Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Clustering algorithm based on minimal path loss ratio for vehicular communication

Emerging vehicular comfort applications pose a host of completely new set of requirements such as maintaining end-to-end connectivity, packet routing, and reliable communication for internet access while on the move. One of the biggest challenges is to provide good quality of service (QoS) such as low packet delay while coping with the fast topological changes. In this paper, we propose a clustering algorithm based on minimal path loss ratio (MPLR) which should help in spectrum efficiency and reduce data congestion in the network. The vehicular nodes which experience minimal path loss are selected as the cluster heads. The performance of the MPLR clustering algorithm is calculated by rate of change of cluster heads, average number of clusters and average cluster size. Vehicular traffic models derived from the Traffic Wales data are fed as input to the motorway simulator. A mathematical analysis for the rate of change of cluster head is derived which validates the MPLR algorithm and is compared with the simulated results. The mathematical and simulated results are in good agreement indicating the stability of the algorithm and the accuracy of the simulator. The MPLR system is also compared with V2R system with MPLR system performing better. © 2013 IEEE.

Throughput-based rate adaptation algorithm for IEEE 802.11 vehicle networks

A key problem with IEEE 802.11 technology is adaptation of the transmission rates to the changing channel conditions, which is more challenging in vehicular networks. Although rate adaptation problem has been extensively studied for static residential and enterprise network scenarios, there is little work dedicated to the IEEE 802.11 rate adaptation in vehicular networks. Here, the authors are motivated to study the IEEE 802.11 rate adaptation problem in infrastructure-based vehicular networks. First of all, the performances of several existing rate adaptation algorithms under vehicle network scenarios, which have been widely used for static network scenarios, are evaluated. Then, a new rate adaptation algorithm is proposed to improve the network performance. In the new rate adaptation algorithm, the technique of sampling candidate transmission modes is used, and the effective throughput associated with a transmission mode is the metric used to choose among the possible transmission modes. The proposed algorithm is compared to several existing rate adaptation algorithms by simulations, which shows significant performance improvement under various system and channel configurations. An ideal signal-to-noise ratio (SNR)-based rate adaptation algorithm in which accurate channel SNR is assumed to be always available is also implemented for benchmark performance comparison.

Clustering algorithm based on minimal path loss ratio for vehicular communication

Emerging vehicular comfort applications pose a host of completely new set of requirements such as maintaining end-to-end connectivity, packet routing, and reliable communication for internet access while on the move. One of the biggest challenges is to provide good quality of service (QoS) such as low packet delay while coping with the fast topological changes. In this paper, we propose a clustering algorithm based on minimal path loss ratio (MPLR) which should help in spectrum efficiency and reduce data congestion in the network. The vehicular nodes which experience minimal path loss are selected as the cluster heads. The performance of the MPLR clustering algorithm is calculated by rate of change of cluster heads, average number of clusters and average cluster size. Vehicular traffic models derived from the Traffic Wales data are fed as input to the motorway simulator. A mathematical analysis for the rate of change of cluster head is derived which validates the MPLR algorithm and is compared with the simulated results. The mathematical and simulated results are in good agreement indicating the stability of the algorithm and the accuracy of the simulator. The MPLR system is also compared with V2R system with MPLR system performing better. © 2013 IEEE.

Design and analysis of distributed utility maximization algorithm for multihop wireless network with inaccurate feedback

Distributed network utility maximization (NUM) is receiving increasing interests for cross-layer optimization problems in multihop wireless networks. Traditional distributed NUM algorithms rely heavily on feedback information between different network elements, such as traffic sources and routers. Because of the distinct features of multihop wireless networks such as time-varying channels and dynamic network topology, the feedback information is usually inaccurate, which represents as a major obstacle for distributed NUM application to wireless networks. The questions to be answered include if distributed NUM algorithm can converge with inaccurate feedback and how to design effective distributed NUM algorithm for wireless networks. In this paper, we first use the infinitesimal perturbation analysis technique to provide an unbiased gradient estimation on the aggregate rate of traffic sources at the routers based on locally available information. On the basis of that, we propose a stochastic approximation algorithm to solve the distributed NUM problem with inaccurate feedback. We then prove that the proposed algorithm can converge to the optimum solution of distributed NUM with perfect feedback under certain conditions. The proposed algorithm is applied to the joint rate and media access control problem for wireless networks. Numerical results demonstrate the convergence of the proposed algorithm. © 2013 John Wiley & Sons, Ltd.

Optimization of cascaded regenerative links based on phase sensitive amplifiers

We develop an analytical method for optimizing phase sensitive amplifiers for regeneration in multilevel phase encoded transmission systems. The model accurately predicts the optimum transfer function characteristics and identifies operating tolerances for different signal constellations and transmission scenarios. The results demonstrate the scalability of the scheme and show the significance of having simultaneous optimization of the transfer function and the signal alphabet. The model is general and can be applied to any regenerative system. © 2013 Optical Society of America.

Optimization method for PSA-based multi-level regenerators

We develop an analytical methodology for optimizing phase regeneration based on phase sensitive amplification. The results demonstrate the scalability of the scheme and show the significance of simultaneous optimization of transfer function and the signal alphabet.

Optimization of DFB fiber laser performance based on a superimposed cavities structure

A simple technique based on superimposed cavities structure for direct real-time assessment of a DFB fiber laser mode condition during operation is demonstrated and used to provide a cavity mode conditioning feedback mechanism to optimize output performance. Significant improvements to the output performance and robustness are achieved over the entire pump power range without ambient isolation.

An Algorithm for Fresnel Diffraction Computing Based on Fractional Fourier Transform

The fractional Fourier transform (FrFT) is used for the solution of the diffraction integral in optics. A scanning approach is proposed for finding the optimal FrFT order. In this way, the process of diffraction computing is speeded up. The basic algorithm and the intermediate results at each stage are demonstrated.

Delimited Massively Parallel Algorithm Based on Rules Elimination for Application of Active Rules in Transition P Systems

In the field of Transition P systems implementation, it has been determined that it is very important to determine in advance how long takes evolution rules application in membranes. Moreover, to have time estimations of rules application in membranes makes possible to take important decisions related to hardware / software architectures design. The work presented here introduces an algorithm for applying active evolution rules in Transition P systems, which is based on active rules elimination. The algorithm complies the requisites of being nondeterministic, massively parallel, and what is more important, it is time delimited because it is only dependant on the number of membrane evolution rules.

Manometry-Based Cough Identification Algorithm

Gastroesophageal reflux disease (GERD) is a common cause of chronic cough. For the diagnosis and treatment of GERD, it is desirable to quantify the temporal correlation between cough and reflux events. Cough episodes can be identified on esophageal manometric recordings as short-duration, rapid pressure rises. The present study aims at facilitating the detection of coughs by proposing an algorithm for the classification of cough events using manometric recordings. The algorithm detects cough episodes based on digital filtering, slope and amplitude analysis, and duration of the event. The algorithm has been tested on in vivo data acquired using a single-channel intra-esophageal manometric probe that comprises a miniature white-light interferometric fiber optic pressure sensor. Experimental results demonstrate the feasibility of using the proposed algorithm for identifying cough episodes based on real-time recordings using a single channel pressure catheter. The presented work can be integrated with commercial reflux pH/impedance probes to facilitate simultaneous 24-hour ambulatory monitoring of cough and reflux events, with the ultimate goal of quantifying the temporal correlation between the two types of events.

Finding the Relationship between a Search Algorithm and a Class of Functions on Discrete Space by Exhaustive Search

* The work is supported by RFBR, grant 04-01-00858-a.

The Development of the Generalization Algorithm Based on the Rough Set Theory

This paper considers the problem of concept generalization in decision-making systems where such features of real-world databases as large size, incompleteness and inconsistence of the stored information are taken into account. The methods of the rough set theory (like lower and upper approximations, positive regions and reducts) are used for the solving of this problem. The new discretization algorithm of the continuous attributes is proposed. It essentially increases an overall performance of generalization algorithms and can be applied to processing of real value attributes in large data tables. Also the search algorithm of the significant attributes combined with a stage of discretization is developed. It allows avoiding splitting of continuous domains of insignificant attributes into intervals.

An Algorithm for Optimal Bipartite PLA Folding

This paper presents some results of PLA area optimizing by means of its column and row folding. A more restricted type of PLA simple folding is considered. It is introduced by Egan and Liu and called as bipartite folding. An efficient approach is presented which allows finding an optimal bipartite folding without exhaustive computational efforts.