http://wpage.unina.it/valerio.persico/pubs/CloudIoT_FGCS.pdf

Integration of Cloud computing and Internet of Things

The Grid 2: Blueprint for a New Computing Infrastructure

Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, inexpensive, and smart sensors resulting in cost effective and easily deployable WSNs. However, researchers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this survey, we give an overview of wireless sensor networks and their application domains including the challenges that should be addressed in order to push the technology further. Then we review the recent technologies and testbeds for WSNs. Finally, we identify several open research issues that need to be investigated in future.

Our survey is different from existing surveys in that we focus on recent developments in wireless sensor network technologies. We review the leading research projects, standards and technologies, and platforms. Moreover, we highlight a recent phenomenon in WSN research that is to explore synergy between sensor networks and other technologies and explain how this can help sensor networks achieve their full potential. This paper intends to help new researchers entering the domain of WSNs by providing a comprehensive survey on recent developments.

Wireless sensor networks: a survey on recent developments and potential synergies

The book aims to provide a broad overview of various topics of the Internet of Things (IoT) from the research and development priorities to enabling technologies, architecture, security, privacy, interoperability and industrial applications. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC ? Internet of Things European Research Cluster from technology to international cooperation and the global "state of play". The book builds on the ideas put forward by the European research Cluster on the Internet of Things Strategic Research Agenda and presents global views and state of the art results on the challenges facing the research, development and deployment of IoT at the global level.

Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems

Privacy and Freedom.

In the past few years, wireless sensor networks (WSNs) have been gaining increasing attention because of their potential of enabling of novel and attractive solutions in areas such as industrial automation, environmental monitoring, transportation business, health-care etc. If we add this collection of sensor derived data to various Web-based social networks or virtual communities, blogs etc., we can have a remarkable transformation in our ability to "see" ourselves and our planet. Our primary goal is to facilitate connecting sensors, people and software objects to build community-centric sensing applications. However, the computational tools needed to launch this exploration may be more appropriately built from the data center "Cloud" computing model than the traditional HPC approaches. In this paper, we propose a framework to enable this exploration by integrating sensor networks to the emerging data center "cloud" model of computing. But there are many challenges to enable this framework. We propose a pub-sub based model which simplifies the integration of sensor networks with cloud based community-centric applications. Also there is a need for internetworking cloud providers in case of violation of service level agreement with users. We discussed these issues and proposed reasonable solutions.

A framework of sensor-cloud integration opportunities and challenges

Cloud-assisted secure video transmission and sharing framework for smart cities

With the advent of future generation mobile communication technologies (5G), there is the potential to allow mobile users to have access to big data processing over different clouds and networks. The increasing numbers of mobile users come with additional expectations for personalized services (e.g., social networking, smart home, health monitoring) at any time, from anywhere, and through any means of connectivity. Because of the expected massive amount of complex data generated by such services and networks from heterogeneous multiple sources, an infrastructure is required to recognize a user's sentiments (e.g., emotion) and behavioral patterns to provide a high quality mobile user experience. To this end, this paper proposes an infrastructure that combines the potential of emotion-aware big data and cloud technology towards 5G. With this proposed infrastructure, a bimodal system of big data emotion recognition is proposed, where the modalities consist of speech and face video. Experimental results show that the proposed approach achieves 83.10 % emotion recognition accuracy using bimodal inputs. To show the suitability and validity of the proposed approach, Hadoop-based distributed processing is used to speed up the processing for heterogeneous mobile clients.

Audio-Visual Emotion Recognition Using Big Data Towards 5G

The promising potential and emerging applications of cloud gaming have drawn increasing interest from academia, industry, and the general public. However, providing a high-quality gaming experience in the cloud gaming framework is a challenging task because of the tradeoff between resource consumption and player emotion, which is affected by the game screen. We tackle this problem by leveraging emotion-aware screen effects in the cloud gaming framework and combining them with remote display technology. The first stage in the framework is the learning or training stage, which establishes a relationship between screen features and emotions using Gaussian mixture model-based classifiers. In the operating stage, a linear programming model provides appropriate screen changes based on the real-time user emotion obtained in the first stage. Our experiments demonstrate the effectiveness of the proposed framework. The results show that our proposed framework can provide a high quality gaming experience while generating an acceptable amount of workload for the cloud server in terms of resource consumption.

Audio–Visual Emotion-Aware Cloud Gaming Framework

In recent years, the Smart City concept has become popular for its promise to improve the quality of life of urban citizens The concept involves multiple disciplines, such as Smart health care, Smart transportation, and Smart community Most services in Smart Cities, especially in the Smart healthcare domain, require the real-time sharing, processing, and analyzing of Big Healthcare Data for intelligent decision making Therefore, a strong wireless and mobile communication infrastructure is necessary to connect and access Smart healthcare services, people, and sensors seamlessly, anywhere at any time In this scenario, mobile cloud computing (MCC) can play a vital role by offloading Big Healthcare Data related tasks, such as sharing, processing, and analysis, from mobile applications to cloud resources, ensuring quality of service demands of end users Such resource migration, which is also termed virtual machine (VM) migration, is effective in the Smart healthcare scenario in Smart Cities In this paper, we propose an ant colony optimization-based joint VM migration model for a heterogeneous, MCC-based Smart Healthcare system in Smart City environment In this model, the user’s mobility and provisioned VM resources in the cloud address the VM migration problem We also present a thorough performance evaluation to investigate the effectiveness of our proposed model compared with the state-of-the-art approaches

Biao Song

Papers

A framework of sensor-cloud integration opportunities and challenges

Cloud-assisted secure video transmission and sharing framework for smart cities

Audio-Visual Emotion Recognition Using Big Data Towards 5G

Audio–Visual Emotion-Aware Cloud Gaming Framework

Mobile Cloud-Based Big Healthcare Data Processing in Smart Cities