Radhika Garg

Design and evaluation of an Impact Analysis Methodology for the adoption of Cloud-based Services (IAMCIS)

An impact analysis of adopting any new technology for fulfilling IT requirements of an organization is a very crucial task. It enables the identification of effects such a technology change will have on the organization from the technical, economical, and organization perspective. In the context of cloud-based solutions these facets are typically more complicated and the impact analysis of such large IT architectures cannot be completed with much accuracy at a high level. Therefore, each major single component of such an architecture has to be evaluated with respect to relevant factors, which appropriately denote the success or failure of the newly adopted solution. This paper develops and evaluates in this context a new impact analysis methodology, termed Impact Analysis Methodology for Cloud-based Services (IAMClS), which estimates the impact for cloud-based solutions in quantifiable terms. IAMCIS is illustrated in conjunction with a representative use case obtained from a survey conducted with 10 organizations, who plan to adopt or have adopted cloud-based solutions for fulfilling their IT requirements.

Decision Support System for Adoption of Cloud-based Services

Adoption of any new technology in an organization is a crucial decision as it can have its impact at technical, economical, and organizational level. One of such decisions is related to adoption of Cloud-based services in an organization. Cloud Computing provides elastic resources as per the demand and provides the facility to pay as per the use. Thus, it is changing the way IT infrastructure is used today with huge benefit of cost savings. However, if the solution adopted by an organization is not fulfilling the requirements, it can have tremendous negative consequences at technical, economical, and organizational level. Therefore, the decision to adopt Cloud-based services should be based on a methodology that supports a wide array of criteria for evaluating the available alternatives. Also, as these criteria or factors can be mutually interdependent and conflicting, a trade-offs-based methodology is needed to make such decisions. This paper, therefore, discusses the design, implementation, and evaluation of the prototype developed for automating the theoretical methodology of Trade-offs based Methodology for Adoption of Cloud-based Services (TrAdeCIS) developed in (Garg and Stiller, 2014). This system is based on Multi-attribute Decision Algorithms (MADA), which selects the best alternative, based on the priorities of criteria of decision maker. In addition the applicability of this methodology to the adoption of cloud-based services in an organization is validated with several use-cases towards the end of the paper. Furthermore, the extendibility of this system to other domains is being evaluated with respect to Train Operating Companies, who wish to find out the best alternative of providing Internet connectivity and voice calls on-board trains.

Trade-off-based Adoption Methodology for Cloud-Based Infrastructures and Services

Adoption and consequent management of cloud-based infrastructures and services is driven by business requirements and objectives within an organization. The decision of either to move from a legacy system to a cloud-based system or to move from one cloud solution to another is based on various factors. A potential customer, therefore, should evaluate (a) relevant factors affecting the adoption of a cloud and (b) impacts cloud services will have on multi-faceted objectives of an organization. Existing methods for such an adoption process do not evaluate these two aspects for the decision of cloud adoption. Thus, this paper fills this gap by introducing a new Trade-off-based Adoption methodology for Cloud-based Infrastructures and Services (TrAdeCIS), which is based on the impact cloud-based services will have on the organization. This methodology developed will support organizations in decisions concerning (a) the selection of cloud service provider, (b) the type of cloud service to be adopted, and (c) the suitable type of cloud to be adopted. TrAdeCIS is illustrated based on a survey conducted with 10 organizations, who have adopted or plan to adopt cloud-based solution to fulfil their advanced IT requirements.

Modeling legal and regulative requirements for ranking alternatives of cloud-based services

The decision to adopt a new technology in an organization is a complex task because of several Non-Functional Requirements (NFR) e.g., availability, interoperability, and presence of several alternatives, e.g., service providers can offer multiple packages. To support such a decision and to select the best alternative a Trade-off based Adoption Methodology for Cloud-based Infrastructure and Services (TrAdeCIS), based on NFR for cloud-based services, was proposed. This methodology makes the decision based on multi-criteria decision algorithms, namely the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Analytic Network Process (ANP). However, in addition, the decision for adopting cloud-based services is also influenced by the presence of various legal and regulative constraints. Therefore, it is crucial to understand, identify, and model the effect of such constraints on the evaluation of NFR and available alternatives. This paper, therefore, uses the Goal-oriented Requirement Language (GRL) to model the effect of legal and regulative constraints on ranking available alternatives with respect to NFR. The paper also discusses the extensibility and applicability of this methodology to other domains that require evaluating the effect of legal and regulative constraints on the adoption decision. To illustrate this, decisions within the domain providing better voice and data quality on-board train is also discussed in this paper.

Legal and Regulative Aspects of IoT Cloud Systems

Organizations envisioning adopting cloud computing have to consider numerous factors, including technical, organizational, economical and relational ones. Legal and regulative constraints increase the complexity and can vary with different deployment models and service levels. Nowadays a growing number of powerful devices are joining the Internet. Data users produce with these devices are continuously posted to online services, which require the use of cloud providers to efficiently handle these data. In our former work we have derived a general federation architecture for clouds from definitions of international organizations, and used it to define common cloud computing usage patterns. The aim of this paper is to revise purely cloud usage patterns and identify scenarios with cases involving Internet of Things (IoT) utilization based on corresponding European projects. These cases are also examined against legal and regulative constraints, in order to help users to better understand IoT ecosystems and companies to design better applications for IoT cloud environments.

Trade-offs Based Decision System for Adoption of Cloud-Based Services

Moving data and applications to the cloud allows users and companies to enjoy considerable benefits. However, these benefits are also accompanied by a number of security issues that should be addressed. Among these, the need to ensure that possible requirements on security, costs, and quality of services are satisfied by the cloud providers, and the need to adopt techniques ensuring the proper protection of their data and applications. In this paper, we present different strategies and solutions that can be applied to address these issues.

Investigating Regulative Implications for User-generated Content and a Design Proposal

Abstract The rapid increase of the Internet connectivity and the data publishing activity, like user-generated content, has lead Internet Service Providers (ISPs) to establish more efficient mechanisms for content delivery, such as caching. Mechanisms such as content-aware-networks and in-network caching reduce network load, server load, and user response time, thus, manage the network. However, caching of content also raises major implications in terms of legal acts and bills (e.g., data privacy, copyright), dealing with access control, validation scheme, and regulations (e.g., contractual obligation, legal restrictions). In general, user-generated content is linked with sensitive information, such as geographical information, medical and financial information, personal identifiable data, photos, videos, and contact information. Therefore, it is essential to secure data and regulate access. The latter, is gained by including access control mechanisms in the data exchange process, where a user requesting data must prove his access rights. Therefore, a user has to show an access ticket, which includes his rights based on legal and regulative implications. In order to secure any kind of data exchange, authentication of each participating communication entity (e.g., content owner, server, and end-user) is essential, which is part of the proposed two-way authentication handshake in this paper that is performed to generate a secure communication channel. The main contribution of this paper is to show that transmission, storage, and usage of user-generated data in caches within the network is manageable within the legal laws on sensitivity, copyright, and privacy. The scope of studying these laws, acts, and policies is restricted to Switzerland (CH), the European Union (EU), and the United States of America (USA). Finally, a solution is presented including access ticketing and two-way authentication mechanisms based oncommonstandards from IP networks.