An Effective Model for Indirect Trust Computation in Pervasive Computing Environment

The performance of indirect trust computation models (based on recommendations) can be easily compromised due to the subjective and social-based prejudice of the provided recommendations. Eradicating the influence of such recommendation remains an important and challenging issue in indirect trust computation models. An effective model for indirect trust computation is proposed which is capable of identifying dishonest recommendations. Dishonest recommendations are identified by using deviation based detecting technique. The concept of measuring the credibility of recommendation (rather than credibility of recommender) using fuzzy inference engine is also proposed to determine the influence of each honest recommendation. The proposed model has been compared with other existing evolutionary recommendation models in this field, and it is shown that the model is more accurate in measuring the trustworthiness of unknown entity.     

Weighted image fusion using cross bilateral filter and non-subsampled contourlet transform

Multidimensional Systems and Signal Processing - This paper provides a fusion technique for multi-focus imaging using cross bilateral filter and non-subsampled contourlet transform. The snapshots...     

Path diversification for future internet end-to-end resilience and survivability

Path Diversification is a new mechanism that can be used to select multiple paths between a given ingress and egress node pair using a quantified diversity measure to achieve maximum flow reliability. The path diversification mechanism is targeted at the end-to-end layer, but can be applied at any level for which a path discovery service is available. Path diversification also takes into account service requirements for low-latency or maximal reliability in selecting appropriate paths. Using this mechanism will allow future internetworking architectures to exploit naturally rich physical topologies to a far greater extent than is possible with shortest-path routing or equal-cost load balancing. We describe the path diversity metric and its application at various aggregation levels, and apply the path diversification process to 13 real-world network graphs as well as 4 synthetic topologies to asses the gain in flow reliability. Based on the analysis of flow reliability across a range of networks, we then extend our path diversity metric to create a composite compensated total graph diversity metric that is representative of a particular topology’s survivability with respect to distributed simultaneous link and node failures. We tune the accuracy of this metric having simulated the performance of each topology under a range of failure severities, and present the results. The topologies used are from national-scale backbone networks with a variety of characteristics, which we characterize using standard graph-theoretic metrics. The end result is a compensated total graph diversity metric that accurately predicts the survivability of a given network topology.     

Interconnecting networks with optimized service provisioning

Telecommunication Systems - A recent trend of peering at geo-diversified Internet exchange points (IXPs) has empowered decades-old proposal of inter-networking and opened up new avenues of business...     

Novel Approach for Modeling Wireless Fading Channels Using a Finite State Markov Chain

Empirical modeling of wireless fading channels using common schemes such as autoregression and the finite state Markov chain (FSMC) is investigated. The conceptual background of both channel structures and the establishment of their mutual dependence in a confined manner are presented. The novel contribution lies in the proposal of a new approach for deriving the state transition probabilities borrowed from economic disciplines, which has not been studied so far with respect to the modeling of FSMC wireless fading channels. The proposed approach is based on equal portioning of the received signal‐to‐noise ratio, realized by using an alternative probability construction that was initially highlighted by Tauchen. The associated statistical procedure shows that a first‐order FSMC with a limited number of channel states can satisfactorily approximate fading. The computational overheads of the proposed technique are analyzed and proven to be less demanding compared to the conventional FSMC approach based on the level crossing rate. Simulations confirm the analytical results and promising performance of the new channel model based on the Tauchen approach without extra complexity costs.     

Finite volume based CFD simulation of pressurized flip-chip underfill encapsulation process

This paper presents the simulation of pressurized underfill encapsulation process for high I/O flip chip package. 3D model of flip chip packages is built using GAMBIT and simulated using FLUENT software. Injection methods such as central point, one line, L-type and U-type are studied. Cross-viscosity model and volume of fluid (VOF) technique are applied for melt front tracking of the encapsulant. The melt front profiles and pressure field for all injection types are analyzed and presented. The pressure distribution within the flip-chip, fill volume versus filling time and viscosity versus shear rate are also plotted. The U-type injection is found to be faster in filling. The numerical results are compared with the previous experimental results and found in good conformity. The strength of CFD software in handling underfill encapsulation problems is proved to be excellent.     

Interaction of α radiation with iron-doped n-type silicon

Deep-level transient spectroscopy (DLTS) measurements were carried out on low-doped n-silicon before and after irradiation with 5.48 MeV α particles at room temperature with a fluence of 10¹⁰ α particles/cm². The DLTS measurements on the samples identified three electron levels E₁, E₂ and E₃ before irradiation. The deep-levels characteristic studies include emission rate signatures, activation energies, defect concentrations and capture cross sections. It was found that all pre-existing defects decreased their amplitudes during irradiation. The decrease in activation energy of level E₃ and noticeable suppression of level E₁ was also observed after irradiation. It was clearly seen that the composite peak E₃ (combination of E₂ and E₃) was successfully resolved after irradiating with α particles. α-irradiation is seen to lead a significant suppression of the iron interstitial defect, and without causing any change in its room temperature annealing characteristics.     

Design considerations of all-optical A/D conversion: nonlinear fiber-optic Sagnac-loop interferometer-based optical quantizing and coding

The authors describe in detail the design considerations of our previously proposed novel optical quantizing and coding method for all-optical analog-to-digital (A/D) conversion using nonlinear optical switches based on the Sagnac interferometer. The multiperiod transfer function, which is the key to quantizing and coding, is achieved through a careful design of the Sagnac interferometer. In the experiments, the intensity of the pulse train input to our A/D converter is manually changed, and the corresponding digital signals are successfully mapped generated. Although the input-pulse trains are not the sampling of real analog signal, the principle of our proposed 3-bit A/D conversion at a 10 gigasample per second (Gsps) rate is demonstrated. The proposed optical quantizing and coding, combined with existing optical sampling techniques, will enable ultrafast photonic A/D conversion without electronics. The potential in the frequency regime of over a few hundred gigasamples per second was investigated by using an optical switch that utilizes the optical Kerr effect for fast operation. It was found out that the wavelength allocations and temporal widths of control and probe pulses have to be optimized with respect to the group-velocity dispersion of highly nonlinear fiber.     

An Enhanced A-MSDU Frame Aggregation Scheme for 802.11n Wireless Networks

The main goal of the IEEE 802.11n standard is to achieve a minimum throughput of 100 Mbps at the MAC service access point. This high throughput has been achieved via many enhancements in both the physical and MAC layers. A key enhancement at the MAC layer is frame aggregation in which the timing and headers overheads of the legacy MAC are reduced by aggregating multiple frames into a single large frame before being transmitted. Two aggregation schemes have been defined by the 802.11n standard, aggregate MAC service data unit (A-MSDU) and aggregate MAC protocol data unit (A-MPDU). As a consequence of the aggregation, new aggregation headers are introduced and become parts of the transmitted frame. Even though these headers are small compared to the legacy headers they still have a negative impact on the network performance, especially when aggregating frames of small payload. Moreover, the A-MSDU is highly influenced by the channel condition due mainly to lack of subframes sequence control and retransmission. In this paper, we have proposed an aggregation scheme (mA-MSDU) that reduces the aggregation headers and implements a retransmission control over the individual subframes at the MSDU level. The analysis and simulations results show the significance of the proposed scheme, specifically for applications that have a small frame size such as VoIP.     

An overview of spectrum sensing techniques for cognitive LTE and LTE-A radio systems

Advanced communication systems, such as long term evolution (LTE) and LTE-advanced (LTE-A) systems, promise to increase the number of users with high-speed data exchange. However, it leads to spectrum scarcity because of the huge size of data exchange with limited spectrum resources. Cognitive radio (CR) technique is considered the best solution for this spectrum scarcity problem. Spectrum sensing (SS), one of the CR techniques is used to detect the spectrum hole of primary user (PU) without interference with PU. In this paper, several SS approaches for LTE and LTE-A systems are investigated in the CR system. These SS approaches are based on two techniques, namely energy detection and cyclostationary feature detection techniques. The first technique includes four approaches of auto-correlation based advanced energy, time domain detection, Welch periodogram and two-stage model algorithms, while the second technique contains two approaches, namely pilot induced cyclostationary and second order cyclostationary algorithms. According to the analysis, the two-stage model and the second order cyclostationary algorithms are better than the other algorithms because they produce accurate results at the expense of system complexity. Hence, in general a good SS algorithms would require some trade-off between complexity and accuracy.