Ernesto Exposito

Handling big data: research challenges and future directions

Today, an enormous amount of data is being continuously generated in all walks of life by all kinds of devices and systems every day. A significant portion of such data is being captured, stored, aggregated and analyzed in a systematic way without losing its “4V” (i.e., volume, velocity, variety, and veracity) characteristics. We review major drivers of big data today as well the recent trends and established platforms that offer valuable perspectives on the information stored in large and heterogeneous data sets. Then, we present a classification of some of the most important challenges when handling big data. Based on this classification, we recommend solutions that could address the identified challenges, and in addition we highlight cross-disciplinary research directions that need further investigation in the future.

Enabling Technologies for Green Internet of Things

Recent technological advances have led to an increase in the carbon footprint. Energy efficiency in the Internet of Things (IoT) has been attracting a lot of attention from researchers and designers over the last couple of years, paving the way for an emerging area called green IoT. There are various aspects (such as key enablers, communications, services, and applications) of IoT, where efficient utilization of energy is needed to enable a green IoT environment. We explore and discuss how the various enabling technologies (such as the Internet, smart objects, sensors, etc.) can be efficiently deployed to achieve a green IoT. Furthermore, we also review various IoT applications, projects and standardization efforts that are currently under way. Finally, we identify some of the emerging challenges that need to be addressed in the future to enable a green IoT.

FPTP: the XQoS aware and fully programmable transport protocol

Development of new communication services demands the complete understanding of the quality of service (QoS) requirements and efficient interaction with resources and the other services of the communication system. This paper proposes the use of a global QoS framework based on a common semantic namespace for the deployment of QoS oriented communication services offered by the fully programmable transport protocol. Experimental results demonstrate the feasibility and advantages of this proposal.

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients’ health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the “Knowledge as a Service” approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

Knowledge as a Service Framework for Disaster Data Management

Each year, a number of natural disasters strike across the globe, killing hundreds and causing billions of dollars in property and infrastructure damage. Minimizing the impact of disasters is imperative in todays society. As the capabilities of software and hardware evolve, so does the role of information and communication technology in disaster mitigation, preparation, response, and recovery. A large quantity of disaster-related data is available, including response plans, records of previous incidents, simulation data, social media data, and Web sites. However, current data management solutions offer few or no integration capabilities. Moreover, recent advances in cloud computing, big data, and NoSQL open the door for new solutions in disaster data management. In this paper, a Knowledge as a Service (KaaS) framework is proposed for disaster cloud data management (Disaster-CDM), with the objectives of 1) storing large amounts of disaster-related data from diverse sources, 2) facilitating search, and 3) supporting their interoperability and integration. Data are stored in a cloud environment using a combination of relational and NoSQL databases. The case study presented in this paper illustrates the use of Disaster-CDM on an example of simulation models.

IREEL: remote experimentation with real protocols and applications over an emulated network

This paper presents a novel e-learning platform called IREEL. IREEL is a virtual laboratory allowing students to drive experiments with real Internet applications and end-to-end protocols in the context of networking courses. This platform consists in a remote network emulator offering a set of pre-defined applications and protocol mechanisms. Experimenters configure and control the emulation and the end-systems behavior in order to perform tests, measurements, and observations on protocols or applications operating under controlled specific networking conditions. A set of end-to-end mechanisms, mainly focusing on transport and application-level protocols, are currently available. IREEL is scalable and easy to use thanks to an ergonomic web interface.

ARMISCOM: Autonomic reflective middleware for management service composition

In services composition the failure of a single service generates an error propagation in the others services involved, and therefore the failure of the system. Such failures often cannot be detected and corrected locally (single service), so it is necessary to develop architectures to enable diagnosis and correction of faults, both at individual (service) as global (composition levels). The middlewares, and particularly reflective middlewares, have been used as a powerful tool to cope with inherent heterogeneous nature of distributed systems in order to give them greater adaptability capacities. In this paper we propose a middleware architecture for the diagnosis of fully distributed service compositions called ARMISCOM, which is not coordinated by any global diagnoser. The diagnosis of faults is performed through the interaction of the diagnoser present in each service composition, and the repair strategies are developed through consensus of each repairer distributed equally in each service composition.

Towards a New Generation of Generic Transport Protocols

Considering that current end to end communication services are not adapted for supporting efficiently distributed multimedia application, this paper introduces a new family of generic transport protocols directly instantiated from application layer quality of service requirements. This Generic Transport Protocol (GTP) has been successfully tested for video on demand systems and is one of the major building block of the currently under development GCAP European project. GTP allows one to apply in the transport layer powerful adaptation mechanisms to the network behavior while preserving application requirements and alleviating network bandwidth and buffering needs

A Multimedia Ontology Driven Architecture framework (MODA) for networked multimedia systems

Heterogeneous multimedia environments make difficult the automatic deployment and interoperability of networked multimedia systems. Diversity of languages, protocols, and hardware platforms lead to major incompatibility issues. Moreover, dynamic multimedia systems instantiation and configuration guided by user and community requirements and preferences are not easy to be performed in this context. This work introduces an ontology framework for automatic networked multimedia systems deployment and configuration driven by the requirements and preferences of the users. A case study illustrating how networked multimedia systems can be dynamically deployed is presented in order to demonstrate the advantages of using this framework.

Using the XQoS platform for designing and developing the QoS-seeker system

The design and development process of complex systems requires an adequate methodology and efficient instrumental support in order to early detect and correct anomalies in the functional and non-functional properties of a new system. In this paper, an extensible and QoS-oriented platform is introduced and its use for designing and developing an advanced QoS location system is presented.