Experience with Applying Formal Methods to Protocol Specification and System Architecture

In the last three years or so we at Enterprise Platforms Group at Intel Corporation have been applying formal methods to various problems that arose during the process of defining platform architectures for Intel's processor families. In this paper we give an overview of some of the problems we have worked on, the results we have obtained, and the lessons we have learned. The last topic is addressed mainly from the perspective of platform architects.     

On collaborative content distribution using multi-message gossip

We study epidemic schemes in the context of collaborative data delivery. In this context, multiple chunks of data reside at different nodes, and the challenge is to simultaneously deliver all chunks to all nodes.     

Trade-offs in scan path and BIST implementations for RAMs

In this article we propose efficient scan path and BIST schemes for RAMs. Tools for automatic generation of these schemes have been implemented. They reduce the design effort and thus allow the designer to select the more appropriate scheme with respect to various constraints.     

Time-Space Label Switching Protocol (TSL-SP)—A New Paradigm of Network Resource Assignment

In this paper we propose a new protocol called time-space label switching protocol (TSL-SP) in optical burst switching (OBS), and define the terms time-space label (TSL) and time-space routing (TSR). An important concept of response time is introduced in the time label mechanism. The TSL-SP is a new technology that can quickly and efficiently forward data with a label on the optical networks. A two-dimension label switched path (TD-LSP) can be set up, that is maintained and deleted by the TSL-SP. For clearly illuminating the operation principles of the TSL-SP, we propose a new approach of orthogonal time-space coordinates in which the vertical coordinate is the space label and the horizontal coordinate is the time label. The proposed TD-LSP can dramatically reduce the routing failure probability and greatly improve the link network efficiency compared with other signaling protocols. Moreover, we define the time-space label control plane that can achieve the higher efficiency. When the TSL-SP is applied to networks, switching performance can be improved by two orders compared to the switching performance with the conventional OBS signaling protocols. The fundamental goal of TSL-SP is to band the signaling and routing functions together closely. Also, the TSL-SP can reduce the complexity of the network, support automatic service offering, and provide traffic engineering.     

On finding optimal and near-optimal lineal spanning trees

The search for good lineal, or depth-first, spanning trees is an important aspect in the implementation of a wide assortment of graph algorithms. We consider the complexity of findingoptimal lineal spanning trees under various notions of optimality. In particular, we show that several natural problems, such as constructing a shortest or a tallest lineal tree, are NP-hard. We also address the issue of polynomial-time, near-optimization strategies for these difficult problems, showing that efficient absolute approximation algorithms cannot exist unlessP = NP.This author's research was supported in part by the Sandia University Research Program and by the National Science Foundation under Grant M IP-8603879.This author's research was supported in part by the National Science Foundation under Grants ECS-8403859 and MIP-8603879.     

Application of parallelized analogical planning to engineering design

Analogical planning provides a means of solving engineering problems where other machine learning methods fail. Unlike many machine learning paradigms, analogy does not require numerous previous examples or a rich domain theory. Instead, analogical planners adapt knowledge of solved problems in similar domains to the current problem. Unfortunately, the analogical planning task is an expensive one. While the process of forming correspondences between a known problem and a new problem is complex, the problem of selecting a base case for the analogy is virtually intractable.This paper addresses the issue of efficiently forming analogical plans. The Anagram planning system is described, which takes advantage of the massively parallel architecture of the Connection Machine to perform base selection and map formation. Anagram provides a tractable solution to analogical planning, with a complexity that is sublinear in the size of the plans.This paper describes the Anagram system and its parallel algorithms. The paper also presents theoretical analyses and empirical results of testing the system on a large database of plans from the domain of automatic programming.     

Surveillance test policy optimization through genetic algorithms using non-periodic intervention frequencies and considering seasonal constraints

In order to maximize systems average availability during a given period of time, it has recently been developed a non-periodic surveillance test optimization methodology based on genetic algorithms (GA). The fact of allowing non-periodic tests turns the solution space much more flexible and schedules can be better adjusted, providing gains in the overall system average availability, when compared to those obtained by an optimized periodic test scheme. This approach, however, turns the optimization problem more complex. Hence, the use of a powerful optimization technique, such as GA, is required.Considering that some particular features of certain systems can turn it advisable to introduce other specific constraints in the optimization problem, this work investigates the application of seasonal constraints for the set of the Emergency Diesel Generation of a typical four-loop pressurized water reactor in order to planning and optimizing its surveillance test policy. In this analysis, the growth of the blackout accident probability during summer, due to electrical power demand increases, was considered. Here, the used model penalizes surveillance test interventions when the blackout probability is higher.Results demonstrate the ability of the method in adapting the surveillance test policy to seasonal constraints. The knowledge acquired by the GA during the searching process has lead to test schedules that drastically minimize test interventions at periods of high blackout probability. It is compensated by more frequent redistributed tests through the periods of low blackout probability in order to improve on the overall average availability at the system level.     

基于遗传算法的工作辊温度场参数优化模型

针对热连轧机工作辊热辊形计算中温度场模型的热交换等参数难以确定的问题 ,建立了基于遗传算法的参数优化模型 ,可以解决复杂条件下的热参数的求解问题。利用优化参数计算的轧辊温度场与实际测量结果一致。     

Algorithms for multiprocessor scheduling with two job lengths and allocation restrictions

A variant of the High Multiplicity Multiprocessor Scheduling Problem with C job lengths is considered, in which jobs can be processed only by machines not greater than a given index. When C=2, polynomial algorithms are proposed, for the feasibility version of the problem and for maximizing the number of scheduled jobs.