DPMSS 2015 - 4th International Workshop on Data-intensive Process Management in Large-Scale Sensor Systems (DPMSS 2015)

Due to recent advances in electronics and communication technologies, Sensor Networks (SNs) have been introduced and are currently emerging as one of the most disruptive technologies enabling and supporting next generation ubiquitous and pervasive computing scenarios. A SN consists of spatially distributed sensor nodes to cooperatively monitor physical, environmental, or human conditions, such as temperature, sound, vibration, pressure, motion, heart rate, blood pressure, ECG, etc. Each node is typically equipped with a radio transceiver or another communications device, a small microcontroller, a flash memory, an energy source, usually a battery; in addition, sensor nodes can also incorporate actuators to directly control devices. Application domains of SNs are broad and range from habitat and ecological monitoring, structural/building monitoring and smart space control, emergency response and remote surveillance, health care and transport systems. In recent years there has been a great surge of interest in SN-based applications, mainly focused on developing hardware, software, and networking architectures needed to enable such applications. In general, SNs can operate as stand-alone networks or be connected to other networks. Real-world experiments have been done with both types of network architectures, even though at much smaller scales than envisioned for the future. In the future, SN will be often seamlessly integrated with decentralized distributed systems based on other networks, particularly IP-based networks. Such integration will raise new issues in the development, deployment and management of such large-scale SN-based systems.
In particular, the management of data populating SN-based systems poses new research challenges ranging from data representation to data indexing, from data processing to querying, from data exchange/fusion to latest data analytics, and so forth. When challenges like those are applied to large-scale SN-based systems, more problematic issues must be faced-off, due to intrinsic drawbacks of state-of-the-art models, algorithms and techniques for representing and managing data over SN-based systems. Indeed, as widely recognized, traditional approaches usually suffer of scalability, reliability and availability limitations over large-scale applicative settings. As related to data-oriented challenges above, managing processes over large-scale SN-based systems requires accessing and elaborating huge amounts of data, even geographically distributed. The convergence of processes and data management over large-scale SN-based systems results in the definition of the so-called data-intensive processes over large-scale SN-based systems, which represents a novel and leading context for a wide research community. In this respect, relevant issues concern with methodologies for modeling and supporting data-intensive processes, integration and fusion approaches over data-intensive processes, activation and enactment paradigms for data-intensive processes over large-scale SN-based systems, and so forth.
The aim of DPMSS 2015 is to capture the new research trends and results in terms of design, architecture and applications for the management of processes and data in large-scale systems based on sensors, optimization of the processing of sensor data streaming; definition and use of innovative paradigms to develop applications in large-scale sensor networks, and their integration with Grid and Cloud infrastructures. This workshop will also identify potential research directions and technologies that will drive innovations within this domain. We anticipate this workshop to establish a pathway for the development of future-generation large-scale sensor-based systems. Specifically, the areas of interest are the following (but are not limited to), and, with particular emphasis, how these areas are investigated in the context of the integration of large-scale SNs with Grid and Cloud infrastructures:
Architectures for the management of large-scale SNs
Sensor data processing using Cloud environments
Specialist sensor networks for Cloud monitoring
Collaborative Wireless Sensor Networks
Integration of WSNs and mobile body sensor networks
Body Area Networks and Clouds
Representation models for data-intensive processes over large-scale SN-based systems;
Indexing strategies for data-intensive processes over large-scale SN-based systems;
Data exchange paradigms of data-intensive processes over large-scale SN-based systems;
Data fusion primitives and methods of data-intensive processes over large-scale SN-based systems;
Data analytics over data-intensive processes over large-scale SN-based systems;
Data scalability, reliability, and availability aspects of data-intensive processes over large-scale SN-based systems;
Models for data-intensive processes over large-scale SN-based systems;
Data access methods for data-intensive processes over large-scale SN-based systems;
Run-time support schemes of data-intensive processes over large-scale SN-based systems;
Integration schemes for data-intensive processes over large-scale SN-based systems;
Workflow paradigms for data-intensive processes over large-scale SN-based systems;
SN-based Systems in e-Health, e-Factory, Smart City, etc.
Sensor data collection via Cloud storage