Clouds commonly store Virtual Machine (VM) images on networked storage. This poses a serious potential scalability bottleneck as launching a single fresh VM instance requires, at minimum, several hundred MB of network reads. As this bottleneck occurs most severely during read-intensive launching of new VMs, we focus on scalably minimizing time to boot a VM and load its critical applications.

A Software Defined Network (SDN) enforces network-wide policies by installing packet-handling rules across a distributed collection of switches. Today's SDN platforms force programmers to decide how to decompose a high-level policy into the low-level rules in each switch. We argue that future SDN platforms should support automatic transformation of policies by moving, merging, or splitting rules across multiple switches. This would simplify programming by allowing programs written on one abstract switch to run over a more complex network topology, and simplify analysis by consolidating a policy spread over multiple switches into a single list of rules. This poster presents our ongoing work on a sound and complete set of axioms for policy transformation, to enable rewriting of rules across multiple switches while preserving the forwarding policy. These axioms are invaluable for creating and analyzing algorithms for optimizing the rewriting of rules.

We explore distributed mechanisms for maintaining the physical layer connectivity of a mobile wireless network while still permitting significant area coverage. Moreover, we require that these mechanisms maintain connectivity despite the unpredictable wireless propagation behavior found in complex real-world environments. To this end, we propose the Spreadable Connected Autonomic Network (SCAN) algorithm, a fully distributed, on-line, low overhead mechanism for maintaining the connectivity of a mobile wireless network. SCAN leverages knowledge of the local (2-hop) network topology to enable each node to intelligently halt its own movement and thereby avoid network partitioning events. By relying on topology data instead of locality information and deterministic connectivity models, SCAN can be applied in a wide range of realistic operational environments. We believe it is for precisely this reason that, to our best knowledge, SCAN was the first such approach to be implemented in hardware. Here, we present results from our implementation of SCAN, finding that our mobile robotic testbed maintains full connectivity over 99% of the time. Moreover, SCAN achieves this in a complex indoor environment, while still allowing testbed nodes to cover a significant area.

We explore distributed mechanisms for maintaining the physical layer connectivity of a mobile wireless network while still permitting significant area coverage. Moreover, we require that these mechanisms maintain connectivity despite the unpredictable wireless propagation behavior found in complex real-world environments. To this end, we propose the Spreadable Connected Autonomic Network (SCAN) algorithm, a fully distributed, on-line, low overhead mechanism for maintaining the connectivity of a mobile wireless network. SCAN leverages knowledge of the local (2-hop) network topology to enable each node to intelligently halt its own movement and thereby avoid network partitioning events. By relying on topology data instead of locality information and deterministic connectivity models, SCAN can be applied in a wide range of realistic operational environments. We believe it is for precisely this reason that, to our best knowledge, SCAN was the first such approach to be implemented in hardware. Here, we present results from our implementation of SCAN, finding that our mobile robotic testbed maintains full connectivity over 99% of the time. Moreover, SCAN achieves this in a complex indoor environment, while still allowing testbed nodes to cover a significant area.

Virtual Appliances (VAs) are Virtual Machines (VMs) geared towards a specific set of tasks. They require little or no configuration, working out-of-the-box. VAs fit neatly into the Cloud Computing paradigm - many copies of an identical machine can be launched in a data center, or home/business users can grab the appliance they need from the cloud to run locally just for so long as required. Companies and projects whose sole offerings are VAs ready for either desktop or data center use [3, 11] attest to the growing popularity of VAs. VMware's Appliance directory alone currently lists over 1400 VAs available for the VMware family of Virtual Machine Monitors (VMMs) [13].

Multimedia content dissemination in mobile settings requires significant bandwidth. Centralized infrastructure is often either inadequate or overly expensive to fill the demand. Here, we study an alternative P2P content dissemination scheme for mobile devices (e.g., smart-phones), which leverages local dedicated caches on these devices to opportunistically fulfill user requests. In our model, the allocation of content in the global distributed cache comprising the union of all local caches, determines the pattern of demand fulfillment. By selectively replicating local content at node meetings, the global cache can be driven towards a more efficient allocation. However, the allocation's efficiency itself is determined by a previously overlooked factor - the impatience of content requesters. By describing user impatience in the form of any monotonically decreasing delay-utility functions, we show that an optimal allocation can be efficient computed or approximated. As users become increasingly impatient, the optimal allocation varies steadily between uniform and highly-skewed towards popular content.