime. However, the communication demand brought by applications and services is hard to predict. Traffic in cellular networks might fluctuate heavily over time to time, which causes burden and waste under different traffic states. Recently, small cell was proposed to enhance spectrum efficiency and energy efficiency in cellular networks. However, how green the small cell network can be is still a question because of the accompanying interference. To meet this challenge, new green technologies should be developed. In this paper, we propose a green small cell planning scheme considering dynamic traffic states. First, we predefine a set of candidate locations for base stations (BSs) in a geographical area and generate a connection graph which contains all possible connections between BSs and user equipments (UEs). Then we adopt a heuristic to switch off small cell BSs (s-BSs) and update BS-UE connections iteratively. Finally we obtain a cell planning solution with energy efficiency without reducing spectrum efficiency and quality-of-service (QoS) requirements. The simulation results show that our dynamic small cell planning scheme has low computational complexity and achieves a significant improvement in energy efficiency comparing with the static cell planning scheme.
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| 12. |
- Zhu, Chunsheng, et al.
(author)
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Green Internet of Things for Smart World
- 2015
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In: IEEE Access. - 2169-3536. ; 3, s. 2151-2162
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Journal article (peer-reviewed)abstract
- Smart world is envisioned as an era in which objects (e.g., watches, mobile phones, computers, cars, buses, and trains) can automatically and intelligently serve people in a collaborative manner. Paving the way for smart world, Internet of Things (IoT) connects everything in the smart world. Motivated by achieving a sustainable smart world, this paper discusses various technologies and issues regarding green IoT, which further reduces the energy consumption of IoT. Particularly, an overview regarding IoT and green IoT is performed first. Then, the hot green information and communications technologies (ICTs) (e.g., green radio frequency identification, green wireless sensor network, green cloud computing, green machine to machine, and green data center) enabling green IoT are studied, and general green ICT principles are summarized. Furthermore, the latest developments and future vision about sensor cloud, which is a novel paradigm in green IoT, are reviewed and introduced, respectively. Finally, future research directions and open problems about green IoT are presented. Our work targets to be an enlightening and latest guidance for research with respect to green IoT and smart world.
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| 13. |
- Zhu, Chunsheng, et al.
(author)
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Pricing Models for Sensor-Cloud
- 2015
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In: 2015 IEEE 7Th International Conference On Cloud Computing Technology And Science (Cloudcom). - 9781467395601 ; , s. 454-457
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Conference paper (peer-reviewed)abstract
- Incorporating ubiquitous wireless sensor networks (WSNs) and powerful cloud computing (CC), Sensor-Cloud (SC) is attracting growing attention from both academia and industry. However, pricing for SC is barely explored. In this paper, filling this gap, five SC pricing models (i.e., SCPM1, SCPM2, SCPM3, SCPM4 and SCPM5) are proposed first. Particularly, they charge a SC user, based on 1) the lease period of the user; 2) the required working time of SC; 3) the SC resources utilized by the user; 4) the volume of sensory data obtained by the user; 5) the SC path that transmits sensory data from the WSN to the user, respectively. Further, analysis is also presented to study and demonstrate the performance of the proposed SCPMs. We believe that the pricing designs and analysis performed in this work could be a very valuable guidance for future researches regarding pricing in SC.
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| 14. |
- Zhu, Chunsheng, et al.
(author)
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Towards Pricing for Sensor-Cloud
- 2020
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In: IEEE Transactions on Cloud Computing. - 2168-7161. ; 8:4, s. 1018-1029
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Journal article (peer-reviewed)abstract
- Motivated by complementing the ubiquitous wireless sensor networks (WSNs) and powerful cloud computing (CC), a lot of attention from both industry and academia has been drawn to Sensor-Cloud (SC). However, SC pricing is barely investigated. Towards pricing for SC, this paper 1) introduces five SC Pricing Models (SCPMs) first. Specifically, to charge a SC user, each SCPM considers one of the following factors respectively: i) the lease period of the SC user; ii) the required working time of SC; iii) the SC resources utilized by the SC user; iv) the volume of sensory data obtained by the SC user; v) the SC path that transmits sensory data from the WSN to the SC user. Further, this paper 2) performs analysis to discuss and exhibit the characteristics of the proposed SCPMs. With that, this paper 3) presents the case studies regarding the application of SCPMs. Eventually, this paper 4) conducts a review about the user behavior study. This paper aims to serve as a very favorable guidance for future research about pricing in SC.
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| 15. |
- Ahlgren, Bengt, et al.
(author)
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Internet of Things for Smart Cities : Interoperability and Open Data
- 2016
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In: IEEE Internet Computing. - : IEEE Computer Society. - 1089-7801 .- 1941-0131. ; 20:6, s. 52-56
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Journal article (peer-reviewed)abstract
- The Internet of Things (IoT) has become a promising technology for addressing societal challenges by connecting smart devices and leveraging Big Data analytics to create smart cities worldwide. As the IoT scales up, it's important to provide interoperability among different devices. Yet current simple standard protocols lack sufficient openness and interoperability. IoT for smart cities needs to guarantee the accessibility of open data and cloud services to allow industries and citizens to develop new services and applications. Here, the authors provide a case study of the GreenIoT platform in Uppsala, Sweden, to demonstrate the idea of interoperability and open data for smart cities.
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| 16. |
- Deng, Weipeng, et al.
(author)
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Energy-Efficient Monitoring of Potential Side Effects from COVID-19 Vaccines
- 2022
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In: Proceedings. - : IEEE. - 9781665454179 - 9781665454186 ; , s. 222-227
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Conference paper (peer-reviewed)abstract
- COVID-19 has affected the world for almost two years causing lots of damages and losses of lives. With the development of sensing technology and digital health, research studies suggest to use wearable devices for monitoring COVID-19 symptoms or analyzing people’s behaviour change. As COVID-19 vaccines are getting widely available, their side effects have raised public concerns, though have not yet been thoroughly studied due to the short deployment time. As far as we know, this work is the first study to use wearable devices and mobile app to collect physiological data to explore potential side effects to human bodies from COVID-19 vaccinations. We designed and developed a mobile sensing system, which can monitor changes of physiological indicators through wearable devices, collect self-reported data from the users and proposed a green data transmission mechanism which can reduce the communication overheads. Pilot study has been conducted to evaluate the feasibility of our system. Preliminary results show that increased resting heart rate (RHR) and changes on average heart rate (HR) are observed in some participants after COVID-19 vaccinations. This study opens up the opportunity to collect larger amount of data and further investigate potential side effects from COVID-19 vaccinations.
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| 17. |
- Ekberg, Pontus, et al.
(author)
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A distributed swarm-intelligent localization for sensor networks with mobile nodes
- 2011
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In: Proc. 7th International Wireless Communications and Mobile Computing Conference. - Piscataway, NJ : IEEE. - 9781424495399 ; , s. 83-88
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Conference paper (peer-reviewed)abstract
- We present a novel distributed localization algorithm, called Swarm-Intelligent Localization (SIL), for computing the physical locations of nodes in wireless sensor networks. The algorithm assumes that only a small fraction of the nodes have a priori knowledge of their positions, and that noisy distance measurements are available between all neighboring nodes. The algorithm has no explicit global state and it can handle nodes that are both mobile and that can arrive in the network at any time. SIL works in two different phases, a coarse phase where nodes compute rough positions for themselves based on information about remote anchors, and a fine phase where nodes iteratively refine their positions from the coarse phase by collaborating with their neighbors. The average computational complexity per node running SIL is very low, namely constant in the network size and linear in the connectivity of the network. We evaluate the algorithm through extensive simulations. The results indicate that SIL is able to compute accurate positions for the majority of nodes in a wide range of network topologies and settings, and that it can handle difficulties such as large distance measurement errors and low network connectivity.
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| 18. |
- Elsts, Atis, et al.
(author)
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A Case for Node-Local Runtime Parameter Adaptation in Wireless Sensor Networks
- 2014
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In: Proc. 10th Swedish National Computer Networking Workshop.
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Conference paper (other academic/artistic)abstract
- The challenges posed to wireless sensor networks by the environments they are deployed cannot always be predicted beforehand. Therefore, adaptive behavior at the run-time may be required to achieve good reliability and energy-efficiency. We present a node-local runtime adaptation algorithm that adapts the over-the-air message encoding based on presence of weak links and external interference in the immediate neighborhood of the node. Evaluation with a network simulator shows that this algorithm leads to significant network-wide reduction of radio duty cycle under specific radio transmission failure models.
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| 19. |
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| 20. |
- Guerreiro, João, et al.
(author)
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Privacy-aware probabilistic sampling for data collection in wireless sensor networks
- 2011
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In: Proc. 7th International Wireless Communications and Mobile Computing Conference. - Piscataway, NJ : IEEE conference proceedings. - 9781424495399 ; , s. 314-319
-
Conference paper (peer-reviewed)abstract
- The rising popularity of web services and their applications to sensor networks enables real-time data collection and queries by users. Unlike traditional periodic data collection, the traffic patterns generated from real-time data collection may expose the interests of users or the locations of unusual events to the attackers. To provide privacy in data collection, we propose a novel probabilistic sampling mechanism that can hide user queries and unusual events in the network, while supporting both routine and on-demand data reporting. Our goal is to prevent attackers from locating the unusual events and identifying interests of users by eavesdropping and analyzing the network traffic. In our probabilistic sampling scheme, the data are carefully reported at random times in order to mask the unusual events and user queries. In the meantime, our scheme can provide users with high data accuracy at minimized communication overheads. Extensive simulations have been conducted to evaluate the security strength, data accuracy and communication overheads of the proposed scheme.
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| 23. |
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| 26. |
- Jiang, Zhihan, et al.
(author)
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Leveraging Machine Learning for Disease Diagnoses based on Wearable Devices : A Survey
- 2023
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In: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662. ; 10:24, s. 21959-21981
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Journal article (peer-reviewed)abstract
- Many countries around the world are facing a shortage of healthcare resources, especially during the post-epidemic era, leading to a dramatic increase in the need for self-detection and self-management of diseases. The popularity of smart wearable devices, such as smartwatches, and the development of machine learning bring new opportunities for the early detection and management of various prevalent diseases, such as cardiovascular diseases, Parkinson’s disease, and diabetes. In this survey, we comprehensively review the articles related to specific diseases or health issues based on small wearable devices and machine learning. More specifically, we first present an overview of the articles selected and classify them according to their targeted diseases. Then, we summarize their objectives, wearable device and sensor data, machine learning techniques, and wearing locations. Based on the literature review, we discuss the challenges and propose future directions from the perspectives of privacy concerns, security concerns, transmission latency and reliability, energy consumption, multi-modality, multi-sensor, multi-devices, evaluation metrics, explainability, generalization and personalization, social influence, and human factors, aiming to inspire researchers in this field.
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| 27. |
- Kaivonen, Sami, et al.
(author)
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Real-time air pollution monitoring with sensors on city bus
- 2020
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In: Digital Communications and Networks. - : KeAi. - 2468-5925 .- 2352-8648. ; 6:1, s. 23-30
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Journal article (peer-reviewed)abstract
- This paper presents an experimental study on real-time air pollution monitoring using wireless sensors on public transport vehicles. The study is part of the GreenIoT project in Sweden, which utilizes Internet-of-Things to measure air pollution level in the city center of Uppsala. Through deploying low-cost wireless sensors, it is possible to obtain more fine-grained and real-time air pollution levels at different locations. The sensors on public transport vehicles complement the readings from stationary sensors and the only ground level monitoring station in Uppsala. The paper describes the deployment of wireless sensors on Uppsala buses and the integration of the mobile sensor network with the GreenIoT testbed. Extensive experiments have been conducted to evaluate the communication quality and data quality of the system.
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| 28. |
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| 29. |
- Li, Shenghui, 1994-, et al.
(author)
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An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning
- 2023
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In: IEEE Transactions on Big Data. - : Institute of Electrical and Electronics Engineers (IEEE). - 2332-7790 .- 2372-2096.
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Journal article (peer-reviewed)abstract
- Byzantine-robust federated learning aims at mitigating Byzantine failures during the federated training process, where malicious participants (known as Byzantine clients) may upload arbitrary local updates to the central server in order to degrade the performance of the global model. In recent years, several robust aggregation schemes have been proposed to defend against malicious updates from Byzantine clients and improve the robustness of federated learning. These solutions were claimed to be Byzantine-robust, under certain assumptions. Other than that, new attack strategies are emerging, striving to circumvent the defense schemes. However, there is a lack of systematical comparison and empirical study thereof. In this paper, we conduct an experimental study of Byzantine-robust aggregation schemes under different attacks using two popular algorithms in federated learning, FedSGD and FedAvg . We first survey existing Byzantine attack strategies, as well as Byzantine-robust aggregation schemes that aim to defend against Byzantine attacks. We also propose a new scheme, ClippedClustering, to enhance the robustness of a clustering-based scheme by automatically clipping the updates. Then we provide an experimental evaluation of eight aggregation schemes in the scenario of five different Byzantine attacks. Our experimental results show that these aggregation schemes sustain relatively high accuracy in some cases, but they are not effective in all cases. In particular, our proposed ClippedClustering successfully defends against most attacks under independent and identically distributed (IID) local datasets. However, when the local datasets are Non-IID, the performance of all the aggregation schemes significantly decreases. With Non-IID data, some of these aggregation schemes fail even in the complete absence of Byzantine clients. Based on our experimental study, we conclude that the robustness of all the aggregation schemes is limited, highlighting the need for new defense strategies, in particular for Non-IID datasets.
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| 30. |
- Li, Wenxiang, et al.
(author)
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Facilities Collaboration in Cloud Manufacturing based on Generalized Collaboration Network
- 2015
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In: Proceedings of the 11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness. - : IEEE. - 9781631900631 ; , s. 298-303
-
Conference paper (peer-reviewed)abstract
- In cloud manufacturing for regional industrial cluster, there is increasing necessity of collaboration among enterprises or facilities. It is valuable to explore the characteristics of these collaboration behaviors for effectively scheduling dispersed manufacturing facilities and organizing their collaboration. The collaborative relation of manufacturing in regional industrial cluster can be described as a generalized social collaboration network. In this paper, we introduce the relevant entities and relations of facilities collaboration, and propose the method for building Facility Collaboration Network (FCN). We further design the dynamically growing process of FCN for different facility selection strategies, including random selection, balanced selection, random selection with preference and balanced selection with preference. Based on the metrics such as network scale, node degree distribution, act degree distribution, average shortest distance and number of cliques, we present the statistical characteristics of FCN, and analyze relevant characteristics and laws for efficient facilities selection in cloud manufacturing.
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| 32. |
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| 33. |
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| 34. |
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| 35. |
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| 36. |
- Man, Yemao, 1987, et al.
(author)
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Energy-efficient automatic location-triggered applications on smartphones
- 2014
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In: Computer Communications. - : Elsevier BV. - 1873-703X .- 0140-3664. ; 50, s. 29-40
-
Journal article (peer-reviewed)abstract
- With the prevalence of localization techniques in smartphones, location-based applications on mobiles have become increasingly popular. However, only minorities of applications can be triggered automatically by the predefined locations of interest without any human interaction. One reason is that the inevitable operation of location detection by GPS is power-intensive. While existing work has focused on energy efficiency in continuous location tracking, energy-efficient location detection for matching predefined location of interest remains to be further explored. This paper proposes a unified framework that supports energy-efficient location detection for automatic location-triggered applications. Our framework triggers desired events only when the user is approaching the predefined locations of interest. Besides the efforts we make to reduce the number of GPS updates by cooperating with other types of on-device sensors, the framework also aims to coordinate multiple location-triggered applications to further reduce energy consumption on location updates. We implemented our framework as a middleware in the Android operating system and conducted extensive real experiments. The experimental results demonstrate that our framework can reduce the number of GPS requests and low the energy consumption of the smartphones significantly.
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| 37. |
- Mumey, Brendan, et al.
(author)
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Ubiquitous sensor data collection with mobile users
- 2014
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In: Proc. 3rd International Conference on Computing, Networking and Communications. - Piscataway, NJ : IEEE Press. - 9781479923588 ; , s. 561-566
-
Conference paper (peer-reviewed)
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| 38. |
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| 39. |
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| 40. |
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| 41. |
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| 42. |
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| 43. |
- Ngai, Edith C.-H.
(author)
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On Providing Sink Anonymity for Sensor Networks
- 2009
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In: Proc. 5th International Wireless Communications and Mobile Computing Conference. - New York : ACM Press. - 9781605585697 ; , s. 269-273
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Conference paper (peer-reviewed)
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| 44. |
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| 45. |
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| 46. |
- Ngai, Edith C.-H., et al.
(author)
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Personalized Mobile-Assisted Smart Transportation
- 2016
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In: 2016 Digital Media Industry And Academic Forum (DMIAF). - 9781509010004 ; , s. 158-160
-
Conference paper (peer-reviewed)abstract
- Digital media covers larger parts of our daily lives nowadays. Mobile services enable a better connected society where citizens can easily access public services, discover events, and obtain important information in the city. We observe the popularity of mobile car sharing applications, such as Uber and Didi Dache. Mobile social applications provide new ways of developing and optimizing public transportation. In this paper, we present a mobile platform for timetable-free traveling. It can capture the traffic demand of citizens in real-time, and support efficient planning and scheduling for vehicles on-demand. At the moment, the platform is targeted for public bus services, but it has great potential to be extended for self-driving vehicles in the future.
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| 47. |
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| 48. |
- Ngai, Edith C.-H., et al.
(author)
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Quality-of-information-aware data collection for mobile sensor networks
- 2014
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In: Pervasive and Mobile Computing. - : Elsevier BV. - 1574-1192 .- 1873-1589. ; 11, s. 203-215
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Journal article (peer-reviewed)abstract
- Quality of information (QoI) in sensor networks measures information attributes such as precision, timeliness, completeness, and relevance of data ultimately delivered to users. It is a challenge to provide the required QoI in mobile sensor networks given the large scale and complexity of the networks with heterogeneous mobile and sensing devices. In this paper, we provide a comprehensive study on major QoI metrics for mobile sensor networks and discuss how QoI-aware data collection can be achieved. The cases with mobile sensors, mobile sinks, and mobile mules carrying data and their impact on QoI are discussed in detail. Mobility creates challenges in terms of timeliness but also opportunities in increased coverage and relevance. In a case study, we design a QoI-aware publish/subscribe system for mobile sensor networks. Users can subscribe to obtain information about events of interest by specifying the target area, sensing context, etc. The subscriptions and the sensing data are delivered to relevant sensors and users by location-based routing. We also discuss techniques that can be applied to further enhance the QoI in our publish/subscribe system. Simulation results demonstrate that the users can receive their subscribed data successfully with low communication overhead. Our publish/subscribe system can also handle mobility of clients smoothly without causing any data loss.
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| 49. |
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| 50. |
- Rodhe, Ioana, et al.
(author)
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On location privacy and quality of information in participatory sensing
- 2012
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In: Proc. 8th ACM Symposium on QoS and Security for Wireless and Mobile Networks. - New York : ACM Press. - 9781450316194 ; , s. 55-62
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Conference paper (peer-reviewed)abstract
- Participatory sensing applications typically bind sensor data to locations. Location privacy preserving mechanisms protecting the location of users introduce therefore an uncertainty in the collected data distributions. We consider two strategies to reconstruct a data distribution after k-anonymity has been applied to the users' location information. We investigate how different parameters for the location privacy preserving mechanism influence both the quality of information and the location privacy of the users. Our results show that the cloak area resulted from applying k-anonymity has a higher impact on both the quality of information and the location privacy than the number of users, k, that are cloaked together.
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