This paper presents the first complete, integrated and end-to-end solution for ad hoc cloud computing environments. Ad hoc clouds harvest resources from existing sporadically available, non-exclusive (i.e. primarily used for some other purpose) and unreliable infrastructures. In this paper we discuss the problems ad hoc cloud computing solves and outline our architecture which is based on BOINC.
Chandra propose a similar idea using Nebulas (synonymous to an cloud) where volunteer resources are used to create a cloud platform @cite_7 . They note that Nebulas are particularly useful for applications that do not have strong performance guarantees and hence the authors focus on the performance and reliability of such platforms.
@cite_7
67629752 2090355322 2151637322 66821545
Current cloud services are deployed on well-provisioned and centrally controlled infrastructures. However, there are several classes of services for which the current cloud model may not fit well: some do not need strong performance guarantees, the pricing may be too expensive for some, and some may be constrained by the data movement costs to the cloud. To satisfy the requirements of such services, we propose the idea of using distributed voluntary resources--those donated by end-user hosts--to form nebulas: more dispersed, less-managed clouds. We first discuss the requirements of cloud services and the challenges in meeting these requirements in such voluntary clouds. We then present some possible solutions to these challenges and also discuss opportunities for further improvements to make nebulas a viable cloud paradigm. Current cloud infrastructures are important for their ease of use and performance. However, they suffer from several shortcomings. The main problem is inefficient data mobility due to the centralization of cloud resources. We believe such clouds are highly unsuited for dispersed-data-intensive applications, where the data may be spread at multiple geographical locations (e.g., distributed user blogs). Instead, we propose a new cloud model called Nebula: a dispersed, context-aware, and cost-effective cloud. We provide experimental evidence for the need for Nebulas using a distributed blog analysis application followed by the system architecture and components of our system. Determining the three-dimensional structure of distant astronomical objects is a challenging task, given that terrestrial observations provide only one viewpoint. For this task, bipolar planetary nebulae are interesting objects of study because of their pronounced axial symmetry due to fundamental physical processes. Making use of this symmetry constraint, we present a technique to automatically recover the axisymmetric structure of bipolar planetary nebulae from two-dimensional images. With GPU-based volume rendering driving a non-linear optimization, we estimate the nebulaýs local emission density as a function of its radial and axial coordinates, and we recover the orientation of the nebula relative to Earth. The optimization refines the nebula model and its orientation by minimizing the differences between the rendered image and the original astronomical image. The resulting model enables realistic 3D visualizations of planetary nebulae, e.g. for educational purposes in planetarium shows. In addition, the recovered spatial distribution of the emissive gas allows validating computer simulation results of the astrophysical formation processes of planetary nebulae. The NEBULA Future Internet Architecture (FIA) project is focused on a future network that enables the vision of cloud computing [8,12] to be realized. With computation and storage moving to data centers, networking to these data centers must be several orders of magnitude more resilient for some applications to trust cloud computing and enable their move to the cloud.