Ant with Artificial Bee Colony Techniques in Vehicular Ad-hoc Networks

A VANET faces many problems due to dynamic changing of networks with certain requirements such as low delay, high (PDR) packet delivery ratio, low routing overhead and throughput. However, numerous routing protocols have been suggested to meet the demands of Quality of Service (QoS), but none of them can consistently maintain the highest level of QoS simultaneously. The proposed method Ant with Artificial Bee Colony Techniques provides better performance when compared to the existing techniques. This work is compared with latest developed Techniques in VANET to find the best path and different performance metrics are used to check the performance. This work premeditated the comparative analysis of Quality of services made by the performance of latest emerging techniques in VANET and will provide the best solution for the recognition problem in finding the best path based on the evaluation of performance of Quality of Service. Simulation results imply the benefits of the proposed Ant with Artificial Bee Colony Techniques (AABC) produces better result when compare to the other conventional method and Ant Colony Techniques(ACT)in terms of high packet delivery ratio, less end-to-end delay and less energy consumption level. The performance is evaluated by using Ns2 simulator and results shows that the AABC successfully achieve the optimal routes

Study on the predictions of gene function and protein structure using multi-SVM and hybrid EDA

制度:新 ; 報告番号:甲3199号 ; 学位の種類:博士(工学) ; 授与年月日:2011/3/15 ; 早大学位記番号:新549

Task Scheduling Using Hamming Particle Swarm Optimization in Distributed Systems

An efficient allocation of tasks to the processors is a crucial problem in heterogeneous computing systems. Finding an optimal schedule for such an environment is an NP-complete problem. Near optimal solutions are obtained within a finite duration using heuristics/meta-heuristics are used instead of exact optimization methods. Heuristics and meta-heuristics are the efficient technologies for scheduling tasks in distributed environment because of their ability to deliver high quality solutions in a reasonable time. Discrete Particle Swarm Optimization (DPSO) is a newly developed meta-heuristic computation technique. To enhance the final accuracy and improve the convergence speed of DPSO, this paper presents a modified DPSO algorithm by adjusting its inertia weight based on Hamming distance and also makes a dependency between the two random parameters r_1 and r_2 to control the balance of individual's and collective information in the velocity updating equation. Three criteria such as make span, mean flow time and reliability cost are used to assess the efficiency of the proposed DPSO algorithm for scheduling independent tasks on heterogeneous computing systems. Computational simulations are performed based on a set of benchmark instances to evaluate the performance of the proposed DPSO algorithm compared to existing methods

DEVELOPING A PERFORMANCE IMPORTANCE MATRIX FOR A PUBLIC SECTOR BUS TRANSPORT COMPANY: A CASE STUDY

This paper presents a study of comparison of the importance attached by the service providers’ and the customers’ with respect to eighteen service characteristics towards the public transportation services provided by a bus company. The survey was conducted in three bus depots in one division of a state road transport undertaking (SRTU) in south India. The importance the SRTU and the customers attach to these characteristics indicates significant differences. This reveals the existence of a gap between customers’ expectations and the service provided by the company. Finally the customer retention and customer development criteria have been. identified.Performance importance matrix, Customer expectations, Public bus transport, Radar chart.

Профессору В. Г. Спицыну - 65 лет

6 января 2013 г. исполнилось 65 лет со дня рождения профессора ТПУ, доктора технических наук, профессора Владимира Григорьевича Спицына

A Statistical Approach to Adaptive Playout Scheduling in Voice Over Internet Protocol Communication

Factors like network delay, latency and bandwidth significantly affect the quality of communication using Voice over Internet Protocol. The use of jitter buffer at the receiving end compensates the effect of varying network delay up to some extent. But the extra buffer delay given for each packet plays a major role in playing late packets and thereby improving voice quality. As the buffer delay increases packet loss rate decreases, which in general is a very good sign. However, an increase of buffer delay beyond a certain limit affects the interactive quality of voice communication. In this paper, we propose a statistical framework for adaptive playout scheduling of voice packets based on network statistics, packet loss rate and availability of packets in the buffer. Experimental results show that the proposed model allocates optimal buffer delay with the lowest packet loss rate when compared with other algorithms

Prediction model of rough rolling force based on CUCKOO-RANDOM FOREST algorithm

In order to improve the prediction accuracy of the roughing force prediction model, a cuckoo-random forest algorithm is proposed in this paper to quickly solve the set value of rolling force based on the standard random forest algorithm. The experimental results show that the prediction accuracy of the cuckoo-random forest algorithm is higher than that of traditional models, and it can effectively predict the set value of rough rolling force