—This paper proposes and develops a novel, iterative model for resource aware-ubiquitous data stream querying (RA-UDSQ). Our model provides timely results to mobile users at regular time intervals specified by the user, thereby executing continuous stream queries. This model is capable of adapting to high data rates of streams and limited memory resources available on a mobile device while exec...

Mining data streams has raised a number of research challenges for the data mining community. These challenges include the limitations of computational resources, especially because mining streams of data most likely be done on a mobile device with limited resources. Also due to the continuality of data streams, the algorithm should have only one pass or less over the incoming data elements. In...

SUMMARY We present a report on the Resource-Aware Visualization Environment (RAVE) project, from its inception and design phases, through implementation choices and final actual use cases. The RAVE (Resource-Aware Visualization Environment) is a distributed, collaborative Grid enabled visualization environment that supports automated resource discovery across heterogeneous machines. RAVE runs a...

Rapid strides in technology have lead to pervasive computing in a spectrum of applications such as crisis management systems, distributed critical systems, medical therapy systems, home entertainment etc. One of the common features in the spectrum of applications has been the reactivity of the systems and context of the environments. The environmental context has become highly sophisticated due...

Current production resource management and scheduling systems often use some mechanism to guarantee fair sharing of computational resources among different users of the system. For example, the user who so far consumed small amount of CPU time gets higher priority and vice versa. However, different users may have highly heterogeneous demands concerning system resources, including CPUs, RAM, HDD...

We present a resource-aware scheduling technique for MapReduce multi-job workloads that aims at improving resource utilization across machines while observing completion time goals. Existing MapReduce schedulers define a static number of slots to represent the capacity of a cluster, creating a fixed number of execution slots per machine. This abstraction works for homogeneous workloads, but fai...

This article introduces a technique to accurately perform static prediction of resource usage for ML-like functional programs with references and arrays. Previous research successfully integrated the potential method of amortized analysis with a standard type system to automatically derive parametric resources bounds. Due to its type-based nature, the analysis is naturally compositional and the...

While there exist several successful techniques for supporting programmers in deriving static resource bounds for sequential code, analyzing the resource usage of message-passing concurrent processes poses additional challenges. To meet these challenges, this article presents an analysis for statically deriving worst-case bounds on the total work performed by message-passing processes. To decom...

An efficient usage of available resources is a substantial requirement for the successful control design in cyber-physical systems. Recent results indicate major benefits of event-based control compared to conventional designs, when resources such as communication, energy, and/or computation, are scarce. In this work we consider multiple control loops which share the communication resource. We ...

In this chapter, we will address the problem of resource discovery that ensures sustained QoS (Quality of Service) for mobile applications. We present two aspects of the resource discovery problem: (i) static resource discovery that determines the best resources to service a request when it is initiated, (ii) dynamic resource reprovisioning that continues to find nearby resources as a mobile cl...