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| '''Routing in delay-tolerant networking''' concerns itself with the
| |
| ability to [[Transport layer|transport]], or route, data from a source to a
| |
| destination, which is a fundamental ability all communication networks must
| |
| have. [[Delay-tolerant networking|Delay- and disruption-tolerant networks
| |
| (DTNs)]] are characterized by their lack of [[Telecommunication circuit|connectivity]], resulting in a lack of instantaneous end-to-end paths. In these challenging environments, popular ad hoc routing protocols such as [[Ad hoc On-demand Distance Vector|AODV]]<ref>C. E. Perkins and E. M. Royer. Ad hoc on-demand distance vector routing. In The Second IEEE Workshop on Mobile Computing Systems and Applications, February 1999.</ref> and [[Dynamic Source Routing|DSR]]<ref>D. B. Johnson and D. A. Maltz. Mobile Computing, chapter Dynamic source routing in ad hoc wireless networks, pages 153–181. Kluwer Academic Publishers, February 1996.</ref> fail to establish routes. This is due to these protocols trying to first establish a complete route and then, after the route has been established, forward the actual data. However, when instantaneous end-to-end paths are difficult or impossible to establish, routing protocols must take to a "store and forward" approach, where data is
| |
| incrementally moved and stored throughout the network in hopes that it will eventually reach its destination.<ref name="burgess2006">John Burgess,
| |
| Brian Gallagher, David Jensen, and Brian Neil Levine. MaxProp: Routing for vehicle-based disruption-tolerant networks. In Proc. IEEE INFOCOM, April
| |
| 2006.</ref><ref>Philo Juang, Hidekazu Oki, Yong Wang, Margaret Martonosi,
| |
| Li Shiuan Peh, and Daniel Rubenstein. Energy-efficient computing
| |
| for wildlife tracking: design tradeoffs and early experiences with
| |
| zebranet. SIGOPS Oper. Syst. Rev., 36(5):96–107, 2002.</ref><ref>Augustin
| |
| Chaintreau, Pan Hui, Jon Crowcroft, Christophe Diot, Richard Gass,
| |
| and James Scott. Impact of human mobility on opportunistic forwarding
| |
| algorithms. IEEE Transactions on Mobile Computing, 6(6):606–620,
| |
| 2007.</ref> A common technique used to
| |
| maximize the probability of a message being successfully transferred is to
| |
| replicate many copies of the message in hopes that one will succeed in
| |
| reaching its destination.<ref name="vahdat2000">Amin Vahdat and
| |
| David Becker. Epidemic routing for partially connected ad hoc
| |
| networks. Technical Report CS-2000-06, Department of Computer Science,
| |
| Duke University, April 2000.</ref>
| |
|
| |
|
| == Routing considerations ==
| |
|
| |
|
| There are many characteristics DTN protocols, including [[routing]], must
| | While this may seem like a stroke of good luck you'll need to be careful. You might think that you can get legal help from one of those websites that sells Florida divorce papers. Personal injury lawyers are needed for most cases associated with some kind of an auto accident. Faster a lawsuit is filed the greater is the chance of claiming rightful compensation. Author: James Stew is conveying information about Stockton personal injury attorney. <br><br>It can potentially be up to 40 percent of the final figure. It is the best thing to discuss before your case’s beginning. Moreover, it is advisable for hiring the lawyer with proper consultation with your relatives or friends. Be careful with those flybynight practitioners as they can just be a nuisance in your life. Hence, personal injury lawyers are likely to be well versed and have more experience with regard to the field of law known as tort law; this also [https://www.google.com/search?hl=en&gl=us&tbm=nws&q=includes+civil&btnI=lucky includes civil] faults and economic or non-economic damages to an individual's property, fame or honor. <br><br>Every tort claim, regardless of its basis, whether intentional, negligence, or strict liability, has two basic issues. [http://www.youtube.com/watch?v=39Q480L-wyU Schwartz lawyers and attorneys] You may ask some recommendation from your peers or friends. Many people think that you can only claim for pain and suffering, and income loss, yet there are in fact various other claims that you can make. However, if an injury approaches him by himself then he does not blame anyone, but if there is other person behind the presence of injury or accident inflicted to him then the victim should not forget to consider the legal obligation that can provide him with the financial help. Generally this information is authentic and a proof of quality of service provided by the lawyer. <br><br>By choosing an attorney that is well suited to take on your case, you are making what can be a difficult and taxing process into a smooth endeavor. Claim denials can be unsettling for the claimants, but it is not the end of the road for the policy holder. Even otherwise, the partner can refuse to cooperate and cause the business to become dysfunctional. If you get affected by spinal cord injury you lose the mobility in your body. The inexperienced and novices would find difficulty in negotiating with insurance companies. <br><br>The most common types of personal injury cases are workplace mishaps, road accidents, domestic accidents, construction mishaps, etc. Claimants must consider consulting a long-term disability lawyer who can advise properly on the case. Its no mystery that car insurance companies like to pay as little as they can. This is why I wanted to take a moment to perhaps pick up where many of these advertisements have left off by not only helping you to determine whether or not you may require these services, but to also help you better understand just how you could benefit from hiring a personal injury lawyer in Vancouver. A bicycle accident attorney Chandler or a bicycle accident attorney Chandler can help you get the compensation you deserve. |
| take into consideration. A first consideration is if information
| |
| about future contacts is readily available. For example, in
| |
| [[Interplanetary Internet|interplanetary communications]], many times a planet or moon
| |
| is the
| |
| cause of contact disruption, and large distance is the cause of
| |
| communication delay. However, due to the [[orbit|laws of physics]], it is
| |
| possible to predict the future in terms of the times contacts will be
| |
| available, and how long they will last. These types of contacts are
| |
| known as ''scheduled'' or ''predictable contacts''.<ref name="jain2004">Sushant
| |
| Jain, Kevin Fall, and Rabin Patra. Routing in a delay-tolerant network. In
| |
| Proc. ACM SIGCOMM, 2004.</ref> On the contrary, in
| |
| disaster recovery networks the future location of communicating
| |
| entities, such as [[Emergency service|emergency responders]], may not be known. These types
| |
| of contacts are known as ''intermittent'' or ''opportunistic contacts''.
| |
| | |
| A second consideration is if [[Mobile computing|mobility]] can be exploited and, if so,
| |
| which nodes are mobile. There are three major cases, classifying the
| |
| level of mobility in the network. First, it is possible that there
| |
| are no mobile entities. In this case, contacts appear and disappear
| |
| based solely on the quality of the communication channel between them.
| |
| For instance, in [[Interplanetary Internet|interplanetary networks]], large objects in space, such
| |
| as planets, can block communicating nodes for a set period of time.
| |
| Second, it is possible that some, but not all, nodes in the network
| |
| are mobile. These nodes, sometimes referred to as [[Data Mule]]s,<ref>Jea D.,
| |
| Somasundara A. A, and Srivastava M. B. Multiple Controlled Mobile Elements
| |
| (Data Mules) for Data Collection in Sensor Networks. In Proc. IEEE/ACM
| |
| International Conference on Distributed Computing in Sensor Systems
| |
| (DCOSS), June 2005.</ref><ref>Rahul C. Shah, Sumit Roy, Sushant Jain,
| |
| and Waylon Brunette. Data MULEs: Modeling a Three-tier Architecture for
| |
| Sparse Sensor Networks. In Proc. IEEE SNPA Workshop, May 2003.</ref>
| |
| are exploited for their mobility. Since they are the primary | |
| source of transitive communication between two non-neighboring nodes
| |
| in the network, an important routing question is how to properly
| |
| distribute data among these nodes. Third,
| |
| it is possible that the vast majority, if not all, nodes in the
| |
| network are mobile. In this case, a routing protocol will most
| |
| likely have more options available during contact opportunities, and
| |
| may not have to utilize each one.<ref name="burgess2006" /><ref
| |
| name="balasubramanian2007">Aruna Balasubramanian, Brian Neil
| |
| Levine, and Arun Venkataramani. DTN routing as a resource
| |
| allocation problem. In Proc. ACM SIGCOMM, August 2007.</ref><ref
| |
| name="spyropoulos2005">Thrasyvoulos Spyropoulos, Konstantinos Psounis,
| |
| and Cauligi S. Raghavendra. Spray and wait: An efficient routing scheme
| |
| for intermittently connected mobile networks. In WDTN ’05: Proceeding of
| |
| the 2005 ACM SIGCOMM workshop on Delay-tolerant networking, 2005.</ref><ref
| |
| name="spyropoulos2007">Thrasyvoulos Spyropoulos, Konstantinos Psounis,
| |
| and Cauligi S. Raghavendra. Spray and focus: Efficient mobility-assisted
| |
| routing for heterogeneous and correlated mobility. In Fifth Annual
| |
| IEEE International Conference on Pervasive Computing and Communications
| |
| Workshops, 2007.</ref> An example of this
| |
| type of network is a disaster recovery network where all nodes
| |
| (generally people and [[Vehicular ad hoc Network|vehicles]]) are mobile.<ref>Samuel C. Nelson,
| |
| Albert F. Harris, and Robin Kravets. Event-driven, role-based mobility
| |
| in disaster recovery networks. In CHANTS 07: Proceedings of the second
| |
| workshop on Challenged Networks, 2007.</ref> A second example is a
| |
| vehicular network where mobile cars, trucks, and buses act as
| |
| communicating entities.<ref name="burgess2006" />
| |
| | |
| A third consideration is the availability of network resources. Many
| |
| nodes, such as mobile phones, are limited in terms of storage space,
| |
| transmission rate, and battery life. Others, such as buses on the
| |
| road, may not be as limited. Routing protocols can utilize this
| |
| information to best determine how messages should be transmitted and
| |
| stored to not over-burden limited resources. As of April 2008, only recently has the
| |
| scientific community started taking resource management into
| |
| consideration, and this is still an active area of research.
| |
| | |
| == Routing protocol classifications ==
| |
| | |
| While there are many characteristics of [[routing protocol]]s, one of the
| |
| most immediate ways to create a taxonomy is based on whether or not
| |
| the protocol creates replicas of messages. Routing protocols that | |
| never replicate a message are considered [[Packet forwarding|forwarding]]-based, whereas
| |
| protocols that do replicate messages are considered
| |
| replication-based. This simple, yet popular, taxonomy was recently
| |
| used by Balasubramanian et al. to classify a large number of DTN
| |
| routing protocols.<ref name="balasubramanian2007" />
| |
| | |
| There are both advantages and disadvantages to each approach, and the
| |
| appropriate approach to use is probably dependent on the scenario at
| |
| hand. Forwarding-based approaches are generally much less wasteful of
| |
| network resources, as only a single copy of a message exists in
| |
| storage in the network at any given time.<ref name="jain2004" /><ref>Dan
| |
| Henriksson, Tarek F. Abdelzaher, and Raghu K. Ganti. A caching-based
| |
| approach to routing in delay-tolerant networks. In Proceedings of
| |
| 16th International Conference on Computer Communications and Networks,
| |
| 2007. ICCCN 2007, 2007.</ref> Furthermore, when
| |
| the destination receives the message, no other node can have a copy.
| |
| This eliminates the need for the destination to provide feedback to
| |
| the network (except for, perhaps, an acknowledgments sent to the
| |
| sender), to indicate outstanding copies can be deleted.
| |
| Unfortunately, forwarding-based approaches do not allow for sufficient
| |
| message delivery rates in many DTNs.<ref name="spyropoulos2005" />
| |
| Replication-based
| |
| protocols, on the other hand, allow for greater message delivery
| |
| rates,<ref name="burgess2006" /> since multiple copies exist in the
| |
| network, and only one (or in
| |
| some cases, as with erasure coding, a few) must reach the destination.
| |
| However, the tradeoff here is that these protocols can waste valuable
| |
| network resources.<ref name="spyropoulos2007" /> Furthermore, many
| |
| flooding-based protocols are
| |
| inherently not scalable. Some protocols, such as Spray and Wait,<ref
| |
| name="spyropoulos2005" />
| |
| attempt to compromise by limiting the number of possible replicas of a given message.
| |
| | |
| It is important to note that the vast majority of DTN routing protocols are [[heuristic]]-based, and non-optimal. This is due to optimality being, in the general DTN case, [[NP-hard]].<ref
| |
| name="balasubramanian2007" /> More specifically "[[online algorithms]] without complete future knowledge and with unlimited computational power, or computationally limited algorithms with complete future knowledge, can be arbitrarily far from optimal".<ref name="balasubramanian2007" />
| |
| | |
| == Replication-based routing ==
| |
| | |
| [[Replication (computer science)|Replication]]-based protocols have recently obtained much attention in
| |
| the scientific community, as they can allow for substantially better
| |
| message delivery ratios than in forwarding-based protocols. These
| |
| types of routing protocols allow for a message to be replicated; each
| |
| of the replicas, as well as the original message itself, are generally
| |
| referred to as message copies or message replicas. Possible issues with
| |
| replication-based routing include:
| |
| # [[network congestion]] in clustered areas,
| |
| # being wasteful with network resources (including bandwidth, storage, and energy), and
| |
| # network scalability.
| |
| | |
| Since network resources may quickly become constrained, deciding which
| |
| messages to transmit first and which messages to drop first play
| |
| critical roles in many routing protocols.
| |
| | |
| === Epidemic routing ===
| |
| | |
| Epidemic routing<ref name="vahdat2000" /> is flooding-based in nature,
| |
| as nodes continuously replicate and transmit messages to newly
| |
| discovered contacts that do not already possess a copy of the
| |
| message. In the most simple case, epidemic routing is flooding;
| |
| however, more sophisticated techniques can be used to limit the
| |
| number of message transfers. Epidemic routing has its roots in
| |
| ensuring distributed databases remain synchronized, and many of
| |
| these techniques, such as rumor mongering, can be directly applied
| |
| to routing.
| |
| | |
| === PRoPHET routing protocol === | |
| | |
| [[#Epidemic routing|Epidemic routing]] is particularly resource hungry
| |
| because it deliberately makes no attempt to eliminate replications
| |
| that would be unlikely to improve the delivery probability of messages.
| |
| This strategy is effective if the opportunistic encounters between nodes
| |
| are purely random, but in realistic situations, encounters are rarely
| |
| totally random. [[Data Mule]]s (mostly associated with a human) move in a
| |
| society and
| |
| accordingly tend to have greater probabilities of meeting certain Mules
| |
| than others.
| |
| The '''Probabilistic Routing Protocol using History of Encounters and Transitivity (PRoPHET)''' protocol uses an algorithm that attempts to exploit
| |
| the non-randomness of real-world encounters by maintaining a set of
| |
| probabilities
| |
| for successful delivery to known destinations in the DTN
| |
| (''delivery predictabilities'') and replicating messages during opportunistic
| |
| encounters only if the Mule that does not have the message
| |
| appears to have a better chance of delivering it. This strategy was
| |
| first documented in a paper from 2003.<ref name="Probabilistic">A. oria, and O. Scheln. Probabilistic routing in
| |
| intermittently connected networks. In Proceedings of the Fourth ACM
| |
| International Symposium on Mobile Ad Hoc Networking and Computing
| |
| (MobiHoc 2003), 2003.</ref>
| |
| | |
| An adaptive algorithm is used to determine the delivery predictabilities
| |
| in each Mule. The Mule ''M'' stores delivery predictabilities
| |
| ''P''(''M'',''D'') for each known destination ''D''. If the Mule has
| |
| not stored a predictability value for a destination ''P''(''M'',''D'')
| |
| is assumed to be zero. The delivery predictabilities used by each Mule
| |
| are recalculated at each opportunistic encounter according to three rules:
| |
| # When the Mule ''M'' encounters another Mule ''E'', the predictability for ''E'' is increased: <br/>''P''(''M'',''E'')<sub>''new''</sub> = ''P''(''M'',''E'')<sub>''old''</sub> + (1 - ''P''(''M'',''E'')<sub>''old''</sub>) * ''L<sub>encounter</sub>'' where ''L<sub>encounter</sub>'' is an initialisation constant.
| |
| # The predictabilities for all destinations ''D'' other than ''E'' are 'aged': <br/>''P''(''M'',''D'')<sub>''new''</sub> = ''P''(''M'',''D'')<sub>''old''</sub> * ''γ<sup>K</sup>'' where ''γ'' is the aging constant and ''K'' is the number of time units that has elapsed since the last aging.
| |
| # Predictabilities are exchanged between ''M'' and ''E'' and the 'transitive' property of predictability is used to update the predictability of destinations ''D'' for which ''E'' has a ''P''(''E'',''D'') value on the assumption that ''M'' is likely to meet ''E'' again: <br/>''P''(''M'',''D'')<sub>''new''</sub> = ''P''(''M'',''D'')<sub>''old''</sub> + (1 - ''P''(''M'',''D'')<sub>''old''</sub>) * ''P''(''M'',''E'') * ''P''(''E'',''D'') * ''β'' where ''β'' is a scaling constant.
| |
| | |
| The protocol has been incorporated into the reference implementation maintained
| |
| by the [http://www.dtnrg.org/ IRTF DTN Research Group] and the current version is
| |
| documented in an
| |
| [http://tools.ietf.org/html/draft-irtf-dtnrg-prophet Internet Draft].<ref>
| |
| A. Lindgren and A. Doria, Probabilistic Routing Protocol for
| |
| Intermittently Connected Networks, Internet Draft - http://tools.ietf.org/html/draft-irtf-dtnrg-prophet,
| |
| February 2010</ref> The protocol has been trialled in real world situations
| |
| during the [http://www.snc.sapmi.net/ Sámi Network Connectivity (SNC)] project
| |
| and is being further developed during the EU Framework Programme 7 project
| |
| [http://www.n4c.eu Networking for Communications Challenged Communities (N4C)].
| |
| | |
| === MaxProp ===
| |
| | |
| MaxProp<ref name="burgess2006" /> was developed at the [[University of Massachusetts Amherst|University of
| |
| Massachusetts, Amherst]] and
| |
| was, in part, funded by [[DARPA]] and the [[National Science Foundation]].
| |
| The original paper is found in the [[IEEE]] INFOCOM 2006 conference.
| |
| MaxProp is [[Flooding (computer networking)|flooding]]-based in nature, in that if a contact is
| |
| discovered, all messages not held by the contact will attempt to be
| |
| replicated and transferred. The intelligence of MaxProp comes in
| |
| determining which messages should be transmitted first and which
| |
| messages should be dropped first. In essence, MaxProp maintains
| |
| an [[Queue (data structure)|ordered-queue]] based on the destination of each message, ordered | |
| by the estimated likelihood of a future transitive path to that | |
| destination.
| |
| | |
| ==== MaxProp core ====
| |
| | |
| To obtain these estimated path likelihoods, each node maintains a
| |
| vector of size <math>n-1</math> (where <math>n</math> is the number of nodes in the network)
| |
| consisting of the likelihood the node has of
| |
| encountering each of the other nodes in the network. Each of
| |
| the <math>n-1</math> elements in the vector is initially set to <math>\frac{1}{|n|-1}</math>,
| |
| meaning the node is equally likely to meet any other node next.
| |
| When the node meets another node, <math>j</math>, the <math>j^\text{th}</math> element of its
| |
| vector is incremented by 1, and then the entire vector is
| |
| [[Normalizing constant|normalized]] such that the sum of all entries add to 1. Note that
| |
| this phase is completely local and does not require transmitting | |
| routing information between nodes.
| |
| | |
| When two nodes meet, they first exchange their estimated
| |
| node-meeting likelihood vectors. Ideally, every node will have
| |
| an up-to-date vector from every other node. With these n | |
| vectors at hand, the node can then compute a shortest path via a
| |
| depth-first search where path weights indicate the probability
| |
| that the link does not occur (note that this is 1 minus the
| |
| value found in the appropriate vector). These path weights are
| |
| summed to determine the total path cost, and are computed over
| |
| all possible paths to the destinations desired (destinations for
| |
| all messages currently being held). The path with the least
| |
| total weight is chosen as the cost for that particular
| |
| destination. The messages are then ordered by destination
| |
| costs, and transmitted and dropped in that order.
| |
| | |
| ==== MaxProp additions ====
| |
| | |
| In conjunction with the core routing described above, MaxProp
| |
| allows for many complementary mechanisms, each helping the message
| |
| delivery ratio in general. First, [[acknowledgement (data networks)|acknowledgement]]s are
| |
| injected into the network by nodes that successfully receive a
| |
| message (and are the final destination of that message). These
| |
| acknowledgements are [[Cryptographic hash function|128-bit hashes]] of the message that are
| |
| flooded into the network, and instruct nodes to delete extra
| |
| copies of the message from their buffers. This helps free space
| |
| so outstanding messages are not dropped as often. Second,
| |
| packets with low hop-counts are given higher priority. This
| |
| helps promote initial rapid message replication to give new
| |
| messages a "[[Head start (positioning)|head start]]". Without this head start, newer
| |
| messages can be quickly starved by older messages, since there
| |
| are generally less copies of new messages in the network.
| |
| Third, each message maintains a "hop list" indicating nodes it
| |
| has previously visited to ensure that it does not revisit a node.
| |
| | |
| === RAPID ===
| |
| | |
| RAPID,<ref name="balasubramanian2007" /> which is an acronym for ''Resource Allocation Protocol for Intentional DTN'' routing, was developed at the University of
| |
| Massachusetts, Amherst. It was first introduced in the [[SIGCOMM]]
| |
| 2007 publication, DTN Routing as a [[Resource allocation|Resource Allocation Problem]].
| |
| The authors of RAPID argue as a base premise that prior DTN routing
| |
| algorithms incidentally effect performance metrics, such as average
| |
| delay and message delivery ratio. The goal of RAPID is to
| |
| intentionally effect a signal routing
| |
| metric. At the time of publication, RAPID has been instrumented to
| |
| intentionally minimize one of three metrics: average delay, missed
| |
| deadlines, and maximum delay.
| |
| | |
| ==== RAPID protocol ====
| |
| | |
| The core of the RAPID protocol is based around the concept of a
| |
| utility function. A [[utility function]] assigns a utility value,
| |
| <math>U_i</math>, to every packet <math>i</math>, which is based on the metric being
| |
| optimized. <math>U_i</math> is defined as the expected contribution of
| |
| packet <math>i</math> to this metric. RAPID replicates packets first that
| |
| locally result in the highest increase in utility. For example,
| |
| assume the metric to optimize is average delay. The utility
| |
| function defined for average delay is <math>U_i = -D(i)</math>,
| |
| basically the
| |
| negative of the average delay. Hence, the protocol replicates
| |
| the packet that results in the greatest decrease in delay.
| |
| RAPID, like MaxProp, is flooding-based, and will therefore
| |
| attempt to replicate all packets if network resources allow.
| |
| | |
| The overall protocol is composed of four steps:
| |
| * Initialization: [[Metadata]] is exchanged to help estimate packet utilities.
| |
| * Direct Delivery: Packets destined for immediate neighbors are transmitted.
| |
| * Replication: Packets are replicated based on marginal utility (the change is utility over the size of the packet).
| |
| * Termination: The protocol ends when contacts break or all packets have been replicated.
| |
| | |
| === Spray and Wait ===
| |
| | |
| Spray and Wait is a routing protocol that attempts to gain the
| |
| delivery ratio benefits of replication-based routing as well as the
| |
| low resource utilization benefits of forwarding-based routing.
| |
| Spray and Wait was developed by researchers at the [[University of Southern California]]. It was first presented at the 2005 ACM
| |
| SIGCOMM conference, under the publication "Spray and Wait: An
| |
| Efficient Routing Scheme for Intermittently Connected Mobile
| |
| Networks". Spray and Wait achieves resource efficiency by setting
| |
| a strict upper bound on the number of copies per message allowed in
| |
| the network.
| |
| | |
| ==== Spray and Wait protocol overview ====
| |
| | |
| The Spray and Wait protocol is composed of two phases: the spray
| |
| phase and the wait phase. When a new message is created in the
| |
| system, a number <math>L</math> is attached to that message indicating the
| |
| maximum allowable copies of the message in the network. During
| |
| the spray phase, the source of the message is responsible for
| |
| "spraying", or delivery, one copy to <math>L</math> distinct "relays". When
| |
| a relay receives the copy, it enters the wait phase, where the
| |
| relay simply holds that particular message until the destination
| |
| is encountered directly.
| |
| | |
| ==== Spray and Wait versions ====
| |
| | |
| There are two main versions of Spray and Wait: vanilla and [[Binary option|binary]]. The two versions are identical except for how the <math>L</math>
| |
| copies reach <math>L</math> distinct nodes during the spray phase. The simplest way to achieve this, known as the [[Vanilla (software)|vanilla]] version, is
| |
| for the source to transmit a single copy of the message to the
| |
| first <math>L-1</math> distinct nodes it encounters after the message is
| |
| created.
| |
| | |
| A second version, referred to as Binary Spray and Wait. Here, | |
| the source starts, as before, with <math>L</math> copies. It then
| |
| transfers
| |
| <math>\text{floor}(L/2)</math> of its copies to the first node it encounters.
| |
| Each
| |
| of these nodes then transfers half of the total number of copies
| |
| they have to future nodes they meet that have no copies of the
| |
| message. When a node eventually gives away all of its copies,
| |
| except for one, it switches into the wait phase where it waits
| |
| for a direct transmission opportunity with the destination. The
| |
| benefit of Binary Spray and Wait is that messages are
| |
| disseminated faster than the vanilla version. In fact, the
| |
| authors prove that Binary Spray and Wait is optimal in terms of
| |
| minimum expected delay among all Spray and Wait schemes,
| |
| assuming node movement is [[Independent and identically-distributed random variables|IID]].
| |
| | |
| == References ==
| |
| {{reflist}}
| |
| | |
| == External links ==
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| *[http://www.dtnrg.org IRTF DTN Research Group website]
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| *[http://www.ietf.org/rfc/rfc4838.txt Bundle Protocol Specification]
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| *[http://www.isi.edu/nsnam/ns/ Network simulator (ns2)]
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| *[http://www.netlab.tkk.fi/tutkimus/dtn/theone/ Opportunistic network environment ONE]
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| *[http://www.ir.bbn.com/projects/spindle/elevatornet/ BBN's ElevatorNet (from SPINDLE project)]
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| *[http://www.snc.sapmi.net/ Sámi Network Connectivity (SNC) project website]
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| *[http://www.n4c.eu Networking for Communications Challenged Communities (N4C) project website]
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| {{DEFAULTSORT:Routing In Delay-Tolerant Networking}}
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| [[Category:Network protocols]]
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