Mobile agent-based approach for efficient network management andresource allocation: framework and applications

Agent programming technology has emerged as a flexible and complementary way to manage resources of distributed systems due to the increased flexibility in adapting to the dynamically changing requirements of such systems. A very promising application of this technology is related to the control of forthcoming networking systems which will represent a competitive marketplace with a multitude of vendors, operators and customers. Thus, new reference models have to be investigated in order to better satisfy users' requirements in a framework where resource allocation is provided under the control of different and often competing stakeholders (users, network providers, service providers, etc.). We believe that autonomy is one of the features that will characterize the behavior of agents in such environment: autonomous choices will be taken as the result of coordination among different cooperating software entities. Following this direction, we describe the efficient integration and adoption of mobile agents and genetic algorithms in the implementation of a valuable strategy for the development of effective market based routes for brokering purposes in the future multioperator network marketplace. The proposed genetic algorithm provides a kind of stochastic algorithm searching process in order to identify optimal resource allocation strategies. The agent-based network management approach represents an underlying framework and structure for the multioperator network model, and can be used to facilitate the collection and dissemination of the required management data, as well as the efficient and distributed operation of the algorithm. We also present some numerical results to assess the performance and operation effectiveness of our approach, by applying it in some test case scenarios     

一种定向无线自组网邻居发现算法

针对使用定向天线的无线移动网络在自组网过程中邻居搜索时间较长且不确定性较大等问题,提出了一种根据二进制编码序列确定收发模式的异步邻居发现算法,通过为每个节点分配独立的二进制编码来确定节点的收发模式,并根据收发状态给出确定的节点波束扫描方式。讨论了应用于该算法的编码需要满足的条件,并给出一个满足要求的编码序列组,在节点时间异步情况下完成邻居发现的时长具有确定的上界。仿真结果表明,相较其他确定时长的异步邻居搜索算法,该算法能够提高节点间相互发现概率,缩减节点邻居发现的平均和最大用时。     

毫微微小区中一种基于分组的资源分配方法

为有效解决毫微微小区间( Femtocell)干扰,采用分布式方式对毫微微小区进行资源管理。首先,对毫微微接入点( FAPs)进行分组。基于Lingo数学建模的思想,提出了一种解决分组优化问题的算法。该算法在使用分支定界算法寻找最优解的同时,通过建立单纯形表剪去偏离最优解方向的分支;其次,每组选择一个簇头为本组内FAPs分配资源,为此,提出了新的子信道分配方法,该方法根据干扰指示矩阵修正子信道分配的情况。仿真结果表明：和其他算法相比,提出的算法不仅能找到分组优化问题的最优解,并且效率更高;另外,提出的资源分配算法不仅减小了用户间干扰,而且提高了户间速率公平。     

A middleware approach for reliable resource selection on Internet‐of‐Things

Decision making plays a vital role in the selection of resources so that they actively participate for communication and computation on the Internet‐of‐Things platform. For the same, they require the elimination of the challenges related to knowledge representation, discovery, trust, and security due to continuously changing mobility patterns, heterogeneity, interoperability, and scalability on the network. To address the challenges, a novel three‐layered approach, namely, middleware approach for reliable resource selection on Internet‐of‐Things (MARRS‐IoT), is proposed. It performs a search through neighbor discovery algorithm and evaluates trust score of the discovered resources, both locally and globally using fuzzy‐decision algorithm and performs efficient communication among resources via hybrid M‐gear protocol. The approach is simulated and compared against algorithms, namely, particle swarm optimization, ants colony optimization, and binary genetic to evaluate its performance. The obtained results support the efficacy of the MARRS‐IoT with respect to throughput and execution time.     

一种优化的人脸图像超分辨率算法

针对传统超分辨率算法存在的局部失真和块效应问题提出了一种改进的算法。算法以马尔科夫模型为基础,在满足图像重构的约束条件下,利用非线性局部搜索技术找到训练集中的最优分块,通过水平相容性检查来实现匹配块间的兼容性。基于Sigmoid函数进行加权处理,提高了匹配的精度。实验结果表明,该算法在获取HR图像的过程中能有效地抑制块效应和局部失真现象的出现,改善了超分辨率图像的质量,与传统算法相比,该算法的鲁棒性较强。     

基于改进遗传算法的网格资源调度算法

网格计算关注大规模的资源和任务调度，要求采用的调度算法能够具有高效性。提出一种基于改进遗传算法的资源调度算法，该算法综合考虑了资源任务分配量以及任务完成时间，从而设计出良好的交叉和选择算子，既能够保留完成时间比较小的个体又能够保留具有一部分优秀资源分配方式的个体．算法具有较好的效率和收敛性。     

Biased Random Walks in Uniform Wireless Networks

A recurrent problem when designing distributed applications is to search for a node with known property. File searching in peer-to-peer (P2P) applications, resource discovery in service-oriented architectures (SOAs), and path discovery in routing can all be cast as a search problem. Random walk-based search algorithms are often suggested for tackling the search problem, especially in very dynamic systems-like mobile wireless networks. The cost and the effectiveness of a random walk-based search algorithm are measured by the excepted number of transmissions required before hitting the target. Hence, to have a low hitting time is a critical goal. This paper studies the effect of biasing random walk toward the target on the hitting time. For a walk running over a network with uniform node distribution, a simple upper bound that connects the hitting time to the bias level is obtained. The key result is that even a modest bias level is able to reduce the hitting time significantly. This paper also proposes a search protocol for mobile wireless networks, whose results are interpreted in the light of the theoretical study. The proposed solution is for unstructured wireless mobile networks.     

A middleware service for employing and evaluating resource management algorithms in distributed networks

The first part of this paper introduces the design of a middleware‐based service which is valuable for distributed networks for mainly managing their resources. The second part evaluates the performance of a distributed intelligent network (D‐IN), which comprises the proposed service together with a resource management algorithm. We test the network's performance by building and emulating its basic functionality, based on distributed object technology (DOT), in a real environment. The resource management algorithm mainly aims at avoiding congestion and balancing load. Its implementation uses the ICALB algorithm (Comput. Commun. 2002; 25 (17):1548–1556) model. Its incorporation is succeeded through the use and implementation of the distributed middleware‐based service. It is a CORBA‐based service that is used for successfully managing resource management algorithms, such as ICALB, facilitate their operation, and solving classes of problems related to communications over the distributed network, sharing of resources spread over the network, scheduling, synchronization, and management of various tasks. By this means we argue that the method that we use can be employed for operating in various distributed networks. We also evaluate the network's performance by measuring various D‐IN node parameters with critical meaning and by showing the improvements that appeared to the D‐IN from the operation of both the ICALB algorithm and the proposed service. Copyright © 2005 John Wiley & Sons, Ltd.     

基于种类-位置模型的可重构资源指派方法

在基于指令集动态可扩展技术的可重构指令集处理器研究中,如何有效使用系统的可重构资源,将很大程度上影响扩展得到的定制指令的功能实现,进而影响系统性能的优化效果.本文针对可重构资源的利用问题,首先设计了一种可重构资源模型,该模型弱化了可重构资源的功能和数量属性,主要提供其种类和位置属性,并能够以此计算资源使用的时间属性.基于此模型,本文将图论中的图着色问题进行扩展,引入多遍着色的思想,提出了一种针对粗粒度可重构资源的资源指派算法,该算法将可重构资源的指派等价为一个图多遍着色问题,通过模型提供的属性参数和限制条件完成指派过程.实验结果验证了算法的有效性,并揭示了资源使用中的规律性,对提高资源利用率和系统性能具有一定的指导意义.     

一种自组织时间同步网

基于NTP协议构建大规模网络的时间同步网时，必须在网络每一节点上事先进行参数配置，如同步源地址等。这种网络拓扑是静态的，时间同步操作必然会受到网络环境变化的制约和影响。扩展定义两个新的NTP包SRP和SAP，将同步源抽象为一种资源，应用网格计算中的分布式资源发现方法，动态的根据网络环境变化以及节点的能力差异配置参数，进而构成了一种自组织时间同步覆盖网。该方法不仅对于NTP协议的进一步完善研究有参考价值，而且使时间同步更可靠、经济、灵活。     

网格资源管理的研究与发现

提出一种采用分布式动态层次结构的资源管理模型方法。依据资源之间的网络通信性能使资源组织成带层次的树型组织结构,根据网格资源类别在逻辑上划分多个社区,使得资源的组织方式能够反映实际的网络拓扑,为计算任务在资源上的合理分配提供了依据,避免了资源选择的盲目性。在该资源管理模型中的资源发现与定位,采用资源树查找算法,多种请求定位策略,可以快速地找到目标结点,提高相应查找时间。资源定位的效率仿真表明这种方法可以提高查找速度和性能。     

基于兴趣和行为预测的移动社交网络动态资源发现机制

针对时延容忍的移动社交网络中的资源发现问题,在三维环境下提出一种基于兴趣和行为预测的动态资源发现机制(IBRD)。IBRD首先从用户的文件资源和信息表中提取兴趣向量,然后通过节点间的余弦相似度计算构造初始的虚拟兴趣社区。之后,通过对移动社交数据的分析,建立半马尔可夫链模型以预测节点的行为和运动轨迹。依据模型的预测结果,实现虚拟兴趣社区的动态维护。最后,基于动态的虚拟兴趣社区构建高效的资源发现策略。IBRD机制在随机网络仿真器(ONE)上得以实现,实验结果表明,IBRD与同类模型相比,具有较高的资源发现成功率、较低的平均时延和通信开销。     

MP2P中资源检索方案研究

MP2P技术中以网络资源的搜索最为重要,因此文章研究了当前一段时间出现的性能出色的资源搜索算法,提高文件检索效率和减少无线环境中的网络拥堵等问题,重点分析了几种比较典型的资源搜索算法:集中式和洪泛式,该检索方式帮助节点在邻居间有效地进行资源请求;分布式资源搜索,有效地提高了查询效率;有基于组或者超级节点的,查询时间缩短了,但是投入的代价偏大。文章对这几种资源搜索算法做了总结和详细对比。     

Power‐conservative server consolidation based resource management in cloud

The cloud computing environment is a real‐time communication network that involves a large number of systems connected in a distributed fashion, for which resources are available on demand. In recent years, due to the enormous growth of data and information, data maintenance tasks involve a major effort in information technology (IT) industries. So, IT industries are concentrating on the cloud computing environment in order to maintain their data and manage their resources. Owing to the increase in the number of data centres, which have an impact on electrical energy cost, peak power dissipation, cooling and carbon emission, power‐conservation‐based resource management is essential. A best‐fit heuristic job placement algorithm is proposed in this paper in order to increase the job allocation percentage, a worst‐fit heuristic virtual machine (VM) placement algorithm is also proposed in order to place the VMs over the physical machines (PMs) thereby reducing the number of the latter allotted, and a server consolidation algorithm is proposed in order to improve power conservation. Copyright © 2014 John Wiley & Sons, Ltd.     

Design and implementation of a distributed evolutionary computing software

Although evolutionary algorithm is a powerful optimization tool, its computation cost involved in terms of time and hardware resources increases as the size or complexity of the problem increases. One promising approach to overcome this limitation is to exploit the inherent parallelism of evolutionary algorithms by creating an infrastructure necessary to support distributed evolutionary computing using existing Internet and hardware resources. This paper presents a Java-based distributed evolutionary computing software (Paladin-DEC), which enhances the concurrent processing and performance of evolutionary algorithms by allowing inter-communications of subpopulations among various computers over the Internet. Such a distributed system enables individuals to migrate among multiple subpopulations according to some patterns to induce diversity of elite individuals periodically, in a way that simulates the species evolve in natural environment. The Paladin-DEC software is capable of keeping data integrity throughout the computation, and is incorporated with the features of robustness, security, fault tolerance, and work balancing. The effectiveness and advantages of the Paladin-DEC are illustrated upon two case studies of drug scheduling in cancer chemotherapy and searching probe sets of yeast genome.     

SDN based network resource selection multi-objective optimization algorithm

For the problem of coexistence of different resource utility objectives and mutual influence of resource selection strategies in the complex structure of software-defined network (SDN),an SDN based network resource selection multi-objective optimization algorithm was proposed.The optimization goals of resource providers and clients were taken into account in the algorithm,and a resource selection multi-objective optimization model was constructed.The model was further solved by the reference vector based multi-objective optimization algorithm.Simulation results show that compared with other algorithms,the proposed algorithm could quickly converge to the uniformly distributed non-inferior solution set,and balance the optimization objects of multi-party in SDN based resource access management.     

虚拟计算环境下面向应用的基于信任的资源匹配模型

为了解决虚拟计算环境中的资源合理调度问题,提出了一种基于信任的资源匹配模型--“资源滑动窗口”模型。首先对资源的静态属性进行分类,然后依据基于时间窗的贝叶斯信任模型对资源节点进行评价,同时考虑资源的负载,动态划分其实时性能。最后综合评估静态和动态属性,确定调度资源分配。该模型为不同任务和属性的资源调度策略奠定了基础,实现了“合适的资源服务于合适的任务”的目的。仿真实验表明所提的模型相对传统的调度算法,具有更高的系统任务执行成功率和资源利用率。     

Quality-of-Service Based Protection in MPLS Control WDM Mesh Networks

Intelligent methods for automatic protection and restoration are critical in optical transport mesh networks. This paper discusses the problem of quality-of-service (QoS)-based protection in terms of the protection-switching time and availability for end-to-end lightpaths in a WDM mesh network. We analyze the backup lightpath-sharing problem in such networks and study the correlation of the working lightpaths and the impact of the correlation on the sharing of the backup lightpaths. We present a multi-protocol-label-switching (MPLS) control-based fully distributed algorithm to solve the protection problem. The proposed algorithm includes intelligent and automatic procedures to set up, take down, activate, restore, and manage backup lightpaths. It greatly reduces the required resources for protection by allowing the sharing of network resources by multiple backup lightpaths. At the same time, it guarantees, if possible, to satisfy the availability requirement even with resource sharing by taking the correlation of working lightpaths into consideration. A simple analysis of the proposed algorithm in terms of computation time and message complexity indicates that the implementation of the algorithm is practical. The illustrative studies that compare the performance of 1:1, unlimited sharing, and QoS-based backup sharing algorithms indicate that QoS-based sharing achieves comparable performance as unlimited sharing, which is much better than the 1:1 backup scheme in terms of connection blocking probability, average number of connections in the network for a given offered load, and network resource utilization.     

802．11无线局域网中AP放置与信道配置的联合算法

在多小区无线局域网规划中,接入访问点(AP)放置与信道配置是两个重要的任务。在给定用户业务需求的条件下,谋求最大系统吞吐率和资源分配的公平性是网络规划的目标,其中公平性由吞吐率均衡因子表征。在传统的规划策略中,AP放置与信道配置被分割为两个先后的步骤;而该文提出的目标函数则将这两个问题联合解决以得到更好的系统性能。当采用全局遍历时,对目标函数寻求全局最优解计算量庞大;因此该文又提出了一种有效的局部最优解搜索算法补丁算法,此算法计算量小,同时能较好地逼近全局最优解。     

A novel leader election algorithm based on resources for ring networks

The leader node in a distributed computing system is responsible to establish coordination among all other nodes that are situated apart geographically. Selection of a suitable leader is one of the major and challenging problems. In this paper, a novel leader election algorithm is proposed based on resources of each node in a ring network. All the nodes compute resource strength values by considering available resources like CPU, memory capacity, and residual energy. A node with the highest resource strength over the network is elected as the leader. The proposed algorithm has also considered sudden failure of the nodes particularly when it is the leader node. Moreover, addition of new nodes is also considered. The proposed algorithm shows improvement on message complexity over the network and resource‐based priority generation, which helps in efficient election of the leader. To validate, the proposed algorithm is extensively simulated as well as real‐life hardware experiment is also done. In the experiment, 2 cases are considered with different weight of the resources, and consequent effects are shown. The results are also compared with the existing algorithms, and it is observed that the proposed work comparably performs better that the existing related algorithms.