2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)最新文献_第4页

Adaptive Edge Analytics for Distributed Networked Control of Water Systems 水系统分布式网络控制的自适应边缘分析

2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI) Pub Date : 2016-04-04 DOI: 10.1109/IoTDI.2015.34

Sokratis Kartakis, Weiren Yu, M. Akhavan, J. Mccann

{"title":"Adaptive Edge Analytics for Distributed Networked Control of Water Systems","authors":"Sokratis Kartakis, Weiren Yu, M. Akhavan, J. Mccann","doi":"10.1109/IoTDI.2015.34","DOIUrl":"https://doi.org/10.1109/IoTDI.2015.34","url":null,"abstract":"Over the last decade, there has been a trend where water utility companies aim to make water distribution networks more intelligent in order to improve their quality of service, reduce water waste, minimize maintenance costs etc., by incorporating IoT technologies. Current state of the art solutions use expensive power hungry deployments to monitor and transmit water network states periodically in order to detect anomalous behaviors such as water leakage and bursts. However, more than 97% of water network assets are remote away from power and are often in geographically remote underpopulated areas, facts that make current approaches unsuitable for next generation more dynamic adaptive water networks. Battery-driven wireless sensor/actuator based solutions are theoretically the perfect choice to support next generation water distribution. In this paper, we present an end-to-end water leak localization system, which exploits edge processing and enables the use of battery-driven sensor nodes. Our system combines a lightweight edge anomaly detection algorithm based on compression rates and an efficient localization algorithm based on graph theory. The edge anomaly detection and localization elements of the systems produce a timely and accurate localization result and reduce the communication by 99% compared to the traditional periodic communication. We evaluated our schemes by deploying non-intrusive sensors measuring vibrational data on a real-world water test rig that have had controlled leakage and burst scenarios implemented.","PeriodicalId":135674,"journal":{"name":"2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126356985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 29

World of Empowered IoT Users 授权物联网用户的世界

2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI) Pub Date : 2016-04-04 DOI: 10.1109/IoTDI.2015.39

Sayed Hadi Hashemi, F. Faghri, Paul Rausch, R. Campbell

{"title":"World of Empowered IoT Users","authors":"Sayed Hadi Hashemi, F. Faghri, Paul Rausch, R. Campbell","doi":"10.1109/IoTDI.2015.39","DOIUrl":"https://doi.org/10.1109/IoTDI.2015.39","url":null,"abstract":"In a world deploying an Internet of Things, sensors and actuators are owned, accessed, and activated by a plethora of individuals and organizations. Access to the data produced by this world can both be beneficial and have drawbacks to society. This data potentially represents the activities of millions of individuals and their possessions collected by billions of \"things'. Aggregations of this data can be analyzed through the Internet and Clouds. This raises possible privacy, security, moral and ethical challenges whose solutions will require flexible protection mechanisms. How do we \"acquire\" and \"distribute\" data at the IoT world scale while retaining the rights of individuals and organizations to protect, use, and share their data? Clearly a well-defined mechanism and control needs to regulate access to the data and its aggregations. Our paper describes a user-centric multi-level multiple granularity mechanism to share the data from these devices to people and organizations. Revisiting the fundamental mechanisms in security for providing protection, our solution uses capabilities, access lists, and access rights following well-understood formal notions for reasoning about access. Our contribution is to describe an auditable, transparent, distributed, decentralized, publication-subscription based, robust mechanism and automation of these ideas in the IoT realm that is well-matched to the current generation of clouds. It is based on well-tested principles and practices used in crypto currencies exploiting block chains of transactions. The scheme puts users (including organizational entities) in the center of control over the access to their collections of sensory data. In our paper, we describe a deployment of these ideas for health care, smart cities, and autonomous cars.","PeriodicalId":135674,"journal":{"name":"2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133247356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 99

A Modular Approach to Context-Aware IoT Applications 上下文感知物联网应用的模块化方法

2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI) Pub Date : 2016-04-01 DOI: 10.1109/IoTDI.2015.13

J. Venkatesh, Christine S. Chan, A. S. Akyurek, T. Simunic

{"title":"A Modular Approach to Context-Aware IoT Applications","authors":"J. Venkatesh, Christine S. Chan, A. S. Akyurek, T. Simunic","doi":"10.1109/IoTDI.2015.13","DOIUrl":"https://doi.org/10.1109/IoTDI.2015.13","url":null,"abstract":"The Internet of Things (IoT) refers to an environment of ubiquitous sensing and actuation, where devices are connected to a distributed backend infrastructure. It offers the opportunity to access a large amount of input data, and process it into contextual information about different system entities for reasoning and actuation. State-of-the-art IoT applications are generally black-box, end-to-end application-specific implementations, and cannot keep up with timely resolution of all this live, continually updated, heterogeneous data. In this work, we propose a modular approach to these context-aware applications, breaking down monolithic applications into an equivalent set of functional units, or context engines. By exploiting the characteristics of context-aware applications, context engines can reduce compute redundancy and computational complexity. In conjunction with formal data specifications, or ontologies, we can replace application-specific implementations with a composition of context engines that use common statistical learning to generate output, thus improving context reuse. We implement interconnected context-aware applications using our approach, extracting both user activity and location context from wearable sensors. We compare our infrastructure to single-stage monolithic implementations, demonstrating a reduction in application latency by up to 65% and execution overhead by up to 50% with only a 3% reduction in accuracy.","PeriodicalId":135674,"journal":{"name":"2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134275638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Query Processing for the Internet-of-Things: Coupling of Device Energy Consumption and Cloud Infrastructure Billing 物联网的查询处理:设备能耗与云基础设施计费的耦合

2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI) Pub Date : 2016-02-10 DOI: 10.1109/IoTDI.2015.37

F. Renna, Joseph Doyle, V. Giotsas, Y. Andreopoulos

{"title":"Query Processing for the Internet-of-Things: Coupling of Device Energy Consumption and Cloud Infrastructure Billing","authors":"F. Renna, Joseph Doyle, V. Giotsas, Y. Andreopoulos","doi":"10.1109/IoTDI.2015.37","DOIUrl":"https://doi.org/10.1109/IoTDI.2015.37","url":null,"abstract":"Audio/visual recognition and retrieval applications have recently garnered significant attention within Internet-of-Things (IoT) oriented services, given that video cameras and audio processing chipsets are now ubiquitous even in low-end embedded systems. In the most typical scenario for such services, each device extracts audio/visual features and compacts them into feature descriptors, which comprise media queries. These queries are uploaded to a remote cloud computing service that performs content matching for classification or retrieval applications. Two of the most crucial aspects for such services are: (i) controlling the device energy consumption when using the service, (ii) reducing the billing cost incurred from the cloud infrastructure provider. In this paper we derive analytic conditions for the optimal coupling between the device energy consumption and the incurred cloud infrastructure billing. Our framework encapsulates: the energy consumption to produce and transmit audio/visual queries, the billing rates of the cloud infrastructure, the number of devices concurrently connected to the same cloud server, and the statistics of the query data production volume per device. Our analytic results are validated via a deployment with: (i) the device side comprising compact image descriptors (queries) computed on Beaglebone Linux embedded platforms and transmitted to Amazon Web Services (AWS) Simple Storage Service, (ii) the cloud side carrying out image similarity detection via AWS Elastic Compute Cloud (EC2) spot instances, with the AWS Auto Scaling being used to control the number of instances according to the demand.","PeriodicalId":135674,"journal":{"name":"2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"164 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132756261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

Control Improvisation with Probabilistic Temporal Specifications 具有概率时间规范的控制即兴

2016 IEEE First International Conference on Internet-of-Things Design and Implementation (IoTDI) Pub Date : 2015-11-07 DOI: 10.1109/IoTDI.2015.33

Ilge Akkaya, Daniel J. Fremont, Rafael Valle, Alexandre Donzé, Edward A. Lee, S. Seshia

引用次数: 15