Fadi A. Aloul

A Mobile GPRS-Sensors Array for Air Pollution Monitoring

An online GPRS-Sensors Array for air pollution monitoring has been designed, implemented, and tested. The proposed system consists of a Mobile Data-Acquisition Unit (Mobile-DAQ) and a fixed Internet-Enabled Pollution Monitoring Server (Pollution-Server). The Mobile-DAQ unit integrates a single-chip microcontroller, air pollution sensors array, a General Packet Radio Service Modem (GPRS-Modem), and a Global Positioning System Module (GPS-Module). The Pollution-Server is a high-end personal computer application server with Internet connectivity. The Mobile-DAQ unit gathers air pollutants levels (CO, NO2, and SO2), and packs them in a frame with the GPS physical location, time, and date. The frame is subsequently uploaded to the GPRS-Modem and transmitted to the Pollution-Server via the public mobile network. A database server is attached to the Pollution-Server for storing the pollutants level for further usage by various clients such as environment protection agencies, vehicles registration authorities, and tourist and insurance companies. The Pollution-Server is interfaced to Google Maps to display real-time pollutants levels and locations in large metropolitan areas. The system was successfully tested in the city of Sharjah, UAE. The system reports real-time pollutants level and their location on a 24-h/7-day basis.

Two factor authentication using mobile phones

This paper describes a method of implementing two factor authentication using mobile phones. The proposed method guarantees that authenticating to services, such as online banking or ATM machines, is done in a very secure manner. The proposed system involves using a mobile phone as a software token for One Time Password generation. The generated One Time Password is valid for only a short user-defined period of time and is generated by factors that are unique to both, the user and the mobile device itself. Additionally, an SMS-based mechanism is implemented as both a backup mechanism for retrieving the password and as a possible mean of synchronization. The proposed method has been implemented and tested. Initial results show the success of the proposed method.

Solving difficult SAT instances in the presence of symmetry

Research in algorithms for Boolean satisfiability and their implementations [23, 6] has recently outpaced benchmarking efforts. Most of the classic DIMACS benchmarks [10] can be solved in seconds on commodity PCs. More recent benchmarks take longer to solve because of their large size, but are still solved in minutes [25]. Yet, small and difficult SAT instances must exist because Boolean satisfiability is NP-complete.We propose an improved construction of symmetry-breaking clauses [9] and apply it to achieve significant speed-ups over current state-of-the-art in Boolean satisfiability. Our techniques are formulated as pre-processing and can be applied to any SAT solver without changing its source code. We also show that considerations of symmetry may lead to more efficient reductions to SAT in the routing domain.Our work articulates SAT instances that are unusually difficult for their size, including satisfiable instances derived from routing problems. Using an efficient implementation to solve the graph automorphism problem [18, 20, 22], we show that in structured SAT instances difficulty may be associated with large numbers of symmetries.

Robust SAT-Based Search Algorithm for Leakage Power Reduction

Leakage current promises to be a major contributor to power dissipation in future technologies. Bounding the maximum and minimum leakage current poses an important problem. Determining the maximum leakage ensures that the chip meets power dissipation constraints. Applying an input pattern that minimizes leakage allows extending battery life when the circuit is in standby mode. Finding such vectors can be expressed as a satisfiability problem. We apply in this paper an incremental SAT solver, PBS [1], to find the minimum or maximum leakage current. The solver is called as a post-process to a random-vector-generation approach. Our results indicate that using a such a generic SAT solver can improve on previously proposed random approaches [7].

Current and future trends in sensor networks: a survey

Sensor networks consist of a large number of very small nodes that are deployed in some geographical area. The purpose of the network is to sense the environment and report what happens in the area it is deployed in. Sensor networks are used in many applications. In military applications they are used for surveillance and target tracking. In industrial applications, sensor networks are used in monitoring hazardous chemicals. They are also used in monitoring the environment and in early fire warning in forests as well as seismic data collections. Sensor networks face new challenges not known in cellular and ad-hoc wireless networks. In this paper, we report on currents and new trends in sensor networks. We also present some of the challenges and future work in sensor networks.

A comparative study of two Boolean formulations of FPGA detailed routing constraints

A Boolean-based router expresses the routing constraints as a Boolðean function which is satisfiable if and only if the layout is routable. Compared to traditional routers, Boolean-based routers offer two unique features: (1) simultaneous embedding of all nets regardless of net ordering, and (2) ability to demonstrate routing infeasibility by proving the unsatisfiability of the generated routing constraint Boolean function. In this paper, we introduce a new Boolean-based FPGA detailed routing formulation that yields an easy-to-evaluate and more scalable routability Boolean function than the previous methods. The routability constraints are expressed in terms of a set of route variables each of which designating a specific detailed route for a given net. Experimental results clearly show the superiðority of this formulation over an earlier formulation that expressed the constraints in terms of track variables.

Faster SAT and smaller BDDs via common function structure

The increasing popularity of SAT and BDD techniques in verification and synthesis encourages the search for additional speed-ups. Since typical SAT and BDD algorithms are exponential in the worst-case, the structure of real-world instances is a natural source of improvements. While SAT and BDD techniques are often presented as mutually exclusive alternatives, our work points out that both can be improved via the use of the same structural properties of instances. Our proposed methods are based on efficient problem partitioning and can be easily applied as pre-processing with arbitrary SAT solvers and BDD packages without source code modifications. Our contribution is validated on the ISCAS circuits and the DIMACS benchmarks. Empirically, our technique often outperforms existing techniques by a factor of two or more. Our results motivate search for stronger dynamic ordering heuristics and combined static/dynamic techniques.

FORCE: a fast and easy-to-implement variable-ordering heuristic

The MINCE heuristic for variable-ordering [1] can successfully reduce the size of BDDs and accelerate SAT-solving. Applications to reachability analysis have also been successful [12]. The main drawback of MINCE is its implementation complexity - the authors used a pre-existing min-cut placer [6] that is several times larger than any existing SAT solver. Tweaking MINCE is difficult.In this work we propose a replacement heuristic, FORCE which is easy to implement from scratch and tweak. It is dramatically faster than MINCE in practice. While FORCE may produce seemingly inferior variable orderings, the difference with MINCE orderings does not affect subsequent SAT-solving.

Efficient symmetry breaking for Boolean satisfiability

Identifying and breaking the symmetries of conjunctive normal form (CNF) formulae has been shown to lead to significant reductions in search times. Symmetries in the search space are broken by adding appropriate symmetry-breaking predicates (SBPs) to an SAT instance in CNF. The SBPs prune the search space by acting as a filter that confines the search to nonsymmetric regions of the space without affecting the satisfiability of the CNF formula. For symmetry breaking to be effective in practice, the computational overhead of generating and manipulating SBPs must be significantly less than the runtime savings they yield due to search space pruning. In this paper, we describe a more systematic and efficient construction of SBPs. In particular, we use the cycle structure of symmetry generators, which typically involve very few variables, to drastically reduce the size of SBPs. Furthermore, our new SBP construction grows linearly with the number of relevant variables as opposed to the previous quadratic constructions. Our empirical data suggest that these improvements reduce search runtimes by one to two orders of magnitude on a wide variety of benchmarks with symmetries.

Shatter: efficient symmetry-breaking for Boolean satisfiability

Boolean satisfiability (SAT) solvers have experienced dramatic improvements in their performance and scalability over the last several years according to E. Goldberg et al. (2002) and are now routinely used in diverse EDA applications. Nevertheless, a number of practical SAT instances remain difficult to solve in SAT 2002 Competition (http://www.satlive.org/SATCompetition/submittedbenchs.html) and continue to defy even the best available SAT solvers according to E. Goldberg et al. (2002). Recent work pointed out that symmetries in the Boolean search space are often to blame. A theoretical framework for detecting and breaking such symmetries was introduced in J. Crawford et al. (1996). This framework was subsequently extended, refined, and empirically shown to yield significant speed-ups for a large number of benchmark classes in F. Aloul et al. (2002). Symmetries in the search space are broken by adding appropriate symmetry-breaking predicates (SBPs) to a SAT instance in conjunctive normal form (CNF). The SBPs prune the search space by acting as a filter that confines the search to nonsymmetric regions of the space without affecting the satisfiability of the CNF formula. For symmetry breaking to be effective in practice, the computational overhead of generating and manipulating the SBPs must be significantly less than the run time savings they yield due to search space pruning. In this paper, we present several new constructions of SBPs that improve on previous work. Specifically, we give a linear-sized CNF formula that selects lex-leaders (among others) for single permutations. We also show how that formula can be simplified by taking advantage of the sparsity of permutations. We test these improvements against earlier constructions and show that they yield smaller SNPs and lead to run time reductions on many benchmarks.