Probabilistic Scheme Research Articles

DRIH-MAC: A Distributed Receiver-Initiated Harvesting-Aware MAC for Nanonetworks

In this paper, we introduce DRIH-MAC, a distributed receiver-initiated medium access control protocol for communication among nanonodes in a wireless electromagnetic nanonetwork. DRIH-MAC is developed based on the following principles: 1) communication starts via the receiver with the goal of maximizing the energy utilization; 2) the distributed scheme for accessing the medium is designed based on graph coloring; and 3) communication scheduling works in coordination with the energy harvesting process. DRIH-MAC is based on a probabilistic scheme to create a scalable and light-weight solution, which minimizes collisions and maximizes the utilization of harvested energy, and can be used in a wide variety of applications. Through simulation experiments, we demonstrate the efficiency of DRIH-MAC in a sample medical monitoring application. In particular, DRIH-MAC can improve energy utilization by 50% as compared to a random MAC protocol. Furthermore, it can satisfy application requirements such as delay, even with low energy harvesting rates.

Probabilistic Three-Party Sharing of Operation on a Remote Qubit

A probabilistic tripartite single-qubit operation sharing scheme is put forward by utilizing a two-qubit and a three-qubit non-maximally entangled state as quantum channels. Some specific comparisons between our scheme and another probabilistic scheme are made. It is found that, if the product of the two minimal coefficients characterizing channel entanglements is greater than 3/16, our scheme is more superior than the other one. Nonetheless, the price is that more classical and quantum resources are consumed, and the operation difficulty is rather increased. Moreover, some important features of the scheme, such as its security, probability and sharer symmetry, are revealed through concrete discussions. Additionally, the experimental feasibility of our scheme is analyzed and subsequently confirmed according to the current experimental techniques.

The estimation of diversity indexes by using stratified allocations of plots, points or transects

The estimation of diversity indexes is considered when species abundance is estimated by means of plots, points or transects placed onto the study region in accordance with probabilistic schemes. Under uniform random sampling–that is when plots, points or transects are uniformly and independently located on the study region–the consistency and the large‐sample normality of diversity index estimators follow from the usual limit theorems as the sampling effort increases. In addition, variance estimation and finite‐sample bias reduction are achieved by means of standard results on the jackknife method. Despite its theoretical simplicity, uniform random sampling may lead to uneven coverage of the study region. In order to avoid this shortcoming, the use of one‐per‐stratum stratified sampling is usually considered. This sampling scheme involves partitioning the study region into subsets of equal size and uniformly selecting a plot, a point or a transect in each of these subsets. The present paper aims to show the consistency and the large‐sample normality of the diversity index estimators under one‐per‐stratum stratified sampling, as well as to deal with variance estimation and bias reduction. Copyright © 2015 John Wiley & Sons, Ltd.

A fault diagnosis system for interdependent critical infrastructures based on HMMs

Modern society depends on the smooth functioning of critical infrastructures which provide services of fundamental importance, e.g. telecommunications and water supply. These infrastructures may suffer from faults/malfunctions coming e.g. from aging effects or they may even comprise targets of terrorist attacks. Prompt detection and accommodation of these situations is of paramount significance.This paper proposes a probabilistic modeling scheme for analyzing malicious events appearing in interdependent critical infrastructures. The proposed scheme is based on modeling the relationship between datastreams coming from two network nodes by means of a hidden Markov model (HMM) trained on the parameters of linear time-invariant dynamic systems which estimate the relationships existing among the specific nodes over consecutive time windows. Our study includes an energy network (IEEE 30 model bus) operated via a telecommunications infrastructure.The relationships among the elements of the network of infrastructures are represented by an HMM and the novel data is categorized according to its distance (computed in the probabilistic space) from the training ones. We considered two types of cyber-attacks (denial of service and integrity/replay) and report encouraging results in terms of false positive rate, false negative rate and detection delay.

Optimal Probabilistic Robust Beamforming for MISO SWIPT Systems with Gaussian Channel Uncertainties

For simultaneous wireless information and power transfer in the multi-input single-output broadcast channel, we propose a probabilistic robust beamforming scheme which minimizes the outage probability of the information receiver subject to the probabilistic energy harvesting constraint where the channel uncertainties are modeled as Gaussian random variables. Expressing the optimization problem by Marcum's Q-functions, we obtain the optimal closed-form beamforming solution. Simulation results show that the proposed scheme outperforms the worst-case robust beamforming scheme.

Crack detection and health monitoring of highway steel-girder bridges

A vibration-based damage-detection methodology is presented in this work to monitor the health condition of a highway steel-girder bridge in Iowa. The contribution of the proposed methodology is to combine the transmissibility function, coherence function, and probabilistic schemes to construct a percent-violation that gives critical information about the health condition of the bridge. The percent-violation creates two alarm severities, watch and warning, depending on how many times the percent-violation successively crosses an objective threshold created from the healthy data. Field results using stochastic operational traffic loading have indicated the capability of the proposed methodology in evaluating the changes in the health condition of a section of the bridge and in consistently detecting cracks of various sizes (30–60 mm) on a sacrificial specimen integrated with the bridge abutment and a floor beam. Fluctuations in environmental and loading conditions have been known to create some uncertainties in most damage-detection processes; however, this work demonstrated that using an objective threshold, these uncertainties will be contained. Additionally, based on the sacrificial specimen’s results, once damage is initiated or propagated on the structure, the effect of these parameters becomes less relevant. The results of additional field testing using controlled impact forces on the sacrificial specimen have reinforced the findings from the operational loading in detecting damage.

A probabilistic strategy for seismic assessment and FRP retrofitting of existing bridges

This study proposes a holistic probabilistic framework to evaluate existing road and railway bridges after an earthquake by means of analytical fragility curves and visual inspections. Although visual inspections are affected by uncertainties, they are usually considered in a deterministic way, while in this work they are taken into account in a probabilistic point manner. Moreover, extra focus is given on retrofitting interventions by means of Fiber Reinforced Polymer materials and their costs. A probabilistic methodology is formed to evaluate possible standardized interventions on existing bridges after a seismic event. The proposed framework, consists of six basic steps and it is applied on a reinforced concrete bridge case study, which is a common structural typology in Italian roadway infrastructural networks. The main aim is to provide useful information to public authorities in order to decide whether or not they should allow traffic over the bridge and whether to repair immediately earthquake-damaged bridges. The outcomes of this framework can be used to improve procedures used for the seismic assessment of the whole road and railway networks to better plan emergency, post-emergency actions and define a general priority for an optimal budget allocation.

Fuzzy soft games

In this work, after introduce the definition of fuzzy soft sets and their basic operations we define two person fuzzy soft games which can apply to problems contain vagueness and uncertainty. We then give four different types solution methods of the games which are fuzzy soft saddle points, fuzzy soft lower and upper values, fuzzy soft dominated strategies and fuzzy soft Nash equilibrium. We also give a probabilistic equilibrium solution method for the two persons fuzzy soft games (tp f s-games) which show that every finite tp f s-game with probabilistic strategies has one solution. Finally, we give an application which shows that the methods can be successfully applied to a financial problem and extended the two person fuzzy soft games to n-person fuzzy soft games.

Efficient and Privacy-preserving Min and k-th Min Computations in Mobile Sensing Systems

Protecting the privacy of mobile phone user participants is extremely important for mobile phone sensing applications. In this paper, we study how an aggregator can expeditiously compute the minimum value or the $k$ th minimum value of all users’ data without knowing them. We construct two secure protocols using probabilistic coding schemes and a cipher system that allows homomorphic bitwise XOR computations for our problems. Following the standard cryptographic security definition in the semi-honest model, we formally prove our protocols’ security. The protocols proposed by us can support time-series data and need not to assume the aggregator is trusted. Moreover, different from existing protocols that are based on secure arithmetic sum computations, our protocols are based on secure bitwise XOR computations, thus are more efficient.

Secure Routing Protocol in Delay TolerantNetworks Using Fuzzy Logic Algorithm

Security is the biggest challenge in MANET. MANET presents various types of security attacks on data exchanges taking place between source and destination. In this misbehavior detection schemes for conventional wireless networks has opposed black hole attack and malicious node occur routing, this proposed technique as a great challenges in networks. In this iTrust, a probabilistic misbehavior detection scheme is highly desirable to assure the secure DTN routing as well as the establishment of the trust, among DTN nodes. A zone (routing zone) of a node is used to collect the node information within the range. In this protocol, it cannot achieve the packet delivery ratio, performance and data loss rate. In this paper we are providing the solution against black hole attack which is based on fuzzy rule. Fuzzy rule is used to identify the infected node as well as provide the solution to reduce data loss over network. Fuzzy logic ranges between the value as {0, 1}. Geographic routing is one of the most suitable routing strategies in wireless mobile Adhoc network mainly due to its scalability. Multi Input Multi Output technique used to send data frequently in routing protocol. Analysis and simulation results demonstrate the effectiveness and efficiency of the drop node analysis, high packet delivery ratio, throughput and delay.

Plaintext checkable encryption with designated checker

This paper introduces a new public-key primitive called designated plaintext checkable encryption (DPCE) in which given a ciphertext, a delegated checker can determine whether the ciphertext decrypts under the same public key to a plaintext chosen by himself. Motivated by various applications, two types of DPCE (of Type-I and II) are defined, depending upon whether the user delegates the plaintext checking right at his will to a delegated checker (Type-I) or the user is required to provide this plaintext checking right to a designated checker (Type-II). We propose several generic random-oracle and standard model constructions for DPCE of both the types based on arbitrary probabilistic or deterministic encryption schemes.

New Limits to Classical and Quantum Instance Compression

Given an instance of a hard decision problem, a limited goal is to compress that instance into a smaller, equivalent instance of a second problem. As one example, consider the problem where, given Boolean formulas $\psi^1, \ldots, \psi^t$, we must determine if at least one $\psi^j$ is satisfiable. An $\mathrm{OR}$-compression scheme for SAT is a polynomial-time reduction $R$ that maps $(\psi^1, \ldots, \psi^t)$ to a string $z$, such that $z$ lies in some “target” language $L'$ if and only if $\bigvee_j [\psi^j \in \mathrm{SAT}]$ holds. (Here, $L'$ can be arbitrarily complex.) AND-compression schemes are defined similarly. A compression scheme is strong if $|z|$ is polynomially bounded in $n = \max_j |\psi^j|$, independent of $t$. Strong compression for SAT seems unlikely. Work of Harnik and Naor [SIAM J. Comput., 39 (2010), pp. 1667--1713] and Bodlaender, Downey, Fellows, and Hermelin [J. Comput. System Sci., 75 (2009), pp. 423--434] showed that the infeasibility of strong OR-compression for SAT would show limits to instance compression for a large number of natural problems. Bodlaender et al. also showed that the infeasibility of strong AND-compression for SAT would have consequences for a different list of problems. Motivated by this, Fortnow and Santhanam [J. Comput. System Sci., 77 (2011), pp. 91--106] showed that if SAT is strongly OR-compressible, then $\mathsf{NP} \subseteq \mathsf{coNP/poly}$. Finding similar evidence against AND-compression was left as an open question. We provide such evidence: we show that strong AND- or OR-compression for SAT would imply nonuniform, statistical zero-knowledge proofs for SAT---an even stronger and more unlikely consequence than $\mathsf{NP} \subseteq \mathsf{coNP/poly}$. Our method applies against probabilistic compression schemes of sufficient “quality” with respect to the reliability and compression amount (allowing for tradeoff). This greatly strengthens the evidence given by Fortnow and Santhanam against probabilistic OR-compression for SAT. We also give variants of these results for the analogous task of quantum instance compression, in which a polynomial-time quantum reduction must output a quantum state that, in an appropriate sense, “preserves the answer” to the input instance. The central idea in our proofs is to exploit the information bottleneck in an AND-compression scheme for a language $L$ in order to fool a cheating prover in a proof system for $\overline{L}$. Our key technical tool is a new method to “disguise” information being fed into a compressive mapping; we believe this method may find other applications.

Optimized Temperature Reduction Schedule for Simulated Annealing Algorithm

Simulated annealing algorithm is one of the well-known tools to achieve the global optima in an optimization problem. It has been widely used and its superiority has been validated to many of the other optimization techniques. Thou the major advantage of SA is to avoid the local optima by accepting weaker solutions, concerns have been raised about the cooling schedule followed by the SA, which plays a very vital role in the quality of result obtained. In this paper we address the cooling scheme of the SA, and propose a new cooling technique called Probabilistic Cooling Scheme (PCS), the SA with PCS is used to optimize the well-known flow shop problems of Carlier and Reeves. The results have been compared to other algorithms found in the literature. SA with PCS was found to achieve superior results in most of the cases.

ENSP: Energy Efficient Next Hop Selection in A Probabilistic Voting-Based Filtering Scheme Using Fuzzy Logic

ENSP: Energy Efficient Next Hop Selection in A Probabilistic Voting-Based Filtering Scheme Using Fuzzy Logic

A Security Method for Multiple Attacks in Sensor Networks: Against False-Report Injection, False-Vote Injection and Wormhole Attacks

In a large-scale wireless sensor network, damage spreads rapidly in the network when under false report injection, false votes injection, or wormhole attacks. These attacks cause finite energy resources to be drained, legitimate reports to be dropped, and data to be intercepted by adversary nodes. A probabilistic voting-based filtering scheme (PVFS) and localized encryption and authentication protocol (LEAP) can be used to cope with these attacks. When multiple attacks occur simultaneously, PVFS and LEAP should be operated together. But the concurrent application of PVFS and LEAP provides inefficient duplications of operations in the sensor network. In this paper, we propose a security method which improves the energy efficiency while maintaining the security level of applying PVFS and LEAP simultaneously. The proposed method was designed by identifying and eliminating the redundancies of employing both methods together and providing more efficient functionalities. Four types of new keys were also designed for simultaneous detection of multiple attacks. We evaluated the effectiveness of the proposed method compared to simply applying PVFS and LEAP simultaneously when under multiple attacks. The experimental results demonstrate that our proposed method saves energy by up to 11% while maintaining detection power.

Development of a probabilistic buckling analysis scheme for continuous welded rail track

Continuous welded rail (CWR) track has several advantages when compared with conventional jointed rail track. However, a thermally induced axial load can lead to the buckling of CWR tracks, which can result in train derailment. The buckling of CWR tracks is affected by several parameters, including the rail’s neutral temperature, misalignment of the rails and ballast resistance. Most of these parameters can be considered as random variables. A deterministic analysis approach is generally used to predict the buckling of CWR tracks; however, it can provide conservative results since it is based on the worst-case scenario of these buckling parameters. This paper presents a probabilistic buckling analysis scheme for CWR tracks.

Thermal Properties and Topology of Epoxy Networks: A Multiscale Simulation Methodology

We present a novel hierarchical multiscale methodology aimed at generating the atomistic structure of epoxy networks and predicting their properties and topology. Our approach combines several computational techniques and consists of four separate procedures: (1) mapping of the polymerizing monomers onto a coarse-grained representation using the method of neural-gas networks, (2) cross-linking the coarse-grained monomers at mesoscale by applying dissipative particle dynamics and a probabilistic reaction scheme, (3) reverse mapping of the coarse-grained polymer network to a fully atomistic representation, and (4) simulation of the atomistic model by means of molecular dynamics technique. As a case study, we simulate DGEBA + DETDA epoxy network formation and analyze the thermal properties and the network topology. It was found that the parameters used for generating the atomistic structures (degree of coarse graining in our case) can significantly influence the network topology and properties. Moreover, we ...

Local probabilistic homogenization schemes for assessment of material uncertainties in solid foams

AbstractThe present study is concerned with a probabilistic model for prediction of the uncertainties in the effective material response of long fiber reinforced thermoplastic materials. The model is based on a simple elasticity model using the rules of mixture together with an ensemble averaging procedure. Assuming the scatter band width of local fiber orientation angle and the local fiber density as random variables, a probabilistic model is obtained. (© 2014 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Modified M-ary QT Algorithm to Improve the Performance of the Anti-collision Protocol for RFID Tag Identification

The Radio Frequency Identification (RFID) system is a newemerging technology used to identify a tag attached to an object. To make RFID systems practical, the cost of RFIDtags is very important. Further, an interrogator should be able to identify thenumber of tags in the reading range in a short time. The most important technical issue in radio frequency identification (RFID) is to correctly and quickly recognize the number of tag IDs in the reader’s communication range. Unlike the probabilistic RFID tag identification schemes, a query tree(QT)-based protocol guarantees the identification of all the tags, where the distribution of tag IDs is assumed to be uniform. In this paper, we proposed an extended M-ary QT protocol, which effectively reduces unnecessary query-response cycles by using a non-sequential m-bit recognition method. The simulation results show that the proposed scheme significantly outperforms M-ary QT schemes in terms of identification time, efficiency and communications overhead.

A survey on probabilistic broadcast schemes for wireless ad hoc networks

Broadcast or flooding is a dissemination technique of paramount importance in wireless ad hoc networks. The broadcast scheme is widely used within routing protocols by a wide range of wireless ad hoc networks such as mobile ad hoc networks, vehicular ad hoc networks, and wireless sensor networks, and used to spread emergency messages in critical scenarios after a disaster scenario and/or an accidents. As the type broadcast scheme used plays an important role in the performance of the network, it has to be selected carefully. Though several types of broadcast schemes have been proposed, probabilistic broadcast schemes have been demonstrated to be suitable schemes for wireless ad hoc networks due to a range of benefits offered by them such as low overhead, balanced energy consumption, and robustness against failures and mobility of nodes. In the last decade, many probabilistic broadcast schemes have been proposed by researchers. In addition to reviewing the main features of the probabilistic schemes found in the literature, we also present a classification of the probabilistic schemes, an exhaustive review of the evaluation methodology including their performance metrics, types of network simulators, their comparisons, and present some examples of real implementations, in this paper.