Distributed De La Garza algorithm for load-balancing routing in wireless sensor networks

Large scale wireless sensor networks raise many challenges in the design of efficient and effective routing algorithm due to their complexity and hardware constraints. However, the scalability challenge may be mitigated from a macroscopic perspective. One example is the distributed De la Garza iteration (DDLGI) algorithm for global routing load-balancing, based on a set of partial differential equations iteratively solved by the De la Garza method. We theoretically analyze the parallelism of DDLGI and illustrate that the region of interest may impact the degree of parallelism and error. Furthermore, though DDLGI always converges, the slow convergence and long-range information exchange problems may lead to excess energy consumption in communication. Thus, we propose various enhanced De la Garza routing (E-DLGR) algorithms to alleviate the energy consumption problem by which nodes may exchange less information and only need to exchange information with closer nodes to complete each iteration. Our theoretical analysis and simulation results show that the proposed E-DLGR algorithms may have less transmission overhead, thus further reducing energy consumption, and converge faster while still maintaining adequate accuracy.

     

Membrane separation of indigenous noroviruses from sewage sludge and treated wastewater.

In this study, feasibility of membrane separation for the removal of indigenous noroviruses (NVs) is evaluated. The indigenous NV gene was never detected from ultrafiltration (UF) permeates of sewage sludge and treated wastewater. Indigenous NV gene was also not detected from permeates of sewage sludge and treated wastewater by microfiltration (MF) with a pore size of 0.1 microm (MF0.1). Even though the pore size of MF (0.1 microm) was much larger than the diameter of virus particle (approximately 30-40nm), more than 4-log10 reduction value (LRV) at maximum was achieved by membrane separation with MF0.1. NV genes were often detected from permeates of sewage sludge and treated wastewater by MF with a pore size of 0.45 microm (MF0.45), although the maximum log10 reduction values were more than 3.59 for sewage sludge and more than 2.90 for treated wastewater. It is important to verify factors determining the removal efficiency of viruses with MF membranes.     

Identification of the adverse effect of nitrate on the phosphate release rate and improvement of EBPR process models.

The adverse effect of nitrate on the phosphate release rate in the anaerobic phase was observed and was hardly explainable with conventional EBPR process models. Four possible mechanisms were proposed including substrate competition, reduced fermentation, parallel reaction and sequential reaction. Batch experiments were designed and conducted to identify the dominant mechanism. Results showed that the sequential reaction was the only possible mechanism where only denitrification occurred if any nitrate existed in the anaerobic phase. Then the phosphate release following after the nitrate was completely removed. Nitrate inhibition effect was added into the PHA storage rate to incorporate the sequential reaction in the conventional ASM3 plus EAWAG bio-P module (ASM3 + P). Nitrate inhibition coefficient, K(I,NO,PAO) was found to be as low as 0.05 mg/L. This correlated well with experimental observation where no also meant that the anaerobic compartment of a continuous flow reactor could be seriously affected by the residual nitrate contained in the sludge recycle flow. This phenomenon caused overestimation of the phosphate uptake rate and consequently underestimation of PO4(3-) -P concentration. This problem was resolved by incorporation of a nitrate inhibition term in the ASM3 + P for more accurate simulation of the EBPR process.     

Ethylene polymerization over MgO‐supported zirconocene catalysts

Supported zirconcene catalysts on a new support, MgO, were prepared and tested in ethylene polymerization. Three types of impregnation methods were employed to find an optimum supporting method for MgO. The direct impregnation of Cp₂ZrCl₂ on MgO showed low metal loading and polymerization activity, while the catalyst had a higher metal loading and polymerization activity when MgO was treated with methylaluminoxane (MAO) before supporting. Treatment of MgO with MAO during the supporting step invoked two types of catalytic sites, which was evidenced by the bimodal molecular weight distribution of the polymer products. MgO is considered to have potential as a support for metallocenes.     

Reducing cycle times in manufacturing and supply chains by input and service rate smoothing

A key performance parameter of a manufacturing network or supply chain is its cycle time; the time that a typical item spends in the network. A previous simulation study on a semiconductor assembly and test facility showed that cycle times could be reduced by having smooth input and service rates. This suggested that there is a “cycle time principle” that, for a system with a specified throughput or input rate, the shortest cycle times are obtained when the input and service rates do not vary over time. We prove that this principle is true for the M/G/1 and M/M/s queueing systems and Jackson networks. The analysis involves establishing several results on the concavity of waiting time probabilities and the convexity of expected waiting times and queue lengths, as functions of input and service rates. These results also have natural uses in other optimization problems.     

Distributed self-stabilizing placement of replicated resources in emerging networks

Emerging large scale distributed networking systems, such as P2P file sharing systems, sensor networks, and ad hoc wireless networks, require replication of content, functionality, or configuration to enact or optimize communication tasks. The placement of these replicated resources can significantly impact performance. We present a novel self-stabilizing, fully distributed, asynchronous, scalable protocol that can be used to place replicated resources such that each node is "close" to some copy of any object. We describe our protocol in the context of a graph with colored nodes, where a node's color indicates the replica/task that it is assigned. Our combination of theoretical results and simulation prove stabilization of the protocol, and evaluate its performance in the context of convergence time, message transmissions, and color distance. Our results show that the protocol generates colorings that are close to the optimal under a set of metrics, making such a protocol ideal for emerging networking systems.     

Effect of light source spectral modulation on wavelength interrogation in fiber Bragg grating sensors and its reduction

In the fiber Bragg grating sensing using a superluminescent diode as the light source and an arrayed waveguide grating as the wavelength interrogator, the wavelength measurement error due to the spectral modulation of the superluminescent diode is theoretically formulated and quantitatively analyzed by computer simulation. It is shown that the wavelength measurement errors produced with the use of real superluminescent diodes are in very good agreement with the theoretical results. In order to reduce the wavelength measurement error due to the spectral modulation of superluminescent diode, two different types of remedies are proposed that utilize the temperature switching of superluminescent diode and that adjust the bandwidths of fiber Bragg grating and arrayed waveguide grating, and their efficacies are experimentally demonstrated together with good quantitative agreement with the theoretical calculation.     

Using classification techniques for informal requirements in the requirements analysis-supporting system

In order to efficiently develop large-scale and complicated software, it is important for system engineers to correctly understand users’ requirements. Most requirements in large-scale projects are collected from various stakeholders located in various regions, and they are generally written in natural language. Therefore, the initial collected requirements must be classified into various topics prior to analysis phases in order to be usable as input in several requirements analysis methods. If this classification process is manually done by analysts, it becomes a time-consuming task. To solve this problem, we propose a new bootstrapping method which can automatically classify requirements sentences into each topic category using only topic words as the representative of the analysts’ views. The proposed method is verified through experiments using two requirements data sets: one written in English and the other in Korean. The significant performances were achieved in the experiments: the 84.28 and 87.91 F1 scores for the English and Korean data sets, respectively. As a result, the proposed method can provide an effective function for an Internet-based requirements analysis-supporting system so as to efficiently gather and analyze requirements from various and distributed stakeholders by using the Internet.