A Software Service Framework Model Based on Agent

This paper presents an agent-based software service framework model called ASF, and defines the basic concepts and structure of ASF model. It also describes the management and process mechanisms in ASF model.

Application of Capability Maturity Model Integration to Innovation Management for Software and Service Companies

To look through innovation management in small project-based firms, such as software engineering companies, which are service firms that conduct projects for their clients, capability maturity model integration （CMMI） is introduced. It is a process improvement approach that provides organizations with the essential elements of effective processes. Taking ABC Software Company as an example, the performances before and after the introduction of CMMI in the firm were compared. The results indicated that after two years of application, the productivity increased 92%, and the ability of detecting errors improved 26.45% ; while the rate of faults and the cost of software development dropped 12.45% and 77.55%, respectively. To conclude, small project-based firms benefit a lot if they take CMMI into their process of innovation management, particularly for those R＆D firms, since the implementation of CMMI leads them to a promising future with higher efficiency and better effects.

Hybrid Chameleon and Honey Badger Optimization Algorithm for QoS-Based Cloud Service Composition Problem

Cloud computing facilitates the great potentiality of storing and managing remote access to services in terms of software as a service(SaaS).Several organizations have moved towards outsourcing over the cloud to reduce the burden on local resources.In this context,the metaheuristic optimization method is determined to be highly suitable for selecting appropriate services that comply with the requirements of the client’s requests,as the services stored over the cloud are too complex and scalable.To achieve better service composition,the parameters of Quality of Service(QoS)related to each service considered to be the best resource need to be selected and optimized for attaining potential services over the cloud.Thus,the cloud service composition needs to concentrate on the selection and integration of services over the cloud to satisfy the client’s requests.In this paper,a Hybrid Chameleon and Honey Badger Optimization Algorithm(HCHBOA)-based cloud service composition scheme is presented for achieving efficient services with satisfying the requirements ofQoS over the cloud.This proposed HCHBOA integrated the merits of the Chameleon Search Algorithm(CSA)and Honey Badger Optimization Algorithm(HBOA)for balancing the tradeoff between the rate of exploration and exploitation.It specifically used HBOA for tuning the parameters of CSA automatically so that CSA could adapt its performance depending on its incorporated tuning factors.The experimental results of the proposed HCHBOA with experimental datasets exhibited its predominance by improving the response time by 21.38%,availability by 20.93%and reliability by 19.31%with a minimized execution time of 23.18%,compared to the baseline cloud service composition schemes used for investigation.

Research on cloud computing and services framework of marine environmental information management

Based on the features of marine environmental data and processing requirements, a cloud computing archi- tecture of marine environment information is proposed, which provides a new cloud technology framework for the integration and sharing of marine environmental information resources. A physical layer, software platform layer and an application layer are illustrated systematically, at the same time, a corresponding solu- tions for many difficult technical problems such as parallel query processing of multi-dimensional, spatio- temporal information, data slice storage, software service flow customization, analysis, reorganization and so on. A prototype system is developed and many different data-size experiments and a comparative analy- sis are done based on it. The experiment results show that the cloud platform based on this framework can achieve high performance and scalability when dealing with large-scale marine data.

Detecting and Preventing of Attacks in Cloud Computing Using Hybrid Algorithm

Cloud computing is the technology that is currently used to provide users with infrastructure,platform,and software services effectively.Under this system,Platform as a Service(PaaS)offers a medium headed for a web development platform that uniformly distributes the requests and resources.Hackers using Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks abruptly interrupt these requests.Even though several existing methods like signature-based,statistical anomaly-based,and stateful protocol analysis are available,they are not sufficient enough to get rid of Denial of service(DoS)and Distributed Denial of Service(DDoS)attacks and hence there is a great need for a definite algorithm.Concerning this issue,we propose an improved hybrid algorithm which is a combination of Multivariate correlation analysis,Spearman coefficient,and mitigation technique.It can easily differentiate common traffic and attack traffic.Not only that,it greatly helps the network to distribute the resources only for authenticated requests.The effects of comparing with the normalized information have shown an extra encouraging detection accuracy of 99%for the numerous DoS attack as well as DDoS attacks.

DPTSV:A Dynamic Priority Task Scheduling Strategy for TSS Deadlock Based on Value Evaluation

This paper analyzes the threat of TCG Software Stack(TSS)/TCM Service Module(TSM) deadlock in multi-user environment such as cloud and discusses its causes and mechanism.In addition,this paper puts forward a dynamic priority task scheduling strategy based on value evaluation to handle this threat.The strategy is based on the implementation features of trusted hardware and establishes a multi-level ready queue.In this strategy,an algorithm for real-time value computing is also designed,and it can adjust the production curves of the real time value by setting parameters in different environment,thus enhancing its adaptability,which is followed by scheduling and algorithm description.This paper also implements the algorithm and carries out its performance optimization.Due to the experiment result from Intel NUC,it is shown that TSS based on advanced DPTSV is able to solve the problem of deadlock with no negative influence on performance and security in multi-user environment.

Cloud Computing of E-Government

Over the past years, many businesses, government and individuals have been started to adopt the internet and web-based technologies in their works to take benefits of costs reduction and better utilization of existing resources. The cloud computing is a new way of computing which aims to provide better communication style and storage resources in a safe environment via the internet platform. The E-governments around the world are facing the continued budget challenges and increasing in the size of their computational data so that they need to find ways to deliver their services to citizens as economically as possible without compromising the achievement of desired outcomes. Considering E-government is one of the sectors that is trying to provide services via the internet so the cloud computing can be a suitable model for implementing E-government architecture to improve E-government efficiency and user satisfaction. In this paper, the adoption of cloud computing strategy in implementing E-government services has been studied by focusing on the relationship between E-government and cloud computing by listing the benefits of creation E-government based on cloud computing. Finally in this paper, the challenges faced the implementation of cloud computing for E-government are discussed in details. As a result from understanding the importance of cloud computing as new, green and cheap technology is contributed to fixing and minimizing the existing problems and challenges in E-government so that the developed and developing countries need to achieve E-government based on cloud computing.

Boosting Collaborative Project Alignment

Managing a large-scale distributed engineering project needs skilled, motivated and committed personnel. Unified and aligned working methods are needed. Project alignment is the process of ensuring that key stakeholders share a common understanding of the project mission, goals, objectives, tactics, work processes and plans and have the required competences and skills. Based on current advances in the area of collaborative networked organizations, project management and Internet web 2.0 technologies, the authors have identified further needs and opportunities for development in the area of Collaborative Project Management. The Project Alignment Booster is a set of software services used to promote collaborative project management. The tool has been developed to suit industrial requirements in the area of large and complicated engineering project management, The paper reports the results of developing a toolkit to support collaborative project alignment.

VARIABILITY MODELING TO DEVELOP FLEXIBLE SERVICE-ORIENTED APPLICATIONS

To cope with requirement changes flexibly and rapidly,the existing component-based paradigm is being evolved into a service-oriented computing paradigm.The main characteristic of the service-oriented computing paradigm is that service-oriented applications are developed as loosely coupled services that reflect business concerns.This paradigm also promotes business agility,facilitating quick reactions to business changes.Therefore,to enhance and support the benefits of the service-oriented computing paradigm,we must consider how to improve flexibility and reusability during the development of service-oriented applications.We propose the variability modeling approach to specify and control the common and distinguishing characteristics of service-oriented applications.That is,the key concepts of product-line technology can be used to make service-oriented applications more flexible and reusable.This paper describes variability modeling at two levels;the composition level and the specification level.At the composition level,we describe the variability of composition and the flow of domain services that fulfill business processes.At the specification level,we present a domain service that is an abstract service with variability.The use of our systematic variability modeling approach can greatly increase the flexibility,applicability,and reusability of service-oriented applications.

Big data analytics with applications

In this paper,recent developments on the Internet of Things(IoT)and its applications are surveyed,and the impact of newly developed Big Data(BD)on manufacturing information systems is especially discussed.Big Data analytics(BDA)has been identified as a critical technology to support data acquisition,storage,and analytics in data management systems in modern manufacturing.The purpose of the presented work is to clarify the requirements of predictive systems,and to identify research challenges and opportunities on BDA to support cloudbased information systems.

Strategies and Methods for Cloud Migration

Legacy system migration to the cloud brings both great challenges and benefits, so there exist various academic research and industrial applications on legacy system migration to the cloud. By analyzing the research achievements and application status,we divide the existing migration methods into three strategies according to the cloud service models integrally. Different processes need to be considered for different migration strategies, and different tasks will be involved accordingly. The similarities and differences between the migration strategies are discussed, and the challenges and future work about legacy system migration to the cloud are proposed. The aim of this paper is to provide an overall presentation for legacy system migration to the cloud and identify important challenges and future research directions.