Atul Gohad

Cloud Pricing Models: A Survey and Position Paper.

In recent years, cloud computing has emerged as a successful mode of delivery for Software as a Service (SaaS) offerings and more generically anything as a service (XaaS) offerings. Cloud computing is, an evolutionary paradigm shift in the ways computing platforms and services are made available to the consumers, and this has been made possible due to numerous technology enablers, along with changing business strategies. These changes have contributed significantly in achieving the market shift from differentiated to undifferentiated price models, thereby helping the market movements from monopolistic to perfect competition, and resulting in converting traditional enterprise class software tools and hardware platforms into a commodity. This paper, is a survey on pricing strategies and schemes employed in cloud offerings wherein we study various mechanisms currently being used. The literature survey encompasses market trends on cloud pricing with specific focus on emerging market scenario of India. Based on the need of providing flexible pricing, we discuss our position on a revenue framework wherein cloud pricing strategy is a function of periodic resource utilization analysis, and provide details of our revenue generation model that depends on cross over of different pricing schemes.

Goal-Driven business process derivation

Solutions to the problem of deriving business processes from goals are critical in addressing a variety of challenges facing the services and business process management community, and in particular, the challenge of quickly generating large numbers of effective process designs (often a bottleneck in industry-scale deployment of BPM). The problem is similar to the planning problem that has been extensively studied in the artificial intelligence (AI) community. However, the direct application of AI planning techniques places an onerous burden on the analyst, and has proven to be difficult in practice. We propose a practical yet rigorous (semi-automated) algorithm for business process derivation from goals. Our approach relies on being able to decompose process goals to a more refined collection of sub-goals whose ontology is aligned with that of the effects of available tasks which can be used to construct the business process. Once process goals are refined to this level, we are able to generate a process design using a procedure that leverages our earlier work on semantic effect annotation of process designs. We illustrate our ideas throughout this paper with a real-life running example, and also present a proof-of-concept prototype implementation.

Model Driven Provisioning in Multi-tenant Clouds

In multi-tenant cloud systems today, provisioning of resources for new tenancy is based on selection from a catalogue published by the cloud provider. The published images are generally a stack of appliances with Infrastructure (IaaS) and Platform (PaaS) layers and optionally Application layers (SaaS). Such a ready-made model enables quicker and streamlined resource provisioning to clients. However, this approach poses certain challenges to clients in the short run and providers in the long run. Unique tenancy requirements from each client are forcibly generalized by selecting one of the available images from the catalogue as the tenancy requirements are not modeled or validated to start with. Moreover, resource provisioning is mostly done towards addressing the peak load expectations in the tenancy. Such a static approach does not help in adapting to dynamically changing tenancy requirements, most often leading to the tenants owning and subsequently paying for more than what they need. In particular, provisioned resources are expected to perform at the same level of quality without accounting for their changing health. In our paper, we propose an extensible dynamic provisioning framework to address these challenges. We start with defining a Tenancy Requirements Model (TRM) which helps map provisioned resources with tenants. The provisioned and candidate resources are also modeled with their Quality of Service (QoS) characteristics which we call Health Grading Model (HGM); this helps in continuous monitoring and grading of resources based on health parameters and enables health prediction for future provisioning. Together, TRM and HGM allow dynamic re-provisioning for existing tenants based on either changing tenancy requirements or health grading predictions. We also present algorithms for prediction based provisioning and tenancy requirement matching. We illustrate our ideas throughout this paper with a running example, and present a proof-of-concept prototype implementation on IBMs Rational Software Architect modeling tool.

Out-of-the-Enterprise B2B Gateway Cloud Service for Emerging Markets

Traditionally, in a typical SOA environment, a B2B gateway is at the edge of an enterprise, and is responsible for performing business document exchanges with other enterprises. In the existing model often used in mature markets, the enterprise needs to incur the cost of hosting and maintaining the gateway. However, the scenario for emerging markets is different, since they are not totally reliant on exchanging business documents electronically. Specifically, the SMB enterprises in emerging markets may not be interested in hosting and maintaining the usually bulky gateway products. In this paper, we propose a novel approach wherein SMB enterprises would exchange secured business information to a B2B cloud service hosted outside of the enterprise. This service offers key B2B protocol capabilities and features such as packaging, security and partner on-boarding. In a typical document exchange flow, the SMB enterprise would send its business information to this B2B cloud service which then packages it using the agreed upon B2B protocol and makes it available to the intended recipient enterprise. Using this model for B2B exchanges would work as an incentive to open up SMB enterprises for B2B business and will go a long way in reducing costs for SMB enterprises.

Towards Self-Adaptive Cloud Collaborations

In multi-tenant collaborative cloud systems, the choice of cloud providers is based on pre-negotiated terms and conditions to help meet Service Level Agreements (SLAs) and streamline resource provisioning. However, these collaborations are not self-adaptive to accommodate changes in tenancy requirements, quality of resources and provider capabilities as provider collaborations remain static over tenancy period. In our paper, we present an approach towards achieving self-adaptive cloud collaborations. Our model selects the best possible cloud collaborations from amongst multiple possible dependent cloud provider collaboration links. The formation of cloud provider collaborations is broadly based on cloud provider capabilities, tenancy requirements, cost modeling of each cloud provider andits functional ability at the Software as a Service (SaaS) layer. We present an algorithm to form dynamic cloud collaborations and thereby determine the most appropriate linkages within the providers. We also illustrate our approach throughout our paper with a realistic running example, and present detailed experimental evaluation via a proof-of-concept prototype implementation.

Formation of Dynamic Collaborative Cloud Links Based on Provider Capability Cost and Resource Health Monitoring

Typically in collaborative cloud systems, the collaborations are formed based on pre-negotiated terms and conditions. Care is taken to ensure that the resources are planned in such a way so as to satisfy the SLA requirements. However, these static collaborations pose certain challenges in the long run, which arise due to the changes in quality of resources and provider capabilities. In such a scenario, there is a need to dynamically establish appropriate collaborations so as to back-fill the resource quality and overcome shortfalls in provider capabilities. Our paper puts forth a mathematical model for cloud provider capabilities along with an approach to establish dynamic cloud provider collaborations. In our approach, once the under functioning resource is identified, we are able to find the most suitable replacement resource from within the same cloud provider or if need be, establish a new collaboration with another provider based on the required resource capabilities. This choice for new collaboration is based on the tenancy requirements, current state of resource utilization and capacity, and health of the specific resource to be replaced. Our algorithms to determine the replacement resource and form the collaboration links are illustrated along with a running example and proof-of-concept implementation.

1 * N Trust Establishment within Dynamic Collaborative Clouds

Federation of security entities in cloud environments has crucial challenges in terms of policy reservations required for each of the multi-tenancy requests. In collaborative clouds, the problem is compounded due to the fact that the tenancy requester would be completely unaware of the end cloud provider. As the tenancy requesters would not have established any negotiation terms with the end cloud provider, it is a complex challenge to ensure dependability in terms of trust, privacy and security of data exchanges. Existing approaches require establishment of point to point trust. However, in the larger context of possible collaborative cloud providers, there is a need for simplified trust management for tenants. Asking the tenants to exclusively establish trust relationships with each other hinders the choice of providers thereby restricting the dynamic collaborations. We propose an approach based on a model wherein a single security mediator is responsible for sharing the required trust with all involved cloud providers within the collaboration. This mediator acts as a hub for all the participant tenants. The tenants establish negotiation terms with the mediator. Whenever the tenancy request needs to be satisfied by a subsequent cloud provider, first a trust is established between the mediator and the new cloud provider. Once this level of trust is accepted and confirmed by the tenancy requester, this provider is added as a trusted provider and tenancy requests can be satisfied by this specific cloud provider.

Monetizing the Cloud: Pricing Model Governance

Infrastructure cloud providers provision computing capacity in the form of virtual instances and charge customers on a time-varying price for the period they use these instances. The providers problem is to choose most appropriate set of resources for provisioning so as to maximize expected revenue and at the same time satisfy tenancy demand fluctuations. This paper describes our position on a pricing model to be used by small or medium sized cloud providers who have limited set of resources, unlike the usual IaaS providers who are assumed to own large data centres. We briefly put forth the currently employed pricing strategies in general and outline challenges and complexities from the perspective of cloud providers. Our model is geared towards maximizing provider revenue and is based on optimal resource capacity utilization and offers a transparent pay-as-you-go payment model.

Smarter Commerce: NLP SpokenWeb Based B2B Messaging

In a traditional B2B world, the enterprises invest substantial amount of money on hosting and maintaining B2B gateways for business interactions with suppliers and customers. There are multitude of B2B frameworks which are catering the needs of these enterprises. However, there is lack of solutions in emerging markets where adaption to technology is a challenge and investment on enterprise level B2B gateway products to perform business document exchanges is almost impossible. In this paper, we extend our earlier research work and implement a speech based B2B messaging solution which would enable MSME (Micro, small and medium enterprises) to interact with existing enterprise gateway infrastructure without any investment. Also, they can perform business document exchanges over phone in their regional language thus giving them the benefit to leverage the advantages of standard B2B processes. This service also offers key B2B protocol capabilities and features such as packaging, security and partner on-boarding. The proposed solution would enable the MSME to perform B2B business in an easier way and will help them go a long way in reducing costs.