The Hopfield-Tank neural network applied to the mobile agent planning problem

Mobile agent planning (MAP) is increasingly viewed as an important technique of information retrieval systems to provide location aware services of minimum cost in mobile computing environment. Although Hopfield-Tank neural network has been proposed for solving the traveling salesperson problem, little attention has been paid to the time constraints on resource validity for optimizing the cost of the mobile agent. Consequently, we modify Hopfield-Tank neural network and design a new energy function to not only cope with the dynamic temporal features of the computing environment, in particular the server performance and network latency when scheduling mobile agents, but also satisfy the location-based constraints such as the starting and end node of the routing sequence must be the home site of the traveling mobile agent. In addition, the energy function is reformulated into a Lyapunov function to guarantee the convergent stable state and existence of the valid solution. Moreover, the objective function is derived to estimate the completion time of the valid solutions and predict the optimal routing path. Simulations study was conducted to evaluate the proposed model and algorithm for different time variables and various coefficient values of the energy function. The experimental results quantitatively demonstrate the computational power and speed of the proposed model by producing solutions that are very close to the minimum costs of the location-based and time-constrained distributed MAP problem rapidly. The spatio-temporal technique proposed in this work is an innovative approach in providing knowledge applicable to improving the effectiveness of solving optimization problems.     

Hybrid information retrieval policies based on cooperative cache in mobile P2P networks

The concept of Peer-to-Peer (P2P) has been introduced into mobile networks, which has led to the emergence of mobile P2P networks, and originated potential applications in many fields. However,mobile P2P networks are subject to the limitations of transmission range, and highly dynamic and unpredictable network topology, giving rise to many new challenges for efficient information retrieval. In this paper, we propose an automatic and economical hybrid information retrieval approach based on cooperative cache. In this method, the region covered by a mobile P2P network is partitioned into subregions, each of which is identified by a unique ID and known to all peers. All the subregions then constitute a mobile Kademlia (MKad) network. The proposed hybrid retrieval approach aims to utilize the floodingbased and Distributed Hash Table (DHT)-based schemes in MKad for indexing and searching according to the designed utility functions. To further facilitate information retrieval, we present an effective cache update method by considering all relevant factors. At the same time, the combination of two different methods for cache update is also introduced. One of them is pull based on time stamp including two different pulls: an on-demand pull and a periodical pull, and the other is a push strategy using update records. Furthermore, we provide detailed mathematical analysis on the cache hit ratio of our approach. Simulation experiments in NS-2 showed that the proposed approach is more accurate and efficient than the existing methods.     

Hybrid information retrieval policies based on cooperative cache in mobile P2P networks

The concept of Peer-to-Peer (P2P) has been introduced into mobile networks, which has led to the emergence of mobile P2P networks, and originated potential applications in many fields. However,mobile P2P networks are subject to the limitations of transmission range, and highly dynamic and unpredictable network topology, giving rise to many new challenges for efficient information retrieval. In this paper, we propose an automatic and economical hybrid information retrieval approach based on cooperative cache. In this method, the region covered by a mobile P2P network is partitioned into subregions, each of which is identified by a unique ID and known to all peers. All the subregions then constitute a mobile Kademlia (MKad) network. The proposed hybrid retrieval approach aims to utilize the floodingbased and Distributed Hash Table (DHT)-based schemes in MKad for indexing and searching according to the designed utility functions. To further facilitate information retrieval, we present an effective cache update method by considering all relevant factors. At the same time, the combination of two different methods for cache update is also introduced. One of them is pull based on time stamp including two different pulls: an on-demand pull and a periodical pull, and the other is a push strategy using update records. Furthermore, we provide detailed mathematical analysis on the cache hit ratio of our approach. Simulation experiments in NS-2 showed that the proposed approach is more accurate and efficient than the existing methods.     

Agents for information retrieval: Issues of mobility and coordination

This paper focuses on agent-based applications for information retrieval on the Web, by specifically analysing mobility and coordination issues. On the one hand, mobile agents well suit the requirements of information retrieval in the new dynamic scenario derived from the Internet. This is due to their capability of moving to the place where the information is stored – therefore saving bandwidth – and to their robustness in the presence of unreliable connections. On the other hand, the search for information by several mobile active agents calls for suitable models to rule the interactions among agents and between agents and execution environments. The paper surveys different coordination approaches and evaluates their impact in information retrieval applications based on mobile agents. The survey outlines the advantages of uncoupled coordination models and points out the suitability of a coordination model based on reactive and programmable tuple spaces: they may increase the safety and the security of the environment while simplifying the task of programming distributed mobile agent applications.     

MAP: Design and implementation of a mobile agents' platform

The recent development of telecommunication networks has contributed to the success of applications such as information retrieval and electronic commerce, as well as all the services that take advantage of communication in distributed systems. In this area, the emerging technology of mobile agents aroused considerable interest. Mobile agents are applications that can move through the network for carrying out a given task on behalf of the user. In this work we present a platform called MAP (Mobile Agents Platform) for the development and the management of mobile agents. The language used both for developing the platform and for carrying out the agents is Java. The platform gives the user all the basic tools needed for creating some applications based on the use of agents. It enables us to create, run, suspend, resume, deactivate, reactivate local agents, to stop their execution, to make them communicate each other and migrate.     

A performance comparison of mobility anchor point selection schemes in Hierarchical Mobile IPv6 networks

Hierarchical Mobile IPv6 (HMIPv6) introduces a mobility anchor point (MAP) that localizes the signaling traffic and hence reduces the handoff latency. In addition to processing binding update messages from mobile nodes (MNs) on behalf of MNs’ home agents (HAs), the MAP performs data traffic tunneling destined to or originated from MNs, both of which will burden the MAP substantially as the network size grows. To provide scalable and robust mobile Internet services to a large number of visiting MNs, multiple MAPs will be deployed. In such an environment, how to select an appropriate MAP has a vital effect on the overall network performance. In this paper, we choose four MAP selection schemes: the furthest MAP selection scheme, the nearest MAP selection scheme, the mobility-based MAP selection scheme, and the adaptive MAP selection scheme. Then, we compare their performances quantitatively in terms of signaling overhead and load balancing. It can be shown that the dynamic schemes (i.e., the mobility-based and the adaptive MAP selection schemes) are better than the static schemes (i.e., the furthest and the nearest MAP selection schemes), since the dynamic schemes can select the serving MAP depending on the MN’s characteristics, e.g., mobility and session activity. In addition, the adaptive MAP selection scheme achieves low implementation overhead and better load balancing compared with the mobility-based MAP selection scheme.     

基于校园环境的移动P2P网络体系研究与设计

由于P2P技术的广泛应用以及无线网络和移动设备的普及,人们提出了基于无线网络的移动P2P网络。文中通过分析移动P2P网络的特点和已有的网络模型,结合校园网络环境的特点,设计出基于校园环境的网络体系结构模型,并对模型的资源查找进行详细的描述。模型被划分成三层结构,底层的网络采用改进后的Kelips路由算法通信,该算法的路由复杂度是一个常数,有效减少资源查找时间,保证节点维护状态信息的实时性和正确性;由超级节点组成的中间层,实行分布式管理,采取泛洪搜索算法来通信;顶层是一些域内中心节点,负责连接外网和解决网络的安全问题。仿真实验表明：该模型能够更好地减少资源查找时间,即使大量节点失效,也可以快速检测到节点间关系变化并进行管理。     

具有负载均衡和蚁群优化的移动P2P路由策略

分析了移动P2P网络的移动节点设备资源更加短缺,网络更加动态多变,建立健壮的路由策略是非常重要的。通过研究移动P2P网络的特征,从路由发现、路由选择、路由保持三个方面入手,提出了一种新的具有负载均衡和蚁群优化的路由策略。利用蚁群算法理论来指导移动agent的全局搜索的路由发现工作,并且结合通用的能量消耗公式计算得到的节点剩余能量和节点业务执行等候队列长度来优化路由选择工作。从仿真实验可以看到,该路由策略在平均端到端的延迟、路由控制负载方面具有性能优势。同时,节约了节点的能量,延长了节点在网络中的生存时间。     

基于服务器集群的云检索系统的研究与示范

在研究云计算及移动搜索引擎的基础上,依据当前技术发展,提出了基于服务器集群的云检索系统模型,该模型由云信息层、云检索集群系统和用户查询框组成.对云检索集群系统中数据存储技术进行了深入研究,提出了分布式云检索数据存储方案.为了提高云检索执行效率,提出了以程序流为核心的云检索软件执行模式.该模型的测试结果表明,系统功能能正确实现,性能表现较好且稳定.通过该模型的示范,给海量信息检索技术提供了拓展思维的方案.     

Fast retrieval of high-dimensional feature vectors in P2P networks using compact peer data summaries

The retrieval facilities of most peer-to-peer (P2P) systems are limited to queries based on a unique identifier or a small set of keywords. The techniques used for this purpose are hardly applicable for content based image retrieval (CBIR) in a P2P network. Furthermore, we will argue that the curse of dimensionality and the high communication overhead prevent the adaptation of multidimensional search trees or fast sequential scan techniques for P2P CBIR. In the present paper we will propose two compact data representations that can be distributed in a P2P network and used as the basis for a source selection. This allows for communicating with only a small fraction of all peers during query processing without deteriorating the result quality significantly. We will also present experimental results confirming our approach.     

Dynamic partner identification in mobile agent-based distributed job workflow execution

This paper is concerned with the design, implementation, and evaluation of algorithms for communication partner identification in mobile agent-based distributed job workflow execution. We first describe a framework for distributed job workflow execution over the Grid: the Mobile Code Collaboration Framework (MCCF). Based on the study of agent communications during a job workflow execution on MCCF, we identify the unnecessary agent communications that degrade the system performance. Then, we design a novel subjob grouping algorithm for preprocessing the job workflow's static specification in MCCF. The obtained information is used in both static and dynamic algorithms to identify partners for agent communication. The mobile agent dynamic location and communication based on this approach is expected to reduce the agent communication overhead by removing unnecessary communication partners during the dynamic job workflow execution. The proof of the dynamic algorithm's correctness and effectiveness are elaborated. Finally, the algorithms are evaluated through a comparison study using simulated job workflows executed on a prototype implementation of the MCCF on a LAN environment and an emulated WAN setup. The results show the scalability and efficiency of the algorithms as well as the advantages of the dynamic algorithm over the static one.     

Towards a hybrid load balancing policy in grid computing system

Grid computing has become conventional in distributed systems due to technological advancements and network popularity. Grid computing facilitates distributed applications by integrating available idle network computing resources into formidable computing power. As a result, by using efficient integration and sharing of resources, this enables abundant computing resources to solve complicated problems that a single machine cannot manage. However, grid computing mines resources from accessible idle nodes and node accessibility varies with time. A node that is currently idle, may become occupied within a second of time and then be unavailable to provide resources. Accordingly, node selection must provide effective and sufficient resources over a long period to allow load assignment. This study proposes a hybrid load balancing policy to integrate static and dynamic load balancing technologies. Essentially, a static load balancing policy is applied to select effective and suitable node sets. This will lower the unbalanced load probability caused by assigning tasks to ineffective nodes. When a node reveals the possible inability to continue providing resources, the dynamic load balancing policy will determine whether the node in question is ineffective to provide load assignment. The system will then obtain a new replacement node within a short time, to maintain system execution performance.     

基于P2P的分布式软件构件库检索机制

为了更好地实现分布式构件库之间的信息共享与交互,使复用者更加便利地在多库中进行构件查找、提高查准率,提出一种基于P2P的分布式软件构件库检索机制。采用分层混合对等网络体系结构,其中的超级节点可以自动地对检索条件进行重构,从而使复用者可以透明地在多库中进行检索。该机制可以有效提高分布式构件库间的信息共享性,以及检索的便捷性与有效性。     

基于非结构化的P2P信息检索关键技术研究

如何在缺少集中控制、大规模、分布式的P2P（peer-to-peer）网络中找到并定位信息是所有的P2P共享系统面临的一个难题．现有的P2P信息检索机制存在着种种不足：基于结构化P2P网络的检索效率很高,然而由于构造过于严格,难以在Internet上普及,而且仅能支持粗粒度的文件共享;非结构化P2P网络实现简单,是P2P共享系统的主要实现方式,但是由于搜索的盲目性,其检索效率又普遍低下．建立了一个新的非结构化P2P共享原型系统．该系统利用改进的蚁群算法进行检索路由,使检索总是倾向于有利的方向．同时,有针对性的推荐服务能够减少盲目搜索,提高文件共享水平．仿真实验的结果表明,该系统所采用的信息检索与信息推荐相结合的策略能够有效地提高P2P信息检索的成功率,降低网络负载．     

WSN in cyber physical systems: Enhanced energy management routing approach using software agents

Recently, the cyber physical system has emerged as a promising direction to enrich the interactions between physical and virtual worlds. Meanwhile, a lot of research is dedicated to wireless sensor networks as an integral part of cyber physical systems. A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices that use sensors to monitor physical or environmental conditions. These autonomous devices, or nodes, combine with routers and a gateway to create a typical WSN system. Shrinking size and increasing deployment density of wireless sensor nodes implies the smaller equipped battery size. This means emerging wireless sensor nodes must compete for efficient energy utilization to increase the WSN lifetime. The network lifetime is defined as the time duration until the first sensor node in a network fails due to battery depletion. One solution for enhancing the lifetime of WSN is to utilize mobile agents. In this paper, we propose an agent-based approach that performs data processing and data aggregation decisions locally i.e., at nodes rather than bringing data back to a central processor (sink). Our proposed approach increases the network lifetime by generating an optimal routing path for mobile agents to transverse the network. The proposed approach consists of two phases. In the first phase, Dijkstra’s algorithm is used to generate a complete graph to connect all source nodes in a WSN. In the second phase, a genetic algorithm is used to generate the best-approximated route for mobile agents in a radio harsh environment to route the sensory data to the base-station. To demonstrate the feasibility of our approach, a formal analysis and experimental results are presented.     

基于智能搜索的坦克机动任务规划

在未来高技术局部战争条件下,坦克不得不面临一个动态复杂的战场环境,这就要求坦克能根据战场环境实时地进行任务规划。以单辆坦克在陆地上的自主机动为背景,提出了一种基于智能搜索的坦克机动任务规划方法。在机动任务规划的实施方面,重点描述了两个基本方面：坦克机动环境的评估及坦克机动任务规划的自主实现。构造了一种智能搜索方法,同时应用这种方法提出了实现坦克自主机动的基本思路,并编制应用程序,进行实例检验。结果表明,这种方法科学合理,为坦克机动任务的规划提供了新思路。神经网络评估方法具有普遍意义,能推广应用于坦克其它方面的任务规划。     

基于神经网络的坦克机动任务规划

在未来高技术局部战争务件下,坦克不得不面临一个动态复杂的战场环境,这就要求坦克能根据战场环境实时地进行任务规划。以单辆坦克在陆地上的自主机动为背景,提出了一种基于神经网络的坦克机动任务规划方法。在机动任务规划的实施方面,重点描述了两个基本方面：坦克机动环境的评估及坦克机动任务规划的自主实现。以神经网络方法为基础,提出了实现坦克自主机动的基本思路,并编制应用程序,进行实例检验。结果表明,这种方法科学合理,为坦克机动任务的规划提供了新思路。神经网络方法具有普遍意义,能推广应用于坦克其它方面的任务规划。     

一种Internet移动代理系统的黄页服务模型

提出了一种基于信度推理网络的移动代理系统黄页服务模型,为自主迁移的移动代理提供迁移决策支持。与现有的移动代理系统黄页服务模型相比,该模型较好地解决了信息局部性和信息更新的问题,其结构具有良好的可扩展性和灵活性,能更好地适应Ｉｎｔｅｒｎｅｔ动态的网络环境。     

基于移动代理具有拥塞控制的AODV路由协议

提出一种基于移动代理的AODV路由协议,来解决Ad Hoc网络的拥塞问题.在网络中引入一定数量的携带拥塞状态的移动代理,移动代理在网络中漫游时选择轻负载的节点为下一跳,并根据节点拥塞状态更新路由表,用较少的信息流量使每个节点及时了解当前网络的拓扑状况.实验结果表明这种路由算法可以有效地平衡网络负载,大大增强了链路的稳定性,降低了端到端的数据传输时延.     

Mobile-agent-based collaborative sensor fusion

Information fusion can assist in the development of sensor network applications by merging capabilities, raw data and decisions from multiple sensors through distributed and collaborative integration algorithms. In this paper, we introduce a multi-layered, middleware-driven, multi-agent, interoperable architecture for distributed sensor networks that bridges the gap between the programmable application layer consisting of software agents and the physical layer consisting of sensor nodes. We adopt an energy-efficient, fault-tolerant approach for collaborative information processing among multiple sensor nodes using a mobile-agent-based computing model. In this model the sink/base-station deploys mobile agents that migrate from node to node following a certain itinerary, either pre-determined or determined on-the-fly, and fuse the information/data locally at each node. This way, the intelligence is distributed throughout the network edge and communication cost is reduced to make the sensor network energy-efficient. We evaluate the performance of our mobile-agent-based approach as well as that of the traditional client/server-based computing model, vis-à-vis energy consumption and execution time, through both analytical study and simulation. We draw important conclusions based on our findings. Finally, we consider a collaborative target classification application, supported by our architectural framework, to illustrate the efficacy of the mobile-agent-based computing model.