sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: The routers simply run the tried and true link-state routing protocol to compute the forwarding decisions, not knowing that the topology they see includes fake nodes (with fake announcements of destination address blocks) and fake links (with fake weights).
Sentence 2: the controller treats the routing pro­tocol as a function from routing messages to forward­ing paths (e.g., using Dijkstra s algorithm), and in­verts the function.
Relationship: entailment
Domain: Networks
Sentence 1: Therefore, it enables the opportunity to reduce the live latency by re­ducing segment duration while still maintaining a constant or controllable number of requests to the server.
Sentence 2: by leveraging server push, our suggested best prac­tice for low latency live streaming is to reduce the segment size until it meets the desired latency requirement, while still considering and counting for additional request over­head and possible impacts on the dynamic bit rate switch­ing.
Relationship: entailment
Domain: Networks
Sentence 1: To verify that the emulator does not incorrectly exclude routes from the set of best eBGP routes, we check that, for each pre.x, the best route at each RR appears in the set of best eBGP routes as computed by the emulator3.
Sentence 2: we consider cases where an RR s best route would have directed traf.c towards some egress router that was not contained in the EGRESS POINTS table.
Relationship: entailment
Domain: Networks
Sentence 1: C DFunif orm can be constructed using the technique described in Section 4, but with the di.erence that before computing the accumulated sum for each ratio sub-range, we add n/R to the count of ratio samples in each sub-range, where R is the number of sub-ranges between 0 and 1.
Sentence 2: n delay ratios are assumed to be uniformly dis­tributed over all ratio sub-ranges.
Relationship: entailment
Domain: Networks
Sentence 1: Global Transmission Control: While the progressive encoding and utility-driven scheduling at each sensor opti­mize for multiple queries at a single radar, there is a need for global control of transmissions to maximize overall util­ity across the network because radars within the same wire­less contention domain share the wireless media and con­tend with each other while transmitting.
Sentence 2: this is useful when queries are not evenly distributed across the network, and some nodes that are handling higher priority queries need more bandwidth than others.
Relationship: entailment
Domain: Networks
Sentence 1: We focus on networks whereby the source is communicating to the destination via a set of multihop relay nodes organized via hierarchical clustering.
Sentence 2: at each hop, a set of clusters are formed using a number of relay nodes where for each cluster, the relay nodes employ two di.erent relaying strategies: i) amplify-and-forward via beamforming, ii) decode-and-forward via beamforming.
Relationship: entailment
Domain: Networks
Sentence 1: By including as features the standard deviation, min, and max values of RSCP and ECIO over a short period (typically 3 seconds, al­though in Section 6 we evaluate other window sizes), the predic­tion accuracy is around 85% for predicting whether we will see good throughput.
Sentence 2: when we predict good through­put, we are right 85% of the time.
Relationship: entailment
Domain: Networks
Sentence 1: This finding suggests that care must be taken when frame bursting technique is used.
Sentence 2: since Multimedia applications have different traffic characteristics from background HTTP and FTP traffic, it might not always be desirable to use maximum frame bursting.Adaptive measures may be taken to adjust the [7] Banchs, A.; Radimirsch, M.; Perez, X.; Assured and expedited forwarding extensions for IEEE 802.11 wireless LAN Quality of Service, 2002.
Relationship: entailment
Domain: Networks
Sentence 1: These studies are based on crawlers that explore the connec­tivity of the Web by following the links on each discovered page, thus reconstructing the topological properties of the visited graph.
Sentence 2: data gathered in large-scale crawls [3, 7, 14, 1, 15] have indicated the presence of a rich and complex architecture underlying the structure of the Web graph.
Relationship: entailment
Domain: Networks
Sentence 1: We also de.ne the order o of the network to be the supremum of all exponents s for which C(n) =n s with high probability: o=sup{s: lim P[C(n) =n s]= 1}.
Sentence 2: (4) n.8 the order of the network is the largest expo­nent with which the capacity is guaranteed to be increasing, ignoring factors that are smaller than polynomial, such as poly-logarithmic factors of the form k1(log n)k2 .
Relationship: entailment
Domain: Networks
Sentence 1: THE TWO-LEVEL APPROACH Theprotocols reviewedintheprevioussection canbefur­ther improved by following a nesting approach in which the k coronas are viewed as k1 macrocoronas of k2 adjacent coronas each.
Sentence 2: each sensor .rst learns in which macrocorona it belongs and then re.nes its training by de­termining the microcorona inside its macrocorona.
Relationship: entailment
Domain: Networks
Sentence 1: Once the best BGP NEXT-HOP is chosen for each destination pre.x, then the IGP next-hop to that BGP NEXT-HOP is computed based on IGP metrics.
Sentence 2: a forwarding entry for a destination pre.x P at a node E is determined by .rst map­ping from P to a BGP NEXT-HOP (A or B) and then from BGP NEXT-HOP to an IGP next-hop (C or D).
Relationship: entailment
Domain: Networks
Sentence 1: Under this assumption, theyderived some interesting re­sultsonthe feasibilityandperformanceof opportunisticforwarding algorithms.
Sentence 2: theirhypothesis implies that for anyfor­warding scheme the mean packet delay is in.nite, if the power-law exponent of the inter-contact time is smaller than or equal to 1 (the case suggestedto holdin practiceby the empirical results sofar).
Relationship: entailment
Domain: Networks
Sentence 1: Thus we come to a clear and very important point: the multi-jurisdictional multi-stage attack problem is a problem that involves both legal and policy tools as well as technical ones; it cannot be solved by technical means alone.
Sentence 2: this means that the problem of cyberexploitations carried out against U.S. industry and government sites is unlikely to be amenable to technical solutions.
Relationship: entailment
Domain: Networks
Sentence 1: Adversary A injectsatleast onepacketthatuses p in each t time steps.That is, for any t2 - t1 = t, Ap (t1,t2) > 0.
Sentence 2: adversary A injects at most z packets that use p,over­al l.for all t, Ap(t) = z.
Relationship: entailment
Domain: Networks
Sentence 1: Data item I in Q1 is allocated at the interval of 16/4.4 throughout the channel where 16 is cycle length and 4 is the allocation frequency of data item I.
Sentence 2: data item I is first allocated on channel 1 at offset 1 and secondly allocated on channel 2 at offset 5 that is Diff(I) away from previously allocated position.
Relationship: entailment
Domain: Networks
Sentence 1: Because LWB uses only Glossy .oods for communication, its ef.ciency de­creases in deep networks that span several tens of hops, and other approaches may perform better [23].
Sentence 2: the length of data (Td ) and schedule (Ts) slots must be suf.cient for a Glossy .ood to cover the entire network.
Relationship: entailment
Domain: Networks
Sentence 1: From its ini­tial function of providing the mapping between human-readable names (e.g., amazon.com ) and obtuse network-level addresses, it evolved to form a basis for building scalable and agile Web plat­forms.
Sentence 2: by changing name-to-address bindings dy­namically and providing different bindings to different clients, Web sites can transparently distribute client load among replicated Web servers or redirect client requests from their own servers to content delivery networks (CDNs), while CDNs and similar platforms can direct incoming requests to speci.c nodes in the platform.
Relationship: entailment
Domain: Networks
Sentence 1: Our question is partially motivated by the re­cent work in the RouteBricks project [4], where the au­thors have explored the feasibility of building high-speed software routers using a mesh of o.-the-shelf desktop-based serversthatparallelize routerfunctionality both acrossmul­tiple servers and across multiple cores within a single server.
Sentence 2: we ask the following question: If we were to implement classi.cation using state-of-the-arts desktops, given that it may .nd applications in router design (e.g., RouteBricks), then what classi.cation speeds can be achieved on it, by designing a fully software-based classi.cation sys­tem that can exploit the degree of parallelism provided by this particular platform?
Relationship: entailment
Domain: Networks
Sentence 1: Ifboth ofthese con­ditions hold, then PV is transparent.In this case, we can in (v, out (u, de.ne the function t(v,u, X)= t u, tv, X)) and note that in u)(t(v, u, F out F(v, u)(X)= F (v, (u, v)(X))).
Sentence 2: the transformation between two neighboring nodes participating in PV can be easily understood as the com­position ofthree functions: the export policy at one node; a .xed, uniform transformation t given by PV ;and the im­port policy at another node.
Relationship: entailment
Domain: Networks
Sentence 1: To avoid this, a TurboRate client determines whether it can join ongoing transmissions by applying a technique similar to the one proposed in [23].
Sentence 2: a TurboRate client is only allowed to transmit concurrently if its interfering power at the AP is below a threshold.4 This limits the amount of residual noise and allows the AP to successfully decode the existing signals after SIC.
Relationship: entailment
Domain: Networks
Sentence 1: [11] analyze hybrid non-obstructed networks comprised by random uni­form one-dimensional, two-dimensional, and a .xed-width strip combined with an overlaying connected backbone of base stations.
Sentence 2: they show that percolation (for­mation of a connected component of in.nite size) never (for any node density) occurs on a line or a strip, and that gains in terms of connectivity from the hybrid structure are only signi.cant when the node spatial distribution is close to one­dimensional.
Relationship: entailment
Domain: Networks
Sentence 1: In order to analyze these pe­riodicities of received wideband signal x(t), a key function SCF is typically utilized, which can be expressed as 8 t t * -j2pat -j2pf t Sx(a, f ) =x(t+ )x (t- )e e dtdt (1) 2 2 -8 The SCF, also termed cyclic spectrum, is a bi-frequency plane with respect to cyclic frequency a and spectral fre­quency f. For communication signals, nonzero value appears only at some speci.c cyclic frequencies, which is related to their symbol rate, chip rate, etc.
Sentence 2: signal with di.erent modulation schemes will exhibit distinct cyclic fre­quencies.
Relationship: entailment
Domain: Networks
Sentence 1: The TCP-friendliness level represents a generic term that describes the ability of a TCP variant to coexist with a dif­ferent TCP variant and fairly share the available bandwidth in the same bottleneck link.
Sentence 2: as the available bandwidth for both classes (AF and BE)) is set to 1.6 Mbps, we will consider that a TCP variant has an enhanced friendliness/fairness level when both are able to equally distribute the available band­width, enabling each of them to obtain around 800 Kbps of goodput.
Relationship: entailment
Domain: Networks
Sentence 1: Precisely, for any n, we describe an n × n matrix M, and a labeling L of the nodes of any n-node graph G, such that greedy routing in (G, (M, L)) per­ v forms in O(min{ps(G) · log2 n, n}) expected num­ber of steps, where ps(G) denotes the pathshape of G. This result has many important corollaries.
Sentence 2: and in contrast with name-independent schemes, the scheme (M, L) yields polylogarithmic ex­pected number of steps of greedy routing for large classes of graphs such as trees and AT-free graphs, including co-comparability graphs, interval and per­mutation graphs [5].
Relationship: entailment
Domain: Networks
Sentence 1: (a) Asymmetric Information (b) Perceived Collision Figure 1: Illustrative example topologies 3.1 Graph-theoretic Formalism exists if only the receiver of .ow nis in vertex v to v m n Here, we formalize the notion of shared information via a simple graph theoretic framework.
Sentence 2: the spa­tially distributed nature of ad hoc networks naturally leads to incomplete information about the other nodes of the net­work.
Relationship: entailment
Domain: Networks
Sentence 1: The wide range of possible applications (intrusion detection systems, environ­mental monitoring, domotics, etc...) requiring WSN tech­nology justi.es the huge number of solutions proposed to improve the e.ciency of sensor devices.
Sentence 2: exper­imental studies have shown that the most power hungry com- 3HUPLVVLRQ WR PDNH GLJLWDO RU KDUG FRSLHV RI DOO RU SDUW RI WKLV ZRUN IRU SHUVRQDO RU FODVVURRP XVH LV JUDQWHG ZLWKRXW IHH SURYLGHG WKDW FRSLHV DUH QRW PDGH RU GLVWULEXWHG IRU SURILW RU FRPPHUFLDO DGYDQWDJH DQG WKDW FRSLHV EHDU WKLV QRWLFH DQG WKH IXOO FLWDWLRQ RQ WKH ILUVW SDJH 7R FRS RWKHUZLVH WR UHSXEOLVK WR SRVW RQ VHUYHUV RU WR UHGLVWULEXWH WR OLVWV UHTXLUHV SULRU VSHFLILF SHUPLVVLRQ DQG RU D IHH :16  0DUFK  'HVHQ]DQR GHO *DUGD ,WDO &#38;RSULJKW k  ,&#38;67     '2,   LFVW VLPXWRROV ponent is the radio transceiver mounted on the sensors, thus optimizing the way sensors communicate through the wire­less medium is key to minimizing the energy consumption of sensor nodes.
Relationship: entailment
Domain: Networks
Sentence 1: 3.3.4 Stable-Backlog is Not Attainable The constraint required in the above analysis, together with (12), is that the .ow will be able, on average, to fully recover from the TO, reaching stable-backlog state before the next loss episode oc­curs.
Sentence 2: pAC = (1/p + W0 - 1),or p = .
Relationship: entailment
Domain: Networks
Sentence 1: Today however, trends in UAV design show significant civilian perspectives for the wider use of lower altitude crafts.
Sentence 2: a growing interest has been observed for LAPs for various missions such as photographic reconnaissance, low-altitude urban traffic surveillance [9], emergency communications in post-disaster situations or unexpected events [10, 11], earth observation and agricultural purposes [12], power beaming [14] and so on.
Relationship: entailment
Domain: Networks
Sentence 1: A useful insight which can help remedy this limitation is that while, in the big picture, the underlying process of object references is dynamic, when studied at a .ner granularity, it can be well-approximated as a piece­wise stationary process.
Sentence 2: if we look at the process of references through a su.ciently small window in the time-space domain, the subprocess observed exhibits a rather stationary behavior.
Relationship: entailment
Domain: Networks
Sentence 1: stable operating states for the network where the machine is not in the process of possibly powering down E. For r3, E is powered down with low use of w, and for r0, both routers are powered up with one or both links experiencing high usage.
Sentence 2: the following invariants can be shown for these states by a straightforward mutual induction on the length of input w: 1. the power-save transducer is in r0 on input w with output y only if w ends with a member of H and y ends with OnE, and 2. the power-save transducer is in r3 on input w with output y only if w ends with ZvLw or ZvZw and y ends with O.E.
Relationship: entailment
Domain: Networks
Sentence 1: Thus, we just refer to the LP relaxation achieved by LP 1.
Sentence 2: although if .nite retransmissions are used during the data forwarding process, the paths are computed based on the solution of LP 1 that assumes in.nite 1Since we assume that all nodes use a .xed transmission power, we set d to the maximum radio range of 30 m. retransmissions2.
Relationship: entailment
Domain: Networks
Sentence 1: Since di.erent destinations are assigned di.erent ranges of LIDs in In.niBand networks, the number of LIDs required for realizing a routing is equal to the sum of the number of LIDs required for each destination.
Sentence 2: the LID assignment problem for a routing can be re­duced to the LID assignment problem for each indi­vidual destination.Let R = {p1,p2, ...} be a routing and D = {d|.pi .
Relationship: entailment
Domain: Networks
Sentence 1: Although there has been no study on the impact of chan­nel estimation on the design of the transmitter and receiver for a BICM-ID-SSD system, the use of PSAM and superim­posed training sequence was widely considered for coded and un-coded systems, see, e.g., [4, 3, 9, 7].
Sentence 2: using pilot symbols for channel estimation in Turbo coded systems has been examined in [9] over correlated fading channels where an iteratively .ltered PSAM (IF-PSAM) algorithm is proposed at the receiver.
Relationship: entailment
Domain: Networks
Sentence 1: In this section, we present measurement .ndings for both commercial RFIDs and computational RFIDs, and show that the synchronization accuracy in practice is suf.cient for Buzz s performance.
Sentence 2: synchronization in backscatter networks has two aspects: The starting offset of the nodes transmissions: Backscatter CDF 1 0.8 0.6 0.4 0.2 0Initial Synchronization Offset in µs Figure 7 CDF of the initial synchronization offset between dif­ferentRFID tags:Both commercial and computationalRFIDs have an initial offset of less than 1µsec which has negligible impact on the performance ofBuzz.
Relationship: entailment
Domain: Networks
Sentence 1: INTRODUCTION In this paper we explore the proposition that location context can be inferred based on the dynamics of user mo- Designers of Internet services increasingly seek to spe­bility.
Sentence 2: we argue that rough location characteri­cialize their behavior and content to re.ect differences zations such as residence , workplace , or travel venue among their users (e.g., location, bandwidth, reputation, (e.g., hotel, airport, cafe, etc.)
Relationship: entailment
Domain: Networks
Sentence 1: Let s call the collection of these ob jects S1.The central manager selects ob jects with the top k partial sums, and sets t1 to be the min of the top k partial sums.
Sentence 2: there­fore, for an arbitrary subset of k objects in S1,the minof their partial sums is = t1.t1 is no less than the bottom partial sum of any subset of k objects in S1.
Relationship: entailment
Domain: Networks
Sentence 1: Thus, the work presented here concludes that if we continue on the path that we are on using TCP Reno as the networking substrate for high-performance computa­tional grids overall network performance will suffer.
Sentence 2: tCP Reno s congestion-control mechanism in­duces burstiness and dependency between streams which ultimately limit the effectiveness of statistical multiplexing in routers.
Relationship: entailment
Domain: Networks
Sentence 1: 4.2 API to Export/Import State We leverage our taxonomy to design a simple API for NFs to export and import pieces of state; it requires minimal NF modi.ca­tions.
Sentence 2: we leverage the well de.ned notion of a .ow (e.g., TCP or UDP connection) and our de.nition of state scope to allow a controller to specify exactly which state to export or import.
Relationship: entailment
Domain: Networks
Sentence 1: The rank of usable path P is de.ned to be one plus the number of edges in the longest path in G from vertex d to vertex P. In particular, the rank of path dis one.
Sentence 2: because G is an acyclic graph, if there is an edge from P to Q,then Q is ranked higher than P.if Qis either an extension of Pto some node, or has the same origin as Pbut more weight, or, having the same weight, is less preferred, then Qis ranked higher than P. The ranks of paths of G can be determined recursively, noting that the paths of rank jare those that have no edge pointing to them in the graph obtained from G by withdrawing all paths with rank less than j.
Relationship: entailment
Domain: Networks
Sentence 1: In .g.6, the relationships between pairs of nodes aredepicted asthey emergefromthetaxonomyproposedin [14], where the followingcategories are distinguished: whole one shot day all > 5 min latency 2.87 h 1.48 h 2.83 h broad­ mean latency 6.63 h 2.55 h 4.74 h cast median latency 6.68 h 3.85 h 3.95 h max latency 15.73 h 5.04 h 24.41 h mean # hops 4-9 3-7 2-10 coverage 98% 100% 44% min latency 1 1 1 uni­ mean latency 2.91 h 40.42 57.73 cast median latency 2.21 h 33.62 46.12 mean # hops 2.98 2.81 2.97  community: high number of contacts with long duration;  familiar stranger: high number of contacts with short du­ration;  stranger: low number of contacts with short duration;  friends: low number of contacts with long duration.
Sentence 2: the mean has been used as a criteria to discriminate among classes, for both the number of contacts and theintra-contacttimes[7].
Relationship: entailment
Domain: Networks
Sentence 1: 4.4 Import and Export Filters At the beginning of this section, we stated a reciprocity assumption according to which we infer the import .lters: if a RS member is (not) blocked by the export .lter it will also be (not) blocked by the import .lter.
Sentence 2: if an AS is willing to send tra.c to a RS member it will also be willing to accept tra.c from it.
Relationship: entailment
Domain: Networks
Sentence 1: A Euclidean lattice L is a discrete subgroup of Rd that spans the Eu­clidean space Rd as a real vector space.
Sentence 2: there exist d vectors {v1,...,vd } in L that are linearly indepen­ .d dent over the real numbers such that L = {k=1 ak vk |ak .
Relationship: entailment
Domain: Networks
Sentence 1: In the case where the two available channels consist of an average and a bad channel (Figure 2), we see that diversity consistently outperforms the single channel con­.gurations.
Sentence 2: when 0.90 = Pmin = 0.95 the improvement is dramatic, e.g., for Pmin =0.94 diversity de­livers an improvement of more than 400% in ER.
Relationship: entailment
Domain: Networks
Sentence 1: A schedule is said to strictly implement DRF if for all .ows i and j, and for any period (t1, t2) they backlog, we have Di(t1, t2) = Dj (t1, t2).
Sentence 2: (1) a strict DRF schedule allows each .ow to receive the same dominant service in any backlogged period.
Relationship: entailment
Domain: Networks
Sentence 1: Our proposed model, that captures the e.ect of overlay graph on the scalability of the system though the relaxation time, canbe usefulin addressing otherquestions as well.
Sentence 2: aninteresting futuredirectionof thisworkwould be to investigate the scalability of di.erent query propa­gation mechanisms, including variants of the above mecha­nismsthatincludepath replicationorcachingofdataitems.
Relationship: entailment
Domain: Networks
Sentence 1: If we condition on being in a shorter period of constancy, then we find very similar curves.
Sentence 2: if we are not in a period of long-lived constancy, then, per the plot, we find that about half the time we are in a lo-minute interval or shorter, and there is not a great deal of difference in the duration of constancy, regardless of whether we consider one-minute or lo-second constancy, or loss runs or loss episodes.
Relationship: entailment
Domain: Networks
Sentence 1: The two tree adaptation heuristics can achieve desirable energy e.ciency while minimizing tree recon.guration overhead under a wide range of tra.c patterns in WSNs.
Sentence 2: the path­quality based heuristic can accurately capture the path qual­ity .uctuations in presence of bursty data requests while the reference-rate based heuristic is more suitable for the data requests with unknown durations.
Relationship: entailment