Dragonfly Interaction Algorithm for Optimization of Queuing Delay in Industrial Wireless Networks

In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet loss.Therefore,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless networks.The term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for mating.As a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base station.This includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue delay.These features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue delay.Statistical analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and efficiency.The results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC 2014.Furthermore,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ANOVA.Moreover,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other algorithms.Simulation results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet loss.The proposed algorithm is also evaluated for the conflicting objectives at Pareto Front,and its analysis reveals that DMOA finds a compromising solution between the objectives,thereby optimizing queue delay.In addition,DMOA on the Pareto front delivers much greater performance when it comes to optimizing the queuing delay for industry wireless networks.

A Greedy Traffic Light and Queue Aware Routing Protocol for Urban VANETs

Vehicular Ad-hoc Networks(VANETs) require reliable data dissemination for time-sensitive public safety applications. An efficient routing protocol plays a vital role to achieve satisfactory network performance. It is well known that routing is a challenging problem in VANETs due to the fast-changing network typology caused by high mobility at both ends of transmission. Moreover, under urban environment, there are two non-negligible factors in routing protocol design, the non-uniform vehicle distribution caused by traffic lights, and the network congestion due to high traffic demand in rush hours. In this paper, we propose a greedy traffic light and queue aware routing protocol(GTLQR) which jointly considers the street connectivity, channel quality, relative distance, and queuing delay to alleviate the packet loss caused by vehicle clustering at the intersection and balance the traffic load among vehicles. Through performance evaluation, we show that our proposed protocol outperforms both TLRC and GLSR-L in terms of packet delivery ratio and end-to-end delay.

A software reliability growth model for component-based software incorporating debugging delay and imperfect debugging

In view of the problems and the weaknesses of component-based software （ CBS ） reliability modeling and analysis, and a lack of consideration for real debugging circumstance of integration tes- ting, a CBS reliability process analysis model is proposed incorporating debugging time delay, im- perfect debugging and limited debugging resources. CBS integration testing is formulated as a multi- queue muhichannel and finite server queuing model （MMFSQM） to illustrate fault detection process （FDP） and fault correction process （FCP）. A unified FCP is sketched, given debugging delay, the diversities of faults processing and the limitations of debugging resources. Furthermore, the impacts of imperfect debugging on fault detection and correction are explicitly elaborated, and the expres- sions of the cumulative number of fault detected and corrected are illustrated. Finally, the results of numerical experiments verify the effectiveness and rationality of the proposed model. By comparison, the proposed model is superior to the other models. The proposed model is closer to real CBS testing process and facilitates software engineer＇ s quantitatively analyzing, measuring and predicting CBS reliability. K

同步定时网络相关选源机制探讨

本文就现阶段同步定时网架构下,影响网络选源机制的相关因素及主、从时钟间验证机制进行分析,并适时提出一些解决方案,以便于将来网络规划及设备研制提供借鉴及参考。

Delay Estimates of Mixed Traffic Flow at Signalized Intersections in China

Two characteristics of Chinese mixed traffic invalidate the conventional queuing delay estimates for western countries. First, the driving characteristics of Chinese drivers lead to different delays even though the other conditions are the same. Second, urban traffic flow in China is often hindered by pedestrians at intersections, such that imported intelligent traffic control systems do not work appropriately. Typical delay estimates for Chinese conditions were obtained from data for over 500 vehicle queues in Beijing collected using charge coupled device （CCD） cameras. The results show that the delays mainly depend on the pro- portion and positions of heavy vehicles in the queue, as well as the start-up situations （with or without interference）. A simplified delay estimation model considers vehicle types and positions that compares well with the observed traffic delays.

An Algorithm to Estimate Time Offset between Measurement Devices

This paper analyzes the necessity of the measurement of one-way delay, and it also points out the errors caused by the time offset between measurement devices. Then we propose an algorithm to estimate time offset between measurement devices in network. With the estimated time offset, we can correct our measuring results. Simulation shows the effectiveness of our algorithm.

OPTIMAL AND INCENTIVE COMPATIBLE PRICING FOR HETEROGENEOUS PERIODS

This paper studies a service firm whose business time can be divided into several periods, each providing different value to customers. Heterogeneous service is a major reason resulting in imbalances between supply and demand. Since customers differ in their degree of impatience, firrns can use differential pricing mechanisms to optimize their objectives and match supply with demand in each period, by inducing customers to choose different periods. We study two types of firrns, an internal firm, the objective of which is to maximize the system＇s （including the f＇nan and all the customers） total net value, and a commercial firm, which aims to optimize its own profit. Though impatience factors are customers＇ private information, for each type of firm, we derive the optimal incentive compatible pricing policy, under which all the coming customers will follow the firm＇s assignment, that is, patient customers will buy the service in high-value periods, but their waiting time will be longer, while impatient customers will enter into the low-value periods, but they will be compensated by shorter waiting times. Furthermore, in the internal firm, we also prove that this mechanism enables the decentralization of decisions, while maintaining centralized system-wide optimality. Numerical analysis shows that when there is sufficient capacity, the internal firm does not always need to set lower prices than the commercial firm in every period.