Obliq is lexically-scoped, untyped, interpreted language that supports distributed object -oriented computation. Obliq objects have state and are local to a site. Obliq computations can roam over the network, while maintaining network connections. Distributed lexical scoping is the key mechanism

A tree similarity algorithm for match-making of agents in e-Business environments is presented. Product/service descriptions of seller and buyer agents are represented as node-labelled, arc-labelled, arc-weighted trees. A similarity algorithm for such trees is developed as the basis for semantic

to reduce access delay in a BAN in the presence of coexistent systems. By opportunistic extraction of idle spaces from a pool of orthogonal channels, CBAS dynamically adjusts a BAN’s channel access pattern according to the current interference environment, and improves the BAN’s visibility among coexistent

AbstractToday, Voice over IP (VoIP) service is emerging as a popular and important application in wireless local area networks (WLANs). While rate adaptation (or link adaptation) has been identied as a key factor determining the performance of WLANs, we have observed that most (if not all) rate

for understanding how evolution can innovate within its genetic rule space. However, conventional cellular automata lack the kind of state feedback that is surely present in nat-ural evolving systems. Each new generation of a population leaves an indelible mark on its environment and thus affects the selective

analysis of strange, soft hadron production as function of energy and reaction volume. We discuss the physical properties of the final state and argue how evidence about the primordial QGP emerges. 1.

The principle aim of this dissertation is to investigate the philosophical application of quantum information theory to interpretational issues regarding the theory of quantum mechanics. Recently, quantum information theory has emerged as a potential source for such an interpretation. The main

Abstract: Mobile ad hoc networks (MANETs) and wireless sensor networks (WSNs) are two recently-developed technologies that uniquely function without xed infrastructure support, and sense at scales, resolutions, and durations previously not possible. While both offer great potential in many applications, developing software for these types of networks is extremely dffcult, preventing their wide-spread use. Three primary challenges are (1) the high level of dynamics within the network in terms of changing wireless links and node hardware con gurations, (2) the wide variety of hardware present in these networks, and (3) the extremely limited computational and energy resources available. Until now, the burden of handling these issues was put on the software application developer. This dissertation presents three novel programming models and middleware systems that address these challenges: Limone, Agilla, and Servilla. Limone reliably handles high levels of dynamics within MANETs. It does this through lightweight coordination primitives that make minimal assumptions about network connectivity. Agilla enables self-adaptive WSN applications via the integration of mobile agent and tuple space programming models, which is critical given the continuously changing network. It is the rst system to successfully demonstrate the feasibility of using mobile agents and tuple spaces within

Heterogeneous wireless sensor networks represent a challenging programming environment. Servilla addresses this by offering a new middleware framework that provides service provisioning. Using Servilla, developers can construct platform-independent applications over a dynamic set of devices

First, I would like to thank to Dimka Karastoyanova and Mariano Cilia for all the fruitful discussions, their guidance and support through the course of this project. Thanks also to Prof. Alejandro Buchmann who sponsored my stay at Technische Universität Darmstadt during the spring of 2004. The special thanks go to my advisor, Mariano Cilia, who has made all this possible. Finally, I’d like to thank to my family for all these years of support.