MTSS: multi-path traffic scheduling mechanism based on SDN

Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers.However,the unbalanced workload of cloud data center network easily leads to the network congestion,the low resource utilization rate,the long delay,the low reliability,and the low throughput.In order to improve the utilization efficiency and the quality of services(QoS)of cloud system,especially to solve the problem of network congestion,we propose MTSS,a multi-path traffic scheduling mechanism based on software defined networking(SDN).MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network.A heuristic traffic balancing algorithm is presented for MTSS,which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing.The experimental results show that MTSS outperforms equal-cost multi-path protocol(ECMP),by effectively reducing the packet loss rate and delay.In addition,MTSS improves the utilization efficiency,the reliability and the throughput rate of the cloud data center network.

Review of Key Management Mechanisms in Wireless Sensor Networks

Recent advancements in wireless communication and microchip techniques have accelerated the development of wireless sensor networks (WSN). Key management in WSN is a critical and challenging problem because of the inner characteristics of sensor networks: deployed in hostile environments, limited resource and ad hoc nature. This paper investigates the constraints and special requirements of key management in sensor network environment, and some basic evaluation metrics are introduced. The key pre-distribution scheme is thought as the most suitable solution for key management problem in wireless sensor networks. It can be classified into four classes: pure probabilistic key pre-distribution, polynomial-based, Blom's matrix-based, and deterministic key pre-distribution schemes. In each class of methods, the related research papers are discussed based on the basic evaluation metrics. Finally, the possible research directions in key management are discussed.

The Optimal Control for the Output Feedback Stochastic System at the Risk-Sensitive Cost

The optimal control of the partially observable stochastic system at the risk-sensitive cost is considered in this paper. The system dynamics has a general correlation between system and measurement noise. And the risk-sensitive cost contains a general quadratic term (with cross terms and extra linear terms). The explicit solution of such a problem is presented here using the output feedback control method. This clean and direct derivation enables one to convert such partial observable problems into the equivalent complete observable control problems and use the routine ways to solve them.

A diffusion-weighted imaging based diagnostic system for early detection of prostate cancer

A new framework for early diagnosis of prostate cancer using Diffusion-Weighted Imaging (DWI) is proposed. The proposed diagnostic approach consists of the following four steps to detect locations that are suspicious for prostate cancer: 1) In the first step, we isolate the prostate from the surrounding anatomical structures based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for the shape priori, the spatial interaction, and the current appearance of prostate tissues and its background (surrounding anatomical structures);2) In order to take into account any local deformation between the segmented prostates at different b-values that could occur during the scanning process due to local motion, a non-rigid registration algorithm is employed;3) A KNN-based classifier is used to classify the prostate into benign or malignant based on three appearance features extracted from registered images;and 4) The tumor boundaries are determined using a level set deformable model controlled by the diffusion information and the spatial interactions between the prostate voxels. Preliminary experiments on 28 patients (17 malignant and 11 benign) resulted in 100% correct classification, showing that the proposed method is a promising supplement to current technologies (biopsy-based diagnostic systems) for the early diagnosis of prostate cancer.

A Void Avoidance Scheme for Grid-Based Multipath Routing in Underwater Wireless Sensor Networks

This work proposes a geographic routing protocol for UWSNs based on the construction of a 3D virtual grid structure, called Void-Avoidance Grid-based Multipath Position-based Routing (VA-GMPR). It consists of two main components, the multipath routing scheme and the grid-based void avoidance (GVA) mechanism for handling routing holes. The multipath routing scheme adopts node-disjoint routes from the source to the sink in order to enhance network reliability and load balancing. While the GVA mechanism handles the problem of holes in 3D virtual grid structure based on three techniques: Hole bypass, path diversion, and path backtracking. The performance evaluation of the VA-GMPR protocol was compared to a recently proposed grid-based routing protocol for UWSNs, called Energy-efficient Multipath Geographic Grid-based Routing (EMGGR). The results showed that the VA-GMPR protocol outperformed the EMGGR protocol in terms of packet delivery ratio, and end-to end-delay. However, the results also showed that the VA-GMPR protocol exhibited higher energy consumption compared to EMGGR.

Wisdom of Artificial Crowds—A Metaheuristic Algorithm for Optimization

Finding optimal solutions to NP-Hard problems requires exponential time with respect to the size of the problem. Consequently, heuristic methods are usually utilized to obtain approximate solutions to problems of such difficulty. In this paper, a novel swarm-based nature-inspired metaheuristic algorithm for optimization is proposed. Inspired by human collective intelligence, Wisdom of Artificial Crowds (WoAC) algorithm relies on a group of simulated intelligent agents to arrive at independent solutions aggregated to produce a solution which in many cases is superior to individual solutions of all participating agents. We illustrate superior performance of WoAC by comparing it against another bio-inspired approach, the Genetic Algorithm, on one of the classical NP-Hard problems, the Travelling Salesperson Problem. On average a 3% - 10% improvement in quality of solutions is observed with little computational overhead.

An Artificial Intelligence Based Virtual Assistant Using Conversational Agents

Conversational agents are natural language interaction interfaces designed to simulate human conversations using Artificial Intelligence (AI). This paper explores current applications of these systems and raises the lack of their availability in education. To address this problem, we provide the design of a conversational agent system, which is efficient and time-saving in assisting student/college seeking information about curriculum, scheduling, teachers, classroom location at any time 24/7/365. To verify and validate the design and implementation of our proposed model, a pilot project has been set up involving three leading academic institutions. This platform is designed and developed to help universities provide continuous and instant assistance to their student, staff, and faculty communities.

随机非线性系统二次跟踪型风险灵敏度指标下的满意输出反馈控制设计

在无限时区跟踪型风险灵敏度(risk-sensitive)指标下,研究了一类严格反馈随机非线性系统的满意输出反馈控制问题,所用指标函数为实际中常见的二次型函数,而非为回避控制器设计及闭环系统性能分析的本质困难而采用的四次型函数,对任意给定的风险灵敏度参数和期望指标值,利用积分反推(integrator backstepping)方法构造性地给出了一个输出反馈控制器,使得闭环系统在概率意义下有界,并且风险灵敏度指标不大于所给的期望值。

Design of satisfaction output feedback controls for stochastic nonlinear systems under quadratic tracking risk-sensitive index

In this paper, the design problem of satisfaction output feedback controls for stochastic nonlinear systems in strict feedback form under long-term tracking risk-sensitive index is investigated. The index function adopted here is of quadratic form usually encountered in practice, rather than of quartic one used to beg the essential difficulty on controller design and performance analysis of the closed-loop systems. For any given risk-sensitive parameter and desired index value, by using the integrator backstepping method, an output feedback control is constructively designed so that the closed-loop system is bounded in probability and the risk-sensitive index is upper bounded by the desired value.