Valuing American Style Options by Least Squares Methods

We investigate the finite sample performance of some recent Monte Carlo estimators under different market scenarios. We find that the accuracy and efficiency of these estimators are remarkable, even when more exotic financial instruments are considered. Finally, we extend the Glasserman and Yu (2004b) methodology to price Asian Bermudan options and basket options

Maximizing Energy-Efficiency in Multi-Relay OFDMA Cellular Networks

This contribution presents a method of obtaining the optimal power and subcarrier allocations that maximize the energy-efficiency (EE) of a multi-user, multi-relay, orthogonal frequency division multiple access (OFDMA) cellular network. Initially, the objective function (OF) is formulated as the ratio of the spectral-efficiency (SE) over the power consumption of the network. This OF is shown to be quasi-concave, thus Dinkelbach's method can be employed for solving it as a series of parameterized concave problems. We characterize the performance of the aforementioned method by comparing the optimal solutions obtained to those found using an exhaustive search. Additionally, we explore the relationship between the achievable SE and EE in the cellular network upon increasing the number of active users. In general, increasing the number of users supported by the system benefits both the SE and EE, and higher SE values may be obtained at the cost of EE, when an increased power may be allocated.Comment: 6 pages, 5 figures, 1 table, to appear in Proc. IEEE 2013 56th Global Communications Conference (GLOBECOM 2013), Atlanta, USA, December, 201

Multi-objective routing optimization using evolutionary algorithms

Wireless ad hoc networks suffer from several limitations, such as routing failures, potentially excessive bandwidth requirements, computational constraints and limited storage capability. Their routing strategy plays a significant role in determining the overall performance of the multi-hop network. However, in conventional network design only one of the desired routing-related objectives is optimized, while other objectives are typically assumed to be the constraints imposed on the problem. In this paper, we invoke the Non-dominated Sorting based Genetic Algorithm-II (NSGA-II) and the MultiObjective Differential Evolution (MODE) algorithm for finding optimal routes from a given source to a given destination in the face of conflicting design objectives, such as the dissipated energy and the end-to-end delay in a fully-connected arbitrary multi-hop network. Our simulation results show that both the NSGA-II and MODE algorithms are efficient in solving these routing problems and are capable of finding the Pareto-optimal solutions at lower complexity than the ’brute-force’ exhaustive search, when the number of nodes is higher than or equal to 10. Additionally, we demonstrate that at the same complexity, the MODE algorithm is capable of finding solutions closer to the Pareto front and typically, converges faster than the NSGA-II algorithm

Efficient parallel mining of association rules on shared-memory multiple-processor machine

In this paper we consider the problem of parallel mining of association rules on a shared-memory multiprocessor system. Two efficient algorithms PSM and HSM have been proposed. PSM adopted two powerful candidate set pruning techniques distributed pruning and global pruning to reduce the size of candidates. HSM further utilized an I/O reduction strategy to enhance its performance. We have implemented PSM and HSM on a SGI Power Challenge parallel machine. The performance studies show that PSM and HSM out perform CD-SM, which is a shared-memory parallel version of the popular Apriori algorithm.published_or_final_versio

Distributed energy spectral efficiency optimization for partial/full interference alignment in multi-user multi-relay multi-cell MIMO systems

The energy spectral efficiency maximization (ESEM) problem of a multi-user, multi-relay, multi-cell system is considered, where all the network nodes are equipped with multiple antenna aided transceivers. In order to deal with the potentially excessive interference originating from a plethora of geographically distributed transmission sources, a pair of transmission protocols based on interference alignment (IA) are conceived, which may be distributively implemented in the network. The first, termed the full-IA protocol, avoids all intra-cell interference (ICI) and other-cell interference (OCI) by finding the perfect interferencenulling receive beamforming matrices (RxBFMs). The second protocol, termed as partial-IA, only attempts to null the ICI. Employing the RxBFMs computed by either of these protocols mathematically decomposes the channel into a multiplicity of non-interfering multiple-input–single-output (MISO) channels, which we term as spatial multiplexing components (SMCs). The problem of finding the optimal SMCs as well as their power control variables for the ESEM problem considered is formally defined and converted into a convex optimization form with the aid of carefully selected variable relaxations and transformations. Thus, the optimal SMCs and power control variables can be distributively computed using both the classic dual decomposition and subgradient methods. The performance of both protocols is characterized, and the ESEM algorithm conceived is compared to a baseline equal power allocation (EPA) algorithm. The results indicate that indeed, the ESEM algorithm performs better than the EPA algorithm in most cases. Furthermore, surprisingly the partial-IA protocol outperforms the full-IA protocol in all cases considered, which may be explained by the fact that the partial-IA protocol is less restrictive in terms of the number of available transmit dimensions at the transmitters. Given the typical cell sizes considered in this paper, the path-loss sufficiently attenuates the majority of the interference, and thus the full-IA protocol over-compensates, when trying to avoid all possible sources of interference. We have observed that, given a sufficiently high maximum power, the partial-IA protocol achieves an energy spectral efficiency (ESE) that is 2.42 times higher than that attained by the full-IA protocol

Cross-layer network lifetime optimization considering transmit and signal processing power in WSNs

Maintaining high energy efficiency is essential for increasing the lifetime of wireless sensor networks (WSNs), where the battery of the sensor nodes cannot be routinely replaced. Nevertheless, the energy budget of the WSN strictly relies on the communication parameters, where the choice of both the transmit power as well as of the modulation and coding schemes (MCSs) plays a significant role in maximizing the network lifetime (NL). In this paper, we optimize the NL of WNSs by analysing the impact of the physical layer parameters as well as of the signal processing power (SPP) P_sp on the NL. We characterize the underlying trade-offs between the NL and bit error ratio (BER) performance for a predetermined set of target signal-to-interference-plus-noise ratio (SINR) values and for different MCSs using periodic transmit-time slot (TS) scheduling in interference-limited WSNs. For a per-link target BER requirement (PLBR) of 10^?3, our results demonstrate that a ’continuous-time’ NL in the range of 0.58?4.99 years is achieved depending on the MCSs, channel configurations, and SPP

Colour Reflectance Investigation of Decolourized Sulfur Dyed Cotton Knitted Fabric via Ozone Plasma Treatment

Ozone plasma treatment is accessible to be applied on shading adjustment and colour fading because of the capacity of ozone production. It is a green process that treats dyed cotton fabric under dry condition so as to avoid chemical pollutants. This study means to explore colour reflectance of decolourized sulfur dyed cotton texture using ozone plasma treatment. Sulfur dyed cotton textures with various colour depths (0.5%, 1.5%, 2.5%) were set up to be treated different plasma parameters, including ozone air concentrations (10%, 30%, 50%, 70%), water contents in terms of weight percentage (35%, 45%) of fabric and ozone air plasma treatment periods (10 mins, 20 mins, 30 mins). The colour fading result is assessed by the colour reflectance in percentage (R%) utilizing spectrophotometer under CIE standard illuminant D65. The valid colour fading based on high percentage of reflectance was demonstrated from plasma treatment under higher ozone air concentration (50% and 70% ozone in air) and longer time length of plasma treatment (20 mins and 30 mins). The level of water content contained in the cotton fabrics is appeared to have noteworthy relationship with the degree of decolourization

A survey of network lifetime maximization techniques in wireless sensor networks

Emerging technologies, such as the Internet of things, smart applications, smart grids and machine-to-machine networks stimulate the deployment of autonomous, selfconfiguring, large-scale wireless sensor networks (WSNs). Efficient energy utilization is crucially important in order to maintain a fully operational network for the longest period of time possible. Therefore, network lifetime (NL) maximization techniques have attracted a lot of research attention owing to their importance in terms of extending the flawless operation of battery-constrained WSNs. In this paper, we review the recent developments in WSNs, including their applications, design constraints and lifetime estimation models. Commencing with the portrayal of rich variety definitions of NL design objective used for WSNs, the family of NL maximization techniques is introduced and some design guidelines with examples are provided to show the potential improvements of the different design criteri