Void avoidance opportunistic routing density rank based for underwater sensor networks

Currently, the Underwater Sensor Networks (UWSNs) is mainly an attractive area due to its technological ability to gather valuable data from underwater environments such as tsunami monitoring sensors, military tactical applications, and environmental monitoring. However, UWSNs are suffering from limited energy, high packet loss, and the use of acoustic communication which have very limited bandwidth and slow transmission. In UWSNs, the energy consumption used is 125 times more during the forwarding of the packet data from source to destination as compare to during receiving data. For this reason, many researchers are keen to design an energy-efficient routing protocol to minimize the energy consumption in UWSNs while at the same time provide adequate packet delivery ratio and less cumulative delay. As such, the opportunistic routing (OR) is the most promising method to be used in UWSNs due to its unique characteristics such as high path loss, dynamic topology, high energy consumption, and high propagation delay. However, the OR algorithm had also suffered from as higher traffic load for selection next forwarding nodes in the progression area, which suppressed the redundant forwarding packet and caused communication void. There are three new proposed algorithms introduced to address all three issues which resulted from using the OR approach in UWSNs. Firstly, the higher traffic load for selection next forwarding nodes in the problematic progression area problem was addressed by using the Opportunistic Routing Density Based (ORDB) algorithm to minimize the traffic load by introducing a beaconless routing to update the neighbor node information protocol. Secondly, the algorithm Opportunistic Routing Density Rank Based (ORDRB) was developed to deal with redundant packet forwarding by introducing a new method to reduce the redundant packet forwarding while in dense or sparse conditions to improve the energy consumption effectively. Finally, the algorithm Void Avoidance Opportunistic Routing Density Rank Based (ORDRB) was developed to deal with the communication void by introducing a simple method to detect a void node and avoid it during the forwarding process. Simulation results showed that ORDB has improved the network performance in terms of energy tax average (25%, 40%), packet delivery ratio (43%, 23%), and cumulative delay (67%, -42%) compared to DBR and UWFlooding routing protocols. While for ORDRB, the network performance improved in terms of energy tax average (0.9%, 53%, 62%), packet delivery ratio (100%, 83%, 58%) and cumulative delay (-270%, -94%, 55%) compared to WDFAD-DBR, DBR and UWFlooding. Lastly, for VAORDRB, the network performance improved in terms of energy tax average (3%, 8%), packet delivery ratio (167%, 261%), and cumulative delay (68%, 57%) compared to EVA-DBR and WDFAD-DBR. Based on the findings of this study, the protocol VAORDRB is a suitable total solution to reduce the cumulative delay and increase the packet delivery ratio in sparse and dense network deployment

Review on energy efficient opportunistic routing protocol for underwater wireless sensor networks

Currently, the Underwater Sensor Networks (UWSNs) is mainly an interesting area due to its ability to provide a technology to gather many valuable data from underwater environment such as tsunami monitoring sensor, military tactical application, environmental monitoring and many more. However, UWSNs is suffering from limited energy, high packet loss and the use of acoustic communication. In UWSNs most of the energy consumption is used during the forwarding of packet data from the source to the destination. Therefore, many researchers are eager to design energy efficient routing protocol to minimize energy consumption in UWSNs. As the opportunistic routing (OR) is the most promising method to be used in UWSNs, this paper focuses on the existing proposed energy efficient OR protocol in UWSNs. This paper reviews the existing proposed energy efficient OR protocol, classifying them into 3 categories namely sender-side-based, receiver-side-based and hybrid. Furthermore each of the protocols is reviewed in detail, and its advantages and disadvantages are discussed. Finally, we discuss potential future work research directions in UWSNs, especially for energy efficient OR protocol design

Evaluation of the performance of underwater wireless sensor networks routing protocols under high-density network

Nowadays, research and development of Underwater Wireless Sensor Networks (UWSNs) widely supporting various available application such as oil/gas monitoring system, tsunami monitoring, disaster prevention, and environmental monitoring has become increasingly popular among academicians and industries. However, to develop efficient communication in UWSNs is a difficult duty due to the irregular nature of the underwater environment. In our previous review [14], we did an elaborate theoretical survey on UWSNs routing protocols. In this work, we are going to evaluate the performance of some of the UWSNs routing protocols under high-density network condition. To simulate a high-density UWSNs, we are placing hundreds of underwater nodes in a small three-dimensional topographical area and study the behavior of the routing protocol and the network. We have chosen to evaluate some of the frequently addressed underwater routing protocols such as Underwater Flooding (UWFlooding), Vector-Based Forwarding (VBF), and Hop by Hop Vector-Based Forwarding (HH-VBF) under this high-density network scenarios. The result of our study shows that VBF and HH-VBF perform better in term of the number of packets received, dropped packets and PDR, while UWFlooding performs better in term of cumulative delay

PLC design for automatic power transfer of 11kv switchgear

An Automated Transfer System (ATS) is to provide automatic power transfers to groups reloading loads from common sources, such as utility services, to alternative sources, such as standby generation, in the event of a normal source failure. The project aims to develop a new design of an automatic power transfer system for the 11kV switchgear. Using the basic building blocks of utility power, system topology, on-site generation, and uninterrupted power supply, the basic role of the automatic transfer system can now be determined. In this role, the Automatic Transfer System (ATS) must achieve two goals. First, the system must be stable where it should operate, even under abnormal power systems, without human intervention. Equally important, it must be able to distinguish when the system conditions do not guarantee transfer to alternate sources. Second, it must be able to control the switchgear as required and, in addition, be able to deliver accurate signal to the required alternative power sources (for example, to initiate start signal to the generator as soon as possible)

Artificial Bee Colony algorithm in estimating kinetic parameters for yeast fermentation pathway

Analyzing metabolic pathways in systems biology requires accurate kinetic parameters that represent the simulated in vivo processes. Simulation of the fermentation pathway in the Saccharomyces cerevisiae kinetic model help saves much time in the optimization process. Fitting the simulated model into the experimental data is categorized under the parameter estimation problem. Parameter estimation is conducted to obtain the optimal values for parameters related to the fermentation process. This step is essential because insufficient identification of model parameters can cause erroneous conclusions. The kinetic parameters cannot be measured directly. Therefore, they must be estimated from the experimental data either in vitro or in vivo. Parameter estimation is a challenging task in the biological process due to the complexity and nonlinearity of the model. Therefore, we propose the Artificial Bee Colony algorithm (ABC) to estimate the parameters in the fermentation pathway of S. cerevisiae to obtain more accurate values. A metabolite with a total of six parameters is involved in this article. The experimental results show that ABC outperforms other estimation algorithms and gives more accurate kinetic parameter values for the simulated model. Most of the estimated kinetic parameter values obtained from the proposed algorithm are the closest to the experimental data

Comparison of Optimization-Modelling Methods for Metabolites Production in Escherichia coli

The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite’s production. Therefore, through constraint-based modelling, various metaheuristic algorithms have been improvised to optimize the desired phenotypes. In this paper, PSOMOMA was compared with CSMOMA and ABCMOMA for maximizing the production of succinic acid in E. coli. Furthermore, the results obtained from PSOMOMA were validated with results from the wet lab experiment

A hybrid of particle swarm optimization and minimization of metabolic adjustment for ethanol production of escherichia coli

Ethanol is a chemical-colourless compound that widely used in pharmaceutical, medicines, food products, and industrial applications. As the demand for ethanol is rising recently, attention has been given on metabolic engineering of Escherichia coli (E.coli) to enhance its production through alteration of its genetic content. This research mainly aimed to optimize ethanol production in E.coli using a gene knockout strategy. Several gene knockout strategies like OptKnock and OptGene have been proposed previously. However, most of them suffer from premature convergence. Hence, a hybrid of Particle Swarm Optimization (PSO) and Minimization of Metabolic Adjustment (MOMA) algorithm is proposed to identify the list of gene knockouts in maximizing the ethanol production and growth rate of E.coli. Experiment results show that the hybrid method is comparable with two state-of-the-art methods in term of growth rate and production

Comparison of Optimization-Modelling Methods for Metabolites Production in Escherichia coli

The metabolic network is the reconstruction of the metabolic pathway of an organism that is used to represent the interaction between enzymes and metabolites in genome level. Meanwhile, metabolic engineering is a process that modifies the metabolic network of a cell to increase the production of metabolites. However, the metabolic networks are too complex that cause problem in identifying near-optimal knockout genes/reactions for maximizing the metabolite’s production. Therefore, through constraint-based modelling, various metaheuristic algorithms have been improvised to optimize the desired phenotypes. In this paper, PSOMOMA was compared with CSMOMA and ABCMOMA for maximizing the production of succinic acid in E. coli. Furthermore, the results obtained from PSOMOMA were validated with results from the wet lab experiment