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We are witnessing the emergence of the ubiquitous resource-infinite computing paradigm. Significant benefits accrue, ranging from added convenience and services for users, to enhanced efficiency and reduced cost for organizations, to improved on-demand resource availability for under-connected areas, extreme environments and distress situations. To this(More)
We foresee the need for dynamically clustering nodes in Wireless Sensor Networks (WSNs) according to a multitude of disparate co-existing contexts. To this end, we propose a distributed, low-overhead context-aware clustering protocol for WSNs. We employ Affinity Propagation (AP) for clustering nodes based on multiple criteria including location, residual(More)
The intrinsically location-aware applications of sensor networks and the need for location-based optimized routing make efficient and accurate location determination of sensor nodes essential. It is practically and economically infeasible to equip all sensor nodes with GPS receivers. A few GPS equipped anchors are therefore used to determine the location of(More)
We present reliable adaptive service-driven efficient routing (muRACER), a routing protocol suite based on a novel service-oriented design for sensor-actuator networks where nodes expose their capabilities to applications as a service profile. A node's service profile consists of a set of services (i.e., sensing and actuation capabilities) that it provides(More)
Next generations distributed cyberspace technologies, such as cloud computing, social networking and mobile applications, are expected to evolve a global cyberspace marketplace for resources and services. In such a large-scale marketplace, users are largely autonomous with vastly diverse requirements, capabilities and trust profiles. Therefore trading(More)
The Software Visualization (SV) discipline investigates approaches and techniques for static and dynamic graphical representations of algorithms, programs (code) and the processed data. SV is concerned primarily with analysis of programs and their development. The goal is to improve our understanding of inherently invisible and intangible software,(More)
The ability to mine large volumes of distributed datasets enables more precise decision making. However, privacy concerns should be carefully addressed when mining datasets distributed over autonomous sites. We propose a new privacy-preserving protocol for association rule mining (P3ARM) over horizontally partitioned data. P3ARM is based on a distributed(More)
— The maximum likelihood (ML) and suboptimum ML (S-ML) detectors are derived in the first order moving average model. The ML and S-ML detectors are employed in the antipodal signaling system, and compared in terms of the bit-error-rate in impulsive environment. Numerical results show that the S-ML detector, despite reduced complexity and simpler structure,(More)