Call for Papers—Service Science Special Issue on Cloud Computing as a Service

Cloud computing and big data: Technologies and applications

Intelligent approaches for security technologies

Research purpose: to develop the technology of operational-technical management of scientific and educational services. Methods: methods of patent research and analysis of critical technologies of information and control systems; methods of system approach to organize and manage IT services to meet business needs. Topicality. The state policy in the sphere of national security and socio-economic development of the Russian Federation, carried out in the face of new threats requires correcting structural imbalances in the economy. National interests should be implemented by means of strategic priorities in the various sectors of the economy, in the financial sphere - the timely implementation of government programs. In the Message of the President of the Russian Federation Vladimir Putin to the Federal Assembly on December 1, 2016 one of the priorities defined the creation of a national research infrastructure, representing the information and technology platform for the integration of the intellectual resources in the field of science, education and production with the aim of creating the conditions for qualitative changes in the field of science and technology. In this connection, scientific-methodical and systematic technical issues to systematize services of scientific and educational institutions of the country and creation of the united informational and analytical system of the management of such services seem to be topical. Within the framework of the whole complex of problems to design such a system, the development issues of technologies for the effective operational-technical management of scientific and educational services are of great interest. Results. The technology of operational-technical management of scientific and educational services was developed, which is a complex of technical solutions to provide information support for the activities of organizational systems – consumers and suppliers of scientific and educational services. This article presents the main provisions of technology for operational-technical management of scientific and educational services, based on innovative technical solutions and taking into account the perspective of digital trends to ensure business services. The business service in the article means IT service that directly supports a business process – the process of providing for scientific or educational service, based on the unified information and managed environment. The proposed technology is the contribution of the scientific community in the realization of the strategic national priorities of the Russian Federation. Conclusion. The advantage for the provided technology, in comparison with analogues, is to increase the efficiency of the management of organizational systems – consumers and suppliers of scientific and educational services, due to the automatic assessment of their business services and automatic management of activities with the assessment. The method, used in this technology, to provide consumers with scientific and educational services in the form of business services in accordance with the concept of IT service management ensures universality of approach to create the knowledge base and algorithms to use the knowledge for managing IT infrastructure support of business services, and to manage business services. This approach allows to optimize the composition of the applications in the management of scientific and educational services, as well as to ensure the conditions at the design stage for analysis and decision-making by the choice of IT infrastructure for the provision of scientific and educational services to consumers.

The complexity of computer systems, networks and applications, as well as the advancements in computer technology, continue to grow at a rapid pace. Mathematical analysis, modeling and optimization have been playing, and continue to play, an important role in research studies to investigate fundamental issues and trade-offs at the core of performance problems in the design and implementation of complex computer systems, networks and applications. On June 20, 2014, the 16th Workshop on MAthematical performance Modeling and Analysis (MAMA 2014) was held in Austin TX, USA, sponsored by ACM SIGMETRICS, and held in conjunction with SIGMETRICS 2014. This workshop seeks to bring together researchers working on the mathematical, methodological and theoretical aspects of performance analysis, modeling and optimization. It is intended to provide a forum at SIGMETRICS conferences for talks on early research in the more mathematical areas of computer performance analysis. These talks tend to be based on very recent research results (including work in progress) or on new research results that will be otherwise submitted only to a journal (or recently have been submitted to a journal). Thus, part of the goal is to complement and supplement the SIGMETRICS Conference program with such talks without removing any theoretical contributions from the main technical program. Furthermore, we continue to experience the desired result of having abstracts from previous MAMA workshops appear as full papers in the main program of subsequent SIGMETRICS and related conferences. All submissions were reviewed by at least 4 members of the program committee, from which a total of 13 were selected for presentation at the MAMA 2014 workshop. This special issue of Performance Evaluation Review includes extended abstracts relating to these presentations (arranged in the order of their presentation), which cover a wide range of topics in the area of mathematical performance analysis, modeling and optimization. The study of Gelenbe examines the backlog of energy and of data packets in a sensor node that harvests energy, computing the properties of energy and data backlogs and discussing system stability. Meyfroyt derives asymptotic results for the coverage ratio under a specific class of spatial stochastic models (Cooperative Sequential Adsorption) and investigates the scalability of the Trickle communication protocol algorithm. The study of Tune and Roughan applies the principle of maximum entropy to develop fast traffic matrix synthesis models, with the future goal of developing realistic spatio-temporal traffic matrices. Bradonjić et al. compare and contrast the capacity, congestion and reliability requirements for alternative connectivity models of large-scale data centers relative to fat trees. The study of Rochman et al. considers the problem of resource placement in network applications, based on a largescale service faced with regionally distributed demands for various resources in cloud computing. Xie and Lui investigate the design and analysis of a rating system and a mechanism to encourage users to participate in crowdsourcing and to incentivize workers to develop high-quality solutions. The study of Asadi et al. formulates a general problem for the joint per-user mode selection, connection activation and resource scheduling of connections using both LTE and WiFi resources within the context of device-todevice communications. Zheng and Tan consider a nonconvex joint rate and power control optimization to achieve egalitarian fairness (max-min weighted fairness) in wireless networks, exploiting the nonlinear Perron-Frobenius theory and nonnegative matrix theory. The study of Goldberg et al. derives an asymptotically optimal control policy for a stochastic capacity problem of dynamically matching supply resources and uncertain demand, based on connections with lost-sales inventory models. Ghaderi et al. investigate a dynamic stochastic bin packing problem, analyzing the fluid limits of the system under an asymptotic best-fit algorithm and showing it asymptotically minimizes the number of servers used in steady state. The study of Tizghadam and Leon-Garcia examines the impact of overlaying or removing a subgraph on the Moore-Penrose inverse of the Laplacian matrix of an existing network topology and proposes an iterative method to find key performance measures. Miyazawa considers a two-node generalized Jackson network in a phase-type setting as a special case of a Markov-modulated twodimensional reflecting random walk and analyzes the tail asymptotics for this reflecting process. The study of Squillante et al. investigates improvement in scalability of search in networks through the use of multiple random walks, deriving bounds on the hitting time to a set of nodes and on various performance metrics.

As data explosion dramatically accelerating from IoT (Internet of Thing) edge devices, high performance server has been dominating deployment in the recent CSPs (Cloud Service Providers) data center for conquering the challenge of huge amount of data processing on cloud computing. Microprocessor architecture advance continues to involve with more core count, higher frequency, as well as larger on-die memory cache size, pursuing for higher computing performance while trading off with more power consumption. Nowadays, CSPs have been experiencing the power constraint challenge of high-performance server deployed for TCO (total cost ownership) efficiency in their traditional typical 4KW co-lo or 8KW self-built air-cooling data center where the infrastructures restructured for liquid cooling is unfeasible.This paper introduces an advanced server system design with 3D VC (3-Dimensional Vaper Chamber) heat sink for power constraint data center deployment. Compared with the traditional air-cooled heat sink solutions, 3D VC heat sink has better temperature uniformity and cost advantages. With the 3D VC thermal solution in server system design, CPU thermal performance can achieve 2°C improvement vs. the solution of traditional heat pipes and VC plates heat sinks, and the TCO saving is up to 15% to 20%.

The most widely touted advantages provided by Amazon EC2 are very similar to those offered by traditional outsourced data centers that offer reduced costs for hardware processing, storage, bandwidth and software. The major difference with EC2-like infrastructure clouds is that they are available to any size firm, from an individual backing up their music collection to a major retailer. Unlike complex data center service agreements, EC2 services are pay by use. Finally, they can be accessed easily through a small number of web services.

The IT Industry and the wider media are abuzz with the phrase “cloud computing” and most of us have no idea what this latest terminology means. This paper starts by addressing the question – “what is cloud computing, and provides an understanding of the technology?” Cloud computing is related to technologies that has been around for ages, however, what can be done differently with the same technology when integrated with Internet is cloud computing.Individuals who might be considering cloud computing services for personal use will also benefit by the information provided. Web sites like Flickr, FaceBook, YouTube and others are used to store and share personal photos, music and videos for free. Easy as: 1). Register, 2). Upload, 3). Share. Free and easy, there has to be a downside, and there is awareness regarding this.There is information regarding cloud computing for businesses! Businesses, who wish to get on the “flight to the clouds” like their peers to keep their heads above the “cloud” and competition. With cloud service providers, businesses can tap into the IT services that they need, when they need, for as long as they need; without investing in any IT infrastructure. The result is a far more agile and cost-effective IT services and this paper looks at how and why.After looking at the good of cloud computing, the bad, and the ugly is revealed. Not all our experiences on the Internet have been totally positive. A range of security and trust issues exist. Individuals and businesses ask is “how secured are their information once it is with the cloud service providers?” There is analysis on the ownership of data and information stored with the cloud service providers and taxonomy of data that you post on social networking web sites.Finally, anecdotes about cloud computing that support our endeavour to compute in the cloud. Cloud computing is not a hype, it is a reality. Cloud computing is not a fad, it is here to stay. The question is no longer “will cloud computing happen?” but “how you are going to exploit this technology?”Keywordscloud computingvirtual computingcluster computingdistributed computingpervasive computing

On the interplay of Internet of Things and Cloud Computing: A systematic mapping study

With the rapid development of national economy, our demand for power resources has also increased rapidly. The traditional power grid can not be achieved operational status of equipment for effective monitoring and control, we will not be able to ensure the quality and quality of electricity service. Cloudbased build smart grid information platform enables gathering the parameter of grid operation state, greatly increasing the economic efficiency of power enterprises. Firstly, cloud computing and smart grid briefly described, and then pointed out that cloud computing applications in the smart grid information platform, and specialized of cloud-based smart grid information platform, in order for the power grid enterprises to enhance their level of service and provide effective reference. KEYWORD: cloud computing; smart power grids; information platform; Application 4th International Conference on Mechanical Materials and Manufacturing Engineering (MMME 2016) © 2016. The authors Published by Atlantis Press 202 3 THE MAIN PROBLEM IS STILL THE SMART GRID INFORMATION PLATFORM FACING The transition to a cloud computing data center. Our data center because of the different regions and the degree of information presents different characteristics, some data centers already have a basic cloud computing capabilities, but most data centers still remain in the initial level, to ensure the normal operation of the existing data center power under the premise, gradual transition to cloud computing data center in order to meet future requirements of the development of smart grid. Restricting data transmission problem. State Grid Corporation between provincial branches and there are a lot of data needs to be transmitted, will bring massive data transmission efficiency decreases, taking into account the load balancing device between the cloud node, thus building a wide area network channels to resolve data transmission problem. Security of data transmission. Data Center for Cloud Computing power companies to build internal private cloud, capable of self-maintenance and management, system wide area network data transmission services, according to the third security zone defined security partition, and install proprietary equipment production area and external public network isolation . 4 CLOUD COMPUTING APPLICATIONS IN THE SMART GRID INFORMATION POLICY PLATFORM Integrate and optimize the management of heterogeneous resources. Among the smart grid systems, data resources, information systems between various platforms and mutually dispersed, severe heterogeneity, thus leading to the integration of the quality of information sharing to increase difficulty, unable to effectively improve network management efficiency for the power distribution system electrical work quality management and marketing operations system maintenance upgrade will not be able to effectively meet demand (Jie Yang, 2014). Cloud computing technology enables the power system to effectively integrate the various business data and computing resources on the basis of information for business collaboration platform built on effective, able to satisfy the huge demand for smart grid information resource sharing. Cloud computing network virtualization and application virtualization technology, the server virtualization technology and other resources to achieve each service abstraction, and then realize the difference between the system and the software effectively eliminated by the appropriate method to achieve the effective integration of information resources, and then to optimize the management, greatly improving the efficiency of heterogeneous resources management applications. Distributed storage and management of large volume of data. After application of smart grid information platform construction, customer service requests varied, huge data volume information brought it to the storage and management of data provides a great challenge. Cloud computing technology in general face amount of data each smart grid system and unit collected using forms distributed storage of data to achieve the effective storage, greatly to ensure the security and reliability of data storage. GFS effective use of technology with each node, the master server is responsible for the effective management of the whole file system, the file system and complete the work of the metadata stored in the data block is the main server for data storage block sliced, and by saving three or more redundant backup storage. At the same time, client access and complete access to the main block server information. Fast Power System Parallel Computation and Treatment. Smart grids and information platform for the large volume of data to provide stable operation of the power grid data base, but more critical is the analysis and design of each system operating data, planning and decision-making, and even failures and transient stability, state estimation and intelligent a variety of computing and content analysis and decision-making process, its huge computing needs, general computing system can not reach its goal (Wang, Mengxue, 2015). Cloud computing technology through parallel computing technology has greatly enhanced parallel processing capability of the power system, which provides parallel programming model makes more simple and efficient parallel algorithms. MapReduce as Google made an important parallel programming model, and its role in large data sets in parallel computing plays a very prominent. Parallel processing job results by the client to achieve effective user submitted, via decomposition automated master role, the corresponding task scheduling to working nodes and nodes work completed by the specific calculations and perform the appropriate task. 5 SMART GRID INFORMATION PLATFORM CLOUD COMPUTING ANALYSIS Cloud Computing Smart Grid Information Platform Architecture. Smart grid technology information platform architecture cloud computing include the following several levels and aspects (Yan Cui, 2015): First, that the platform infrastructure layer is the integration of the various hardware resources and related management capabilities of virtualized using virtual technology to achieve the corresponding hardware devices such as computers and network storage devices abstraction, and then complete the automation and optimization of resource data and load management; secondly, the main platform for the integration of the various layers of software

There are several definitions and measurements for scalability, elasticity, and efficiency in cloud computing. However, stakeholders face minimal direction when selecting measures and definitions for these high-quality traits, which might result in misconceptions. It seems that there is not a lot of proof to support the assertion that cloud computing is more cost-effective than traditional data center procedures, despite the fact that it is currently all the rage. It usually makes use of elastic, dynamically expandable, on-demand self-service accessibility and pools of frequently used virtual resources. An entirely new model for the provision of IT services is introduced by cloud computing. Because of cloud computing rapid startup, flexibility, scalability, and cost, it has the potential to improve business and IT operations. Despite its many benefits and affordable options for IT service and growth, cloud computing poses new threats and the possibility of security lapses. Management needs to understand and evaluate cloud computing risks in order to protect systems and data from security vulnerabilities. In order to provide safe cloud computing environments, this study focuses on risk reduction for cloud computing security.

The concept Cloud computing has not only reshaped the field of distributed systems but also fundamentally changed how business potential extends today. In recent advancements, Cloud computing applications are provided as services to end-users. The application services hosted under Cloud computing model have complex provisioning, configuration, and deployment requirements How to use Cloud computing resources efficiently and gain the maximum profits with efficient utilization of resources is one of the Cloud computing service providers' ultimate goals. Repetitive evaluation of the performance of Cloud provisioning policies, application workload models, and resources performance models in dynamic system are difficult to achieve and rather a time consuming and costly approach. To overcome this challenge, Cloud analyst simulator based on Cloud Sim has been proposed which enables the modeling and simulation in cloud's ambience. The objective of this paper is to prove that the choice of VM Scheduling Policy in Cloud computing model significantly improves the application performance under resource and service demand variations. We will discuss different Virtual Machine (VM) Scheduling Policies implemented and their performance analysis in Virtual environment of cloud computing in order to achieve better Quality of Service (QoS).

Increasingly, academic and industrial leaders are recognizing that college graduates need new skills to address business and technical issues in a service business environment. Because services depend critically on people working together and with technology to provide value for others, these new skills include the ability to integrate across traditional disciplinary areas to obtain globally effective solutions. Service Science, Management and Engineering (SSME) is one such approach to properly focusing education and research on services, and to preparing tomorrow's graduates to work in an expanding services economy. Papers in this volume were developed from the 2006 conference hosted by IBM, Service Science, Management, and Engineering - Education for the 21st Century. The book incorporates a variety of perspectives, informed by an international background in SSME experience and education, including management, business, social science, computer science and engineering.

Cloud Computing provides higher level services and shared pools of configurable resources with minimal management effort over the internet. Cloud Computing achieves coherence and economic of scale by means of shared resources. The growth of cloud computing depends on the high availability of low cost computers, storage devices and networks as well as hardware virtualization and utility computing. Service Level Agreement (SLA) is a service commitment tool between a cloud service provider and a cloud customer. Using SLA in cloud computing, reduce the chances of disappointing the cloud customer and manage the expectation between the service provider and the customer. The challenge is, it is very difficult to handle all request by the cloud providers at a time during peak hours and to keep up SLA. So when there is an uneven request arrival pattern, the cloud resources may either be underutilized or over-utilized. In order to balance the load, the load balancer plays the major role in cloud computing. The load balancing algorithm equalizes the workload and computing resources in a cloud computing environment. It allows an organization to manage their workload demands by allocating resources among multiple servers and thus it minimizes the response time, minimize the waiting time, maximize the throughput time, maximize the resource utilization and minimize the communication delays of the server by meeting the SLA. The major goal of this study is to review both the existing static and dynamic load balancing algorithms proposed till now and to design and implement a Load balancer that uses a Meta Heuristics approach – Ant Colony Optimization technique to perform balancing the load so that the SLA is met evenly without any issues. Each of the load balancing algorithms is compared with other algorithms theoretically and experimentally one of it is tested with the proposed system using AWS Cloud PaaS (Platform as a Service).

This paper presents a new idea of cognitive systems dedicated to cloud computing. Especially presents backgrounds, introduction and description of service management procedures and algorithms dedicated to cloud computing and infrastructure. Cognitive methods based on semantic description and interpretation procedures. Described idea will be dedicated to secure service management procedures, especially in the cloud and fog stages. The proposed algorithms of cognitive service management will be presented and described by use of semantic aspects. Semantic analysis is used to extract meaning of analysed data. Also, in management processes is possible to analyse meaning aspects. These kinds of analysis can be used in different application areas. This paper presents services management protocols in the cloud and in the fog. In both of these stages is possible realised management procedure by application of secure methods and protocols. This paper presents the sharing techniques for data security in cloud computing.

Cloud computing (CC) services can offer substantial cost-effective global operational and relationship benefits if the cooperation between logistics and CC services are resilient. Potential vulnerabilities to cooperation of CC and logistics service providers can occur with respect to vital factors such as security and trust. Extant studies have demonstrated CC benefits as well as few challenges associated with CC services application. However, no extant study has examined the inter-organisational benefits based on cooperative resilience between CC and logistics service providers in terms of both capability and trust vulnerability factors. This study examines the cooperative resilience of logistics and CC service providers based on innovation diffusion theory within a supply chain risk assessment framework. Using structural equation modelling techniques, we investigate the relationship between the vulnerability factor (trust), capability factor (security) and collaboration benefits (relationship and operational) offered by CC service providers based on 236 Chinese logistics service firms’ perceptions of CC adoption. The results indicate Chinese logistics companies perceive security impediments as a major factor affecting cooperative resilience between logistics service and CC service providers.