分布式系统中基于移动代理的负载均衡模型和负载更新算法的研究

在分布式控制中,结点间的信息交互一般都是通过广播的方式来进行的,占用了大量的网络资源。其次,由于各个结点很难准确地了解整个系统的负载状况及变化,因此很难实现整体的负载均衡。论文首先介绍了基于移动代理的负载均衡结构。通过移动代理良好的移动性、智能性等优点,可以解决传统负载均衡的这些问题。其次,文章分析了传统负载信息更新方法,提出了基于移动代理的ULIMA负载信息更新算法,通过仿真实验证明了该算法的有效性,从而可以较大地提高了负载均衡系统的性能和效率。     

Agent-based artificial immune system approach for adaptive damage detection in monitoring networks

This paper presents an agent-based artificial immune system approach for adaptive damage detection in distributed monitoring networks. The presented approach establishes a new monitoring paradigm by embodying desirable immune attributes, such as adaptation, immune pattern recognition, and self-organization, into monitoring networks. In the artificial immune system-based paradigm, a group of autonomous mobile monitoring agents mimic immune cells (such as B-cells) in the natural immune system, interact locally with monitoring environment, and respond to emerging problems through simulated immune responses. The presented immune-inspired monitoring paradigm has been applied to structural health monitoring. The “antibody” of a mobile monitoring agent is a pattern recognition algorithm tuned to a certain type of structural damage pattern. The mobile monitoring agent performs damage diagnosis based on structural dynamic response data. Mobile monitoring agents communicate with each other and collaborate with network components based on agent interaction protocols defined in agent standards, the Foundation for Intelligent Physical Agents standards. A mobile agent system embedded in sensor nodes supports the selective generation, migration, communication, and management of mobile monitoring agents automatically. The active structural health monitoring is achieved by distributing mobile monitoring agents to the sites where they are needed. The structural damage diagnosis using mobile monitoring agents and artificial immune pattern recognition method has been tested using a scaled steel bridge structure. The test result shows the feasibility of using this approach for real-time structural damage diagnosis.     

一种动态负载均衡机制的研究与实现

高性能集群工作方式越来越受到人们的关注。通常集群是一组通过网络连接的多个异构的计算机系统。在集群工作模式下,一个非常重要的问题就是要确保负载量的均衡。由于目前的负载均衡系统大多只支持同构集群环境,且均衡粒度为作业级,过于粗糙,所以不能很好的适用于并行程序中并行任务的均衡。本文提出了一种并行程序的开发框架,使用移动Agent技术解决任务的动态迁移性,为程序员提供了一个简单的开发接口,大大地简化了他们的工作。系统采用java和Aglet平台开发而成。实验表明,该系统灵活有效。     

基于移动代理的负载平衡策略

在异构计算环境中负载平衡是一个重要问题。移动代理是一种新的分布计算模式,具有许多优势,比如移动代理能够从一台机器移动到另一台机器执行任务。该文提出了一个基于移动代理的并行计算框架,利用一个二段负载平衡策略使程序能够适应不断变化的异构计算环境。实验结果显示移动代理不仅能够用于并行计算,而且能够有效地改善负载平衡。     

移动环境下基于移动代理的应用框架设计

随着网络技术的发展和移动设备的普及，用户希望能随时随地对资源进行访问。但是，由于移动网络连接带宽低且移动单元本身资源贫乏，移动环境为分布应用开发提出了新的挑战。移动代理技术以其节省带宽、异步性等特征，为移动计算提供了良好的解决方案。本文首先讨论了移动代理系统的设计，然后提出一个基于移动代理的移动应用框架
架，最后给出了相应的应用实例。     

Optimal control of mobile monitoring agents in immune-inspired wireless monitoring networks

This paper studies optimal control of mobile monitoring agents in artificial-immune-system-based (AIS-based) monitoring networks. In AIS-based structural health monitoring (SHM) networks, the active structural health monitoring is performed by a group of mobile monitoring agents equipped with damage pattern recognition algorithms. The mobile monitoring agents mimic immune cells in the natural immune system and patrol a structure to detect damage patterns using their receptors (feature vectors), damage pattern recognition algorithms, and the dynamic response data of the structure. The optimal control of mobile monitoring agents includes agent generation and distribution. The generation of mobile monitoring agents is optimized to minimize the response time for the mobile monitoring agents to diagnose structural damage in a sub-network and maximize the average affinity of monitoring agents′ receptors to the damaged sensor data feature vector. The objective functions for distributing mobile monitoring agents are to increase the detection probability and extend network life by balancing energy consumption of sensor nodes in the network. The presented optimization algorithms are developed using multi-objective genetic algorithms. The impact of the algorithm parameters on the performance of the algorithm is also investigated.     

一种基于移动代理的网络管理系统及性能分析

当前所用的网络管理系统大都属于集中式管理模式,因此,在性能、可扩展性、灵活性等方面具有很大的局限性.基于移动代理的网络管理是针对这些不足而提出的具有潜力的解决方案之一,但是要精确地判定在什么条件下移动代理比传统的客户/服务器模式更有效是比较困难的.为此,提出了一个定量模型,从理论上分析和比较了两种结构的流量和响应时间,并就移动代理和SNMP(simple network management protocol)的性能进行了模拟实验比较.理论和实验结果都表明,当被管理的网络设备数在一定范围内时,移动代理的性能比SNMP的性能要好;对于移动代理访问固定数量的设备后再返回到网络管理器这种方案,移动代理的性能有较大的提高.     

Mobile Agent在网络管理中应用

探讨了传统的基于SNMP协议的网络管理系统的不足，分析了集中式网络管理方法的局限性和比较了各种分布式网络管理技术优缺点后，提出了采用移动代理技术(Mobile Agent)来实现网络管理并描述了一种用于设计和开发网络管理系统的移动代理技术的概要性实现框架。文章表明在网络管理中采用移动代理技术可以很好地解决目前集中式网络管理中遇到的相关问题，能有效提高网络管理的可靠性和效率。     

Multi-Agent Coordination by Decentralized Estimation and Control

We describe a framework for the design of collective behaviors for groups of identical mobile agents. The approach is based on decentralized simultaneous estimation and control, where each agent communicates with neighbors and estimates the global performance properties of the swarm needed to make a local control decision. Challenges of the approach include designing a control law with desired convergence properties, assuming each agent has perfect global knowledge; designing an estimator that allows each agent to make correct estimates of the global properties needed to implement the controller; and possibly modifying the controller to recover desired convergence properties when using the estimates of global performance. We apply this framework to the problem of controlling the moment statistics describing the location and shape of a swarm. We derive conditions which guarantee that the formation statistics are driven to desired values, even in the presence of a changing network topology.      

A dynamic resource management in mobile agent by artificial neural network

In this paper, a resource management for dynamic load balancing in mobile agent by artificial neural network scheme (ANN-DLB) is presented to maximize the number of the served tasks in developing high performance cluster. This dynamic load balance with the growth of the service type and user number in the mobile networks of the higher performance is required in service provision and throughput. Most of the conventional policies are used in load indices with the threshold value to decide the load status of the agent hosts by CPU or memory. The main factor influencing the workload is the competitions among the computing resources such as CPU, memory, I/O and network. There are certain I/O data of the intensive applications where load balancing becomes the important issue. This relationship between the computing resources is very complex to define the rules for deciding the workload. This paper proposed a new dynamic load balancing for evaluating the agent hosts’ workload with the artificial neural network (ANN). By applying the automatic learning of the back-propagation network (BPN) model can establish the ANN model and also can measure the agent host loading with five inputs: CPU, memory, I/O, network and run-queue length. The structure of the load balancing system is composed of three design agents: the load index agent (LIA), the resource management agent (RMA) and the load transfer agent (LTA). These experimental results reveal that the proposed ANN-DLB yields better performance than the other methods. These results demonstrate that the proposed method has high throughput, short response time and turnaround time, and less agent host negotiation complexity and migrating tasks than the previous methods.     

Mobile agents in wireless devices

The networks that connect handheld wireless devices such as cell phones and PDAs suffer from low bandwidth and a high incidence of network errors. By employing mobile agents, such devices could provide a reliable technology for message transport over wireless links. Mobile agents are inherently distributed software entities that reduce the load on the network when they move. Mobile agents can be employed in wireless handheld devices in two ways: An agent platform could be installed on the device, enabling mobile agents to run directly on it, or devices could access and use remote mobile agents running on wired networks. Each approach is viable and has its own advantages and domain-specific applications. Some high-end devices would benefit from running a mobile agent platform that lets agents run locally, but this would not be beneficial to others because of processing power and memory constraints or for security reasons.     

基于移动Agent的分布式路由算法研究

移动Agent技术能较好地适应Internet分布式的特点，将其引入网络分布式路由计算领域是对Internet路由系统的革新。本文指出了传统路由算法存在的问题，提出基于移动Agent的分布式路由算法，就路由表的初始化、通信网络中Agent的数量控制、网络链路故障后路由表的更新、后向Agent的消亡等方面进行了讨论，并进行了仿真实验和性能分析。     

A Direct Execution Approach to Simulating Mobile Agent Algorithms

Mobile agent technology has been applied to develop the solutions for various kinds of parallel and distributed computing problems. However, performance evaluation of mobile agent algorithms remains a difficult task, mainly due to the characteristics of mobile agents such as distributed and asynchronous execution, autonomy and mobility. This paper proposes a general approach based on direct execution simulation for evaluating the performance of mobile agent algorithms by collecting and analyzing the information about the agents during their execution. We describe the proposed generic simulation model, named MADES, the architecture of a software environment based on MADES, and a prototype implementation. A mobile agent-based distributed load balancing algorithm has been used for experiments with the prototype.     

Locality-sensitive task allocation and load balancing in networked multiagent systems: Talent versus centrality

With the development of large scale multiagent systems, agents are always organized in network structures where each agent interacts only with its immediate neighbors in the network. Coordination among networked agents is a critical issue which mainly includes two aspects: task allocation and load balancing; in traditional approach, the resources of agents are crucial to their abilities to get tasks, which is called talent-based allocation. However, in networked multiagent systems, the tasks may spend so much communication costs among agents that are sensitive to the agent localities; thus this paper presents a novel idea for task allocation and load balancing in networked multiagent systems, which takes into account both the talents and centralities of agents. This paper first investigates the comparison between talent-based task allocation and centrality-based one; then, it explores the load balancing of such two approaches in task allocation. The experiment results show that the centrality-based method can reduce the communication costs for single task more effectively than the talent-based one, but the talent-based method can generally obtain better load balancing performance for parallel tasks than the centrality-based one.     

一种平衡负载的分布式动态型微移动管理方案

目前微移动管理方案大多是采用分层的原则,在子域外设置一个外地管理代理（FMA）作为区域代理。移动主机（MH）在域内进行移动时只需向FMA进行注册,而对家乡代理（HA）透明。为了弥补MH数量过多而导致的FMA负载过大的缺陷,提出了一种平衡负载的分布式动态型微移动管理方案。该方案在网络中放置多个区域移动代理来实现分布式的域内主机移动管理,并采用一种由网络根据自身的负载情况动态地选择区域移动代理的算法。该算法有效避免了传统方案中FMA在MH数量过多时负载过大的问题,且没有对网络拓扑结构和区域移动代理的位置做任何强制性要求。分析和仿真均表明,当主机数量快速递增时网络的负载平衡状况得到了改善。     

Mobile agent-enabled framework for structuring and building distributed systems on the internet

Mobile agent has shown its promise as a powerful means to complement and enhance existing technology in various application areas. In particular, existing work has demonstrated that MA can simplify the development and improve the performance of certain classes of distributed applications, especially for those running on a wide-area, heterogeneous, and dynamic networking environment like the Internet. In our previous work, we extended the application of MA to the design of distributed control functions, which require the maintenance of logical relationship among and/or coordination of proc- essing entities in a distributed system. A novel framework is presented for structuring and building distributed systems, which use cooperating mobile agents as an aid to carry out coordination and cooperation tasks in distributed systems. The framework has been used for designing various distributed control functions such as load balancing and mutual ex- clusion in our previous work. In this paper, we use the framework to propose a novel ap- proach to detecting deadlocks in distributed system by using mobile agents, which dem- onstrates the advantage of being adaptive and flexible of mobile agents. We first describe the MAEDD (Mobile Agent Enabled Deadlock Detection) scheme, in which mobile agents are dispatched to collect and analyze deadlock information distributed across the network sites and, based on the analysis, to detect and resolve deadlocks. Then the design of an adaptive hybrid algorithm derived from the framework is presented. The algorithm can dynamically adapt itself to the changes in system state by using different deadlock detec- tion strategies. The performance of the proposed algorithm has been evaluated using simulations. The results show that the algorithm can outperform existing algorithms that use a fixed deadlock detection strategy.     

Mobile crowdsensing with mobile agents

We introduce mobile agents for mobile crowdsensing. Crowdsensing campaigns are designed through different roles that are implemented as mobile agents. The role-based tasks of mobile agents include collecting data, analyzing data and sharing data in the campaign. Mobile agents execute and control the campaign autonomously as a multi-agent system and migrate in the opportunistic network of participants’ devices. Mobile agents take into account the available resources in the devices and match participants’ privacy requirements to the campaign requirements. Sharing of task results in real-time facilitates cooperation towards the campaign goal while maintaining a selected global measure, such as energy efficiency. We discuss current challenges in crowdsensing and propose mobile agent based solutions for campaign execution and monitoring, addressing data collection and participant-related issues. We present a software framework for mobile agents-based crowdsensing that is seamlessly integrated into the Web. A set of simulations are conducted to compare mobile agent-based campaigns with existing crowdsensing approaches. We implemented and evaluated a small-scale real-world mobile agent based campaign for pedestrian flock detection. The simulation and evaluation results show that mobile agent based campaigns produce comparable results with less energy consumption when the number of agents is relatively small and enables in-network data processing with sharing of data and task results with insignificant overhead.     

基于Honeyd的星型结构分布式系统压力测试框架的设计与实现

星型结构分布式系统的集中节点容易成为负载的瓶颈,鉴于此,提出一种基于Honeyd实现的星型结构分布式系统压力测试框架:借助Honeyd建立虚拟网络来模拟系统工作节点的硬件环境,并且开发基于虚拟网络的简单网络服务,取代在物理机器上运行真实服务的测试过程.分别使用传统的性能测试工具和基于Honeyd的压力框架在典型的星型结构分布式系统上实施了压力测试,实验证明了该方法的可行性、准确性和效率.     

一种基于智能移动代理的网络故障检测系统

随着网络规模的急剧扩大和结构的日趋复杂化,网络故障管理越来越重要.在一个复杂的通信网络中,故障是不可避免的,但是对故障的及时探测和识别对于提高网络的可靠性是非常重要的.监测数据包是网络故障检测中常用的方法,但是在大规模网络中会产生巨量的数据包.为此,人们提出了几种方法.但是这些方法都是建立在集中式管理体系结构之上的,因而没有良好的可扩展性、灵活性和本地处理能力.针对这些问题,提出了一种基于智能移动代理的网络故障检测系统结构,并用Java和aglet实现.实验表明,这种系统结构对于网络故障的检测是非常有效的     

Mobile Agent-Based Performance Management for the Virtual Home Environment

Virtual Home Environment (VHE) encompasses the deployment and management of adaptable services that retain any personalized service aspects, irrespective of terminal, network' and geographic location. We assert that the dynamic nature of the VHE requires management capabilities that can be suitably provided through the use of mobile agent technology. We examine four different engineering solutions for the realization of a VHE performance management component that allows service adaptation in relation to the available network Quality-of-Service (QoS). The mobile agent approach is compared with competing technologies in order to identify the benefits of this novel application of mobile agents, discuss its drawbacks' and finally focus on the lessons learned from our prototype system. Although mobile agents are typically associated with increased performance costs, it is through agent migration that we were able to address the VHE requirements of universality, dynamic programmability, and network technology independence.