A P2P-based intelligent resource discovery mechanism in Internet-based distributed systems

Internet-based distributed systems enable globally-scattered resources to be collectively pooled and used in a cooperative manner to achieve unprecedented petascale supercomputing capabilities. Numerous resource discovery approaches have been proposed to help achieve this goal. To report or discover a multi-attribute resource, most approaches use multiple messages, with one message for each attribute, leading to high overhead of memory consumption, node communication, and subsequent merging operation. Another approach can report and discover a multi-attribute resource using one query by reducing multi-attribute to a single index, but it is not practically effective in an environment with a large number of different resource attributes. Furthermore, few approaches are able to locate resources geographically close to the requesters, which is critical to system performance. This paper presents a P2P-based intelligent resource discovery (PIRD) mechanism that weaves all attributes into a set of indices using locality sensitive hashing, and then maps the indices to a structured P2P overlay. PIRD can discover resources geographically close to requesters by relying on a hierarchical P2P structure. It significantly reduces overhead and improves search efficiency and effectiveness in resource discovery. It further incorporates the Lempel–Ziv–Welch algorithm to compress attribute information for higher efficiency. Theoretical analysis and simulation results demonstrate the efficiency of PIRD in comparison with other approaches. It dramatically reduces overhead and yields significant improvements on the efficiency of resource discovery.     

PIVOT: An adaptive information discovery framework for computational grids

In a traditional computational grid environment, the owners of resources usually provide information about their resources extracted by pre-configured information services or web services. However, such information is not sufficient for the scheduler in the high-performance distributed computing. To solve this problem, we propose a scalable grid information service framework, named PIVOT (adaPtive Information discoVery framewOrk for compuTational grid). By using deadline-constrained flooding collector dissemination and P2P-like information collection schemes, PIVOT provides an active mechanism to collect application-specific resource information. In particular, PIVOT provides a resource information service for application-specific schedulers. The best-effort performance on overhead traffic and communication latency during information discovery is guaranteed by two new distributed cooperative algorithms. The experimental results in the simulations and real computational grid platform demonstrate that PIVOT has a high level of adaptability for application-specific resource information discovery, and also improves the accuracy of resource allocation and the efficiency of executing parallel tasks in traditional information services.     

VEGA Infrastructure for Resource Discovery in Grids

Grids enable users to share and access large collections and various types of re-sources in wide areas, and how to locate resources in such dynamic, heterogeneous and autonomousdistributed environments is a key and challenging issue. In this paper, a three-level decentralizedand dynamic VEGA Infrastructure for Resource Discovery (VIRD) is proposed. In this architec-ture, every Border Grid Resource Name Server (BGRNS) or Grid Resource Name Server (GRNS)has its own local policies, governing information organization, management and searching. Changesin resource information are propagated dynamically among GRNS servers according to a link-state-like algorithm. A client can query its designated GRNS either recursively or iteratively. Optimizing techniques, such as shortcut, are adopted to make the dynamic framework more flexible and effi-cient. A simulator called SimVIRD is developed to verify the proposed architecture and algorithm.q.Experiment results indicate that this architecture could deliver good scalability and performance for grid resource discovery.     

集成P2P模式的网格资源发现算法研究

网格计算和对等计算有很多可以融合的特征。在传统的网格环境中,资源的发现和定位主要用集中式或者分层式来解决,随着网格规模的扩大,这种方式明显不适合网格环境。另一方面,P2P为大规模分布式环境下有效地发现资源提供了可扩展性方案。首先提出了一种集成P2P模式的网格资源管理模型,然后基于该模型提出了一种融合遗传和蚂蚁算法的资源发现算法。理论分析和仿真证明了遗传蚂蚁算法能有效地提高P2PGrid环境下的资源发现性能。     

CycloidGrid: A proximity-aware P2P-based resource discovery architecture in volunteer computing systems

Volunteer computing which benefits from idle cycles of volunteer resources over the Internet can integrate the power of hundreds to thousands of resources to achieve high computing power. In such an environment the resources are heterogeneous in terms of CPU speed, RAM, disk capacity, and network bandwidth. So finding a suitable resource to run a particular job becomes difficult. Resource discovery architecture is a key factor for overall performance of peer-to-peer based volunteer computing systems. The main contribution of this paper is to develop a proximity-aware resource discovery architecture for peer-to-peer based volunteer computing systems. The proposed resource discovery algorithm consists of two stages. In the first stage, it selects resources based on the requested quality of service and current load of peers. In the second stage, a resource with higher priority to communication delay is selected among the discovered resources. Communication delay between two peers is computed by a network model based on queuing theory, taking into account the background traffic of the Internet. Simulation results show that the proposed resource discovery algorithm improves the response time of user’s requests by a factor of 4.04 under a moderate load.     

一种基于索引P2P分层的网格资源发现模型

网格资源发现是网格研究中的重要组成部分,随着P2P网络的兴起,许多新的概念和研究方向为网格研究提供了思路。针对网格环境下集中式和无结构P2P资源发现机制的缺陷,提出了一种基于索引P2P分层的网格资源发现模型,引入了索引P2P分层网络,充分利用了网格环境中节点性能的差异,具有较好的资源查找发现功能,并且对大规模的网格具有较好的适应性。     

基于用户行为和社区发现的P2P资源检索方法

针对目前P2P（对等网）系统资源所存在的带宽占用严重、检索效率低下等问题,提出一种基于用户行为和社区发现的P2P资源检索方法。通过分析P2P文件系统中的海量的检索和下载行为,在DHT的结构化P2P网络之上构建资源关系网,挖掘资源之间的深层关系,用社区划分算法对资源划分社区后进行检索,用户的查询请求快速定位到相关的资源。实验表明,该方法有效提高了查全率和查准率。     

Soft sets based symbiotic organisms search algorithm for resource discovery in cloud computing environment

The dynamicity, coupled with the uncertainty that occurs between advertised resources and users’ resource requirement queries, remains significant problems that hamper the discovery of candidate resources in a cloud computing environment. Network size and complexity continue to increase dynamically which makes resource discovery a complex, NP-hard problem that requires efficient algorithms for optimum resource discovery. Several algorithms have been proposed in literature but there is still room for more efficient algorithms especially as the size of the resources increases. This paper proposes a soft-set symbiotic organisms search (SSSOS) algorithm, a new hybrid resource discovery solution. Soft-set theory has been proved efficient for tackling uncertainty problems that arises in static systems while symbiotic organisms search (SOS) has shown strength for tackling dynamic relationships that occur in dynamic environments in search of optimal solutions among objects. The SSSOS algorithm innovatively combines the strengths of the underlying techniques to provide efficient management of tasks that need to be accomplished during resource discovery in the cloud. The effectiveness and efficiency of the proposed hybrid algorithm is demonstrated through empirical simulation study and benchmarking against recent techniques in literature. Results obtained reveal the promising potential of the proposed SSSOS algorithm for resource discovery in a cloud environment.     

Behavioral modeling and formal verification of a resource discovery approach in Grid computing

Grid computing is the federation of resources from multiple locations to facilitate resource sharing and problem solving over the Internet. The challenge of finding services or resources in Grid environments has recently been the subject of many papers and researches. These researches and papers evaluate their approaches only by simulation and experiments. Therefore, it is possible that some part of the state space of the problem is not analyzed and checked well. To overcome this defect, model checking as an automatic technique for the verification of the systems is a suitable solution. In this paper, an adopted type of resource discovery approach to address multi-attribute and range queries has been presented. Unlike the papers in this scope, this paper decouple resource discovery behavior model to data gathering, discovery and control behavior. Also it facilitates the mapping process between three behaviors by means of the formal verification approach based on Binary Decision Diagram (BDD). The formal approach extracts the expected properties of resource discovery approach from control behavior in the form of CTL and LTL temporal logic formulas, and verifies the properties in data gathering and discovery behaviors comprehensively. Moreover, analyzing and evaluating the logical problems such as soundness, completeness, and consistency of the considered resource discovery approach is provided. To implement the behavior models of resource discovery approach the ArgoUML tool and the NuSMV model checker are employed. The results show that the adopted resource discovery approach can discovers multi-attribute and range queries very fast and detects logical problems such as soundness, completeness, and consistency.     

IndexPeer:半结构化P2P系统资源发现模型及其DHT算法*

提出了一种基于半结构化P2P系统的资源发现模型——IndexPeer模型。该模型采用三层索引结构,由下至上分别为virtual organization 层、service peer 层和indexpeer层。IndexPeer充分利用P2P系统中的节点性能差异,具有高效的查找功能,且对网络的高度动态性有良好的适应性。针对Index Peer模型的体系结构,对该模型的结构化层DHT算法进行了研究和设计。基于small-world的仿真实验表明,IndexPeer模型的体系结构及其结构化层DHT算法具有较好的鲁棒性和一定的可扩展性。     

Context-based caching and routing for P2P web service discovery

In modern heterogeneous environments, such as mobile, pervasive and ad-hoc networks, architectures based on web services offer an attractive solution for effective communication and inter-operation. In such dynamic and rapidly evolving environments, efficient web service discovery is an important task. Usually this task is based on the input/output parameters or other functional attributes, however this does not guarantee the validity or successful utilization of retrieved web services. Instead, non-functional attributes, such as device power features, computational resources and connectivity status, that characterize the context of both service providers and consumers play an important role to the quality and usability of discovery results. In this paper we introduce context-awareness in web service discovery, enabling the provision of the most appropriate services at the right location and time. We focus on context-based caching and routing for improving web service discovery in a mobile peer-to-peer environment. We conducted a thorough experimental study, using our prototype implementation based on the JXTA framework, while simulations are employed for testing the scalability of the approach. We illustrate the advantages that this approach offers, both by evaluating the context-based cache performance and by comparing the efficiency of location-based routing to broadcast-based approaches. Recommended by: Zakaria Maamar     

A P2P strategy for QoS discovery and SLA negotiation in Grid environment

In recent years, Grid systems and Peer to Peer networks are the most commonly-used solutions to achieve the same goal: the sharing of resources and services in heterogeneous, dynamic, distributed environments. Many studies have proposed hybrid approaches that try to conjugate the advantages of the two models. This paper proposes an architecture that integrates the P2P interaction model in Grid environments, so as to build an open cooperative model wherein Grid entities are composed in a decentralized way. In particular, this paper focuses on a QoS aware discovery algorithm for P2P Grid systems, analyzing protocol and explaining techniques used to improve its performance.     

Nondominated local coteries for resource allocation in grids and clouds

The resource allocation problem is a fundamental problem in Grid and Cloud computing environments. This paper focuses on constructing nondominated (ND) local coteries to solve the problem in a distributed way. Distributed algorithms using coteries usually incur low communication overheads and have high degrees of fault-tolerance, and ND coteries are candidates for the algorithms to achieve the highest degree of fault-tolerance. A new type of coteries, called p-coteries, is defined to aid the construction of local coteries. Theorems about the nondomination of p-coteries are then developed, and an operation, called pairwise-union (p-union), is proposed to help generate ND p-coteries, which in turn can be used to generate ND local coteries for solving the resource allocation problem.     

一种基于P2P的非集中式网格资源发现方法

有效地发现网格的各种资源是影响网格整体性能的一个重要因素。针对资源发现在网格规模及应用不断扩展过程中变得越来越复杂的问题,在网格环境中融合Web Service技术,同时引入P2P思想,将资源发现模型分为内外两层,提出一个非集中式的网格资源发现方法,并应用于制造网格之中。实验证明,该模式有效解决了集中式模式带来的节点瓶颈等问题,并大幅降低分布式系统中资源发现产生的网络流量,具有高效性、可扩展性和鲁棒性。     

基于纳什议价的P2P社会网络资源共享

针对Peer-to-Peer（P2P）社会网络中存在的自由下载问题,本文提出一种基于纳什议价的节点资源共享博弈。首先,将节点共享资源分为两类:公共品资源和俱乐部资源。将社会网络中的节点关系集合分为：朋友集合 和普通集合 。节点在 集合中共享的资源作为公共品资源,在 集合中作为俱乐部资源。其次,本文采用纳什议价的方法证明存在节点共享能力、保证不同集合中节点共享资源的最小服务质量以及最大化节点共享资源效用函数的条件下,共享资源节点根据纳什议价权力对不同集合进行资源共享,达到最优的资源共享。再次,分析了基于纳什议价节点共享资源的公平性。最后,通过仿真验证表明：节点共享资源的收益和资源共享量与不同集合议价权力都正相关,保证最小服务质量的资源共享其公平性因子高于不存在服务质量保证的资源共享公平性因子。仿真结果验证了理论分析结果。     

Self-scaling cooperative discovery of service compositions in unstructured P2P networks

We propose an efficient technique for improving the performance of automatic and cooperative compositions in unstructured Peer-to-Peer networks during service discovery. The technique exploits a probabilistic forwarding algorithm that uses different sources of knowledge, such as network density and service grouping, to reduce the amount of messages exchanged in the network. The technique, analysed in several network configurations by using a simulator to observe resolution time, recall and message overhead, presents good performance especially in dense and large-scale service networks.     

An effective and robust two-phase resource allocation scheme for interdependent tasks in mobile ad hoc computational Grids

This paper addresses the problem of resource allocation to interdependent tasks in mobile ad hoc computational Grids. Dependencies between tasks imply that there can be heavy communication induced by data transfers between tasks executed on separate nodes. The communication in mobile ad hoc Grids is always expensive and unreliable, and therefore plays a critical role in application performance. There are several factors that contribute to communication cost. Unreliable and short-term connectivity can increase communication cost due to frequent failure and activation of links, and ineffective resource allocation can increase communication cost due to multi hop communication between dependent tasks. To reduce communication cost, an effective and robust resource allocation scheme is required. However, the design of such a scheme for mobile ad hoc computational Grids exhibits numerous difficulties due to the constrained communication environment, node mobility, and lack of pre-existing network infrastructure.     

P2P网络下基于K-Wmeans聚类算法的Web服务发现研究

针对P2P网络的动态性、分布性等特点,提出了一种运用加权改进的K-Wmeans算法对Web服务进行聚类分析的方法。通过对P2P网络中各个节点上Web服务进行分布式聚类,可使服务请求者按照类别更准确快速地发现所需的Web服务。最后分析了算法的时间复杂度,并通过实验证明了此种方法在P2P环境下的Web服务聚类中存在一定的优越性。