Showing papers in "IEEE Internet Computing in 2015"

From the Internet of Things to the Internet of People

Abstract: There's growing interest in developing applications for the Internet of Things. Such applications' main objective is to integrate technology into people's everyday lives, to be of service to them en masse. The form in which this integration is implemented, however, still leaves much room for improvement. Usually, the user must set parameters within the application. When the person's context changes, they have to manually reconfigure the parameters. What was meant to be a commodity in an unforeseen situation then becomes extra noise. This article describes a reference architecture that improves how people are integrated with the IoT, with smartphones doing the connecting. The resulting integration opens the way to new IoT scenarios supporting evolution towards the Internet of People.

Cloud Resource Orchestration Programming: Overview, Issues, and Directions

Abstract: Cloud computing provides on-demand access to affordable hardware (such as multicore CPUs, GPUs, disk drives, and networking equipment) and software (databases, application servers, load-balancers, data processors, and frameworks). The pervasiveness and power of cloud computing alleviates some of the problems that application administrators face in their existing hardware and locally managed software environments. However, the rapid increase in scale, dynamicity, heterogeneity, and diversity of cloud resources necessitates having expert knowledge about programming complex orchestration operations (for example, selection, deployment, monitoring, and runtime control) on those resources to achieve the desired quality of service. This article provides an overview of the key cloud resource types and resource orchestration operations, with special focus on research issues involved in programming those operations. The Web Extra can be found at https://s3.amazonaws.com/ieeecs.cdn.csdl.public/mags/ic/2015/05/mic2015050046s1.docx.

Multimodal Wearable Sensing for Fine-Grained Activity Recognition in Healthcare

Abstract: State-of-the-art in-home activity recognition schemes with wearable devices are mostly capable of detecting coarse-grained activities (sitting, standing, walking, or lying down), but can't distinguish complex activities (sitting on the floor versus the sofa or bed). Such schemes often aren't effective for emerging critical healthcare applications -- for example, in remote monitoring of patients with Alzheimer's disease, bulimia, or anorexia -- because they require a more comprehensive, contextual, and fine-grained recognition of complex daily user activities. Here, a novel approach for in-home, fine-grained activity recognition uses multimodal wearable sensors on multiple body positions, along with lightly deployed Bluetooth beacons in the environment. In particular, this solution exploits measuring user's ambient environment and location context with wearable sensing and Bluetooth beacons, along with user movement captured with accelerometer and gyroscope sensors. The proposed algorithm is a two-level supervised classifier with both levels running on a server. In the first level, multisensor data from wearables on each body position are collected and analyzed using the proposed modified conditional random field (CRF)-based supervised activity classifier. The classified activity state from each of the wearables data are then fused for deciding the user's final activity state. Preliminary experimental results are presented on the classification of 19 complex daily activities of a user at home.

Web-Based Management of the Internet of Things

Abstract: The Internet of Things (IoT) is an emerging paradigm where physical objects are connected and communicate over the Web. The IoT system presented here seamlessly integrates virtual and physical worlds to efficiently manage things of interest (TOIs), where services and resources offered by things easily can be monitored, visualized, and aggregated for value-added services by users. Using practical experience gained from this system, the authors identify several RaD opportunities for building future IoT applications.

Governance Challenges for the Internet of Things

Abstract: Before citizens and consumers can trust the infrastructure of the Internet of Things (IoT), they must feel that their personal data are protected. Here, the authors discuss how legal frameworks regarding data protection will need to be adjusted.

A Vision of Swarmlets

Abstract: Swarmlets are applications and services that leverage networked sensors and actuators with cloud services and mobile devices. This article offers a way to construct swarmlets by composing "accessors,"' which are wrappers for sensors, actuators, and services, that export an actor interface. Actor semantics provides ways to compose accessors with disciplined and understandable concurrency models, while hiding from the swarmlet the details of the mechanisms by which the accessor provides sensor data, controls an actuator, or accesses a service. This architecture can leverage the enormous variety of mechanisms that have emerged for such interactions, including HTTP, Websockets, CoAP, and MQTT. Recognizing that these standards have emerged because of huge variability of requirements for bandwidth, latency, and security, accessors embrace heterogeneity instead of attempting to homogenize.

Smart Cities' Data: Challenges and Opportunities for Semantic Technologies

Abstract: How can we innovate smart systems for smart cities, to make data available homogeneously, inexpensively, and flexibly while supporting an array of applications that have yet to exist or be specified?

Energy-Harvesting Wearables for Activity-Aware Services

Abstract: Recent advancements in energy-harvesting hardware have created an opportunity for realizing batteryless wearables for continuous and pervasive human activity recognition (HAR). Unfortunately, power consumption of accelerometers used in conventional HAR is relatively high compared to the amount of power that can be harvested practically, which limits the usefulness of energy harvesting. Here, the authors present and evaluate a novel energy-harvesting wearable sensor architecture, HAR from Kinetic Energy (HARKE), that doesn't require using an accelerometer. Using off-the-shelf products, the authors demonstrate that the voltage of a kinetic harvester exhibits distinguishable patterns to distinctly infer human activities. Their results demonstrate that HARKE is as accurate as an accelerometer-based HAR system, yet consumes only a small fraction of the limited harvested energy.

Privacy Concerns for Photo Sharing in Online Social Networks

Abstract: As wireless networks flourish, Internet users can access social network platforms (such as Facebook and Twitter) through personal electronic devices anywhere and anytime. However, because users often deploy social network platforms in a public network setting, a common concern remains about how to guarantee privacy for photo sharing. Although most platforms aim to protect such privacy, few are able to reach the goal. This work focuses on an interesting potential privacy risk, called the deletion delay of photo sharing, by pinpointing and investigating the risk's existence in some well-known social network platforms.

An Avatar Architecture for the Web of Things

Abstract: The Web of Things extends the Internet of Things by leveraging Web-based languages and protocols to access and control each physical object. In this article, the authors summarize ongoing work promoting the concept of an avatar as a new virtual abstraction to extend physical objects on the Web. An avatar is an extensible and distributed runtime environment endowed with an autonomous behavior. Avatars rely on Web languages, protocols, and reason about semantic annotations to dynamically drive connected objects, exploit their capabilities, and expose user-understandable functionalities as Web services. Avatars are also able to collaborate together to achieve complex tasks.

An Internet of Things for Healthcare

Abstract: Mobile health technologies and the Internet of Things (IoT) could provide automatic approaches to diagnosing health concerns, taking a step beyond information retrieval.

CometCloud: Enabling Software-Defined Federations for End-to-End Application Workflows

Abstract: Emerging applications, from big science to the Internet of Things, increasingly involve dynamic and data-driven end-to-end workflows with large and often heterogeneous requirements. These applications require platforms that dynamically and flexibly combine resources across systems and data centers--for example, to aggregate capacity or capabilities, or integrate data stores when moving data is no longer an option. The CometCloud project at the Rutgers Discovery Informatics Institute (RDI2) aims to provide infrastructure and programming support for enabling such end-to-end application workflows. CometCloud enables flexible software-defined synthesis of custom cyberinfrastructure through the autonomic, on-demand federation of geographically distributed compute and data resources. CometCloud exposes the federated cyberinfrastructure using elastic cloud abstractions and science-as-a-service platforms. The authors introduce CometCloud, use sample application use cases to illustrate its operation, and present current and future research directions toward supporting pervasive application workflows enabled by the Internet of Things.

Dynamic Social Structure of Things: A Contextual Approach in CPSS

Abstract: The emergence of cyber-physical-social systems (CPSS) and context-aware technologies has helped boost a growing interest in building frameworks for adaptive smart services that hide heterogeneity in the infrastructure and support services by seamlessly integrating the cyber, physical, and social worlds. However, this entails an enormous amount of computational and networking contextual complexity. Here, the proposed smart services framework in CPSS (called Dynamic Social Structure of Things, or DSSoT) boosts sociality and narrows down the contextual complexity based on situational awareness. DSSoT monitors spatiotemporal situations and, depending on users' individual goals and other social aspects, induces and structures relevant social objects and smart services in a temporal network of interactions. An application using DSSoT, called Airport Dynamic Social, provides a proof of concept.

I Know Where You've Been: Geo-Inference Attacks via the Browser Cache

Abstract: To provide more relevant content and better responsiveness, many websites customize their services according to users' geolocations. However, if geo-oriented websites leave location-sensitive content in the browser cache, other sites can sniff that content via side channels. The authors' case studies demonstrate the reliability and power of geo-inference attacks, which can measure the timing of browser cache queries and track a victim's country, city, and neighborhood. Existing defenses cannot effectively prevent such attacks, and additional support is required for a better defense deployment.

Trust Networks: Topology, Dynamics, and Measurements

Abstract: Thanks to the availability of user profiles and records of activity, online social network analysis can discover complex individual and social behavior patterns. The emergence of trust between users of online services is one of the most important phenomena, but it's also hard to detect in records of users' interactions, and even harder to replicate by abstract, generative models. Here, the authors investigate the emergence of "trusted" users (over time) by studying the evolution of topological and centrality measures of the network of trust within the overall social network. To do so, large datasets of user activity are studied from Ciao and Epinions (two online platforms with an explicit notion of trust controlled by users), and Prosper (a micro-lending site where trust remains implicit). The implications of such findings are discussed, particularly regarding how to enable trust in online platforms and interaction, with implications for trust-based activities.

Harvesting Opinions and Emotions from Social Media Textual Resources

Abstract: Harvesting sentiments from social media textual resources can reveal insightful information. The understanding and modeling of such resources are key requirements for accurately capturing the conveyed sentiments. Here, the authors consider multiple approaches, with an emphasis on detecting sentiments in Web 2.0 textual resources.

An Architecture and Guiding Framework for the Social Enterprise

Abstract: With the widespread adoption of social (aka Web 2.0) technologies like social networks, blogs, and wikis, there is a growing interest in looking into how enterprises should capitalize on these technologies. The social enterprise is the one that on top of having an online presence on the Internet, strives to open up new communication channels with stakeholders using social technologies. Building upon previous works on social business processes and on practical experiences on adopting such technologies in different Brazilian companies, this paper suggests an architecture and guiding framework for the social enterprise in terms of how to bridge the gap between the business world and social world and how to integrate social technologies into the enterprise's day-to-day operations.

Bidding Strategies for Spot Instances in Cloud Computing Markets

Abstract: In recent times, spot pricing -- a dynamic pricing scheme -- is becoming increasingly popular for cloud services. This new pricing format, though efficient in terms of cost and resource use, has added to the complexity of decision making for typical cloud computing users. To recommend bidding strategies in spot markets, we use a simulation study to understand the implications that provider-recommended strategies have for cloud users. We use data based on Amazon's Elastic Compute Cloud spot market to provide users with guidelines when considering tradeoffs between cost, wait time, and interruption rates.

Physical-Cyber-Social Computing: Looking Back, Looking Forward

Abstract: Physical-cyber-social (PCS) computing involves a holistic treatment of data, information, and knowledge from the physical, cyber, and social worlds to integrate, understand, correlate, and provide contextually relevant abstractions to humans and the applications that serve them. PCS computing extends current progress in cyber-physical, socio-technical, and cyber-social systems. Here, the guest editors consider powerful ways to exploit data available through various Internet of Things (IoT), citizen and social sensing, Web, and open data sources that are seeing explosive growth. This special issue highlights a variety of PCS applications, such as smart firefighting, intelligent infrastructure, and user guidance in an airport.

Detecting and Preventing Online Identity Deception in Social Networking Services

Abstract: In the past decade social networking services (SNS) flooded the Web. The nature of such sites makes identity deception easy, offering a quick way to set up and manage identities, and then connect with and deceive others. Fighting deception requires a coordinated approach by users and developers to ensure detection and prevention. This article identifies the most prevalent approaches in detecting and preventing identity deception (from both a user's and developer's perspective), evaluating their efficiency, and providing recommendations to help eradicate this issue.

Thingsonomy: Tackling Variety in Internet of Things Events

Abstract: The Internet of Things (IoT) will connect billions of devices to the Internet and create a large-scale dynamic and open environment with high heterogeneity. To assure rapid adoption of IoT applications, application developers and users need to be abstracted from IoT infrastructure via scalable middleware. Event-processing systems have the potential to contribute in filling the gap between the IoT infrastructure and applications layers. Event processing follows a decoupled model of interaction in space, time, and synchronization. However, the dimension of semantic coupling still exists and poses a challenge to scalability in highly semantically heterogeneous and dynamic environments such as the IoT. Here, the authors describe an approach based on loosely coupled producers and consumers enabled with approximate semantic matching of events. They emphasize a practitioner perspective to IoT architectures for building software that can tackle heterogeneity of IoT events.

Microbloggers as Sensors for Public Transport Breakdowns

Abstract: Microblogging has spread to fields where real-time awareness is crucial, such as predicting natural disasters or health outbreaks. Services such as Twitter can provide time-sensitive information from citizens, who have become sensors of important events by means of their digital footprints left through the use of mobile devices. User-generated data in urban contexts have been explored, mainly to infer and monitor public transport flows. Here, the authors use the observations and complaints from human sensors, collected through Twitter, to demonstrate how social sensing has the ability to detect breakdowns in a public transport network in real time, beyond official surveillance information. The system collects, filters, and processes the large datasets obtained to detect the daily problems in a public transport railway network of a major city and disseminate the results for user consumption through graphical rendering.

Where Is Everywhere: Bringing Location to the Web

Abstract: Hitherto rich geographical information has been a valuable, but highly specialized, corner of the Web. A linked Web that understands geographical concepts will immediately make much of the Web more useful to the developers of Web applications and will provide an important context for the emerging Internet of Things.

Requirements for and Barriers towards Interoperable eHealth Technology in Primary Care

Abstract: Despite eHealth technology's rapid growth, eHealth applications are rarely embedded within primary care, mostly because systems lack interoperability. This article identifies requirements for, and barriers towards, interoperable eHealth technology from healthcare professionals' perspective -- the people who decide when (and which) patients use the technology. After distributing surveys and performing interviews, the authors coded the data and applied thematic analyses. They subdivided results according to levels of interoperability, as workflow process, information, applications, and IT infrastructure. They found that implementing interoperable eHealth technology in primary care succeeds only when all identified levels of interoperability are taken into account.

The Origin and Evolution of Multistakeholder Models

Abstract: Various domains have adopted multistakeholder models (MSMs) to address and deal with global challenges, such as sustainability, environment, climate, and Internet governance. Here, the authors examine the use of MSMs and their historical evolution, fundamentals, and characteristics. They also present examples of how such models are used in the global Internet governance ecosystem. Finally, the article presents a series of research questions that can be tackled to improve the efficiency of multistakeholder processes.

Matching Over Linked Data Streams in the Internet of Things

Abstract: The Internet of Things (IoT) envisions smart objects collecting and sharing data at a global scale via the Internet. One challenging issue is how to disseminate data to relevant data consumers efficiently. This article leverages semantic technologies, such as Linked Data, which can facilitate machine-to-machine communications to build an efficient stream dissemination system for Semantic IoT. The system integrates Linked Data streams generated from various data collectors and disseminates matched data to relevant data consumers based on user queries registered in the system. Here, the authors present a new data structure, TP-automata, designed to suit the high-performance needs of Linked Data stream dissemination. They evaluate the system using a real-world dataset generated in a Smart Building IoT Project. The proposed system can disseminate Linked Data streams at one million triples per second with 100,000 registered user queries, which is several orders of magnitude faster than existing techniques.

The Effectiveness of Security Images in Internet Banking

Abstract: Internet banking websites often use security images as part of the login process, under the theory that they can help foil phishing attacks. Previous studies, however, have yielded inconsistent results about users' ability to notice that a security image is missing. This article describes an online study of 482 users that attempts to clarify the extent to which users notice and react to the absence of security images. Most participants (73 percent) entered their password when the security image and caption were removed. The authors found that changing the appearance and other characteristics of the security image generally had little effect on whether users logged in when the security image was absent. Additionally, they subjected the passwords created by participants to a password-cracking algorithm and found that participants with stronger passwords were less likely (64.7 percent versus 80.1 percent) to enter their passwords when the security image was missing.

SDM^2 Cast An OpenFlow-Based, Software-Defined Scalable Multimedia Multicast Streaming Framework

Abstract: Software-defined networking (SDN) has emerged as a promising network technology supporting the intelligent and dynamic nature of future networks and applications. Against this changing network landscape, the authors design an SDN-based, scalable multimedia multicast streaming framework, which optimizes multimedia flow management and provides scalability and flexibility. The proposed framework is capable of in-network identification, processing, and management of media streams. It implements network-layer multicast similar to IP multicast, but it allows admission control in a multicast context. An implemented prototype shows the proposed framework's possibilities and results.

On Schema.org and Why It Matters for the Web

Abstract: Schema.org has addressed a critical issue for the Web - making it simple to annotate the data inside webpages at least for the most popular types of Web content. This has made it possible to deploy existing applications such as rich snippets more widely. However, schema.org still has a long way to go as new applications arise. In fact, the question often comes up whether schema.org is an end-all solution for defining terminology for the Semantic Web. At the current stage, the answer is definitely no, as much more in-depth vocabularies exist in specialized domains such as medicine. Over time, however, schema.org may provide a core linking hub for these more specialized efforts, the same way Dbpedia has become the linking hub of the Linked Data Web. The main challenge for schema.org is to be able to scale as it receives an increasing number of requests for extensions and alignment with existing efforts. Defining the right extension mechanisms and processes to support our growth is the schema.org steering group's current priority.

Access Control and the Internet of Things

Abstract: Where and how should access control be exercised over cyber-physical systems? Here, Vint Cerf deliberates a possible way to secure such systems.