Let (S,d) be a finite metric space, where each element p S has a non-negative weight w(p). We study spanners for the set S with respect to weighted distance function d w , where d w (p,q) is w(p)+d(p,q)+wq if p≠q and 0 otherwise. We present a general method for turning spanners with respect to the d-metric into spanners with respect to the d w -metric. For any given ε>0, we can apply our method to obtain (5+ε)-spanners with a linear number of edges for three cases: points in Euclidean space ℝ d , points in spaces of bounded doubling dimension, and points on the boundary of a convex body in ℝ d where d is the geodesic distance function. We also describe an alternative method that leads to (2+ε)-spanners for points in ℝ d and for points on the boundary of a convex body in ℝ d . The number of edges in these spanners is O(nlogn). This bound on the stretch factor is nearly optimal: in any finite metric space and for any ε>0, it is possible to assign weights to the elements such that any non-complete graph has stretch factor larger than 2-ε.

The paper proposes to integrate performance analysis in the early phases of the model-driven development process for Software Product Lines (SPL). We start by adding generic performance annotations to the UML model representing the set of core reusable SPL assets. The annotations are generic and use the MARTE Profile recently adopted by OMG. A first model transformation realized in the Atlas Transformation Language (ATL), which is the focus of this paper, derives the UML model of a specific product with concrete MARTE performance annotations from the SPL model. A second transformation generates a Layered Queueing Network performance model for the given product by applying an existing transformation approach named PUMA, developed in previous work. The proposed technique is illustrated with an e-commerce case study that models the commonality and variability in both structural and behavioural SPL views. A product is derived and the performance of two design alternatives is compared.

The verification of non-functional requirements of software models (such as performance, reliability, scalability, security, etc.) requires the transformation of UML models into different analysis models such as Petri nets, queueing networks, formal logic, etc., which represent the system at a higher level of abstraction. The paper proposes a new "abstraction-raising" transformation approach for generating analysis models from UML models. In general, such transformations must bridge a large semantic gap between the source and the target model. The proposed approach is illustrated by a transformation from UML to Klaper (Kernel LAnguage for PErformance and Reliability analysis of component-based systems).

The time required for a sequence of operations on a data structure is usually measured in terms of the worst possible such sequence. This, however, is often an overestimate of the actual time required. Distribution-sensitive data structures attempt to take advantage of underlying patterns in a sequence of operations in order to reduce time complexity, since access patterns are non-random in many applications. Unfortunately, many of the distribution- sensitive structures in the literature require a great deal of space overhead in the form of pointers. We present a dictionary data structure that makes use of both randomization and existing space-efficient data structures to yield very low space overhead while maintaining distribution sensitivity in the expected sense.

Intrusion detection, area coverage and border surveillance are important applications of wireless sensor networks today. They can be (and are being) used to monitor large unprotected areas so as to detect intruders as they cross a border or as they penetrate a protected area. We consider the problem of how to optimally move mobile sensors to the fence (perimeter) of a region delimited by a simple polygon in order to detect intruders from either entering its interior or exiting from it. We discuss several related issues and problems, propose two models, provide algorithms and analyze their optimal mobility behavior.

Let φ be a random Boolean formula that is an instance of 3-SAT. We consider the problem of computing the least real number such that if the ratio of the number of clauses over the number of variables of φ strictly exceeds κ, then φ is almost certainly unsatisfiable. By a well known and more or less straightforward argument, it can be shown that κ 3.

The design and analysis of community-scale energy systems and incentives is a non-trivial task. The challenge of such undertakings is the well-documented uncertainty of building occupant behaviours. This is especially true in the residential sector, where occupants are given more freedom of activity compared to work environments. Further complicating matters is the dearth of available measured data. Building performance simulation tools are one approach to community energy analysis, however such tools often lack realistic models for occupant-driven demands, such as appliance and lighting (AL) loads. For community-scale analysis, such AL models must also be able to capture the temporal and inter-dwelling variation to achieve realistic estimates of aggregate electrical demand. This work adapts the existing Centre for Renewable Energy Systems Technology (CREST) residential energy model to simulate Canadian residential AL demands. The focus of the analysis is to determine if the daily, seasonal, and inter-dwelling variation of AL demands estimated by the CREST model is realistic. An in-sample validation is conducted on the model using 22 high-resolution measured AL demand profiles from dwellings located in Ottawa, Canada. The adapted CREST model is shown to broadly capture the variation of AL demand variations observed in the measured data, however seasonal variation in daily AL demand behaviour was found to be under-estimated by the model. The average and variance of daily load factors was found to be similar between measured and modelled. The model was found to under-predict the daily coincidence factors of aggregated demands, although the variance of coincident factors was shown to be similar between measured and modelled. A stochastic baseload input developed for this work was found to improve estimates of the magnitude and variation of both baseload and peak demands.

Persuasive technologies are increasingly ubiquitous, but the strategies they utilise largely originate in America. Consumer behaviour research shows us that certain persuasion strategies will be more effective on some cultures than others. We claim that the existing strategies will be less effective on non-American audiences than they are on American audiences, and we use information from interviews to show that there exists much scope to develop persuasive technologies from a collectivism-focused perspective. To illustrate the development of such a tool, we describe the design of a collectivism-focused financial planning tool.

Given an integer k ≥ 2, we consider the problem of computing the smallest real number t(k) such that for each set P of points in the plane, there exists a t(k)-spanner for P that has chromatic number at most k. We prove that t(2)∈=∈3, t(3)∈=∈2, , and give upper and lower bounds on t(k) for k∈>∈4. We also show that for any ε>∈0, there exists a (1∈+∈ε)t(k)-spanner for P that has O(|P|) edges and chromatic number at most k. Finally, we consider an on-line variant of the problem where the points of P are given one after another, and the color of a point must be assigned at the moment the point is given. In this setting, we prove that t(2)∈=∈3, , , and give upper and lower bounds on t(k) for k∈>∈4.