Delay-based Admission Control to sustain QoS in a Managed IEEE 802.11 Wireless LANs

International audienc

Unequal and interleaved FEC protocol for robust MPEG-4 multicasting over wireless LAN

International audience" Unequal and interleaved FEC protocol for robust MPEG-4 multicasting over wireless LA

Historical Data Storage for Large Scale Sensor Networks

International audienceWireless sensor networks are rapidly finding their way through a plethora of new applications like precision farm- ing and forestry, with increasing network scale, system complexity, and data rate. While scalable MAC and rout- ing protocols for sensor networks have been well dressed in recent years, the scalability of the back-end storage architecture has been largely overlooked. As a result, current storage and retrieval architectures usually lead to an excessive I/O cost when it comes to improv- ing the scalability and responsiveness of the system. In this paper, we present a scalable backend storage and retrieval architecture to support very large volumes of real- time measurements from wireless sensor networks. In particular, our contribution provides: (i) a database partitioning and structuring scheme coupled with a double- buffering technique to reduce the end-to-end delay while minimizing the processing power, and (ii) an optimized historical measurement data query format tailored for superior performance in terms of data retrieval responsive- ness. Through a realistic emulator for large scale sensor network, we evaluate this storage and retrieval system to illustrates its delay and I/O benefits in both high and low traffic rate scenarios. The evaluation guides our design of an adaptive design, that applies batch insert method for smaller deployments to reduce insertion delay, and double-buffering for larger deployments to reduce I/O cost and avoid saturation, at the cost of higher delay

Historical data storage for large scale sensor networks

Wireless sensor networks are rapidly finding their way through a plethora of new applications like precision farming and forestry, with increasing network scale, system complexity, and data rate. While scalable MAC and routing protocols for sensor networks have been well addressed in recent years, the scalability of the back-end storage architecture has been largely overlooked. As a result, current storage and retrieval architectures usually lead to an excessive I/O cost when it comes to improving the scalability and responsiveness of the system. In this paper, we present a scalable backend storage and retrieval architecture to support very large volumes of real-time measurements from wireless sensor networks. In particular, our contribution provides: (i) a database partitioning and structuring scheme coupled with a double-buffering technique to reduce the end-to-end delay while minimizing the processing power, and (ii) an optimized historical measurement data query format tailored for superior performance in terms of data retrieval responsiveness. Through a realistic emulator for large scale sensor network, we evaluate this storage and retrieval system to illustrates its delay and I/O benefits in both high and low traffic rate scenarios. The evaluation guides our design of an adaptive design, that applies batch insert method for smaller deployments to reduce insertion delay, and double-buffering for larger deployments to reduce I/O cost and avoid saturation, at the cost of higher delay. Copyright 2009 ACM

Large scale environmental monitoring through integration of sensor and mesh networks

Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper. © 2008 by the authors