Dilshan Silva

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The idea of priority encoding transmission (PET), although very useful to provide graceful degradation of performance in the presence of packet loss, presents a challenge when one tries to apply it in a random network coding environment. So far, the only solution proposed relies on the rateless feature of network coding and is therefore not suitable for(More)
It is shown that the error correction problem in random network coding is closely related to a generalized decoding problem for rank-metric codes. This result enables many of the rich tools devised for the rank metric to be naturally applied to random network coding. The generalized decoding problem introduced in this paper allows partial information about(More)
This paper presents a new methodology for collaborative sensor data management known as WikiSensing. It is a novel approach that incorporates online collaboration with sensor data management. We introduce the work on this research by describing the motivation and challenges of designing and developing an online collaborative sensor data management system.(More)
The drive toward smart cities alongside the increasing adoption of personal sensors is leading to big sensor data, which is so large and complex that traditional methods for utilizing it are inadequate. Although systems exist for storing and managing large-scale sensor data, the real value of such data are the insights it could enable. However, no current(More)
The drive toward smart cities alongside the rising adoption of personal sensors is leading to a torrent of sensor data. While systems exist for storing and managing sensor data, the real value of such data is the insight which can be generated from it. However there is currently no platform which enables sensor data to be taken from collection, through use(More)
The problem of error correction in both coherent and noncoherent network coding is considered under an adversarial model. For coherent network coding, where knowledge of the network topology and network code is assumed at the source and destination nodes, the error correction capability of an (outer) code is succinctly described by the rank metric; as a(More)
In large-scale machine-to-machine sensor networks, the applications such as urban air pollution monitoring require information management over widely distributed sensors under restricted power, processing, storage, and communication resources. The continual increases in size, data generating rates, and connectivity of sensor networks present significant(More)
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