Large Number Of Services Research Articles

Scale-out NUMA

Emerging datacenter applications operate on vast datasets that are kept in DRAM to minimize latency. The large number of servers needed to accommodate this massive memory footprint requires frequent server-to-server communication in applications such as key-value stores and graph-based applications that rely on large irregular data structures. The fine-grained nature of the accesses is a poor match to commodity networking technologies, including RDMA, which incur delays of 10-1000x over local DRAM operations. We introduce Scale-Out NUMA (soNUMA) -- an architecture, programming model, and communication protocol for low-latency, distributed in-memory processing. soNUMA layers an RDMA-inspired programming model directly on top of a NUMA memory fabric via a stateless messaging protocol. To facilitate interactions between the application, OS, and the fabric, soNUMA relies on the remote memory controller -- a new architecturally-exposed hardware block integrated into the node's local coherence hierarchy. Our results based on cycle-accurate full-system simulation show that soNUMA performs remote reads at latencies that are within 4x of local DRAM, can fully utilize the available memory bandwidth, and can issue up to 10M remote memory operations per second per core.

Scale-out NUMA

Emerging datacenter applications operate on vast datasets that are kept in DRAM to minimize latency. The large number of servers needed to accommodate this massive memory footprint requires frequent server-to-server communication in applications such as key-value stores and graph-based applications that rely on large irregular data structures. The fine-grained nature of the accesses is a poor match to commodity networking technologies, including RDMA, which incur delays of 10-1000x over local DRAM operations. We introduce Scale-Out NUMA (soNUMA) -- an architecture, programming model, and communication protocol for low-latency, distributed in-memory processing. soNUMA layers an RDMA-inspired programming model directly on top of a NUMA memory fabric via a stateless messaging protocol. To facilitate interactions between the application, OS, and the fabric, soNUMA relies on the remote memory controller -- a new architecturally-exposed hardware block integrated into the node's local coherence hierarchy. Our results based on cycle-accurate full-system simulation show that soNUMA performs remote reads at latencies that are within 4x of local DRAM, can fully utilize the available memory bandwidth, and can issue up to 10M remote memory operations per second per core.

Child and Parent Characteristics Affecting the Authorization and Expenditure of Funds for Early Intervention Services

This article examines parent and child characteristics that are associated with utilization of funds authorized under Part C of the Individuals With Disabilities Education Act (IDEA). Child age and the presence of parent service needs are among the variables that influence how much early intervention service is available for infants and toddlers with developmental delays and disabilities, as authorized by the Individual Family Service Plan (IFSP). Higher levels of child need were associated with a larger number of services authorized, and greater amounts of unspent funds. It appears that children of high needs parents are less likely to use additional services their children need. These findings are interpreted to suggest that family and child characteristics that promote larger authorizations for Part C services may also limit their ability to utilize all of the services identified in the IFSP. In addition, this study found that contrary to expectations, the home environment was not superior to specialty and clinic settings on parent involvement in early intervention activities.

Analysis and Enhancement of Service Discovery Framework

Web service is a software system designed to exploit the internet and its infrastructure for interacting with application available in remote machine in any corner of the world. Standard web protocols and XML coding are made use of .Large number of services are available on the web which can be composed to form a new useful service .Since more than one service might suite for our business application, discovering and selecting appropriate service is an challenge in e-business .We provide a spectrum of work investigated by researchers and suggest a framework which considers the QoS factors required by the clients and provide the suitable service to the client.

CLOUD COMPUTING AND ITS SECURITY ASPECTS

Cloud computing is a new computing paradigm in the field of it that provides hosted services to a large number of user on demand basis over the internet. They are internet based network that has large numbers of servers. It allows to use the services only when you want and pay only for the amount what you have used. Since cloud computing share distributed resources over an open environment, so security becomes a major concern here. To improve the work performance different services are distributed on different servers but the security and safety aspects are remaining insufficient. Security is the one of major issues that hampers the growth of cloud. So, in this paper we first try to give an idea about cloud computing and then concentrate on the major security aspects of cloud computing paradigm.

EFFICIENT LARGE-SCALE SERVICE CLUSTERING VIA SPARSE FUNCTIONAL REPRESENTATION AND ACCELERATED OPTIMIZATION

Clustering techniques offer a systematic approach to organize the diverse and fast increasing Web services by assigning relevant services into homogeneous service communities. However, the ever increasing number of Web services poses key challenges for building large-scale service communities. In this paper, we tackle the scalability issue in service clustering, aiming to accurately and efficiently discover service communities over very large-scale services. A key observation is that service descriptions are usually represented by long but very sparse term vectors as each service is only described by a limited number of terms. This inspires us to seek a new service representation that is economical to store, efficient to process, and intuitive to interpret. This new representation enables service clustering to scale to massive number of services. More specifically, a set of anchor services are identified that allows each service to represent as a linear combination of a small number of anchor services. In this way, the large number of services are encoded with a much more compact anchor service space. Despite service clustering can be performed much more efficiently in the compact anchor service space, discovery of anchor services from large-scale service descriptions may incur high computational cost. We develop principled optimization strategies for efficient anchor service discovery. Extensive experiments are conducted on real-world service data to assess both the effectiveness and efficiency of the proposed approach. Results on a dataset with over 3,700 Web services clearly demonstrate the good scalability of sparse functional representation and the efficiency of the optimization algorithms for anchor service discovery.

Availability Allocation for Distributed Clusters of the Cloud Infrastructure

The cloud environment capitalizes on the built-in redundancy of the large number of servers that make them up by enabling high levels of availability and reliability for applications. In this paper, we address the availability problem of the heterogeneous distributed clusters in the cloud and propose an availability allocation model with the goal of maximizing the system reliability. The allocation model involves three kinds of services according to the coupling classification. And the availability analysis scheme is designed for each coupling type. Besides, the prior knowledge of all the server availability value is imported to simplify the service disposal and achieve an optimal solution in a short time. The experiments show that this algorithm finds a good initial solution for availability allocation problem.

Online load balancing under graph constraints

In several data center settings, each arriving job may only be served by one of a subset of servers. Such a graph constraint can arise due to several reasons. One is locality of the data needed by a job; for example, in content farms (e.g. in Netflix or YouTube) a video request can only be served by a machine that possesses a copy. Motivated by this, we consider a setting where each job, on arrival, reveals a deadline and a subset of servers that can serve it. The job needs to be immediately allocated to one of these servers, and cannot be moved thereafter. Our objective is to maximize the fraction of jobs that are served before their deadlines. For this online load balancing problem, we prove an upper bound of 1-1/e on the competitive ratio of non-preemptive online algorithms for systems with a large number of servers. We propose an algorithm - INSERT RANKING - which achieves this upper bound. The algorithm makes decisions in a correlated random way and it is inspired by the work of Karp, Vazirani and Vazirani on online matching for bipartite graphs. We also show that two more natural algorithm, based on independent randomness, are strictly suboptimal, with a competitive ratio of 1/2.

Série histórica de custos com terapia de substituição renal no município do Rio de Janeiro (1995-2009)

Objetivou-se avaliar a tendência temporal do custo total de terapia de substituição renal e a proporção entre custo e solicitações de Autorizações de Procedimentos Ambulatoriais de Alta Complexidade/Custo no município do Rio de Janeiro, entre 1995 e 2009, em totais e segundo prestador. Estudo quantitativo, descritivo, tipo série temporal. Utilizaram-se informações referentes aos valores e quantidades de autorizações de procedimentos de alta complexidade para terapia de substituição renal por ano, disponíveis no DATASUS, coletadas entre fevereiro e março de 2011. Observou-se tendência crescente para o custo total e o total de autorizações destes procedimentos (y=3,8414x + 16,904, R²=0,9665 e y=14519x + 299719, R²=0,8835, respectivamente). Há uma diferença estatisticamente significativa (p<0,001) da variação da tendência quando comparados os serviços públicos e os privados. Conclui-se que há uma tendência em programar cada vez mais serviços nos hospitais públicos, tornando crescente a demanda por profissionais qualificados para atuação na área.

The concept of DSM AND ADT INTEGRATION in the PRODUCT DESIGN PROCESS

In manufacturing, product design is often very complex and requires the participation of a large number of services and material resources. Managing these resources can be very costly in terms of time, risk and money. The use of well-known tools (e.g. PERT, CPM and Gantt) alone cannot establish a detailed andoptimized planning in the execution of different stages and tasks of a project. To address this problem theDesign Structure Matrix (DSM) and the Axiomatic Design Theory (ADT) appear to be an interesting solution.This paper presents a DSM and ADT integrated tool as a part of the decomposition-integration problem inproduct design development process, where the latter is more concerned with mapping customer’s needs from functional requirements to design parameters, while the former is better suited to modelling the interactions and the integration of the design parameters. It also presents some algorithms related to both DSM and ADT used for manipulating projects-based DSM information, coordination and timing requirements, and provides a complementary between them. The discussion in this paper addresses the implementation of concurrent design engineering which is the greatest challenge faced by design managers.

The need for speed and stability in data center power capping

Data centers can lower costs significantly by provisioning expensive electrical equipment (such as UPS, diesel generators, and cooling capacity) for the actual peak power consumption rather than server nameplate power ratings. However, it is possible that this under-provisioned power level is exceeded due to software behaviors on rare occasions and could cause the entire data center infrastructure to breach the safety limits. A mechanism to cap servers to stay within the provisioned budget is needed, and processor frequency scaling based power capping methods are readily available for this purpose. We show that existing methods, when applied across a large number of servers, are not fast enough to operate correctly under rapid power dynamics observed in data centers. We also show that existing methods when applied to an open system (where demand is independent of service rate) can cause cascading failures in the software service hosted, causing the service performance to fall uncontrollably even when power capping is applied for only a small reduction in power consumption. We discuss the causes for both these short-comings and point out techniques that can yield a safe, fast, and stable power capping solution. Our techniques use admission control to limit power consumption and ensure stability, resulting in orders of magnitude improvement in performance. We also discuss why admission control cannot replace existing power capping methods but must be combined with them.

Memetic algorithms applied to the optimization of workflow compositions

The selection of services of a workflow based on Quality of Service (QoS) attributes is an important issue in service-oriented systems. QoS attributes allow for a better selection process based on non-functional quality criteria such as reliability, availability, and response time. Past research has mostly addressed this problem with optimal methods such as linear programming approaches. Given the nature of service-oriented systems where large numbers of services are available with different QoS values, optimal methods are not suitable and therefore, approximate techniques are necessary. In this paper, we investigate Genetic algorithms and particle swarm optimization for the service selection process. In particular, both methods are combined with an optimal assignment algorithm (Munkres algorithm) in order to achieve higher solution qualities (success ratios) and to form a so called memetic algorithm. Experiments are conducted to investigate the suitability of the approaches and to compare the memetic algorithms with their non-memetic counterparts. The results reveal that the memetic algorithms are very suitable for the application to the workflow selection problem.

Use of Mental Health Services by Survivors of Intimate Partner Violence

Fifty women survivors of intimate partner violence (IPV) were recruited from a legal advocacy program to participate in a study designed to assess current rates of posttraumatic stress disorder (PTSD), depression, and alcohol and substance abuse among a sample of abused women and to examine the types of services survivors of IPV had used in the previous 12 months. In addition, the authors sought to understand how the presence of substance abuse, PTSD, and/or depression affects access and utilization of services by IPV survivors. Fifty-four percent of these IPV survivors were experiencing either PTSD, clinical depression, or both. While women with either PTSD or depression used a significantly larger number of services overall, the majority had not used any mental health services, even though they frequently reported services were accessible. Given the high rates of PTSD and depression in this sample, these abused women were clearly not receiving adequate mental health care. Furthermore, many reported having trouble accessing housing, legal services, crisis lines, and medical care—services that are fundamental to safety. Practitioners working with abused women should assess for PTSD and depression, and be prepared to either treat each condition or provide effective referrals.

Research on New Algorithm of Network Topology Design Based on Cloud Integration

Analyzed integrated logical structure of the cloud, back-end cloud computing systems, tens of thousands of servers, how to organize such a large number of servers is the cloud computing system efficient and stable operation of one of the key issues. We surveyed the requirement of cloud computing networking. Analyzed the architecture of cloud computing networking topology, and thought that the networking topology should be composed of two parts the center switch trunk and some tree shape branch subnet. Then we proposed the Self Adaptive Algorithm for the center swish trunk’s topology design based on the graph theory, optimization theory and classic greedy algorithm. Finally we do some experiments and comparison to verify the algorithm’s usability and advantages.

Municipal service delivery: A multi‐stakeholder framework

AbstractA large number of services that affect people's lives in modern economies are delivered by cities. This paper proposes a framework for municipal service delivery. Within this framework, the paper highlights challenges cities face when combining human and automated service delivery. The paper also describes how to harness social media to facilitate citizen engagement in the process of addressing some of these challenges. Lastly, the paper underlines the need for institutional arrangements and flexible software systems that can facilitate citizen‐centered municipal service delivery and social media engagement. © 2012 Wiley Periodicals, Inc.

A distributed multi-agent planning approach for automated web services composition

The ability to automatically answer a request that requires the composition of a set of web services has received much interest in the last decade, as it supports B2B applications. It aims at selecting and inter-connecting services provided by different partners in response to client requests. Planning techniques are used widely in the literature to describe web services composition problem. However, since web services proliferate day after day, classical planners are no longer well suited to compose web services in a reasonable time. This weakness is due to the explosion of the search space caused by the large number of services and the broad range of data exchanged among services. Therefore it is more interesting to use a decentralized planner to distribute the search space and the computing load taking into account the distributed nature of the problem. In this paper, we propose a distributed multi-agent approach to solving the web services composition problem at runtime. Our approach consists of a set of web services agents where each agent has a set of services organised in a graph. To respond to a request, agents propose their best local partial plans which are partial paths in the graph. They then coordinate their partial plans to provide the best global plan for the submitted request. The analysis of the complexity and the results of the implementation show the ability of our approach to scaling up when compared to the state-of-the-art techniques for automated web services composition.

Automatically configuring the network layer of data centers for cloud computing

With the requirement of very large data centers for cloud computing, the challenge lies in how to produce a scalable and inexpensive design to interconnect a large number of servers in data centers while providing fault tolerance and high network capacity. Internet Protocol (IP)-based data center networks (DCNs) can support a sufficiently large number of machines and dynamic multi-path routing. However, the complex and error-prone manual configuration of IP-based DCNs hinders its deployment. In this paper, we propose DCZeroconf, a fully automatic IP address configuration mechanism, to eliminate the burden of manual configurations of the IP addresses of servers and switches in data centers. We have implemented a prototype system to validate the effectiveness of DCZeroconf via extensive experiments and simulations. The evaluation results demonstrate that DCZeroconf supports different topologies, and the assigned IP addresses can be automatically adjusted upon dynamic topology changes. In addition, the entire automatic process can be completed in seconds or less.

Web service composition algorithm based on TOPSIS

Independent quality of service (QoS) registration center is difficult to monitor QoS with lots of requests in Internet environment with a large number of services and lots of service requests. It is able to reduce the load and decrease the failure rate by using multiple QoS registration centers to monitor QoS of some services with lots of requests. In addition, the heterogeneous QoS data close to user's habitual expression and adapts to the environment with complexity and uncertainty. This paper introduces a novel Web service composition algorithm based on technique for order preference by similarity to an ideal solution (TOPSIS) (WSCA_TOPSIS) to solve the above difficulties for the first time. WSCA_TOPSIS can support multiple decision-makers and heterogeneous QoS data. It includes three main steps: normalizing decision matrix, evaluating alternatives synthetically and evaluating group alternatives synthetically. Other contributions of the paper include a novel algorithm of aggregating QoS and a set of experiments that demonstrate the benefits and effectiveness of our approach. Experimental results show that the proposed algorithm can better support Web service composition with heterogeneous QoS data and multiple decision-makers.

Negotiating Services with ASEAN: The EU between the WTO and Japan

In future Free Trade Agreement (FTA) negotiations between the EU and individual Association of Southeast Asian Nations (ASEAN) members, trade in services will feature prominently. Such negotiations will be constrained by the network of ASEAN's bilateral Economic Partnership Agreements (EPAs) with Japan, because the EPAs' approach differs from the EU approach at the World Trade Organization's Doha Round in two ways. First, Japan adopted the approach to services trade liberalization favoured by ASEAN. Second, Japan accepted ASEAN's regulations in the services sectors that they liberalized and allowed the movement of certain categories of natural persons to Japan. In return, ASEAN countries opened a large number of services sectors to Japanese investment.

Automatic Language Translation

In this paper, the authors demonstrate that language diversity imposes a significant barrier in message communication like Short Messaging Service (SMS). SMS and other messaging services, including Multimedia Messaging Service (MMS) and e-mail, are widely used for person-to-person and Business-to-Consumer (B2C) communications due to their reach, simplicity and reliability of delivery. Reach and service delivery can be further enhanced if the message is delivered in the recipient’s preferred language. Using language translation software and a database server, the authors show that the messages can be delivered as per language preference of the recipient irrespective of the language of the original message. They demonstrate the proposed mechanism can deliver a large number of services, such as education, health care management, notification in emergency situations, news and weather reports, to those who are currently not able to access them due to language barrier.