36031983
Semidefinite programming for ad hoc wireless sensor network localization
10134807
A semidefinite programming approach to tensegrity theory and realizability of graphs
Recently, Connelly and Sloughter [14] have introduced the notion of d-realizability of graphs and have, among other things, given a complete characterization of the class of 3-realizable graphs. However, their work has left open the question of finding an algorithm for realizing those graphs. In this paper, we resolve that question by showing that the semidefinite programming (SDP) approach of [11, 32] can be used for realizing 3-realizable graphs. Specifically, we use SDP duality theory to show that given a graph G and a set of lengths on its edges, the optimal dual multipliers of a certain SDP give rise to a proper equilibrium stress for some realization of G. Using this result and the techniques in [14, 31], we then obtain a polynomial time algorithm for (approximately) realizing 3-realizable graphs. Our results also establish a little-explored connection between SDP and tensegrity theories and allow us to derive some interesting properties of tensegrity frameworks.
12762926
Theory of semidefinite programming for Sensor Network Localization
AbstractWe analyze the semidefinite programming (SDP) based model and method for the position estimation problem in sensor network localization and other Euclidean distance geometry applications. We use SDP duality and interior-point algorithm theories to prove that the SDP localizes any network or graph that has unique sensor positions to fit given distance measures. Therefore, we show, for the first time, that these networks can be localized in polynomial time. We also give a simple and efficient criterion for checking whether a given instance of the localization problem has a unique realization in
$$\mathcal{R}^2$$ using graph rigidity theory. Finally, we introduce a notion called strong localizability and show that the SDP model will identify all strongly localizable sub-networks in the input network.
9510976
An interior point potential reduction algorithm for the linear complementarity problem
AbstractThe linear complementarity problem (LCP) can be viewed as the problem of minimizingxTy subject toy=Mx+q andx, y⩾0. We are interested in finding a point withxTy  0. The algorithm proceeds by iteratively reducing the potential function
$$f(x,y) = \rho \ln x^T y - \Sigma \ln x_j y_j ,$$
 where, for example,ρ=2n. The direction of movement in the original space can be viewed as follows. First, apply alinear scaling transformation to make the coordinates of the current point all equal to 1. Take a gradient step in the transformed space using the gradient of the transformed potential function, where the step size is either predetermined by the algorithm or decided by line search to minimize the value of the potential. Finally, map the point back to the original space.A bound on the worst-case performance of the algorithm depends on the parameterλ*=λ*(M, ε), which is defined as the minimum of the smallest eigenvalue of a matrix of the form
$$(I + Y^{ - 1} MX)(I + M^T Y^{ - 2} MX)^{ - 1} (I + XM^T Y^{ - 1} )$$
 whereX andY vary over the nonnegative diagonal matrices such thateTXYe ⩾ε andXjjYjj⩽n2. IfM is a P-matrix,λ* is positive and the algorithm solves the problem in polynomial time in terms of the input size, |log ε|, and 1/λ*. It is also shown that whenM is positive semi-definite, the choice ofρ = 2n+
$$\sqrt {2n} $$
 yields a polynomial-time algorithm. This covers the convex quadratic minimization problem.
206798229
On affine scaling algorithms for nonconvex quadratic programming
We investigate the use of interior algorithms, especially the affine-scaling algorithm, to solve nonconvex — indefinite or negative definite — quadratic programming (QP) problems. Although the nonconvex QP with a polytope constraint is a “hard” problem, we show that the problem with an ellipsoidal constraint is “easy”. When the “hard” QP is solved by successively solving the “easy” QP, the sequence of points monotonically converge to a feasible point satisfying both the first and the second order optimality conditions.
6954893
How Partial Knowledge Helps to Solve Linear Programs
We present results on how partial knowledge helps to solve linear programs. In particular, if a linear system,Ax=bandx?0, has an interior feasible point, then we show that finding a feasible point to this system can be done inO(n2.5c(A)) iterations by the layered interior-point method, and each iteration solves a least-squares problem, wherenis the dimension of vectorxandc(A) is the condition number of matrixAdefined by Vavasis and Ye. This complexity bound is reduced by a factornfrom that when this property does not exists. We also present a result for solving the problem using a little strong knowledge.
19594900
Reuse-Conducive Development Environments
Despite its well-recognized benefits, software reuse has not met its expected success due to technical, cognitive, and social difficulties. We have systematically analyzed the reuse problem (especially the cognitive and social difficulties faced by software developers who reuse) from a multidimensional perspective, drawing on our long-term research on information retrieval, human-computer interaction, and knowledge-based systems. Based on this analysis, we propose the concept of reuse-conducive development environments, which encourage and enable software developers to reuse through the smooth integration of reuse repository systems and development environments. We have designed, implemented, and evaluated CodeBroker—a reuse-conducive development environment—that autonomously locates and delivers task-relevant and personalized components into the current software development environment. Empirical evaluations of CodeBroker have shown that the system is effective in promoting reuse by enabling software developers to reuse components unknown to them, reducing the difficulties in locating components, and augmenting the programming capability of software developers.
1476378
Toward an understanding of the motivation of open source software developers
An Open Source Software (OSS) project is unlikely to be successful unless there is an accompanied community that provides the platform for developers and users to collaborate. Members of such communities are volunteers whose motivation to participate and contribute is of essential importance to the success of OSS projects. In this paper, we aim to create an understanding of what motivates people to participate in OSS communities. We theorize that learning is one of the motivational forces. Our theory is grounded in the learning theory of Legitimate Peripheral Participation, and is supported by analyzing the social structure of OSS communities and the co-evolution between OSS systems and communities. We also discuss practical implications of our theory for creating and maintaining sustainable OSS communities as well as for software engineering research and education.
12123304
Integrating active information delivery and reuse repository systems
Although software reuse can improve both the quality and productivity of software development, it will not do so until software developers stop believing that it is not worth their effort to find a component matching their current problem. In addition, if the developers do not anticipate the existence of a given component, they will not even make an effort to find it in the first place.
Even the most sophisticated and powerful reuse repositories will not be effective if developers don't anticipate a certain component exists, or don't deem it worthwhile to seek for it. We argue that this crucial barrier to reuse is overcome by integrating active information delivery, which presents information without explicit queries from the user, and reuse repository systems. A prototype system, CodeBroker, illustrates this integration and raises several issues related to software reuse.
17936055
An Empirical User Study of an Active Reuse Repository System
This paper reports an empirical user study of an active reuse repository system. Instead of waiting passively for software developers to initiate the component location process with a well-defined reuse query, active reuse repository systems infer reuse queries from syntactic and semantic cues present in partially constructed programs in development environments, and proactively deliver components that match the inferred reuse queries. The reported empirical user study of an implemented active reuse repository system called CodeBroker shows that active repository systems promote reuse by motivating and enabling software developers to reuse components whose existence is not anticipated, and reducing the cost of reuse through the automation of the component location process.
17341139
Context-aware browsing of large component repositories
The paper proposes a novel approach to locating software components from a large component repository: context-aware browsing. Without any explicit input from software developers, this approach automatically locates and presents a list of software components that could possibly be used in the current development situation. This automation of the component location process not only greatly reduces the search space of components so that software developers can easily browse and choose the desired components, but also enables software developers to use components whose existence they do not even anticipate. A software agent that supports context-aware browsing has been developed and evaluated.