10880026
Term Algebras with Length Function and Bounded Quantifier Alternation
Term algebras have wide applicability in computer science. Unfortunately, the decision problem for term algebras has a nonelementary lower bound, which makes the theory and any extension of it intractable in practice. However, it is often more appropriate to consider the bounded class, in which formulae can have arbitrarily long sequences of quantifiers but the quantifier alternation depth is bounded. In this paper we present new quantifier elimination procedures for the first-order theory of term algebras and for its extension with integer arithmetic. The elimination procedures deal with a block of quantifiers of the same type in one step. We show that for the bounded class of at most k quantifier alternations, regardless of the total number of quantifiers, the complexity of our procedures is k-fold exponential (resp. 2k fold exponential) for the theory of term algebras (resp. for the extended theory with integers).
13956689
The Decidability of the First-Order Theory of Knuth-Bendix Order
Two kinds of orderings are widely used in term rewriting and theorem proving, namely recursive path ordering (RPO) and Knuth-Bendix ordering (KBO). They provide powerful tools to prove the termination of rewriting systems. They are also applied in ordered resolution to prune the search space without compromising refutational completeness. Solving ordering constraints is therefore essential to the successful application of ordered rewriting and ordered resolution. Besides the needs for decision procedures for quantifier-free theories, situations arise in constrained deduction where the truth value of quantified formulas must be decided. Unfortunately, the full first-order theory of recursive path orderings is undecidable. This leaves an open question whether the first-order theory of KBO is decidable. In this paper, we give a positive answer to this question using quantifier elimination. In fact, we shall show the decidability of a theory that is more expressive than the theory of KBO.
6519292
Event Correlation: Language and Semantics
Event correlation is a service provided by middleware platforms that allows components in a publish/subscribe architecture to subscribe to patterns of events rather than individual events. Event correlation improves the scalability and performance of distributed systems, increases their analyzability, while reducing their complexity by moving functionality to the middleware. To ensure that event correlation is provided as a standard and reliable service, it must possess well-defined and unambiguous semantics.
4227795
Decision Procedures for Queues with Integer Constraints
Queues are a widely used data structure in programming languages. They also provide an important synchronization mechanism in modeling distributed protocols. In this paper we extend the theory of queues with a length function that maps a queue to its size, resulting in a combined theory of queues and Presburger arithmetic. This extension provides a natural but tight coupling between the two theories, and hence the general Nelson-Oppen combination method for decision procedures is not applicable. We present a decision procedure for the quantifier-free theory and a quantifier elimination procedure for the first-order theory that can remove a block of existential quantifiers in one step.
7279338
Decision procedures for term algebras with integer constraints
Term algebras can model recursive data structures which are widely used in programming languages. To verify programs we must be able to reason about these structures. However, as programming languages often involve multiple data domains, in program verification decision procedures for a single theory are usually not applicable. An important class of mixed constraints consists of combinations of data structures with integer constraints on the size of data structures. Such constraints can express memory safety properties such as absence of memory overflow and out-of-bound array access, which are crucial for program correctness. In this paper we extend the theory of term algebras with the length function which maps a term to its size, resulting in a combined theory of term algebras and Presburger arithmetic. This arithmetic extension provides a natural but tight coupling between the two theories, and hence the general purpose combination methods like Nelson-Oppen combination are not applicable. We present decision procedures for quantifier-free theories in structures with an infinite constant domain and with a finite constant domain. We also present a quantifier elimination procedure for the extended first-order theory that can remove a block of existential quantifiers in one step.
14645298
Verifying Balanced Trees
Balanced search trees provide guaranteed worst-case time performance and hence they form a very important class of data structures. However, the self-balancing ability comes at a price; balanced trees are more complex than their unbalanced counterparts both in terms of data structure themselves and related manipulation operations. In this paper we present a framework to model balanced trees in decidable first-order theories of term algebras with Presburger arithmetic. In this framework, a theory of term algebras (i.e., a theory of finite trees) is extended with Presburger arithmetic and with certain connecting functions that map terms (trees) to integers. Our framework is flexible in the sense that we can obtain a variety of decidable theories by tuning the connecting functions. By adding maximal pathand minimal pathfunctions, we obtain a theory of red-black trees in which the transition relation of tree self-balancing (rotation) operations is expressible. We then show how to reduce the verification problem of the red-black tree algorithm to constraint satisfiability problems in the extended theory.
18579061
An Efficient Frequency Scaling Approach for Energy-Aware Embedded Real-Time Systems
The management of energy consumption in battery-operated embedded and pervasive systems is increasingly important in order to extend battery lifetime or to increase the number of applications that can use the system's resources. Dynamic voltage and frequency scaling (DVFS) has been introduced to trade off system performance with energy consumption. For real-time applications, systems supporting DVFS have to balance the achieved energy savings with the deadline constraints of applications. Previous work has used periodic evaluation of an application's progress (e.g., with periodic checkpoints inserted into application code at compile time) to decide if and how much to adjust the frequency or voltage. Our approach builds on this prior work and addresses the overheads associated with these solutions by replacing periodic checkpoints with iterative checkpoint computations based on predicted best-, average-, and worst-case execution times of real-time applications (e.g., obtained through compile-time analysis or profiling).
9447451
Building intrusion-tolerant secure software
In this work, we develop a secret sharing based compiler solution to achieve confidentiality, integrity and availability (intrusion tolerance) of critical data together, rather than tackling them one by one as in previous approaches. Under our scheme, the compiler automatically identifies some critical data values, whereas the user specifies some others. The compiler generates code for scattering/assembling and verifying of those critical data values using secret sharing scheme. In this way, we achieve data confidentiality and integrity. We also provide mechanisms to gracefully recover upon data tampering, achieving intrusion tolerance. The implementation of our secret sharing scheme is carefully crafted to achieve low overhead. We further propose several compiler optimizations such as secret-sharing-aware register allocation, rematerialization etc. to reduce the cost of secret sharing further, making our scheme a practical solution in a high performance system.
2589663
Hardware assisted control flow obfuscation for embedded processors
With more applications being deployed on embedded platforms, software protection becomes increasingly important. This problem is crucial on embedded systems like financial transaction terminals, pay-TV access-control decoders, where adversaries may easily gain full physical accesses to the systems and critical algorithms must be protected from being cracked. However, as this paper points out that protecting software with either encryption or obfuscation cannot completely preclude the control flow information from being leaked. Encryption has been widely studied and employed as a traditional approach for software protection, however, the control flow information is not 100% hidden with solely encrypting the code. On the other hand, pure software-based obfuscation has been proved inefficient to protect software due to its lack of theoretical foundation and considerable performance overhead introduced by complicated transformations. Moreover, even though obfuscation can prevent static reverse engineering, attacker can still successfully bypass the obfuscation by monitoring the dynamic program execution.To address all of these shortcomings, this paper presents a hardware assisted obfuscation technique that is capable of obfuscating the control flow information dynamically. Dynamic obfuscation changes memory access sequence on-the-fly and conceals recurrent instruction access sequences from being identified. Our scheme makes it provably difficult for the attacker to extract any useful information. Our results show that a high-level security protection is possible with only minor performance penalty. Finally, we show that our scheme can be implemented on embedded systems with very little hardware overhead.
579951
Improving performance of distribution tracking through background mismatch
This paper proposes a new density matching method based on background mismatching for tracking of nonrigid moving objects. The new tracking method extends the idea behind the original density-matching tracker, which tracks an object by finding a contour in which the photometric density sampled from the enclosed region most closely matches a model density. This method can be quite sensitive to the initial curve placements and model density. The new method eliminates these sensitivities by adding a second term to the optimization: the mismatch between the model density and the density sampled from the background. By maximizing this term, the tracking algorithm becomes significantly more robust in practice. Furthermore, we show the enhanced ability of the algorithm to deal with target objects, which possess smooth or diffuse boundaries. The tracker is in the form of a partial differential equation, and is implemented using the level-set framework. Experiments on synthesized images and real video sequences show our proposed methods are effective and robust; the results are compared with several existing methods.
1202850
Anycast Algorithms Supporting Optical Burst Switched Grid Networks
In this paper we consider implementing optical burst switching as a technology for building grids with computationally intensive requirements. This architecture has been referred to as grid-over-OBS (GoOBS). First, we briefly describe the proposed layered grid architecture and show how OBS can be positioned within the grid architecture. Then, we present a generic framework for anycast routing in the context of GoOBS when requests don't have an explicit destination address and they can be serviced by any appropriate grid resource. We also develop several algorithms to support anycasting when only a single copy of a request is transmitted. Through simulation analysis, we show the performance of our anycast algorithms and compare them with traditional shortest-path unicast routing in which all jobs have specific addresses. Our performance analysis focuses on blocking probability of requests and average end-to-end delay