This document gives an overview of the Next Steps in Signaling (NSIS) framework and protocol suite created by the NSIS Working Group during the period of 2001-2010. It also includes suggestions on how the industry can make use of the new protocols and how the community can exploit the extensibility of both the framework and existing protocols to address future signaling needs.

This threats document provides a detailed analysis of the security threats relevant to the Next Steps in Signaling (NSIS) protocol suite. It calls attention to, and helps with the understanding of, various security considerations in the NSIS Requirements, Framework, and Protocol proposals. This document does not describe vulnerabilities of specific parts of the NSIS protocol suite.

We consider a class of quadratic programs with linear complementarity constraints (QPLCC) which belong to mathematical programs with equilibrium constraints (MPEC). We investigate various stationary conditions and present new and strong necessary and sufficient conditions for global and local optimality. Furthermore, we propose a Newton-like method to find an M-stationary point in finite steps ...

We derive a simple error estimate for equally spaced, polynomial interpolation of power series that does not require the uniform bounds on derivatives of the Cauchy remainder. The key steps are expressing Newton coefficients in terms of Stirling numbers S(i, j) of the second kind and applying the concavity of lnS(i, j).

In this paper, we first present a brief review about the feasible interior-point algorithm for P∗(κ)-horizontal linear complementarity problems (HLCPs) based on new directions. Then we present a new infeasible interior-point algorithm for these problems. The algorithm uses two types of full-Newton steps which are called feasibility steps and centering steps. The algorithm starts from strictly f...

In this paper we propose a new class of primal-dual path-following interior point algorithms for solving monotone linear complementarity problems. At each iteration, the method would select a target on the central path with a large update from the current iterate, and then the Newton method is used to get the search directions, followed by adaptively choosing the step sizes, which are e.g. the ...

In this paper we propose a new class of primal-dual path-following interior point algorithms for solving monotone linear complementarity problems. At each iteration, the method would select a target on the central path with a large update from the current iterate, and then the Newton method is used to get the search directions, followed by adaptively choosing the step sizes, which are e.g. the ...

For convex minimization we introduce an algorithm based on VU-space decomposition. The method uses a bundle subroutine to generate a sequence of approximate proximal points. When a primal-dual track leading to a solution and zero subgradient pair exists, these points approximate the primal track points and give the algorithm’s V, or corrector, steps. The subroutine also approximates dual track ...