This paper presents LBFS, a network file system designed for low bandwidth networks. LBFS exploits similarities between files or versions of the same file to save bandwidth. It avoids sending data over the network when the same data can already be found in the server's file system or the client's cache. Using this technique, LBFS achieves up to two orders of magnitude reduction in bandwidth utilization on common workloads, compared to traditional network file systems

This paper shows how to quickly move the state of a run-ning computer across a network, including the state in its disks, memory, CPU registers, and I/O devices. We call this state a capsule. Capsule state is hardware state, so it

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We have developed a new approach for reliably multicasting timecritical data to heterogeneous clients over mesh-based overlay networks. To facilitate intelligent content pruning, data streams are comprised of a sequence of XML packets and forwarded by application-level XML routers. XML routers perform contentbased routing of individual XML packets to other routers or clients based upon queries that describe the information needs of downstream nodes. Our PC-based XML router prototype can route an 18 Mbit per second XML stream. Our routers use

Wireless transmission of a bit can require over 1000 times more energy than a single 32-bit computation. It would therefore seem desirable to perform significant computation to reduce the number of bits transmitted. If the energy required to compress data is less than the energy required to send it, there is a net energy savings and consequently, a longer battery life for portable computers. This paper reports on the energy of lossless data compressors as measured on a StrongARM SA-110 system. We show that with several typical compression tools, there is a net energy increase when compression is applied before transmission. Reasons for this increase are explained, and hardwareaware programming optimizations are demonstrated. When applied to Unix compress, these optimizations improve energy efficiency by 51%. We also explore the fact that, for many usage models, compression and decompression need not be performed by the same algorithm. By choosing the lowest-energy compressor and decompressor on the test platform, rather than using default levels of compression, overall energy to send compressible web data can be reduced 31%. Energy to send harder-to-compress English text can be reduced 57%. Compared with a system using a single optimized application for both compression and decompression, the asymmetric scheme saves 11% or 12% of the total energy depending on the dataset.

Despite traditional web caching techniques, redundant data is often transferred over HTTP links. These redundant transfers result from both resource modification and aliasing. Resource modification causes the data represented by a single URI to change; often, in transferring the new data, some old data is retransmitted. Aliasing, in contrast, occurs when the same data is named by multiple URIs, often in the context of dynamic or advertising content. Traditional web caching techniques index data by its name and thus often fail to recognize and take advantage of aliasing. In this work we present Value-Based Web Caching, a technique that eliminates redundant data transfers due to both resource modification and aliasing using the same algorithm. This algorithm caches data based on its value, rather than its name. It is designed for use between a parent and child proxy over a low bandwidth link, and in the common case it requires no additional message round trips. The parent proxy stores a small amount of soft-state per client that it uses to eliminate redundant transfers. The additional computational requirements on the parent proxy are small, and there are virtually no additional computational or storage requirements on the child proxy. Finally, our algorithm allows the parent proxy to serve simultaneously as a traditional web cache and is orthogonal to other bandwidth-saving measures such as data compression. In our experiments, this algorithm yields a significant reduction in both bandwidth usage and user-perceived time-to-display versus traditional web caching.

Motivated by the prospect of readily available Content Addressable Storage (CAS), we introduce the concept of file recipes. A file's recipe is a first-class file system object listing content hashes that describe the data blocks composing the file. File recipes provide applications with instructions for reconstructing the original file from available CAS data blocks. We describe one such application of recipes, the CASPER distributed file system. A CASPER client opportunistically fetches blocks from nearby CAS providers to improve its performance when the connection to a file server traverses a low-bandwidth path. We use measurements of our prototype to evaluate its performance under varying network conditions. Our results demonstrate significant improvements in execution times of applications that use a network file system. We conclude by describing fuzzy block matching, a promising technique for using approximately matching blocks on CAS providers to reconstitute the exact desired contents of a file at a client.

Abstract — We present an incremental network programming mechanism which reprograms wireless sensors quickly by transmitting the incremental changes for the new program version. Using the Rsync algorithm we generate the difference of the two program images, which allows us to distribute just the key changes of the program. Unlike previous approaches, our design does not assume any prior knowledge of the program code structure and can be applied to any hardware platform. To meet the resource constraints of wireless sensors we tuned the Rsync algorithm which was originally made for updating binary files among compuationally powerful machines. In our design, the sensor node processes the delivery and the decoding of the difference script in separate steps. This makes it easy to extend for multi-hop network programming. We are able to achieve the speedup of 9.1 for changing a constant and 2.1 to 2.5 for changing a few lines in the source code over the non-incremental delivery. I.

Ongoing advancements in technology lead to everincreasing storage capacities. In spite of this, optimizing storage usage can still provide rich dividends. Several techniques based on delta-encoding and duplicate block suppression have been shown to reduce storage overheads, with varying requirements for resources such as computation and memory. We propose a new scheme for storage reduction that reduces data sizes with an effectiveness comparable to the more expensive techniques, but at a cost comparable to the faster but less effective ones. The scheme, called Redundancy Elimination at the Block Level (REBL), leverages the benefits of compression, duplicate block suppression, and delta-encoding to eliminate a broad spectrum of redundant data in a scalable and efficient manner. REBL generally encodes more compactly than compression (up to a factor of 14) and a combination of compression and duplicate suppression (up to a factor of 6.7). REBL also encodes similarly to a technique based on delta-encoding, reducing overall space significantly in one case. Furthermore, REBL uses super-fingerprints, a technique that reduces the data needed to identify similar blocks while dramatically reducing the computational requirements of matching the blocks: it turns comparisons into hash table lookups. As a result, using super-fingerprints to avoid enumerating matching data objects decreases computation in the resemblance detection phase of REBL by up to a couple orders of magnitude.

The ability to update the program code installed on wireless sensor nodes plays an import role in the highly dynamic environments sensor networks are often deployed in. Such code update mechanisms should support flexible reconfiguration and adaptation of the sensor nodes but should also operate in an energy and time efficient manner. In this paper, we present FlexCup, a flexible code update mechanism that minimizes the energy consumed on each sensor node for the installation of arbitrary code changes. We describe two different versions of FlexCup and show, using a precise hardware emulator, that our mechanism is able to perform updates up to 8 times faster than related code update algorithms found in the literature, while consuming only an eighth of the energy.