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497 lines
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497 lines
28 KiB
Plaintext
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Allmydata "Tahoe" Architecture
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OVERVIEW
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The high-level view of this system consists of three layers: the grid, the
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virtual drive, and the application that sits on top.
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The lowest layer is the "grid", basically a DHT (Distributed Hash Table)
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which maps URIs to data. The URIs are relatively short ascii strings
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(currently about 140 bytes), and each is used as references to an immutable
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arbitrary-length sequence of data bytes. This data is distributed around the
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grid in a large number of nodes, such that a statistically unlikely number
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of nodes would have to be unavailable for the data to become unavailable.
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The middle layer is the virtual drive: a tree-shaped data structure in which
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the intermediate nodes are directories and the leaf nodes are files. Each
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file contains both the URI of the file's data and all the necessary metadata
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(MIME type, filename, ctime/mtime, etc) required to present the file to a
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user in a meaningful way (displaying it in a web browser, or on a desktop).
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The top layer is where the applications that use this virtual drive operate.
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Allmydata uses this for a backup service, in which the application copies the
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files to be backed up from the local disk into the virtual drive on a
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periodic basis. By providing read-only access to the same virtual drive
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later, a user can recover older versions of their files. Other sorts of
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applications can run on top of the virtual drive, of course, anything that
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has a use for a secure, robust, distributed filestore.
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Note: some of the description below indicates design targets rather than
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actual code present in the current release. Please take a look at roadmap.txt
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to get an idea of how much of this has been implemented so far.
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THE BIG GRID OF PEERS
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Underlying the grid is a large collection of peer nodes. These are processes
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running on a wide variety of computers, all of which know about each other in
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some way or another. They establish TCP connections to one another using
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Foolscap, an encrypted+authenticated remote message passing library (using
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TLS connections and self-authenticating identifiers called "FURLs").
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Each peer offers certain services to the others. The primary service is the
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StorageServer, which offers to hold data for a limited period of time (a
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"lease"). Each StorageServer has a quota, and it will reject lease requests
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that would cause it to consume more space than it wants to provide. When a
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lease expires, the data is deleted. Peers might renew their leases.
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This storage is used to hold "shares", which are themselves used to store
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files in the grid. There are many shares for each file, typically around 100
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(the exact number depends upon the tradeoffs made between reliability,
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overhead, and storage space consumed). The files are indexed by a piece of
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the URI called the "verifierid", which is derived from the contents of the
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file. Leases are indexed by verifierid, and a single StorageServer may hold
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multiple shares for the corresponding file. Multiple peers can hold leases on
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the same file, in which case the shares will be kept alive until the last
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lease expires. The typical lease is expected to be for one month: enough time
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for interested parties to renew it, but not so long that abandoned data
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consumes unreasonable space. Peers are expected to "delete" (drop leases) on
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data that they know they no longer want: lease expiration is meant as a
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safety measure.
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In this release, peers learn about each other through the "introducer". Each
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peer connects to this central introducer at startup, and receives a list of
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all other peers from it. Each peer then connects to all other peers, creating
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a fully-connected topology. Future versions will reduce the number of
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connections considerably, to enable the grid to scale to larger sizes: the
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design target is one million nodes. In addition, future versions will offer
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relay and NAT-traversal services to allow nodes without full internet
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connectivity to participate. In the current release, nodes behind NAT boxes
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will connect to all nodes that they can open connections to, but they cannot
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open connections to other nodes behind NAT boxes. Therefore, the more nodes
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there are behind NAT boxes the less the topology resembles the intended
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fully-connected mesh topology. (See also
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http://allmydata.org/trac/tahoe/ticket/22 ).
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FILE ENCODING
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When a file is to be added to the grid, it is first encrypted using a key
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that is derived from the hash of the file itself. The encrypted file is then
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broken up into segments so it can be processed in small pieces (to minimize
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the memory footprint of both encode and decode operations, and to increase
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the so-called "alacrity": how quickly can the download operation provide
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validated data to the user, basically the lag between hitting "play" and the
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movie actually starting). Each segment is erasure coded, which creates
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encoded blocks that are larger than the input segment, such that only a
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subset of the output blocks are required to reconstruct the segment. These
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blocks are then combined into "shares", such that a subset of the shares can
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be used to reconstruct the whole file. The shares are then deposited in
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StorageServers in other peers.
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A tagged hash of the original file is called the "fileid", while a
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differently-tagged hash of the original file provides the encryption key. A
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tagged hash of the *encrypted* file is called the "verifierid", and is used
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for both peer selection (described below) and to index shares within the
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StorageServers on the selected peers.
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The URI contains the fileid, the verifierid, the encryption key, any encoding
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parameters necessary to perform the eventual decoding process, and some
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additional hashes that allow the download process to validate the data it
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receives.
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On the download side, the node that wishes to turn a URI into a sequence of
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bytes will obtain the necessary shares from remote nodes, break them into
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blocks, use erasure-decoding to turn them into segments of crypttext, use the
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decryption key to convert that into plaintext, then emit the plaintext bytes
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to the output target (which could be a file on disk, or it could be streamed
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directly to a web browser or media player).
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All hashes use SHA256, and a different tag is used for each purpose.
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Netstrings are used where necessary to insure these tags cannot be confused
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with the data to be hashed. All encryption uses AES in CTR mode. The erasure
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coding is performed with zfec (a python wrapper around Rizzo's FEC library).
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A Merkle Hash Tree is used to validate the encoded blocks before they are fed
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into the decode process, and a second tree is used to validate the shares
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before they are retrieved. The hash tree root is put into the URI.
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Note that the number of shares created is fixed at the time the file is
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uploaded: it is not possible to create additional shares later. The use of a
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top-level hash tree also requires that nodes create all shares at once, even
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if they don't intend to upload some of them, otherwise the hashroot cannot be
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calculated correctly.
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URIs
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Each URI represents a specific set of bytes. Think of it like a hash
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function: you feed in a bunch of bytes, and you get out a URI. The URI is
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deterministically derived from the input data: changing even one bit of the
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input data will result in a drastically different URI. The URI provides both
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"identification" and "location": you can use it to locate/retrieve a set of
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bytes that are probably the same as the original file, and then you can use
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it to validate that these potential bytes are indeed the ones that you were
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looking for.
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URIs refer to an immutable set of bytes. If you modify a file and upload the
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new version to the grid, you will get a different URI. URIs do not represent
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filenames at all, just the data that a filename might point to at some given
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point in time. This is why the "grid" layer is insufficient to provide a
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virtual drive: an actual filesystem requires human-meaningful names and
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mutability, while URIs provide neither. URIs sit on the "global+secure" edge
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of Zooko's Triangle[1]. They are self-authenticating, meaning that nobody can
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trick you into using the wrong data.
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The URI should be considered as a "read capability" for the corresponding
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data: anyone who knows the full URI has the ability to read the given data.
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There is a subset of the URI (which leaves out the encryption key and fileid)
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which is called the "verification capability": it allows the holder to
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retrieve and validate the crypttext, but not the plaintext. Once the
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crypttext is available, the erasure-coded shares can be regenerated. This
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will allow a file-repair process to maintain and improve the robustness of
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files without being able to read their contents.
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The lease mechanism will also involve a "delete" capability, by which a peer
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which uploaded a file can indicate that they don't want it anymore. It is not
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truly a delete capability because other peers might be holding leases on the
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same data, and it should not be deleted until the lease count (i.e. reference
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count) goes to zero, so perhaps "cancel-the-lease capability" is more
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accurate. The plan is to store this capability next to the URI in the virtual
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drive structure.
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PEER SELECTION
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When a file is uploaded, the encoded shares are sent to other peers. But to
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which ones? The "peer selection" algorithm is used to make this choice.
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In the current version, the verifierid is used to consistently-permute the
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set of all peers (by sorting the peers by HASH(verifierid+peerid)). Each file
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gets a different permutation, which (on average) will evenly distribute
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shares among the grid and avoid hotspots.
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This permutation places the peers around a 2^256-sized ring, like the rim of
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a big clock. The 100-or-so shares are then placed around the same ring (at 0,
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1/100*2^256, 2/100*2^256, ... 99/100*2^256). Imagine that we start at 0 with
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an empty basket in hand and proceed clockwise. When we come to a share, we
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pick it up and put it in the basket. When we come to a peer, we ask that peer
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if they will give us a lease for every share in our basket.
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The peer will grant us leases for some of those shares and reject others (if
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they are full or almost full). If they reject all our requests, we remove
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them from the ring, because they are full and thus unhelpful. Each share they
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accept is removed from the basket. The remainder stay in the basket as we
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continue walking clockwise.
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We keep walking, accumulating shares and distributing them to peers, until
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either we find a home for all shares, or there are no peers left in the ring
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(because they are all full). If we run out of peers before we run out of
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shares, the upload may be considered a failure, depending upon how many
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shares we were able to place. The current parameters try to place 100 shares,
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of which 25 must be retrievable to recover the file, and the peer selection
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algorithm is happy if it was able to place at least 75 shares. These numbers
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are adjustable: 25-out-of-100 means an expansion factor of 4x (every file in
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the grid consumes four times as much space when totalled across all
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StorageServers), but is highly reliable (the actual reliability is a binomial
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distribution function of the expected availability of the individual peers,
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but in general it goes up very quickly with the expansion factor).
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If the file has been uploaded before (or if two uploads are happening at the
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same time), a peer might already have shares for the same file we are
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proposing to send to them. In this case, those shares are removed from the
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list and assumed to be available (or will be soon). This reduces the number
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of uploads that must be performed.
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When downloading a file, the current release just asks all known peers for
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any shares they might have, chooses the minimal necessary subset, then starts
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downloading and processing those shares. A later release will use the full
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algorithm to reduce the number of queries that must be sent out. This
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algorithm uses the same consistent-hashing permutation as on upload, but
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instead of one walker with one basket, we have 100 walkers (one per share).
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They each proceed clockwise in parallel until they find a peer, and put that
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one on the "A" list: out of all peers, this one is the most likely to be the
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same one to which the share was originally uploaded. The next peer that each
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walker encounters is put on the "B" list, etc.
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All the "A" list peers are asked for any shares they might have. If enough of
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them can provide a share, the download phase begins and those shares are
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retrieved and decoded. If not, the "B" list peers are contacted, etc. This
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routine will eventually find all the peers that have shares, and will find
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them quickly if there is significant overlap between the set of peers that
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were present when the file was uploaded and the set of peers that are present
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as it is downloaded (i.e. if the "peerlist stability" is high). Some limits
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may be imposed in large grids to avoid querying a million peers; this
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provides a tradeoff between the work spent to discover that a file is
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unrecoverable and the probability that a retrieval will fail when it could
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have succeeded if we had just tried a little bit harder. The appropriate
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value of this tradeoff will depend upon the size of the grid, and will change
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over time.
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Other peer selection algorithms are being evaluated. One of them (known as
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"tahoe 2") uses the same consistent hash, starts at 0 and requests one lease
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per peer until it gets 100 of them. This is likely to get better overlap
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(since a single insertion or deletion will still leave 99 overlapping peers),
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but is non-ideal in other ways (TODO: what were they?). It would also make it
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easier to select peers on the basis of their reliability, uptime, or
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reputation: we could pick 75 good peers plus 50 marginal peers, if it seemed
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likely that this would provide as good service as 100 good peers.
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Another algorithm (known as "denver airport"[2]) uses the permuted hash to
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decide on an approximate target for each share, then sends lease requests via
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Chord routing. The request includes the contact information of the uploading
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node, and asks that the node which eventually accepts the lease should
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contact the uploader directly. The shares are then transferred over direct
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connections rather than through multiple Chord hops. Download uses the same
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approach. This allows nodes to avoid maintaining a large number of long-term
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connections, at the expense of complexity, latency, and reliability.
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SWARMING DOWNLOAD, TRICKLING UPLOAD
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Because the shares being downloaded are distributed across a large number of
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peers, the download process will pull from many of them at the same time. The
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current encoding parameters require 25 shares to be retrieved for each
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segment, which means that up to 25 peers will be used simultaneously. This
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allows the download process to use the sum of the available peers' upload
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bandwidths, resulting in downloads that take full advantage of the common 8x
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disparity between download and upload bandwith on modern ADSL lines.
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On the other hand, uploads are hampered by the need to upload encoded shares
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that are larger than the original data (4x larger with the current default
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encoding parameters), through the slow end of the asymmetric connection. This
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means that on a typical 8x ADSL line, uploading a file will take about 32
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times longer than downloading it again later.
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Smaller expansion ratios can reduce this upload penalty, at the expense of
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reliability. See RELIABILITY, below.
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FILETREE: THE VIRTUAL DRIVE LAYER
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The "virtual drive" layer is responsible for mapping human-meaningful
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pathnames (directories and filenames) to pieces of data. The actual bytes
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inside these files are referenced by URI, but the "filetree" is where the
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directory names, file names, and metadata are kept.
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The current release has a very simplistic filetree model. There is a single
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globally-shared directory structure, which maps filename to URI. This
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structure is maintained in a central node (which happens to be the same node
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that houses the Introducer), by writing URIs to files in a local filesystem.
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A future release (probably the next one) will offer each application the
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ability to have a separate file tree. Each tree can reference others. Some
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trees are redirections, while others actually contain subdirectories full of
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filenames. The redirections may be mutable by some users but not by others,
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allowing both read-only and read-write views of the same data. This will
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enable individual users to have their own personal space, with links to
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spaces that are shared with specific other users, and other spaces that are
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globally visible. Eventually the application layer will present these pieces
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in a way that allows the sharing of a specific file or the creation of a
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"virtual CD" as easily as dragging a folder onto a user icon.
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The URIs described above are "Content Hash Key" (CHK) identifiers[3], in
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which the identifier refers to a specific, unchangeable sequence of bytes. In
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this project, CHK identifiers are used for both files and immutable versions
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of directories: the tree of directory and file nodes is serialized into a
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sequence of bytes, which is then uploaded and turned into a URI. Each time
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the directory is changed, a new URI is generated for it and propagated to the
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filetree above it. There is a separate kind of upload, not yet implemented,
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called SSK (short for Signed Subspace Key), in which the URI refers to a
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mutable slot. Some users have a write-capability to this slot, allowing them
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to change the data that it refers to. Others only have a read-capability,
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merely letting them read the current contents. These SSK slots can be used to
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provide mutability in the filetree, so that users can actually change the
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contents of their virtual drive. Redirection nodes can also provide
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mutability, such as a central service which allows a user to set the current
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URI of their top-level filetree. SSK slots provide a decentralized way to
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accomplish this mutability, whereas centralized redirection nodes are more
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vulnerable to single-point-of-failure issues.
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FILE REPAIRER
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Each node is expected to explicitly drop leases on files that it knows it no
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longer wants (the "delete" operation). Nodes are also expected to renew
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leases on files that still exist in their filetrees. When nodes are offline
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for an extended period of time, their files may decay (both because of leases
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expiring and because of StorageServers going offline). A File Verifier is
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used to check on the health of any given file, and a File Repairer is used to
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to keep desired files alive. The two are conceptually distinct (the repairer
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is run if the verifier decides it is necessary), but in practice they will be
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closely related, and may run in the same process.
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The repairer process does not get the full URI of the file to be maintained:
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it merely gets the "repairer capability" subset, which does not include the
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decryption key. The File Verifier uses that data to find out which peers
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ought to hold shares for this file, and to see if those peers are still
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around and willing to provide the data. If the file is not healthy enough,
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the File Repairer is invoked to download the crypttext, regenerate any
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missing shares, and upload them to new peers. The goal of the File Repairer
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is to finish up with a full set of 100 shares.
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There are a number of engineering issues to be resolved here. The bandwidth,
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disk IO, and CPU time consumed by the verification/repair process must be
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balanced against the robustness that it provides to the grid. The nodes
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involved in repair will have very different access patterns than normal
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nodes, such that these processes may need to be run on hosts with more memory
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or network connectivity than usual. The frequency of repair runs directly
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affects the resources consumed. In some cases, verification of multiple files
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can be performed at the same time, and repair of files can be delegated off
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to other nodes.
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The security model we are currently using assumes that peers who claim to
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hold a share will actually provide it when asked. (We validate the data they
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provide before using it in any way, but if enough peers claim to hold the
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data and are wrong, the file will not be repaired, and may decay beyond
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recoverability). There are several interesting approaches to mitigate this
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threat, ranging from challenges to provide a keyed hash of the allegedly-held
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data (using "buddy nodes", in which two peers hold the same block, and check
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up on each other), to reputation systems, or even the original Mojo Nation
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economic model.
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SECURITY
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The design goal for this project is that an attacker may be able to deny
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service (i.e. prevent you from recovering a file that was uploaded earlier)
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but can accomplish none of the following three attacks:
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1) violate privacy: the attacker gets to view data to which you have not
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granted them access
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2) violate consistency: the attacker convinces you that the wrong data is
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actually the data you were intending to retrieve
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3) violate mutability: the attacker gets to modify a filetree (either the
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pathnames or the file contents) to which you have not given them
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mutability rights
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Data validity and consistency (the promise that the downloaded data will
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match the originally uploaded data) is provided by the hashes embedded the
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URI. Data security (the promise that the data is only readable by people with
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the URI) is provided by the encryption key embedded in the URI. Data
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availability (the hope that data which has been uploaded in the past will be
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downloadable in the future) is provided by the grid, which distributes
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failures in a way that reduces the correlation between individual node
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failure and overall file recovery failure.
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Many of these security properties depend upon the usual cryptographic
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assumptions: the resistance of AES and RSA to attack, the resistance of
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SHA256 to pre-image attacks, and upon the proximity of 2^-128 and 2^-256 to
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zero. A break in AES would allow a privacy violation, a pre-image break in
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SHA256 would allow a consistency violation, and a break in RSA would allow a
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mutability violation. The discovery of a collision in SHA256 is unlikely to
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allow much, but could conceivably allow a consistency violation in data that
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was uploaded by the attacker. If SHA256 is threatened, further analysis will
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be warranted.
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There is no attempt made to provide anonymity, neither of the origin of a
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piece of data nor the identity of the subsequent downloaders. In general,
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anyone who already knows the contents of a file will be in a strong position
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to determine who else is uploading or downloading it. Also, it is quite easy
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for a coalition of more than 1% of the nodes to correlate the set of peers
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who are all uploading or downloading the same file, even if the attacker does
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not know the contents of the file in question.
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Also note that the file size and verifierid are not protected. Many people
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can determine the size of the file you are accessing, and if they already
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know the contents of a given file, they will be able to determine that you
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are uploading or downloading the same one.
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A likely enhancement is the ability to use distinct encryption keys for each
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file, avoiding the file-correlation attacks at the expense of increased
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storage consumption.
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The capability-based security model is used throughout this project. Filetree
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operations are expressed in terms of distinct read and write capabilities.
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The URI of a file is the read-capability: knowing the URI is equivalent to
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the ability to read the corresponding data. The capability to validate and
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repair a file is a subset of the read-capability. The capability to read an
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SSK slot is a subset of the capability to modify it. These capabilities may
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|
be expressly delegated (irrevocably) by simply transferring the relevant
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|
secrets. Special forms of SSK slots can be used to make revocable delegations
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|
of particular directories. Certain redirections in the filetree code are
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|
expressed as Foolscap "furls", which are also capabilities and provide access
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|
to an instance of code running on a central server: these can be delegated
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|
just as easily as any other capability, and can be made revocable by
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|
delegating access to a forwarder instead of the actual target.
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The application layer can provide whatever security/access model is desired,
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|
but we expect the first few to also follow capability discipline: rather than
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|
user accounts with passwords, each user will get a furl to their private
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|
filetree, and the presentation layer will give them the ability to break off
|
|
pieces of this filetree for delegation or sharing with others on demand.
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|
RELIABILITY
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|
|
|
File encoding and peer selection parameters can be adjusted to achieve
|
|
different goals. Each choice results in a number of properties; there are
|
|
many tradeoffs.
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|
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|
First, some terms: the erasure-coding algorithm is described as K-out-of-N
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|
(for this release, the default values are K=25 and N=100). Each grid will
|
|
have some number of peers; this number will rise and fall over time as peers
|
|
join, drop out, come back, and leave forever. Files are of various sizes,
|
|
some are popular, others are rare. Peers have various capacities, variable
|
|
upload/download bandwidths, and network latency. Most of the mathematical
|
|
models that look at peer failure assume some average (and independent)
|
|
probability 'P' of a given peer being available: this can be high (servers
|
|
tend to be online and available >90% of the time) or low (laptops tend to be
|
|
turned on for an hour then disappear for several days). Files are encoded in
|
|
segments of a given maximum size, which affects memory usage.
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|
|
|
The ratio of N/K is the "expansion factor". Higher expansion factors improve
|
|
reliability very quickly (the binomial distribution curve is very sharp), but
|
|
consumes much more grid capacity. The absolute value of K affects the
|
|
granularity of the binomial curve (1-out-of-2 is much worse than
|
|
50-out-of-100), but high values asymptotically approach a constant that
|
|
depends upon 'P' (i.e. 500-of-1000 is not much better than 50-of-100).
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|
|
|
Likewise, the total number of peers in the network affects the same
|
|
granularity: having only one peer means a single point of failure, no matter
|
|
how many copies of the file you make. Independent peers (with uncorrelated
|
|
failures) are necessary to hit the mathematical ideals: if you have 100 nodes
|
|
but they are all in the same office building, then a single power failure
|
|
will take out all of them at once. The "Sybil Attack" is where a single
|
|
attacker convinces you that they are actually multiple servers, so that you
|
|
think you are using a large number of independent peers, but in fact you have
|
|
a single point of failure (where the attacker turns off all their machines at
|
|
once). Large grids, with lots of truly-independent peers, will enable the
|
|
use of lower expansion factors to achieve the same reliability, but increase
|
|
overhead because each peer needs to know something about every other, and the
|
|
rate at which peers come and go will be higher (requiring network maintenance
|
|
traffic). Also, the File Repairer work will increase with larger grids,
|
|
although then the job can be distributed out to more peers.
|
|
|
|
Higher values of N increase overhead: more shares means more Merkle hashes
|
|
that must be included with the data, and more peers to contact to retrieve
|
|
the shares. Smaller segment sizes reduce memory usage (since each segment
|
|
must be held in memory while erasure coding runs) and increases "alacrity"
|
|
(since downloading can validate a smaller piece of data faster, delivering it
|
|
to the target sooner), but also increase overhead (because more blocks means
|
|
more Merkle hashes to validate them).
|
|
|
|
In general, small private grids should work well, but the participants will
|
|
have to decide between storage overhead and reliability. Large stable grids
|
|
will be able to reduce the expansion factor down to a bare minimum while
|
|
still retaining high reliability, but large unstable grids (where nodes are
|
|
coming and going very quickly) may require more repair/verification bandwidth
|
|
than actual upload/download traffic.
|
|
|
|
|
|
------------------------------
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|
|
|
[1]: http://en.wikipedia.org/wiki/Zooko%27s_triangle
|
|
|
|
[2]: all of these names are derived from the location where they were
|
|
concocted, in this case in a car ride from Boulder to DEN. To be
|
|
precise, "tahoe 1" was an unworkable scheme in which everyone holding
|
|
shares for a given file formed a sort of cabal which kept track of all
|
|
the others, "tahoe 2" is the first-100-peers in the permuted hash, and
|
|
this document descibes "tahoe 3", or perhaps "potrero hill 1".
|
|
|
|
[3]: the terms CHK and SSK come from Freenet,
|
|
http://wiki.freenetproject.org/FreenetCHKPages ,
|
|
although we use "SSK" in a slightly different way
|
|
|