From the World Wide Web to supply chains and scientific simulations, distributed systems are a widely used and important approach to building computational systems. Tracking provenance within these systems is crucial for determining the trustworthiness of data they produce, troubleshooting problems, assigning responsibility for decisions, and improving performance. To facilitate such tracking, ...

By developing a taxonomy of existing systems, libraries and frameworks used for developing Mixed Reality and Ubiquitous Computing environments, it can be seen that little effort has been made to research applications that share the characteristics of these two fields. Solutions have focussed on meeting the needs of each project in turn, rather than developing a generalised middleware, which wou...

Effective Big Data analytics pose several difficult challenges for modern data management architectures. One key such challenge arises from the naturally streaming nature of big data, which mandates efficient algorithms for querying and analyzing massive, continuous data streams (that is, data that is seen only once and in a fixed order) with limited memory and CPU-time resources. Such streams ...

This work investigates bandwidth tracking algorithms in a version of a distributed heterogeneous data dissemination system called the Agile Information Control Environment (AICE). In this environment, the probability of setup or rejection of communication requests has to be derived without any updated knowledge of the actual topologies of the underlying networks. In this paper, a network learni...

This paper describes a United States Air Force Advanced Technology Demonstration (ATD) that applied value-based scheduling to produce an adaptive, distributed tracking component appropriate for consideration by the Airborne Warning and Control System (AWACS) program. This tracker was designed to evaluate application-specific Quality of Service (QoS) metrics to quantify its ability to provide tr...

We describe distributed tracking of a linear dynamical system via networked sensors. The networked sensors communicate with each other by means of a multihop protocol over a communication network. MMSEoptimal solution is Kalman filtering when measurements are available centrally, but new methods are required to account for communication constraints. We derive optimal algorithms to deal with arb...

In wireless sensor network energy cutback is considered as a principle intensive challenge which is studied largely in the Wireless Sensor Networks (WSN) literature. On the other hand introduction of audio video streaming in wireless architecture reveals additional challenges. The image and video transmission not only demands for energyefficiency but also requires Quality of Service (QoS) assur...

While traditional databases have focused on single query evaluation in a centralized setting, emerging applications require continuous tracking of queries on data that is widely distributed and constantly updated. We describe such scenarios, and describe the challenges involved in designing communication-efficient protocols for the tracking tasks we define. We outline some solutions to these pr...

In this paper, we study the problem of distributed multi-agent optimization over a network, where each agent possesses a local cost function that is smooth and strongly convex. The global objective is to find a common solution that minimizes the average of all cost functions. Assuming agents only have access to unbiased estimates of the gradients of their local cost functions, we consider a dis...

Distributed target tracking has been a widely studied problem for different applications, more recently considering distributed particle filter techniques for Wireless Sensor Networks (WSNs). However, the adaptation of distributed tracking filters to sensor networks with limited field-of-view and large raw-data management constraints under realistic networking conditions has not yet received en...