Hsin-Hung Cho

Metaheuristics for the deployment of 5G

It is not difficult to anticipate that the system capacity and spectral efficiency of 5G will be greater than those of 4G, and so will the number of network-connected wireless devices. Moreover, the infrastructure of wireless communications today will not meet the requirements of a 5G environment because a large number of traffic flows will be generated between a large number of heterogeneous devices. The deployment strategy is one of the promising solutions to meet the expected demands of 5G. This article begins with a brief review of the deployment problem of wireless communication and a hyperdense deployment problem (HDDP) definition for the requirements of 5G. A simple example for illustrating how a metaheuristic algorithm can be used to solve the HDDP is then given. Finally, some open and possible research issues are discussed to suggest future research trends on this problem.

A Robust Coverage Scheme for UWSNs Using the Spline Function

Wireless sensor technologies have been in development for a long time. Many wireless sensor technology studies have been conducted on improving device performance. Huge technology resources were recently found under the ocean. Previous research methods cannot mapping the underwater environment directly. Underwater wireless sensor networks are being developed for ocean resources deep water exploration. However, little agreement has been reached on an appropriate underwater dedicated distribution model. We focus on accurately depicting 3-D underwater sensor placement based on the coverage issue. Therefore, we design a novel distribution model using the spline function for more accurate underwater wireless sensor placement.

An Efficient Charger Planning Mechanism of WRSN Using Simulated Annealing Algorithm

The limited energy of sensor can be regarded as an optimization problem aimed at finding some useful deployment strategies for a set of chargers, but it typically might spend a lot of computation costs. In order to provide a good solution for reducing a large number of chargers caused by all the sensor nodes need to be covered, add the motor to some particular chargers is an alternative solution. That is why some recent studies attempted to develop the movable charger based algorithms to enhance transmission range. However, most movable charger-based algorithms are the greedy or rule-based algorithms, they will easy fall into local optimum at early iteration and consequently the end results will far away to global optimum. That is why it still has rooms for improvement. This paper will present a simulated annealing-based algorithm to improve the deployment result of wireless sensor network. The simulation results show that the proposed method can reduce the number of chargers significantly for full coverage.

Movable-charger-based planning scheme in wireless rechargeable sensor networks

In order to extend basic functions of wireless sensor network (WSN), many researchers have begun to study rechargeable wireless sensor networks that use of Wireless Charging Technology to supply power for sensor nodes so that the wireless sensor networks have the sustainability. The main classifications of wireless charger antenna are Directional Antenna and Unidirectional Antenna respectively. We combine the advantages of charging antenna and the movable feature via motor to improve the problem that the existing covered area are less but including excessive number of sensors. In this way, we can achieve effective arrangement to cover all target sensor nodes by each chargers. In this paper, we propose a heuristic algorithm called Movable-Charger-based Algorithm (MCBA). It uses overlapping times as a main principle thus we can find out a minimum number of deployed chargers. Finally, the simulation results show that our proposed method can effectively deploys the position of chargers according various status of the factory.

A fair cloud resource allocation using data envelopment analysis

Internet technology is advancing with each passing day, the users demand is also increasing. Of course the users will more concern to quality of service. The vendors must find out a win win method of resource allocation to meet users and itself. Therefore, the resource allocation of cloud computing has become one of hottest topics. In literatures, some researchers have proposed resource allocation methods which include allocation of virtual machines and service classification, etc. However, these methods are based on subjective observations that lead to the overall cloud architecture becomes imbalance. In order to prevent such situation happened, we use the Data Envelopment Analysis (DEA) to solve the imbalance problem. In this paper, our analysis is start from the users requests, and use the DEA to evaluate the whole cloud parameters. Then we can find out the resource allocation policy which is the most suitable between the users and vendors.

Application-oriented offloading in heterogeneous networks for mobile cloud computing

ABSTRACT Nowadays Internet applications have become more complicated that mobile device needs more computing resources for shorter execution time but it is restricted to limited battery capacity. Mobile cloud computing (MCC) is emerged to tackle the finite resource problem of mobile device. MCC offloads the tasks and jobs of mobile devices to cloud and fog environments by using offloading scheme. It is vital to MCC that which task should be offloaded and how to offload efficiently. In the paper, we formulate the offloading problem between mobile device and cloud data center and propose two algorithms based on application-oriented for minimum execution time, i.e. the Minimum Offloading Time for Mobile device (MOTM) algorithm and the Minimum Execution Time for Cloud data center (METC) algorithm. The MOTM algorithm minimizes offloading time by selecting appropriate offloading links based on application categories. The METC algorithm minimizes execution time in cloud data center by selecting virtual and physical machines with corresponding resource requirements of applications. Simulation results show that the proposed mechanism not only minimizes total execution time for mobile devices but also decreases their energy consumption.

Markov-based Emergency Message Reduction Scheme for Roadside Assistance

Currently, almost every family has at least one car; thus, vehicle density is increasing annually. However, road capacity is finite; consequently, traffic accident frequency may increase due to increasing vehicle density. Typically, car accidents result in traffic congestion because vehicles behind the accident are not aware of the event and continue to follow the front queue. To address this problem, some emergency services, such as emergency message broadcasting, have been proposed. However, not all drivers want to receive such messages because they intend to exit the route prior to the accident scene, which means that communication resources may be wasted. In this paper, we propose a prediction model to forecast vehicles behavior based on a Markov chain and identify which vehicles require the emergency message. In addition, the proposed model includes an efficient policy based on the shortest path for police cars and ambulances such that they can attend the accident scene quickly and relieve traffic congestion. Simulation results show that the proposed method reduces unnecessary message transmission and increases road utilization efficiently.

Enhanced SA-based charging algorithm for WRSN

The wireless rechargeable sensor network is a technology to solve lifetime problem for wireless sensor network. Most researches discussed about the outdoor scenario but there are few studies focused on the indoor scenario. Actually, wireless sensor network is very important for the indoor scenario. The reason is that sensors help factory control production for better quality as well as both of disaster relief and prevention are also need to deploy sensors in the indoor scenario. These instances have the concept of sustainable development because sensors cannot be suddenly interrupted so that the expected benefits cannot be realized. As in the example just mentioned, quality of production is no longer to be guaranteed and disaster will not be prevented. That is why the wireless rechargeable sensor network becomes more popular. There are many low cost charger deployment algorithms have been proposed. However, these works almost have opportunity to fall into local optimum. This paper will present a layoff algorithm to combine simulated annealing-based algorithm to achieve optimization for wireless rechargeable sensor network. The simulation results show that the proposed method can reduce the number of chargers efficiently but just need same time with simulated annealing-based algorithm.

SA-Based Multimedia Conversion System for Multi-users Environment

Nowadays multimedia applications surround our life. The relevant technologies of multimedia have been widely used anywhere, e.g. education, medicine, research, transportation and recreation, as long as people who has a mobile device. The computing ability of mobile device is growing rapidly, but it still has its limitations. One of significant influence on most mobile devices is the active time of them depend on the capacity of battery. Multimedia may make battery runs out quickly because it usually carries a large amount of information and data so that it leads to a great quantity of calculation and bandwidth requirement. In order to alleviate the computation amount of mobile devices, we propose an adaptive cloud-based multimedia conversion system to eliminate energy consumption and unnecessary occupancy on bandwidth in accordance with the capability and network state of users’ mobile devices. Then we propose a Simulated Annealing-based algorithm to solve the optimization problem of scheduling for a multi-user environment.

Initialization of Software Defined Wireless Bacteria-Inspired Network Platform

Fifth generation mobile network is a development trend for information and communication industry. In order to meet requirement which presented by some organizations which are working on 5 G standards and regulations, we had proposed a Software-Defined Wireless Bacteria-Inspired Network (SDWBIN) platform. In this paper, we will introduce how we initialize this prospective platform.