2008
Conference article
Open Access
A secure middleware for wireless sensor networks
Vairo C, Albano M, Chessa S
SMEPP Light is a middleware for Wireless Sensor Networks (WSNs) based on mote-class sensors. It is derived from the specification developed under the framework of the SMEPP pro ject, to deal with the hardware and software constraints of WSNs. SMEPP Light features group management, group- level security policies, mechanisms for query injection and data collection based on a subscribe/event mechanism, and adaptable energy efficiency mechanisms. In this paper we present the SMEPP Light specification, its architecture and its main protocols for communication, security, and energy efficiency.DOI: 10.4108/icst.mobiquitous2008.3888
Metrics:
Vairo C, Albano M, Chessa S
SMEPP Light is a middleware for Wireless Sensor Networks (WSNs) based on mote-class sensors. It is derived from the specification developed under the framework of the SMEPP pro ject, to deal with the hardware and software constraints of WSNs. SMEPP Light features group management, group- level security policies, mechanisms for query injection and data collection based on a subscribe/event mechanism, and adaptable energy efficiency mechanisms. In this paper we present the SMEPP Light specification, its architecture and its main protocols for communication, security, and energy efficiency.DOI: 10.4108/icst.mobiquitous2008.3888
Metrics:
See at:
IRIS Cnr 
| dl.acm.org | IRIS Cnr | eudl.eu | IRIS Cnr | ISTI Repository | arpi.unipi.it 
| dblp.uni-trier.de | dblp.uni-trier.de | Archivio della Ricerca - Università di Pisa | doi.org | doi.org | doi.org | eudl.eu | eudl.eu | Archivio della Ricerca - Università di Pisa | CNR IRIS | www.sciencedirect.com
2013
Conference article
Restricted
Distributed neural computation over WSN in ambient intelligence
Bacciu D, Gallicchio C, Lenzi A, Chessa S, Micheli A, Pelagatti S, Vairo C
Ambient Intelligence (AmI) applications need information about the surrounding environment. This can be collected by means of Wireless Sensor Networks (WSN) that also analyze and build forecasts for applications. The RUBICON Learning Layer implements a distributed neural computation over WSN. In this system, measurements taken by sensors are combined by using neural computation to provide future forecasts based on previous measurements and on the past knowledge of the environment.Source: ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING, pp. 147-154. Salamanca, 22-24 May 2013
DOI: 10.1007/978-3-319-00566-9_19
Project(s): RUBICON
Metrics:
Bacciu D, Gallicchio C, Lenzi A, Chessa S, Micheli A, Pelagatti S, Vairo C
Ambient Intelligence (AmI) applications need information about the surrounding environment. This can be collected by means of Wireless Sensor Networks (WSN) that also analyze and build forecasts for applications. The RUBICON Learning Layer implements a distributed neural computation over WSN. In this system, measurements taken by sensors are combined by using neural computation to provide future forecasts based on previous measurements and on the past knowledge of the environment.Source: ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING, pp. 147-154. Salamanca, 22-24 May 2013
DOI: 10.1007/978-3-319-00566-9_19
Project(s): RUBICON
Metrics:
See at:
doi.org | CNR IRIS | CNR IRIS | link.springer.com
2012
Other
Restricted
Dynamic Detection and Tracking of Composite Events in Wireless Sensor Networks
Vairo Claudio Francesco
In questa tesi si presenta un sistema (MaD-WiSe) per la gestione efficiente di dati in reti di sensori senza fili (WSN) in scenari statici, e si forniscono diverse tecniche di ottimizzazione validate da risultati sperimentali su una rete di sensori reale. Si presenta inoltre un nuovo linguaggio dichiarativo (EQL) per esprimere eventi compositi da rilevare e tracciare in modo dinamico e autonomo e si fornisce uno schema di implementazione e un simulatore per la valutazione delle performance.
Vairo Claudio Francesco
In questa tesi si presenta un sistema (MaD-WiSe) per la gestione efficiente di dati in reti di sensori senza fili (WSN) in scenari statici, e si forniscono diverse tecniche di ottimizzazione validate da risultati sperimentali su una rete di sensori reale. Si presenta inoltre un nuovo linguaggio dichiarativo (EQL) per esprimere eventi compositi da rilevare e tracciare in modo dinamico e autonomo e si fornisce uno schema di implementazione e un simulatore per la valutazione delle performance.
See at:
etd.adm.unipi.it | CNR IRIS | CNR IRIS
2024
Other
Open Access
SUN D5.1 - SUN Platform architecture
Ferdinando Bosco, Giovanni Di Marco, Alexandru Stan, George Loukas, Panagiotis Kasnesis, Lazaros Toumanidis, Ioannis Paraskevopoulos, Vincent Mendez, Leesa Joyce, Claudio Vairo, Spyridon Symeonidis, Sotiris Diplaris, Vasileios-Rafail Xefteris, Ilias Poulios, Panagiotis Vrachnos, Georgios Loupas, Orestis Sarakatsanos
This document reports the SUN Architecture design and technical specifications for implementing the SUN XR Platform.Project(s): SUN
Ferdinando Bosco, Giovanni Di Marco, Alexandru Stan, George Loukas, Panagiotis Kasnesis, Lazaros Toumanidis, Ioannis Paraskevopoulos, Vincent Mendez, Leesa Joyce, Claudio Vairo, Spyridon Symeonidis, Sotiris Diplaris, Vasileios-Rafail Xefteris, Ilias Poulios, Panagiotis Vrachnos, Georgios Loupas, Orestis Sarakatsanos
This document reports the SUN Architecture design and technical specifications for implementing the SUN XR Platform.Project(s): SUN
2012
Conference article
Restricted
Self-sustaining learning for robotic ecologies.
Bacciu D, Broxvall M, Coleman S, Dragone M, Gallicchio C, Gennaro C, Guzman R, Lopez R, Lozanopeiteado H, Ray A, Renteria A, Saffiotti A, Vairo C
The most common use of wireless sensor networks (WSNs) is to collect environmental data from a specific area, and to channel it to a central processing node for on-line or off-line analysis. The WSN technology, however, can be used for much more ambitious goals. We claim that merging the concepts and technology of WSN with the concepts and technology of distributed robotics and multi-agent systems can open new ways to design systems able to provide intelligent services in our homes and working places. We also claim that endowing these systems with learning capabilities can greatly increase their viability and acceptability, by simplifying design, customization and adaptation to changing user needs. To support these claims, we illustrate our architecture for an adaptive robotic ecology, named RUBICON, consisting of a network of sensors, effectors and mobile robots.
Bacciu D, Broxvall M, Coleman S, Dragone M, Gallicchio C, Gennaro C, Guzman R, Lopez R, Lozanopeiteado H, Ray A, Renteria A, Saffiotti A, Vairo C
The most common use of wireless sensor networks (WSNs) is to collect environmental data from a specific area, and to channel it to a central processing node for on-line or off-line analysis. The WSN technology, however, can be used for much more ambitious goals. We claim that merging the concepts and technology of WSN with the concepts and technology of distributed robotics and multi-agent systems can open new ways to design systems able to provide intelligent services in our homes and working places. We also claim that endowing these systems with learning capabilities can greatly increase their viability and acceptability, by simplifying design, customization and adaptation to changing user needs. To support these claims, we illustrate our architecture for an adaptive robotic ecology, named RUBICON, consisting of a network of sensors, effectors and mobile robots.
2013
Other
Open Access
RUBICON - Final version of the communication layer
Dragone M, Gennaro C, Vairo C, Saffiotti A
This deliverable (D1.3.2) takes place at the end of Task 1.3 Final version of Communication Layer at M24 of RUBICON WP1. The goal of the RUBICON Communication Layer (CML) is to provide communication and integration mechanisms built upon middleware for WSN/WSANs and robotic ecologies. Together with D1.2 and D1.4, this deliverable presents a set of requirements and specifications supported by the final version of the software, as delivered at M24. In addition to this report with an appendix documenting the CML API, the main part of the deliverable consists of the published software, available on the RUBICON code repository and later to be released on the project webpage. This report furthermore summarizes, in brief, the state and the achievement of all tasks scheduled for M13-M24 of RUBICON WP1.Project(s): RUBICON
Dragone M, Gennaro C, Vairo C, Saffiotti A
This deliverable (D1.3.2) takes place at the end of Task 1.3 Final version of Communication Layer at M24 of RUBICON WP1. The goal of the RUBICON Communication Layer (CML) is to provide communication and integration mechanisms built upon middleware for WSN/WSANs and robotic ecologies. Together with D1.2 and D1.4, this deliverable presents a set of requirements and specifications supported by the final version of the software, as delivered at M24. In addition to this report with an appendix documenting the CML API, the main part of the deliverable consists of the published software, available on the RUBICON code repository and later to be released on the project webpage. This report furthermore summarizes, in brief, the state and the achievement of all tasks scheduled for M13-M24 of RUBICON WP1.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2012
Other
Open Access
RUBICON - Core Learning Services API and Documentation V.1.0
Bacciu D, Gallicchio C, Micheli A, Vairo C, Chessa S, Bonuccelli M, Dragone M, Amato G
This report describes the release 1.0 of the "Core Learning Service API" software, presented as deliverable D2.2. We focus here on a description of the design and current implementation status of this software, and we outline the future work to be performed as part of tasks 2.4 - 2.5, leading up to the second release in deliverable D2.3 in month 30.Project(s): RUBICON
Bacciu D, Gallicchio C, Micheli A, Vairo C, Chessa S, Bonuccelli M, Dragone M, Amato G
This report describes the release 1.0 of the "Core Learning Service API" software, presented as deliverable D2.2. We focus here on a description of the design and current implementation status of this software, and we outline the future work to be performed as part of tasks 2.4 - 2.5, leading up to the second release in deliverable D2.3 in month 30.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2012
Other
Open Access
RUBICON - Preliminary version of Communication Layer
Broxvall M, Gennaro C, Vairo C, Saffiotti A
This report describes the software, Preliminary version of Communication Layer, presented as deliverable D1.3.1 for RUBICON. We focus here on a description of the design and implementation of this software, the exact scope of the current implementation and outline the future work to be performed as part of task 1.2 - 1.4, leading up to deliverable D1.3.2 in month 24. In addition to this report with an appendix documenting the communication layer API, the main part of the deliv- erable consists of the published software, available on the RUBICON code repository and later to be released on the project webpage. This report furthermore summarizes, in brief, the state of workpackage WP1 and the achievement of all tasks scheduled for M1-M12 of RUBICON.Project(s): RUBICON
Broxvall M, Gennaro C, Vairo C, Saffiotti A
This report describes the software, Preliminary version of Communication Layer, presented as deliverable D1.3.1 for RUBICON. We focus here on a description of the design and implementation of this software, the exact scope of the current implementation and outline the future work to be performed as part of task 1.2 - 1.4, leading up to deliverable D1.3.2 in month 24. In addition to this report with an appendix documenting the communication layer API, the main part of the deliv- erable consists of the published software, available on the RUBICON code repository and later to be released on the project webpage. This report furthermore summarizes, in brief, the state of workpackage WP1 and the achievement of all tasks scheduled for M1-M12 of RUBICON.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2011
Other
Open Access
RUBICON - Control Layer Architecture
Dragone M, Broxvall M, Pecora F, Saffiotti A, Swords D, Abdelnaby S, Vairo C, Gennaro C
This deliverable (D3.1) takes place at the end of the first task (T3.1 - Functional Design and Specifications) of WP3 - the RUBICON Control Layer. The goal of the Control Layer is to exercise high level control over the sensing/acting/communication capabilities of the RUBICON system. This control focuses on devising suitable action and configuration strategies while exploiting the RUBICON Learning Layer (WP2) to adapt these strategies to the environment and improve their quality over time. Together with D1.1, D2.1, and D4.1, this deliverable presents a set of requirements and specifications to support the development of the RUBICON system . The requirements reported here provide a collection of statements to inform research directions for the RUBICON project. They are based on several inputs: the Description of Work (DoW) document, a Closed Workshop (June 20-23, OÌ^rebro), the case studies described in Section 2.1 (which combine contributions from all the RUBICON partners), the requirements described in deliverables D2.1 and D4.1, as well as input from several informal discussions among the project consortium. These inputs are used to carry out domain analysis, leading to the identification of the requirements for the Control Layer. After that, this document examines the state of the art in control solutions applicable to robotic ecologies in order to provide a first approximation of the design of the control layer and its most important interactions with the other layers of the RUBICON architecture. Finally, this deliverable provides the specifications of a test-plan to be used for the development and the evaluation of the various releases of the RUBICON middleware.Project(s): RUBICON
Dragone M, Broxvall M, Pecora F, Saffiotti A, Swords D, Abdelnaby S, Vairo C, Gennaro C
This deliverable (D3.1) takes place at the end of the first task (T3.1 - Functional Design and Specifications) of WP3 - the RUBICON Control Layer. The goal of the Control Layer is to exercise high level control over the sensing/acting/communication capabilities of the RUBICON system. This control focuses on devising suitable action and configuration strategies while exploiting the RUBICON Learning Layer (WP2) to adapt these strategies to the environment and improve their quality over time. Together with D1.1, D2.1, and D4.1, this deliverable presents a set of requirements and specifications to support the development of the RUBICON system . The requirements reported here provide a collection of statements to inform research directions for the RUBICON project. They are based on several inputs: the Description of Work (DoW) document, a Closed Workshop (June 20-23, OÌ^rebro), the case studies described in Section 2.1 (which combine contributions from all the RUBICON partners), the requirements described in deliverables D2.1 and D4.1, as well as input from several informal discussions among the project consortium. These inputs are used to carry out domain analysis, leading to the identification of the requirements for the Control Layer. After that, this document examines the state of the art in control solutions applicable to robotic ecologies in order to provide a first approximation of the design of the control layer and its most important interactions with the other layers of the RUBICON architecture. Finally, this deliverable provides the specifications of a test-plan to be used for the development and the evaluation of the various releases of the RUBICON middleware.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2013
Other
Open Access
RUBICON - Integration of Communication Layer and Robotic Components
Gennaro C, Dragone M, Saffiotti A, Lozano H, Di Rocco M, Vairo C
This deliverable (D1.2) describes the work carried out in the Task 1.2 Integration of Robotic Components and WSAN. In particular, T1.2 concerns the integration of previously existing robotic devices and software components to satisfy the requirements posed by Task 1.1, which involves the generic integration of pre-existing robotic com- munication tools (Part of the PEIS-ROS bridge) and the integration of specific PEIS Ecology functionalities to non-PEIS side of Communication Layer. This latter task includes the routing between islands and the access to non-WSN sensors inside WSN network.Project(s): RUBICON
Gennaro C, Dragone M, Saffiotti A, Lozano H, Di Rocco M, Vairo C
This deliverable (D1.2) describes the work carried out in the Task 1.2 Integration of Robotic Components and WSAN. In particular, T1.2 concerns the integration of previously existing robotic devices and software components to satisfy the requirements posed by Task 1.1, which involves the generic integration of pre-existing robotic com- munication tools (Part of the PEIS-ROS bridge) and the integration of specific PEIS Ecology functionalities to non-PEIS side of Communication Layer. This latter task includes the routing between islands and the access to non-WSN sensors inside WSN network.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2013
Other
Open Access
RUBICON - Proxy-specific Software Suite
Dragone M, Gennaro C, Saffiotti A, Vairo C
This deliverable takes place at the end of (M24) of the RUBICON project WP1 building the RUBICON Com- munication Layer (CML). The CML provides communication and integration mechanisms built upon middleware for wireless sensor and actuator networks (WSANs) and robotic ecologies. The objective of this deliverable is to describe the output of the work carried out in Task 1.4: Adaptation of existing data-sharing middle-ware and proxy solutions for WSN/robot integration. This task involves the identification of common component description for automatic discovery of hardware and processing capabilities and the provision of standard mechanisms that the higher layers of the RUBICON system can use to interact with the underlying sensing and acting infrastruc- ture, including computational constrained devices. Such a set of functionalities is accomplished by the RUBICON component Proxy for WSAN, which extends the functionalities of the Gateway, i.e. the bridge between the Peis middleware and the WSAN described in D1.3.1. The extension of the Gateway includes the generic mechanisms for representation of motes sensor and actuation capabilities, the routing between multiple islands, and the integra- tion of heterogeneous networks. This document refines the initial proxy design presented in D1.3.1. It discusses the motivations behind the design choices and the methods used to ground that initial prototype in the final design and the implementation of the CML in line with the communication stack presented in D1.3.2. The results of this deliverable will be an input and the basis for the integration work to be carried out in WP5 in both the transport and the Ambient Assisted Living application scenarios.Project(s): RUBICON
Dragone M, Gennaro C, Saffiotti A, Vairo C
This deliverable takes place at the end of (M24) of the RUBICON project WP1 building the RUBICON Com- munication Layer (CML). The CML provides communication and integration mechanisms built upon middleware for wireless sensor and actuator networks (WSANs) and robotic ecologies. The objective of this deliverable is to describe the output of the work carried out in Task 1.4: Adaptation of existing data-sharing middle-ware and proxy solutions for WSN/robot integration. This task involves the identification of common component description for automatic discovery of hardware and processing capabilities and the provision of standard mechanisms that the higher layers of the RUBICON system can use to interact with the underlying sensing and acting infrastruc- ture, including computational constrained devices. Such a set of functionalities is accomplished by the RUBICON component Proxy for WSAN, which extends the functionalities of the Gateway, i.e. the bridge between the Peis middleware and the WSAN described in D1.3.1. The extension of the Gateway includes the generic mechanisms for representation of motes sensor and actuation capabilities, the routing between multiple islands, and the integra- tion of heterogeneous networks. This document refines the initial proxy design presented in D1.3.1. It discusses the motivations behind the design choices and the methods used to ground that initial prototype in the final design and the implementation of the CML in line with the communication stack presented in D1.3.2. The results of this deliverable will be an input and the basis for the integration work to be carried out in WP5 in both the transport and the Ambient Assisted Living application scenarios.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2013
Other
Open Access
RUBICON - Core Learning Services API and Documentation V.2.0
Bacciu D, Gallicchio C, Micheli A, Vairo C, Chessa S, Dragone M
This report describes the release 2.0 of the "Core Learning Service API" software, presented as deliverable D2.3. We focus here on a description of the design and implementation of this software, and we provide an experimental evaluation of its performance on real-world data from the RUBICON application scenarios in WP5.Project(s): RUBICON
Bacciu D, Gallicchio C, Micheli A, Vairo C, Chessa S, Dragone M
This report describes the release 2.0 of the "Core Learning Service API" software, presented as deliverable D2.3. We focus here on a description of the design and implementation of this software, and we provide an experimental evaluation of its performance on real-world data from the RUBICON application scenarios in WP5.Project(s): RUBICON
See at:
CNR IRIS | ISTI Repository | CNR IRIS
2022
Software
Metadata Only Access
Extension image recognition system
Bolettieri P, Vairo C
Image recognition system realised for the ESA Extension project. The system is able to visually recognise the main monuments of the city of L'Aquila.
Bolettieri P, Vairo C
Image recognition system realised for the ESA Extension project. The system is able to visually recognise the main monuments of the city of L'Aquila.
See at:
gitea-s2i2s.isti.cnr.it | CNR IRIS
2010
Journal article
Restricted
MaD-WiSe: a distributed stream management system for wireless sensor networks
Amato G, Chessa S, Vairo C
Wireless sensor networks (WSN) are composed of several sensors having limited memory, processing power, communication bandwidth, and energy, which cooperate in performing a given task. The use of the database paradigm has emerged in the last few years as a viable solution to manage data in such a context. In this paper we present the MaD-WiSe system, a distributed query processing framework that moves the processing of the query into the network. MaD-WiSe reconsiders various aspects related to database system design and it reinterprets them according to the WSN constraints and requirements. In particular it considers the aspects related to the definition of a query language to formalize the queries, a stream model to manage data acquired by the sensors, a query algebra to define the operators that actually perform the query, and energy efficiency and query optimization strategies for saving energy.Source: SOFTWARE-PRACTICE & EXPERIENCE, vol. 40 (issue 5), pp. 431-451
DOI: 10.1002/spe.965
Metrics:
Amato G, Chessa S, Vairo C
Wireless sensor networks (WSN) are composed of several sensors having limited memory, processing power, communication bandwidth, and energy, which cooperate in performing a given task. The use of the database paradigm has emerged in the last few years as a viable solution to manage data in such a context. In this paper we present the MaD-WiSe system, a distributed query processing framework that moves the processing of the query into the network. MaD-WiSe reconsiders various aspects related to database system design and it reinterprets them according to the WSN constraints and requirements. In particular it considers the aspects related to the definition of a query language to formalize the queries, a stream model to manage data acquired by the sensors, a query algebra to define the operators that actually perform the query, and energy efficiency and query optimization strategies for saving energy.Source: SOFTWARE-PRACTICE & EXPERIENCE, vol. 40 (issue 5), pp. 431-451
DOI: 10.1002/spe.965
Metrics:
See at:
Software Practice and Experience | CNR IRIS | CNR IRIS | onlinelibrary.wiley.com | Software Practice and Experience
2009
Conference article
Restricted
Optimizing network-side queries with timestamp-join in wireless sensor networks
Amato G, Chessa S, Vairo C
This paper proposes a new method for optimizing in-network distributed queries that perform join of data produced simultaneously by different sensors in a wireless sensor network. We adopt a modified version of the standard join operator that relates tuples having the same timestamp, and an optimized version of it, which provides on-demand, pull-mode, data acquisition from sensors. The optimizer uses an algebraic approach based on transformation rules and ordering of operators to generate and chose a query plan that reduces the query execution cost in terms of consumed energy. We implemented these join operations in a query processor for mica-class sensors and we performed extensive tests to prove that our approach may reduce energy required to process a long running query, by order of magnitudes, with respect to non optimized query plans.DOI: 10.1109/iecon.2009.5415256
Metrics:
Amato G, Chessa S, Vairo C
This paper proposes a new method for optimizing in-network distributed queries that perform join of data produced simultaneously by different sensors in a wireless sensor network. We adopt a modified version of the standard join operator that relates tuples having the same timestamp, and an optimized version of it, which provides on-demand, pull-mode, data acquisition from sensors. The optimizer uses an algebraic approach based on transformation rules and ordering of operators to generate and chose a query plan that reduces the query execution cost in terms of consumed energy. We implemented these join operations in a query processor for mica-class sensors and we performed extensive tests to prove that our approach may reduce energy required to process a long running query, by order of magnitudes, with respect to non optimized query plans.DOI: 10.1109/iecon.2009.5415256
Metrics:
See at:
doi.org | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2010
Conference article
Restricted
Modeling detection and tracking of complex events in wireless sensor networks
Vairo C, Amato G, Chessa S, Valleri P
Current approaches to the query of wireless sensor networks address specific sources such as individual sensors or transducers. We believe that it is important to have a higher level mechanism of abstraction for querying a sensor network. In this work we aim at querying complex events, where such an event is modeled as a condition computed over a complex aggregate of sensed data. When the condition becomes true then the event is detected and tracked. In this paper we present a model for detecting and tracking such complex events in a WSN and we propose a declarative language for the event definition and for the detection and tracking specification and we also discuss its implementation guidelines.DOI: 10.1109/icsmc.2010.5642242
Metrics:
Vairo C, Amato G, Chessa S, Valleri P
Current approaches to the query of wireless sensor networks address specific sources such as individual sensors or transducers. We believe that it is important to have a higher level mechanism of abstraction for querying a sensor network. In this work we aim at querying complex events, where such an event is modeled as a condition computed over a complex aggregate of sensed data. When the condition becomes true then the event is detected and tracked. In this paper we present a model for detecting and tracking such complex events in a WSN and we propose a declarative language for the event definition and for the detection and tracking specification and we also discuss its implementation guidelines.DOI: 10.1109/icsmc.2010.5642242
Metrics:
See at:
doi.org | CNR IRIS | ieeexplore.ieee.org | CNR IRIS
2008
Software
Metadata Only Access
Mad-Wise: Versione con routing multi-hop
Amato G, Chessa S, Vairo C
Nuova versione del proptotipo MadWise con supporto per la comunicazione MultiHop
Amato G, Chessa S, Vairo C
Nuova versione del proptotipo MadWise con supporto per la comunicazione MultiHop
See at:
CNR IRIS
2009
Other
Restricted
Optimizing network-side queries with timestamp-join in wireless sensor networks
Amato G, Chessa S, Vairo C
This paper proposes a new method for optimizing innetwork distributed queries that perform join of data produced simultaneously by different sensors in a wireless sensor network. We adopt a modified version of the standard join operator that relates tuples having the same timestamp, and an optimized version of it, which provides on-demand, pull-mode, data acquisition from sensors. The optimizer uses an algebraic approach based on transformation rules and ordering of operators to generate and chose a query plan that reduces the query execution cost in terms of consumed energy. We implemented these join operations in a query processor for mica-class sensors and we performed extensive tests to prove that our approach may reduce energy required to process a long running query, by order of magnitudes,with respect to non optimized query plans.
Amato G, Chessa S, Vairo C
This paper proposes a new method for optimizing innetwork distributed queries that perform join of data produced simultaneously by different sensors in a wireless sensor network. We adopt a modified version of the standard join operator that relates tuples having the same timestamp, and an optimized version of it, which provides on-demand, pull-mode, data acquisition from sensors. The optimizer uses an algebraic approach based on transformation rules and ordering of operators to generate and chose a query plan that reduces the query execution cost in terms of consumed energy. We implemented these join operations in a query processor for mica-class sensors and we performed extensive tests to prove that our approach may reduce energy required to process a long running query, by order of magnitudes,with respect to non optimized query plans.
2010
Other
Restricted
Modeling detection and tracking of complex events in wireless sensor networks
Amato G, Chessa S, Vairo C, Valleri P
Current approaches to the query of wireless sensor networks address specific sources such as individual sensors or transducers. We believe that it is important to have a higher level mechanism of abstraction for querying a sensor network. In this work we aim at querying complex events, where such an event is modeled as a condition computed over a complex aggregate of sensed data. When the condition becomes true then the event is detected. In this paper we present a model for detecting and tracking such complex events in a WSN and we propose a declarative language for the event definition and for the detection and tracking specification and we also discuss its implementation guidelines.
Amato G, Chessa S, Vairo C, Valleri P
Current approaches to the query of wireless sensor networks address specific sources such as individual sensors or transducers. We believe that it is important to have a higher level mechanism of abstraction for querying a sensor network. In this work we aim at querying complex events, where such an event is modeled as a condition computed over a complex aggregate of sensed data. When the condition becomes true then the event is detected. In this paper we present a model for detecting and tracking such complex events in a WSN and we propose a declarative language for the event definition and for the detection and tracking specification and we also discuss its implementation guidelines.
2011
Conference article
Restricted
Efficient detection of composite events in wireless sensor networks: design and evaluation
Amato G, Chessa S, Gennaro C, Vairo C
One of the most promising use of Wireless Sensor Networks is in the field of the event warning applications. However, depending on the communication scheme adopted, the amount of the exchanged data may be huge, with large energy consumption. In this paper we study the efficiency of two approaches to composite event detection in Wireless Sensor Networks. The first solution approaches the problem by collecting all the available information in a single sensor that performs the real event detection. If the area covered by the network is wide this approach may result inefficient. In the second solution, the sensors may exchange among themselves the sensed data and execute locally the event detection, with the advantage of propagating the sensed data only in a smaller area.DOI: 10.1109/iscc.2011.5983943
Project(s): RUBICON
Metrics:
Amato G, Chessa S, Gennaro C, Vairo C
One of the most promising use of Wireless Sensor Networks is in the field of the event warning applications. However, depending on the communication scheme adopted, the amount of the exchanged data may be huge, with large energy consumption. In this paper we study the efficiency of two approaches to composite event detection in Wireless Sensor Networks. The first solution approaches the problem by collecting all the available information in a single sensor that performs the real event detection. If the area covered by the network is wide this approach may result inefficient. In the second solution, the sensors may exchange among themselves the sensed data and execute locally the event detection, with the advantage of propagating the sensed data only in a smaller area.DOI: 10.1109/iscc.2011.5983943
Project(s): RUBICON
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