Cloud computing is increasingly gaining inroads among a variety of organizational users. As clouds are introduced for use by enterprises, service providers, and governmental and educational entities, new challenges related to the interconnection between such clouds emerge. Cloud administrators seek to maintain acceptable levels of autonomy and control over their cloud infrastructure, while ensuring the integrity of the cloud services. At the same time, they are expected to enable cross-cloud services, including mobility of workloads between clouds. We present the design and implementation of a technology that enables live mobility of virtual machines between clouds, while enforcing the cloud insularity requirements of autonomy, privacy, and security. We also provide an empirical evaluation of our solution, demonstrating its viability and compliance with requirements.

RESERVOIR project is developing an advanced system and service management approach that will serve as the infrastructure for cloud computing and communications and future Internet of services by creative coupling of service virtualization, grid computing, networking and service management techniques. This paper presents work in progress for the integration and management of such systems into a new generation of managed service infrastructure.

Today's system management tools focus on a computer as a visible enclosure of both computational resources (CPU and memory) and the functionality and data that reside in the storage subsystem. Recent technological trends, such as shared SAN or NAS storage and virtualization, have the potential to break this tight association between functionality and machines. We describe the design and implementation of ENCOMPASS - an image management system centered around a shared storage repository of "master system images", each representing different functionality. The functionality is provisioned by "cloning" master images, associating the resulting "clone images" with specified physical and/or virtual resources ("machines"), customizing the clone images for the specific environment and circumstances, and automatically performing the necessary operations to activate the clones. "Machines" $physical or virtual - are merely computational resources that do not have any permanent association with functionality. ENCOMPASS supports the complete lifecycle of a system image, including reallocation and re-targeting of resources, maintenance, updates, etc. It separates image creation from image management from resource allocation policies - an emerging trend that is manifested in particular by proliferation of turn-key "virtual appliances".

Oceano is a prototype of a highly available, scaleable, and manageable infrastructure for an e-business computing utility. It enables multiple customers to be hosted on a collection of sequentially shared resources. The hosting environment is divided into secure domains, each supporting one customer. These domains are dynamic: the resources assigned to them may be augmented when the load increases and reduced when load dips. This dynamic resource allocation enables flexible service level agreements (SLAs) with customers in an environment where peak loads are an order of magnitude greater than the normal steady state.

Complex problems, such as driving, can be solved more easily by decomposing them into smaller subproblems, solving each sub-problem, and then integrating the solutions. In the case of an autonomous vehicle, the integrated system should be able to react in real time to a changing environment and to reason about ways to achieve its goals. This paper describes the approach taken on the UMass Mobile Perception Laboratory (MPL) to integrate independent processes (each solving a particular aspect of the navigation problem) into a fully capable autonomous vehicle. >

Complex problems, such as driving, can be solved by decomposing them into simpler sub-problems, solving each sub-problem, and then integrating the solutions. In the case of an autonomous vehicle, the integrated system should be able to "react" in real time to a changing environment and to "reason" about ways to achieve its goals. This paper describes the approach taken on the UMass Mobile Perception Laboratory (MPL) to integrate independent processes (each solving a particular aspect of the navigation problem) into a fully capable autonomous vehicle.