sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: Table 5: The minimum average hop distance in the clustering of Washington DC (66094 nodes) Clusters Avg hop dist Max cluster size 17 4.28 5396 18 4.18 5401 19 4.05 5397 20 3.93 5409 21 3.86 5331 22 3.79 5295 23 3.73 5161 24 3.65 4530 25 3.56 5327 26 3.50 5165 Table 6: The minimum average hop distance in the clustering of Rotterdam (94713 nodes) Clusters Avg hop dist Max cluster size 24 3.37 7034 25 3.30 6264 26 3.18 6264 27 3.11 6264 28 3.07 6415 29 3.05 6415 30 3.01 5837 31 2.90 4736 32 2.87 5173 33 2.84 5173 Our tests also showed that 70 - 90% of the time is spent on achieving an improvement in average hop distance of less then 2%, and in rare situations this improvement can be at most 10%.
Sentence 2: increasing the size of the lo­cal neighborhood beyond 25 neighbors does not result in a signi.cant improvement in the average hop distance.
Relationship: entailment
Domain: Networks
Sentence 1: In fact, by the above joint-state constructions insecure protocols can be turned into secure ones (see Figure 1).
Sentence 2: since real-world security protocols typically do not use pre-established SIDs, at least not explicitly and not in the particular way stipulated by the theorems, the joint state composition theo­rems are unsuitable for the modular and faithful analysis of such protocols; at most idealized/modi.ed protocols, but not the origi­nal real-world protocols, can be analyzed in this modular way.
Relationship: entailment
Domain: Networks
Sentence 1: The di.er- Figure 8: The Average CDF of Error Distance with Clustering in (a) Scenario 1 and (b) Scenario 2 ences in the average CDFs of the error distance between the two clustering methods and without clustering is min­imal (less than 0.05, for error distances less than 4m and negligible at larger distances).
Sentence 2: no signi.­cant di.erence in the probability of selecting a location is observed if clustering is used.
Relationship: entailment
Domain: Networks
Sentence 1: A semantically se­cure protocol is one in which the communications do not reveal any advantageous information to the adversary [21].
Sentence 2: there may be some correlation between hAB and hAE , especially if Eve is physically close to Bob, and thus it might be possible for Eve to estimate certain bits (such as sign bits) of hAB and this, combined with partial decoding, can allow her to infer some bit values of x, or to narrow down the possible decodings of y .
Relationship: entailment
Domain: Networks
Sentence 1: But more impor­tantly, when combined with the analysis of the aggregation of trees in Figure 5, these results suggest that the FIBs of even the most central routers would remain manageable un­der current hardware technology.
Sentence 2: our anal­ysis suggests that routing in an information-centric network can scale, despite or perhaps thanks to the use of expres­sive descriptors.
Relationship: entailment
Domain: Networks
Sentence 1: For example, when g(t, N) ~ßt or D(t)= O(1), we have P{TI >t}~e -ßt as expected.
Sentence 2: when g(t, N) ~a log t, -a log t -a we get P{TI >t}~ e = t. we get the desired power-law behavior when the length of the V boundary is scaled as D(t) ~ t/(a log t).
Relationship: entailment
Domain: Networks
Sentence 1: The Internet does not currently publish the complete PG, but it is easy to construct an approximation of the PG by aggregating BGP routing tables from multiple vantage points in the network, as is currently done by sites like RouteViews [6] and FixedOrbit [1].
Sentence 2: an edge exists between any two vertices X and Y in PG if some BGP routing table contains a path in which ASes X and Y are adjacent.
Relationship: entailment
Domain: Networks
Sentence 1: If x+infs=0[ß(s) -a(s)] =0, it follows from A ~mb (f,a), S~sc (g,ß), Lemma 2.1 and Lemma 2.4.
Sentence 2: for the delay, by de.nition, D(t)= inf{d = 0: A(t) = A * (t+ d)}, which implies that, for any x=0, if D(t) >x, there must be A(t) >A * (t+ x), since otherwise if there would be A(t) = A * (t+ x) and we would have D(t) = x which contradicts the condition D(t) >x.if event {D(t) >x} happens, event {A(t) >A * (t+ x)}must happen, or {D(t) >x}.
Relationship: entailment
Domain: Networks
Sentence 1: Moreover, the maximum achievable power seems to depend more on the conges­tion model (M/M/1 or M/D/1) than the distribution of the network nodes (uniform or according to RWP model).
Sentence 2: by evaluating each scenario numerically for different values of d it turns out that the maximum achievable power .max is indepen­dent of the transmission range d. the optimal point maximising the power (the ratio between throughput, A(tot) · B, and the mean delay E[T ]) is constant for any value of d. Hence, for a given traf.c topology T de.ning relative traf.c intensities the maximum achievable power is a certain constant and we have .
Relationship: entailment
Domain: Networks
Sentence 1: At this, we can use the fact that the face currently traversed can as well be traversed in the opposite direction by switching between left and right hand rule.
Sentence 2: when the after crossing variant selects the intersected edge vw and the left hand rule we obtain the opposite face traversal direction by using the right hand rule and starting with the edge lying in clockwise direction from vw.
Relationship: entailment
Domain: Networks
Sentence 1: Ultimately, it is not particularly surprising that we are able to provoke router drops, even with a single .ow run­ning across a single enterprise router, when we consider that this measurement ensemble is constructed with packet rates approaching 16 million packets per second and IPGs of only 72 bits, very close to the ultimate allowed minimum of 40 bits.
Sentence 2: the 10GbE standards allows for packet 10For larger input IPDs (1500-Byte packets at 1 and 3 Gbps and 46-Byte packets at 1 Gbps), small sample sizes mask the phenomenon.
Relationship: entailment
Domain: Networks
Sentence 1: It is well-known that the impact of unreliable links manifests itself at the higher layers, specifically on the MAC and routing protocols, significantly impacting aggregate sensor network performance.
Sentence 2: one will have to characterize a) the channel rate vs. range/Doppler profiles as a function of frequency, bandwidth, transmit-receive geometry, ocean acoustic parameters etc., and b) theoretical upper bounds on link capacity to explore important trade-offs: since both available bandwidth and channel attenuation increase with frequency, an optimum frequency band/signal bandwidth for our environment can be computed.
Relationship: entailment
Domain: Networks
Sentence 1: The intuition follows from the conventional abstraction that the analog radio (also known as the RF front-end) is a black-box that takes the digital baseband signal, converts it to analog, up-converts it to the carrier frequency, scales it to the right power and sends it.
Sentence 2: the assumption has been that the radio preserves the original baseband signal except for power scaling and frequency shifting.
Relationship: entailment
Domain: Networks
Sentence 1: In addition, we develop techniques to achieve .exibility by design­ing measurement experiments that maximize the information gain for different design objectives and constraints.
Sentence 2: our approach can support the following requirements: (i) differenti­ated design for providing better resolution to certain parts of the network, (ii) augmented design for conducting additional measure­ments given existing observations, and (iii) joint design for sup­porting multiple users interested in different parts of the network.
Relationship: entailment
Domain: Networks
Sentence 1: Given a time sequence of failure scores S = {s0, s1, ..., sn}for a particular edge (or vertex), we use a series of Stu­dent s t-tests to determine whether the addition of the latest score s0 introduces a statistically signi.cant change in the sequence of scores.
Sentence 2: we are interested in de­tecting two di.erent score patterns over time, namely spikes and gradual increases, seen in Figure 5.
Relationship: entailment
Domain: Networks
Sentence 1: This choice of path vector might seem ironic, given that our goal is to improve on BGP s path vector routing; but we use path vector only to make pathlets known, not to pick packets routes.
Sentence 2: the dissemination path attribute (corresponding to BGP s ASPATH) is used only for detection of loops in the dissemination channel, not as a path along which to route data packets.
Relationship: entailment
Domain: Networks
Sentence 1: The PATS and SAP system presented in this paper similarly uses  OGC s  frameworks  to distribute  and integrate  sensor  data  in standardized formats but local solutions are developed to collect the sensor data from the field.
Sentence 2: our use of mesh networking of mobile sensors is included in the framework of a SOS Observatory, as  defined by OGC s  SWE  Geoprocessing workflows [9].
Relationship: entailment
Domain: Networks
Sentence 1: We say that a data series has a log-log slope function C(n) if, for all i where i = k, w(C(n) * i) <w(i)/n,and C(n) is the smallest value satisfying this criteria (n is an integer here).
Sentence 2: in order to achieve a factor of n reduction in the value, one should go a factor of C(n) deeper down the list.
Relationship: entailment
Domain: Networks
Sentence 1: THE INTERFERENCE NUMBER In this section, we introduce a new link metric for estimat­ing interference, which is a generalization of coverage, and we propose a metric to measure interference in multi-hop communications.
Sentence 2: as observed in the previous section, the de.nition of cov­erage is purely geometric, and it relies on the assumption of perfect circular coverage of the radio signal.this de.nition relies on a speci.c radio channel model, which does not account for shadowing and fading e.ects.Other notions of interference have been recently proposed in [11] and in [12], but they are similar to coverage in that they also are purely geometric de.nitions and rely on a speci.c radio channel model.
Relationship: entailment
Domain: Networks
Sentence 1: Also each link (u, v) has an error probability, denoted by e(u, v), which is the probability that a transmission over link (u, v) is not successful.
Sentence 2: node u must consume at least w(u, v) power to have a chance of 1 - e(u, v) to transmit a packet to node v. No transmission is possible otherwise.
Relationship: entailment
Domain: Networks
Sentence 1: Knowledge of groups can greatly enhance many aspects of communicationinDTNs,including unicast[4], anycast and multicast routing, information access control, and privacy.
Sentence 2: it has been shown that contacting a node s group or a.liation is an e.ective and e.cient .rst step to­wards contacting the node itself [4].
Relationship: entailment
Domain: Networks
Sentence 1: However, this does not mean that all .ow setups should be mediated by a central controller.
Sentence 2: micro.ows (a micro.ow is equivalent to a speci.c end-to-end connection) can be divided into three broad categories: security-sensitive .ows, which must be handled centrally to maintain secu­rity properties; signi.cant .ows, which should be handled centrally to maintain global QoS and congestion properties; and normal .ows, whose setup can be devolved to individual switches.
Relationship: entailment
Domain: Networks
Sentence 1: By locally collecting and analyzing smartphone application traces, we found periodic transfers are caused by multiple factors such as polling, keep­alive messages for push-based services, advertisement transfers, and user-behavior measurement.
Sentence 2: we found popular applications that either unnecessarily (e.g., Facebook) or aggres­sively(e.g., Pandora andTextfree)issueperiodic transfers,leading to signi.cant waste of radio resources andhandset energy.
Relationship: entailment
Domain: Networks
Sentence 1: However, since the MR is responsible for the mobility management for mobile nodes in its mobile network, the context of the binding update is changed to network prefix binding update.
Sentence 2: consider the example in Figure 2, when HMR2 obtains LCoAHMR2 and RCoAHMR2, HMR2 will send a network prefix binding update to MAP­HMR to bind the NetworkPrefixHMR2 with LCoAHMR2 such that packets destined to the mobile network of HMR2 will be routed to LCoAHMR2.
Relationship: entailment
Domain: Networks
Sentence 1: Recognizing these facts and challenges, we note that oftentimes mobile users are .exible on the travel paths, and that there typically exist many alternative paths for a pair of source and destination in metro areas.
Sentence 2: mobile users may be willing to tradeoff certain extra travel delay (or travel distance) to their destinations for better network access quality on a trip, especially when such a trip can be planned in advance.
Relationship: entailment
Domain: Networks
Sentence 1: It holds that G is 3-colorable exactly if the maximum total throughput is Tmax = ftop - fbot.
Sentence 2: if G is 3-colorable, each sender wi with color ci in the original graph is assigned a time-spectrum block (0,8,fbot +(ci -1)(ftop -fbot)/3,(ftop -fbot)/3).
Relationship: entailment
Domain: Networks
Sentence 1: With this paper we provide a .rst account of the e.ect of di.erent models of mobility on a typical ad hoc clustering organization.
Sentence 2: we consider a basic clustering algorithm, the Distributed and Mobility Adaptive Clustering (DMAC) [7] protocol, and we evaluate its performance when the network nodes move ac­cording to the random way point mobility model, the ran­dom walk mobility model (Brownian motion) [12] and the Manhattan mobility model [20].
Relationship: entailment
Domain: Networks
Sentence 1: In the event that the server receives an incorrectly formatted message, or one with clearly incorrect data (such as a report of a thousand OVC in a given village), instead of entering incorrect data into the 16 http://zope.org database, the system flags the message for review by a human operator.
Sentence 2: messages that cannot be properly parsed are flagged, and depending on the data, we could implement range-validation as well, which will only allow specific, reasonable ranges of values for different fields.
Relationship: entailment
Domain: Networks
Sentence 1: Leveraging the ac­quired PoP locations, we examine the implications of geo­footprint of eyeball ASes on their connectivity to the rest of the Internet.
Sentence 2: we present a case study that re­veals a much more complex picture of AS-level connectivity as compared to what the more traditional but geography­agnostic BGP-or traceroute-based approaches depict.
Relationship: entailment
Domain: Networks
Sentence 1: Us­ing SIP tra.c traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP tra.c be­havior in an operational network and demonstrate the e.ec­tiveness of our general pro.ling methodology.
Sentence 2: we show how our pro.ling methodology can help identify performance anomalies through a case study.
Relationship: entailment
Domain: Networks
Sentence 1: Many problems become easier in metrics of bounded doubling dimension [10, 17, 15, 20, 19, 18, 9, 14, 13], including metric embeddings, the traveling salesman problem, compact data structures, distance estimation and .nding nearest neighbors.
Sentence 2: doubling metrics can be viewed as a generalization of growth-bounded met­rics [16, 10, 6], which have been shown to provide a good approximation of communication cost metrics on the Inter­net.
Relationship: entailment
Domain: Networks
Sentence 1: 4 Network Stamp Availability To provide uptime service-level-agreement (SLA) of a geo-distributed service, a key requirement is to analyze the availability of a network stamp hosting the service and then compute the number of network stamps needed to meet the service SLA.
Sentence 2: we need to exam­ine two key aspects: (a) the failure characteristics of the individual components comprising a network stamp, and (b) the effectiveness of network redundancy, typically deployed as a resiliency mechanism, in handling net­work failures.
Relationship: entailment
Domain: Networks
Sentence 1: 4.1.2 Grid with random perturbation In this simulation, we put about 3500 nodes on a grid and then perturbed each point by a random shift.
Sentence 2: for each original grid node we create two random numbers modulo the length and the width of each block of the grid, the use these two small numbers to perturb the positions of the nodes.
Relationship: entailment
Domain: Networks
Sentence 1: A strategy pro.le s * is a Nash equilibrium (NE) if, for each player i: ** * ui(si ,s -i) = ui(si,s -i), .si .
Sentence 2: si (11) in a NE, none of the players can unilaterally change his strategy to increase his payo.. A player can also play each of his pure strategies with some probability using mixed strategies.A mixed strategy xi of player i is a probability distribution de.ned over the pure strategies si.
Relationship: entailment
Domain: Networks
Sentence 1: 1.2 Our contribution In this paper, we present the .rst fully distributed al­gorithm to augment arbitrary bounded growth graphs 1 into navigable small worlds in polylogarithmic time and space.
Sentence 2: we optimize the greedy routing performance in any arbitrary bounded growth graph by running a polyloga­rithmic time and space distributed procedure that will only add one single entry to each address book, without recom­puting the distance labeling of its nodes.
Relationship: entailment
Domain: Networks
Sentence 1: Each packet experiences a large amount of processing, queueing and contention at each hop, as shown in Figure 1.
Sentence 2: the packet has to be processed at three layers for header stripping etc., re-queued at the network and MAC layers, processed again for header insertion, and re-contend for channel access, with the obligatory backoff and retransmission.
Relationship: entailment
Domain: Networks
Sentence 1: A .fth motivation that arose after the initial development of TBIT was that of testing not just the TCP behavior of web servers, but also testing the TCP behavior determined by equipment on the path to the server.
Sentence 2: the tests of ECN behavior in Sec­tion 4.6 are in part testing for the presence of .rewalls and load­balancers that block access to servers from hosts attempting to ne­gotiate ECN.
Relationship: entailment
Domain: Networks
Sentence 1: One way to deal with the high concentration of data on the nodes in sparse region or near network holes is to use rejection sam­pling [27].
Sentence 2: we select a random geographical location g ' and round to the closest sensor node g. But we only accept the node g with probability A/(cnA(g)), where A(g)is the Voronoi cell area of node g, Ais the total area of the domain from which g ' is selected, n is the number of sensors, and c is a suf.ciently large universal constant to make sure A/(cnA(g)) = 1.
Relationship: entailment
Domain: Networks
Sentence 1: However, we can use Bloom .lters to avoid lookups in sub­sets that contain no matching rules, making it possible to sustain high throughput.
Sentence 2: we demonstrate a method, based on Bloom .lters and hash tables, that can classify a packet in 4 + p+ o memory accesses where o is a small constant « 1 determined by the false positive proba­bility of the Bloom .lters.
Relationship: entailment
Domain: Networks
Sentence 1: In this paper we address the fundamental and practical question whether the load on the wire­lesschannel canbe reducedifperiodicbeacon messages are trans­mitted over multiple hops with reduced transmit power instead ofbeing transmittedover one hop with high transmit power.
Sentence 2: welookatthepossible bandwidthsavings that canbe achieved by piggybacking forwarded messages into the own next beacon transmission.
Relationship: entailment
Domain: Networks
Sentence 1: In addition, the number of active threads shown 19000 18500Samples (1 sample = 5 seconds) Figure 4: Number of TCP resets during normal load and DoS attack 580 in Figure 5, shows a spike at the time of execution of the security test which did not recover fully from the DoS at­ tack.
Sentence 2: the number of active threads remaining in the post-attack baseline time frame is about 555, which is larger than the original number of baseline threads (about 540-550.)
Relationship: entailment
Domain: Networks
Sentence 1: In particular, 1% of endpoints account for more than 60% of the traf.c, and 5% endpoints carry more than 95% of traf.c in all cases.
Sentence 2: we apply the endpoint approach to classify traf.c for the Asian and S. American ISPs for which we have packet-level traces.5 we do this in two phases.
Relationship: entailment
Domain: Networks
Sentence 1: ai,t for t > tnow or a set of events Zf consisting of multiple Zi,f s. Such a set could, for instance, be representing visibility changes of a complete 802.11 network consisting of multiple access points.
Sentence 2: we are interested in events where ai,t-1 = 1 and ai,t = 0 because this paper deals with out-of-range prediction.
Relationship: entailment
Domain: Networks
Sentence 1: the characteristic function V (S)= {(rn)n.N .XN : {rn}n.S = {k}k.S and rm = m, .m .N S } for each coalition S. N .
Sentence 2: here the condition {rn}n.S =  m by adopting the cooperation strategy (rm)m.S ,the coalition S is a group that is mutually the best for all its members [3].
Relationship: entailment
Domain: Networks
Sentence 1: This family of standards de.nes the archi­tecture, communication model, management structure, se­curity mechanisms and physical access for wireless commu­nications in the vehicular environment.
Sentence 2: the IEEE 802.11p MAC layer interacts with the IEEE 1609.4 [1] to enable multichannel operations of IEEE 802.11p-based radio interfaces.
Relationship: entailment
Domain: Networks
Sentence 1: Because one can take down the entire network by attacking the centralized server, as was the case with the legal attack on Nap­ster [1], most of the peer-to-peer networks have since then aban­doned a completely centralized search index in favor of distributed search primitives.
Sentence 2: the three most popular peer-to-peer networks, that is, the eDonkey, FastTrack, and Gnutella networks, which have approximately between 1,000,000 and 3,000,000 users each,2 all rely on two-tiered hierarchical topologies, where nodes are split between leaf nodes and hubs (called ultrapeers in Gnutella, su­pernodes in FastTrack, and servers in eDonkey).
Relationship: entailment
Domain: Networks
Sentence 1: 5.1 Kernel support While the Linux TCP stack required fairly deep modi­.cation, a key aspect to both the design and implementa­tion of TFO is that it does not affect TCP congestion con­trol.
Sentence 2: since congestion control only takes place after TCP s handshake completes, and TFO is only in use during the handshake, the two are entirely separate.
Relationship: entailment
Domain: Networks
Sentence 1: We want our model to be simple and practical, so that it can be readily deployed, and to cover a wide range of physical layer con.gura­tions, so that it can be applied in many settings and for many tasks.
Sentence 2: the scope of our model is 802.11n including multiple antenna modes, of which single antenna 802.11a/g is a subset.
Relationship: entailment
Domain: Networks
Sentence 1: Let z be any intermediate node in the path q(u, v).
Sentence 2: the displacement of z from f is the perpendicular (Euclidean) distance from x(z)to f. The deviation of q(u, v) from f, denoted deviation(q), is the maximum displacement of any intermediate node z of q from f.deviation(q) measures how closely the path q(u, v) stays to the straight line (geodesic) from x(u)to x(v).
Relationship: entailment
Domain: Networks
Sentence 1: While our optimization problems have been formulated in the context of data communication in networks, our prob­lems also have applications to network design and multicom­modity facility location.
Sentence 2: the minimum-cost 2-spanner problem studied by Dodis and Khanna [6] and Kortsarz and Peleg [14, 15], is a special case of our data dis­semination problem under the unicast model for non-metric cost functions.
Relationship: entailment