I/O intensive workloads running in virtual machines can suffer massive performance degradation. Direct assignment of I/O devices to virtual machines is the best performing I/O virtualization mechanism, but its performance still remains far from the bare-metal (non-virtualized) case. The primary gap between direct assignment I/O performance and bare-metal I/O performance is the overhead of mapping the VM's memory pages for DMA in IOMMU translation tables. One could avoid this overhead by mapping all of the VM's pages for the lifetime of the VM, but this leads to memory consumption which is unacceptable in many scenarios.

A major problem in wireless networks is how to route either broadcast, unicast or multicast traffic so as to maximize the lifetime, i.e., the time until the battery of a transmitting node drains out. Focusing on the fundamental single-session problem, our solution approach is based on the employment of multi-topology routing schemes. Such a scheme consists of a set of routing topologies, which are employed sequentially, for some prescribed duration times.First, we consider the standard wireless environment of multiple recipients, which correspond to omnidirectional antennas. For the cases of either single-topology schemes or unicast sessions, we establish optimal solutions of polynomial complexity. For the general (multi-topology) cases of broadcast and multicast, which are NP-hard, we derive a novel heuristic scheme, and demonstrate its efficiency by way of simulations.We then consider an alternative, single-recipient wireless environment, which corresponds to the important case of directional antennas. While the employment of directional antennas is known to posses significant advantages over the traditional omnidirectional transmission, the problem of lifetime maximization under this environment has received only limited attention.We demonstrate that the change from the traditional (multiple-recipients) environment to the single-recipient environment is of major significance in terms of computational complexity and produces an interesting twist of difficulty: namely, for the standard model, the single-topology broadcast problem is computationally solvable and the multi-topology problem is NP-hard, while the opposite holds for the single-recipient model. Finally, we discuss the extension of our results to the case of multiple sessions.

Lempel-Ziv (1977) based compression algorithms are universal, not assuming any prior knowledge of the file to be compressed or its statistics. Accordingly, the reference dictionary of these textual substitution compression algorithms includes only segments of the already-processed portion of the file. It is often the case, though, that both, compressor and decompressor, even when they reside on different sites, share knowledge of files (e.g., devices managed by a server, or software customers holding older releases of products). For such cases, we suggest the addition of shared files to the reference dictionary. Preferably, files to be included are those which resemble the file to be compressed. Such an extension of the reference dictionary lengthens the matches found while compressing the file, and thus lessens the number of matches needed to cover the file. We found that with a careful selection (which can be automated) of the shared files to be included, the advantage of the decrease in the number of matches overwhelms the disadvantage of the increase in the number of bits needed to express the index of each match in the extended dictionary. Altogether, compression attainable by our proposed scheme can be significantly better than with the original Lempel-Ziv dictionary. Maintaining and searching a dictionary that is much larger than the original Lempel-Ziv dictionary demand strong computational resources and suits off-line more than on-line compression. We thus conclude that in the client/server environment, where shared files commonly exist, and the server enjoys extensive computational resources, the scheme suggested is advantageous for transferring files from the server to its clients.