Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment consisting of various cloud infrastructures by aggregating different IaaS provider capabilities coming from both the commercial and the academic area. In this paper, we introduce a federated cloud management solution that operates the federation through utilizing cloud-brokers for various IaaS providers. In order to enable an enhanced provider selection and inter-cloud service executions, an integrated monitoring approach is proposed which is capable of measuring the availability and reliability of the provisioned services in different providers. To this end, a minimal metric monitoring service has been designed and used together with a service monitoring solution to measure cloud performance. The transparent and cost effective operation on commercial clouds and the capability to simultaneously monitor both private and public clouds were the major design goals of this integrated cloud monitoring approach. Finally, the evaluation of our proposed solution is presented on different private IaaS systems participating in federations.     

DiDuSoNet: A P2P architecture for distributed Dunbar-based social networks

Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. One of the most important challenges is the data availability problem when a user is offline. In this paper we propose DiDuSoNet, a novel P2P Distributed Online Social Network where users can exercise full access control on their data. Our system exploits trust relationships for providing a set of important social services, such as trustness, information diffusion, and data availability. In this paper we show how our system manages the problem of data availability by proposing a new P2P dynamic trusted storage approach. By following the Dunbar concept, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Differently from other approaches, nodes chosen to keep data replicas are not statically defined but dynamically change according to users churn. In according to our previous work, we use only two online profile replicas at time. By using real Facebook data traces we prove that our approach offers high availability.     

P2P网中基于文件分片的副本建立策略*

在大规模P2P网络中,为了提高数据的可用性,可以通过在系统中多个节点上建立数据副本的方法来增加数据的冗余度.为了减小副本建立的开销,可采用一种基于文件分片的副本建立策略,将需要复制的数据文件先进行分片,然后把这些分片在一组选取好的候选节点间进行分发复制.该方法能够充分利用网络带宽,明显减小建立副本所需的时间开销.     

基于对等模型的分布式协同设计系统

为了解决分布式协同设计系统中的信息快速检索以及多副本同步等问题,引入了对等模型,给出了该系统的功能模型、信息检索模型等。提出了DHT的对等信息检索方法,保证了用户能够在分布式协同设计系统中快速共享资源。采用基于DHT的分布式互斥等算法作为协同数据的一致性维护方法,给出了系统的具体实现方法和实例。     

Continually Answering Constraint k-NN Queries in Unstructured P2P Systems

We consider the problem of efficiently computing distributed geographical k-NN queries in an unstructured peer-to-peer (P2P) system,in which each peer is managed by an individual organization and can only communicate with its logical neighboring peers.Such queries are based on local filter query statistics,and require as less communication cost as possible,which makes it more difficult than the existing distributed k-NN queries.Especially,we hope to reduce candidate peers and degrade communication cost.In this paper,we propose an efficient pruning technique to minimize the number of candidate peers to be processed to answer the k-NN queries.Our approach is especially suitable for continuous k-NN queries when updating peers,including changing ranges of peers,dynamically leaving or joining peers,and updating data in a peer. In addition,simulation results show that the proposed approach outperforms the existing Minimum Bounding Rectangle (MBR.)-based query approaches,especially for continuous queries.     

Scalable and topology-aware reconciliation on P2P networks

Collaborative applications are characterized by high levels of data sharing. Optimistic replication has been suggested as a mechanism to enable highly concurrent access to the shared data, whilst providing full application-defined consistency guarantees. Nowadays, there are a growing number of emerging cooperative applications adequate for Peer-to-Peer (P2P) networks. However, to enable the deployment of such applications in P2P networks, it is required a mechanism to deal with their high data sharing in dynamic, scalable and available way. Previous work on optimistic replication has mainly concentrated on centralized systems. Centralized approaches are inappropriate for a P2P setting due to their limited availability and vulnerability to failures and partitions from the network. In this paper, we focus on the design of a reconciliation algorithm designed to be deployed in large scale cooperative applications, such as P2P Wiki. The main contribution of this paper is a distributed reconciliation algorithm designed for P2P networks (P2P-reconciler). Other important contributions are: a basic cost model for computing communication costs in a DHT overlay network; a strategy for computing the cost of each reconciliation step taking into account the cost model; and an algorithm that dynamically selects the best nodes for each reconciliation step. Furthermore, since P2P networks are built independently of the underlying topology, which may cause high latencies and large overheads degrading performance, we also propose a topology-aware variant of our P2P-reconciler algorithm and show the important gains on using it. Our P2P-reconciler solution enables high levels of concurrency thanks to semantic reconciliation and yields high availability, excellent scalability, with acceptable performance and limited overhead.     

Design and evaluation of P2P overlays for energy negotiation in smart micro-grid

The increasing availability of distributed renewable energy sources such as photo-voltaic (PV) panels has introduced new requirements for innovative power grid infrastructures. Information technologies provide new opportunities for developing techniques to optimize the energy usage by a new generation of smart-grids. Here we investigate an original solution that aims at maximizing the self-consumption within a neighborhood based on a collaborative approach. Distributed software agents plan and enforce the optimal schedule of consuming appliances according to the prediction of energy production by PV panels, the estimated energy profile of consuming devices and the user's preferences and constraints. Finally we focus on the performance evaluation of a negotiation protocol that allows agents to find a sub-optimal solution for the global schedule, comparing results obtained by a prototype implementation and experimenting different technologies.     

An OS-ELM based distributed ensemble classification framework in P2P networks

Although classification in centralized environments has been widely studied in recent years, it is still an important research problem for classification in P2P networks due to the popularity of P2P computing environments. The main target of classification in P2P networks is how to efficiently decrease prediction error with small network overhead. In this paper, we propose an OS-ELM based ensemble classification framework for distributed classification in a hierarchical P2P network. In the framework, we apply the incremental learning principle of OS-ELM to the hierarchical P2P network to generate an ensemble classifier. There are two kinds of implementation methods of the ensemble classifier in the P2P network, one-by-one ensemble classification and parallel ensemble classification. Furthermore, we propose a data space coverage based peer selection approach to reduce high the communication cost and large delay. We also design a two-layer index structure to efficiently support peer selection. A peer creates a local Quad-tree to index its local data and a super-peer creates a global Quad-tree to summarize its local indexes. Extensive experimental studies verify the efficiency and effectiveness of the proposed algorithms.     

基于P2P和XML内容的发布订阅系统

介绍了一种面向大规模分布式应用的发布订阅中间件系统,系统采用一种结合了下推树和自下而上树自动机的XPath订阅快速匹配算法,支持XPath多谓词和分支特性。系统事件代理P2P网络节点之间的事件或订阅消息路由采用了扩展的Chord路由协议和订阅聚合、覆盖等多种优化措施。实验结果表明,系统具有较好的效率和性能,能满足面向大规模分布式应用的要求。     

基于P2P计算的动态多副本开销模型

在多个结点上保持副本是提高P2P或网格计算环境可用性的一个有效途径。不可靠的对等点和网络环境以及用户访问模式的多样性使得难以确定多少个副本能够满足用户高可用性的需求。文章提出了一种最小开销模型来预测和动态控制副本数量。为了隐藏系统中对等点的不可靠性,在考虑多副本的同时通过一种冗余机制预测系统中的副本数量。仿真结果表明,该系统具有更好的可用性和低的副本开销。     

基于P2P的分布式多媒体服务

在两个层次的P2P网络中,利用组间复制算法将多媒体内容复制到各个组中,改善分布效率;组内复制算法将多媒体内容复制到Peer中,提高内容的可用性。模拟显示本系统的时延比FreeNet网络小20%,比随机复制系统小50%,能提供更好的视频服务质量,该方法是分布式、可扩展、高效的。     

BitDew: A data management and distribution service with multi-protocol file transfer and metadata abstraction

Desktop Grids use the computing, network and storage resources from idle desktop PCs distributed over multiple-LANs or the Internet to compute a large variety of resource-demanding distributed applications. While these applications need to access, compute, store and circulate large volumes of data, little attention has been paid to data management in such large-scale, dynamic, heterogeneous, volatile and highly distributed Grids. In most cases, data management relies on ad hoc solutions, and providing a general approach is still a challenging issue. A new class of data management service is desirable to deal with such a variety of file transfer protocols than client/server, P2P or the new and emerging Cloud storage service.To address this problem, we propose the BitDew framework, a programmable environment for automatic and transparent data management on computational Desktop Grids. This paper describes the BitDew programming interface, its architecture, and the performance evaluation of its runtime components. BitDew relies on a specific set of metadata to drive key data management operations, namely life cycle, distribution, placement, replication and fault tolerance with a high level of abstraction. The BitDew runtime environment is a flexible distributed service architecture that integrates modular P2P components such as DHTs (Distributed Hash Tables) for a Distributed Data Catalog and collaborative transport protocols for data distribution. We explain how to plug-in new or existing protocols and we give evidence of the versatility of the framework by implementing HTTP, FTP and BitTorrent protocols and access to the Amazon S3 and IBP Wide Area Storage. We describe the mechanisms used to provide asynchronous and reliable multi-protocols transfers. Through several examples, we describe how application programmers and BitDew users can exploit BitDew's features. We report on performance evaluation using micro-benchmarks, various usage scenarios and data-intense bioinformatics application, both in the Grid context and on the Internet. The performance evaluation demonstrates that the high level of abstraction and transparency is obtained with a reasonable overhead, while offering the benefit of scalability, performance and fault tolerance with little programming cost.     

Towards an autonomic performance management approach for a cloud broker environment using a decomposition–coordination based methodology

Efficient resource allocation of computational resources to services is one of the predominant challenges in a cloud computing environment. Furthermore, the advent of cloud brokerage and federated cloud computing systems increases the complexity of cloud resource management. Cloud brokers are considered third party organizations that work as intermediaries between the service providers and the cloud providers. Cloud brokers rent different types of cloud resources from a number of cloud providers and sublet these resources to the requesting service providers. In this paper, an autonomic performance management approach is introduced that provides dynamic resource allocation capabilities for deploying a set of services over a federated cloud computing infrastructure by considering the availability as well as the demand of the cloud computing resources. A distributed control based approach is used for providing autonomic computing features to the proposed framework via a feedback-based control loop. This distributed control based approach is developed using one of the decomposition–coordination methodologies, named interaction balance, for interactive bidding of cloud computing resources. The primary goals of the proposed approach are to maintain the service level agreements, maximize the profit, and minimize the operating cost for the service providers and the cloud broker. The application of interaction balance methodology and prioritization of profit maximization for the cloud broker and the service providers during resource allocation are novel contributions of the proposed approach.     

Data Placement in P2P Data Grids Considering the Availability, Security, Access Performance and Load Balancing

Data dependability is an important issue in data Grids. Replication schemes have been widely used in distributed systems to ensure availability and improve access performance. Alternatively, data partitioning schemes (secret sharing, erasure coding with encryption) can be used to provide availability and, in addition, to offer confidentiality protection. In peer-to-peer data Grids, such confidentiality protection is essential since the nodes hosting the data shares may not be trustworthy or may be compromised. However, difficulties in generating new shares and potential security concerns for share reallocation make a pure data partitioning scheme not easily adaptable to dynamic user access patterns. In this paper, we consider combining replication and data partitioning to assure data availability, confidentiality, load balance, and efficient access for data Grid applications. Data are partitioned and shares are dispersed. The shares may be replicated to achieve better performance, load balance, and availability. Models for assessing confidentiality, availability, load balance, and communication cost are developed and used as the metrics to guide placement decisions. Due to the nature of contradicting goals, we model the placement decision problem as a multi-objective problem and use a genetic algorithm to determine solutions that are approximate to the Pareto optimal placement solutions.     

面向分布式协同设计的对等信息共享系统

为了实现分布式协同设计中的共享信息快速检索以及多副本同步,提出了基于对等网结构的信息共享系统,给出了该信息共享系统的节点模型、管理策略及信息检索模型,提出了一种结合分布式哈希表和聚类的检索方法,保证了用户能够在协同设计系统中快速地精确检索和“盲目”检索,实现了系统的用户透明。为了保证分布式多副本同步,提出“对等锁”作为一致性维护方法。该文给出了系统的具体实现方法,并给出了实例。     

Towards a data processing plane: An automata-based distributed dynamic data processing model

Data processing complexity, partitionability, locality and provenance play a crucial role in the effectiveness of distributed data processing. Dynamics in data processing necessitates effective modeling which allows the understanding and reasoning of the fluidity of data processing. Through virtualization, resources have become scattered, heterogeneous, and dynamic in performance and networking. In this paper, we propose a new distributed data processing model based on automata where data processing is modeled as state transformations. This approach falls within a category of declarative concurrent paradigms which are fundamentally different than imperative approaches in that communication and function order are not explicitly modeled. This allows an abstraction of concurrency and thus suited for distributed systems. Automata give us a way to formally describe data processing independent from underlying processes while also providing routing information to route data based on its current state in a P2P fashion around networks of distributed processing nodes. Through an implementation, named Pumpkin, of the model we capture the automata schema and routing table into a data processing protocol and show how globally distributed resources can be brought together in a collaborative way to form a processing plane where data objects are self-routable on the plane.     

一个P2P分布式数字签名系统

提出了一个基于P2P网络的分布式数字签名系统（PDDSS）,利用 peer节点进行CA的数字签名运算,取代了传统CA的集中式服务器。系统具有低成本,高可扩展性,高可用性和容侵性,同时采用可验证门限技术和主动密码技术确保CA私钥的安全。     

P2P data replication and trustworthiness for a JXTA-Overlay P2P system using fuzzy logic

P2P systems are very important for future distributed systems and applications. In such systems, the computational burden of the system can be distributed to peer nodes of the system. Therefore, in decentralized systems users become themselves actors by sharing, contributing and controlling the resources of the system. This characteristic makes P2P systems very interesting for the development of decentralized applications. Data replication techniques are commonplace in P2P systems. Data replication means storing copies of the same data at multiple peers thus improving availability and scalability. The trustworthiness of peers also is very important for safe communication in P2P system. The trustworthiness of a peer can be evaluated based on the reputation and actual behaviour of peers to provide services to other peers. In this paper, we propose two fuzzy-based systems for data replication and peer trustworthiness for JXTA-Overlay P2P platform. The simulation results have shown that in the first system, replication factor increases proportionally with increase of number of documents per peer, replication percentage and scale of replication per peer parameters and the second system can be used successfully to select the most reliable peer candidate to execute the tasks.     

基于混合式拓扑结构的P2P信息查找系统的研究和设计

对等网络所面临的两个最基本的问题是如何进行信息有效查找、定位以及如何进行网络的自我管理。本文介绍了一种基于混合式拓扑结构的分布式信息查找(DHH)体制。该体制可以实现信息的高效查找和节点的自我管理,同时达到可扩展性、有效性、可靠性、负载均衡和用户匿名性等指标。