Cloud Datacenter Selection Using Service Broker Policies:A Survey

Amid the landscape of Cloud Computing(CC),the Cloud Datacenter(DC)stands as a conglomerate of physical servers,whose performance can be hindered by bottlenecks within the realm of proliferating CC services.A linchpin in CC’s performance,the Cloud Service Broker(CSB),orchestrates DC selection.Failure to adroitly route user requests with suitable DCs transforms the CSB into a bottleneck,endangering service quality.To tackle this,deploying an efficient CSB policy becomes imperative,optimizing DC selection to meet stringent Qualityof-Service(QoS)demands.Amidst numerous CSB policies,their implementation grapples with challenges like costs and availability.This article undertakes a holistic review of diverse CSB policies,concurrently surveying the predicaments confronted by current policies.The foremost objective is to pinpoint research gaps and remedies to invigorate future policy development.Additionally,it extensively clarifies various DC selection methodologies employed in CC,enriching practitioners and researchers alike.Employing synthetic analysis,the article systematically assesses and compares myriad DC selection techniques.These analytical insights equip decision-makers with a pragmatic framework to discern the apt technique for their needs.In summation,this discourse resoundingly underscores the paramount importance of adept CSB policies in DC selection,highlighting the imperative role of efficient CSB policies in optimizing CC performance.By emphasizing the significance of these policies and their modeling implications,the article contributes to both the general modeling discourse and its practical applications in the CC domain.

基于Broker/Service模型的分布式产品数据管理系统架构研究

本文给出了基于Broker/Service模型的产品数据管理系统 (PDM)的体系结构及其原型的实现。它主要包括事件引擎和相应的功能Broker,其中事件引擎是一个WebService注册中心 ,它管理WebService的WSDL文件 ,并从中提取出EA规则 ,事件引擎根据EA规则进行传递、探测事件并触发Broker执行相应服务。基于Broker/Service模型的PDM结构降低了整个信息系统的复杂度 ,进一步提高了软件的开发效率 ,从而加快了系统的构建周期。

An Adaptive Trust Model of Web Services

This paper proposes a dynamic Web service trust (WS Trust) model, and somecorresponding trust metric evaluation algorithms. The main goal is to evaluate the trustworthinessand predict the future bchaxiors of entities in oeder to help users find trustworthy Web serviceproviders and prevent users from providing unfair ratings against service providers.

Service Model for Multi-Provider IP Service Management

In order to solve the problems associated with Internet IP services management, a generic service model for n multi-providcr IP service management is proposed, which is based on a generalization of the bandwidth broker idea introduced in the differentiated services （DiffServ） environment. This model consists of a hierarchy of service brokers, which makes it fit into providing end-to-end Internet services with QoS support. A simple and sealable mechanism is used to communicate with other cooperative domains to enable customers to dynamically setup services connections over multiple DiffServ domains. The simulation results show that the proposed model is real-time, which can deal with many flow requests in a short period of time, so that it is fit for the service management in a reasonably large network.

面向应用的可裁减嵌入式数据库管理系统

提出了一种可行的可裁减数据库的体系结构,阐述了系统如何实现功能的动态加载和扩展来适应特定应用的需要,为嵌入式数据库带来了新的解决方法。

Cloud Data Center Selection Using a Modified Differential Evolution

The interest in selecting an appropriate cloud data center is exponentially increasing due to the popularity and continuous growth of the cloud computing sector.Cloud data center selection challenges are compounded by ever-increasing users’requests and the number of data centers required to execute these requests.Cloud service broker policy defines cloud data center’s selection,which is a case of an NP-hard problem that needs a precise solution for an efficient and superior solution.Differential evolution algorithm is a metaheuristic algorithm characterized by its speed and robustness,and it is well suited for selecting an appropriate cloud data center.This paper presents a modified differential evolution algorithm-based cloud service broker policy for the most appropriate data center selection in the cloud computing environment.The differential evolution algorithm is modified using the proposed new mutation technique ensuring enhanced performance and providing an appropriate selection of data centers.The proposed policy’s superiority in selecting the most suitable data center is evaluated using the CloudAnalyst simulator.The results are compared with the state-of-arts cloud service broker policies.

Publishing NextGEOSS data on the GEOSS Platform

This paper is the second of a series that describes some of the main dataset resources presently shared through the GEOSS Platform. The GEOSS Platform was created as the technological tool to implement interoperability among the Global Earth Observation System of Systems (GEOSS);it is a brokering infrastructure that presently brokers more than 190 autonomous data catalogs and information systems. This paper is focused on the analysis of the NextGEOSS datasets describing the data publishing process from NextGEOSS to the GEOSS platform. In particular, both the administrative registration and the technical registration were taken into consideration. One of the most important data shared by the GEOSS Platform are the NextGEOSS datasets: the present study provides some insights in terms of GEOSS user searches for NextGEOSS data.