sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: This result stands in sharp contrast with several previ­ously proven facts.
Sentence 2: roughgarden and Tar­dos [20] studied a related model in which network users may carry more than a negligible fraction of the overall tra.c and showed that the cost of routing sel.shly is provably larger in general networks than in networks with parallel links; Roughgarden [17] showed that the equilibria in a Stackel­berg game related to the tra.c model of this paper are 1For example, it su.ces for the class to satisfy a mild and standard convexity assumption, to be closed under multipli­cation by positive scalars, and to possess some latency func­tion that is positive when evaluated with zero congestion.
Relationship: entailment
Domain: Networks
Sentence 1: In such schemes, dense regions of objects are considered a cluster and low density regions are con­sidered as noise.
Sentence 2: we selected DBScan [20], since it is well known and offers several advantages: it automatically deter­mines the number of clusters (contrary for example to the k-means algorithm); it is robust to noise, i.e., isolated samples; and .nally it does not have any bias versus any cluster shape.
Relationship: entailment
Domain: Networks
Sentence 1: 3.1.3 Optimization Schemes Strategy 1: In the stragegy 1, the simple mobility model is used.
Sentence 2: to reduce geocast latency error time(i.e., to reduce Pc), we have to decrease geolocation update time interval, r. as the mobility model will show, Pc ~ 0 as T ~-+ 0.
Relationship: entailment
Domain: Networks
Sentence 1: 4.3 Lower Bound on Eavesdropper Through­put We carry out an analysis similar to the one in Section 4.2, to derive a lower bound on .E(n) in our construction.
Sentence 2: we obtain su.cient conditions for .e(n) such that: lim P(.E(n)= µ)=1,forsomeconstant µ> 0. n.8 We derive a lower bound on .E(n)that is independent of d and hence the phase of operation.
Relationship: entailment
Domain: Networks
Sentence 1: We thus can establish the desired cost-e.cient communication backbone by .nding the minimum cost path for each pair of gateway nodes iand irn.
Sentence 2: the desired mini­ im mum cost backbone is an undirected graph (also a spanning subgraph of PCG), denoted by MCG(s), where the set of 2A multi-hop path may exist which has a smaller aggregate cost than ..
Relationship: entailment
Domain: Networks
Sentence 1: Having evaluated the packet clustering technique in iso­lation, we now explore how this technique can be used to perform complex tra.c analysis attacks.
Sentence 2: we demonstrate that the ability to associate packets with their transmitting devices with relatively high accuracy provides su.cient information toperforma sophisticated website .n­gerprinting tra.c analysis attack in which the source of an encrypted HTTP session is discovered using only packet size information [4].
Relationship: entailment
Domain: Networks
Sentence 1: We want to know the expected down­stream bandwidth at the next time step.
Sentence 2: from Figure 2(b) above, this yields: X cf(x0, 1) = p0j · bbw(xj ) (1) .j the expected downstream network band­width one step in the future is the sum (over all states in the Markov chain) of the best bandwidth observed at each  Figure 3: Example Markov model with best-bandwidth results.
Relationship: entailment
Domain: Networks
Sentence 1: Routers forward data to their outgoing interfaces according to the interface s speed, therefore links always remain fully utilised.3 Each interface of the router keeps track of the re­quests that it has forwarded upstream (towards the source) for all other interfaces, per unit time.
Sentence 2: each interface calculates the following ratio for each of the rest of the interfaces of the router: Reqs for Ii yi-.i = (1) Reqs for "Ii- where Ii is interface i and Ii- are the rest of the in­terfaces.
Relationship: entailment
Domain: Networks
Sentence 1: The contributions in this paper are manifold.
Sentence 2: we: thoroughly examined and quanti.ed the interaction between TCP, on-demand ad hoc routing and wireless 802.11 MAC protocols, illustrating the signi.cance of such interaction, analytically investigated the TCP operational range and used the insight from that investigation to propose the fractional window increment (FeW) scheme,  evaluated our proposed scheme over a variety of sce­narios and showed signi.cant improvement over legacy TCP,  compared our proposed scheme to recent related work (namely, ADTCP and LRED) showing the signi.cant advantages gained by using the FeW scheme.
Relationship: entailment
Domain: Networks
Sentence 1: 4.7 Enforcement of System Management Actions The usage of SDN in our risk analysis environment is two-fold: it manages flows according to applications requests and creates a feedback loop into the system.
Sentence 2: when the SDN application receives a notification of the existence of an anomaly, it can decide to initiate some countermeasure (the Data Fusion component in the Figure 1 does not make such decisions).
Relationship: entailment
Domain: Networks
Sentence 1: As the .gure shows, the NMF-based al­gorithm has a lower false positive rate on average, and its standard deviation reduces to 0 when the number of sam­ples is more than 30.
Sentence 2: in the balanced topology, the NMF-based algorithmcanalways .nd thecorrectFGsgiven enoughfailuresamples.
Relationship: entailment
Domain: Networks
Sentence 1: 3.1 TIE Ranking Metric Our mechanism allows each router to have a ranking of the egress points for each destination pre.x.
Sentence 2: router i has a metric m(i, p, e), across all pre.xes p and egress points e. For each pre­.x, the router considers the set of possible egress points and selects the one with the smallest rank, and then forwards packets over a tunnel that follows the shortest path through the network to that egress point.
Relationship: entailment
Domain: Networks
Sentence 1: The n-tuple of mixed strategies ( q1,··· ,q n) previous theorem: is said to be a relative .-Nash equilibrium, if for each i, " mn n 1 = i = n, we have: di( q1,··· ,q i-1,q i,q i+1, ··· ,q n) = XX X ae 2 ( qj,ewj )di( q1,··· ,q i-1,q, q i+1, ··· ,q n)+., forall q .S( qi).
Sentence 2: f(Q)= ße qj,ewj + 2 e=1 j=1 j=1 a n-tuple of mixed strategies( q1,··· ,q n) # n X is not a relative .-Nash equilibrium, if there exists some i, 2 qj,e +ae qj,ewj (1 - )1 = i = n, and some q .S( qi)with 2 j=1 di( q1,··· ,q i-1,q, q i+1, ··· ,q n) Proof.
Relationship: entailment
Domain: Networks
Sentence 1: The goal of this work is to explore the interdependencies be­tween the three functions in order to maximize the bene.ts from their deployment.
Sentence 2: we want to: (a) understand the ca­pabilities and bene.ts that one should expect from each optimiza­tion function, and (b) identify the conditions that are conducive for applying these functions in isolation or in combination.
Relationship: entailment
Domain: Networks
Sentence 1: Using the result in lemma 1, we propose to decompose the transmission range of radius r of a sensor node si , denoted by rr (si ) , into nccb = »r / dmin ÿ CCBs centered at si with interior radii 0 , dmin , , (nccb -1) × dmin , and exterior radii dmin , 2 × d , , , respectively.
Sentence 2: each CCB min nccb × dmin has a width equal to .
Relationship: entailment
Domain: Networks
Sentence 1: Tie persistence: It is the stability of ties across time as number of time-ticks in which a link is ob­served, over the total number of time-ticks.
Sentence 2: pij = P Aij (t)/m, where Pij is the persistence of tie eij , Aij is 1 t if users i and j communicated in time-tick t and 0 otherwise, and m is the total number of time-ticks.
Relationship: entailment
Domain: Networks
Sentence 1: Most HCs (93%) displayed certi.cates from CAs which had more than 100 certi.cates in our total sample.9 This is strikingly di.erent from re­ports by some other researchers.
Sentence 2: netcraft [13] in January 2008 reported approximately one quarter of the certi.cates in their survey as being self-signed.
Relationship: entailment
Domain: Networks
Sentence 1: The proposed distributed routing solutions are tailored for the characteristics of the underwater environment, e.g., our solu­tions take explicitly into account the very high propagation delay, which may vary in horizontal and vertical links, the different com­ponents of the transmission loss, the impairment of the physical channel, the extremely limited bandwidth, the high bit error rate, and the limited battery energy.
Sentence 2: our routing solutions allow achieving two appar­ently con.icting objectives, i.e., increasing the ef.ciency of the channel by transmitting a train of short packets back-to-back;and limiting the packet error rate by keeping the transmitted packets short.
Relationship: entailment
Domain: Networks
Sentence 1: Finally, we note that, in practice, each node may start with i =1 (or anyother agreed upon constant) and run until atleastits respec­tive estimate of dlglnn is reached before terminating for some constant d = 3.
Sentence 2: there is no need to start at exactly round i = 3lglnn;indeed, nodes maynot agree on such a value and we discuss thisfurtherinSection4.2.
Relationship: entailment
Domain: Networks
Sentence 1: What is surprising, however, 0.6 is that the (observed) spam emails from botnets are switching away 0.5 from dynamic IP ranges to static IP addresses.
Sentence 2: the 0.4 Fraction covered by most common hash value 0.1 0  percentage of spam campaigns that had at least 80% of dynamic 0.3 IP addresses dropped signi.cantly from 52% in November 2006 to 0.2 0.1 14% in June 2007.
Relationship: entailment
Domain: Networks
Sentence 1: De.nition 3: A random geometric graph G(n, r)is a geometric graph in which the n nodes are independently and uniformly randomly distributed in a metric space.
Sentence 2: it is a random graph in which the link existence probability p between two nodes u and v is determined by their geometric distance in a way that p =1 for .u - v.= r and p =0 otherwise.
Relationship: entailment
Domain: Networks
Sentence 1: As the AoA measuring procedure run by ACMod is concerned with only the relative phase offsets between the RX USRP2 units, we simply need to align the phases of the RX USRP2 units to one of them (e.g., the .rst RX USRP2 unit).
Sentence 2: we can calibrate the i-th RX USRP2 units by subtracting .
Relationship: entailment
Domain: Networks
Sentence 1: Sub-optimal Routing Because the AS is the player who makes the routing decisions on behalf of the users, there exists the potential for a signi.cant moral hazard.
Sentence 2: given a .xed amount of tra.c to route, the AS can, will, and (as a pro.t-maximizing .rm) should make decisions which will decrease (or perhaps even minimize) its cost, at the expense of poorer service to the user.
Relationship: entailment
Domain: Networks
Sentence 1: Z, the classi.er decides whether (i, j) cor­responds to a true zero or a false zero and sets Tb(i, j) = 0 or 1 respectively.
Sentence 2: our goal is to set the values of T (Z) (i.e., the subset of the elements of Tbthat correspond b to the indices in Z) in such a way that they agree with the corresponding values of T (Z).
Relationship: entailment
Domain: Networks
Sentence 1: This in­equality is true because in Line 4, every demand is increased by at most a factor of 2 and crucially there is no frag­mentation: Because demands are all powers of 2, and time­spectrum blocks are assigned greedily in non-increasing or­der, it holds that when a demand DD is assigned, every ij available non-overlapping free space has size at least DD ij .
Sentence 2: in the neighborhood of link (vg,vh) with maximal Sgh(t), the only reason why Fmax may be larger than Sgh(t) is the rounding.
Relationship: entailment
Domain: Networks
Sentence 1: 4.3 Synchronization Concerns An existing mechanism for an anycast CDN with load­balancing capability maps connections to edge servers at the granularity of an ingress router [6].
Sentence 2: the load 0 10 20 30 40 50 60 70 80 Time(secon ds) Figure 8: Queue length versus time.
Relationship: entailment
Domain: Networks
Sentence 1: In this paper we propose a different transition with ClosedFlow, illustrated in the bottom half of Figure 1, which allows SDN control over existing legacy hardware.
Sentence 2: with no new hardware pur­chases an SDN controller, such as Floodlight [5] or Ryu [4], can run network controlling applications but instead of targeting OpenFlow switches, legacy devices can be targeted (with no modi.cations to the applications, only to the code that interfaces with hardware).
Relationship: entailment
Domain: Networks
Sentence 1: The node will generate another beacon if the CCA checks indicate busy medium, or will go to sleep otherwise.
Sentence 2: on our MICAz motes, if at least 20 consecutive CCA checks indicate busy medium during this time, the RI-MAC adaptation code noti.es the BeaconManager of a collision; the BeaconManager then generates another beacon with a larger BW value, if necessary.
Relationship: entailment
Domain: Networks
Sentence 1: 2.1 Intuition in the Continuous Case Picture the following continuous variant of our problem: Given a (possibly non-simply) connected region R .R2 and some point p .R we call that point seed , we consider the isolevels of the geodesic distance function dp from p in the domain R as in Figure 2.
Sentence 2: for any point x .R, dp(x) denotes the minimum Euclidean length of an open curve G .R with one endpoint being p, the other x.Or in other words, dp(x) is the length of the shortest path from p to x which stays within R and avoids all holes.
Relationship: entailment
Domain: Networks
Sentence 1: We will not know the true F2(Se(t)) unless we do per-.ow analysis for each parameter setting, which can be prohibitive.
Sentence 2: in­stead we use the estimated second moment F2est(Se(t)), as long as F est 2 (Se(t)) closely approximates F2(Se(t)).we try to .nd parameters that minimize the estimated total energy of F est forecast errors t 2 (Se(t)).
Relationship: entailment
Domain: Networks
Sentence 1: Thispaperpresentsthehigh-level concepts anddesigndeci­sions used to realize the key routing component of the Mo­bilityFirst architecture, which is a clean-slate project being conducted as part of the NSF Future Internet Architecture program.
Sentence 2: we describe GSTAR, a mobility­centricgeneralized storage-aware routing approachbased on thefollowingkeydesignprinciples: separationof namesfrom addresses, late binding of routable addresses, in-network storage, and conditional routingdecision space.
Relationship: entailment
Domain: Networks
Sentence 1: Therefore, special treatment of the graph is required by a variety of network algo­rithms and protocols.
Sentence 2: many geometry-oriented al­gorithms, such as geometric routing [1 4], autonomous localiza­tion [5, 6], sensor coverage [7], network segmentation [8], and dis­tributed data storage and processing [9], all depend on a typeof subgraph called triangulation.
Relationship: entailment
Domain: Networks
Sentence 1: In this work, we demonstrate that it is feasible to success­fully receive and decode OFDM modulation while sampling below the Nyquist frequency.
Sentence 2: we show that a standards­compliant 802.11a/g frame transmitted at 6 or 9 Mbps can be de­tected, received, and decoded by a receiver running at a 50% or even 25% clock rate given suf.cient channel quality.
Relationship: entailment
Domain: Networks
Sentence 1: The ETT metric for a route is the sum of the ETTs for each of the route s links.
Sentence 2: srcr assumes the fol­lowing relation between the throughputs ti of a route s hops and the route s end-to-end throughput t: 1 t = P(1) 1 i ti This relation is reasonably accurate for short routes where at most one hop can send at a time [24].
Relationship: entailment
Domain: Networks
Sentence 1: Although the current version of OVX presents all the core features expected from a network virtualization platform, we are currently designing three additional functionalities that will improve the usability and the performance of the tool.
Sentence 2: we are focusing on: Snapshotting and migration of vSDNs: in a virtualiza­tion environment, the ability to preserve the state and data of a Virtual Machine (VM) at a speci.c point in time has become a key functionality.
Relationship: entailment
Domain: Networks
Sentence 1: Hence, our proposed two-level antenna cancellation solution based on phase o.set can be readily extended to MIMO systems by using standard linear antenna array con­.gurations.
Sentence 2: to generate an N × M MIMO +FD system, we start by placing two sets of antennas (N transmit and M receive) on two perpendicular axis to allow for N × M MIMO (in each direction of FD) as shown in Fig.
Relationship: entailment
Domain: Networks
Sentence 1: Yet, in WPF, if the system wants to share resources fairly between users, it can give one time slot to each zone suc­cessively as it is done in WPF(1,1,1) where P(az)=1/3.
Sentence 2: the probability to choose a user will be 1/3· 1/10(recall that users in the same Zone z have the 1 to be selected) exactly as in the ideal same probability nz homogeneous system.
Relationship: entailment
Domain: Networks
Sentence 1: 2.1 Incumbents to Protect Within 802.22, the sensing mechanism is designed to offer protection to two types of incumbents, namely, the TV service and wireless microphones.
Sentence 2: wireless microphones are licensed secondary users of the spectrum, and are allowed by FCC to operate on vacant TV channels on a non-interfering basis (please refer to Part 74 of the FCC rules)4.
Relationship: entailment
Domain: Networks
Sentence 1: Energy-conservation fairness improves both aggregate system throughput and overall system energy-ef.ciency signi.cantly, be­cause its airtime allocation is determined by considering both as­pects of the transmission-strategy diversity: transmission-rate di­versity and transmit-power diversity.
Sentence 2: it improves the aggregate system throughput by more than 25% over that of air­time fairness and more than 2.5 times that of the DCF.
Relationship: entailment
Domain: Networks
Sentence 1: In[16]theauthorshavede.ned analgorithmwhich allowsto estimateit.Theterm DQk has been de.ned as in (7) to make a positive contribution when the instantaneous queue length qk is lower than its previ­ous value, and a negative contribution in the opposite case.
Sentence 2: the AWM gateway detects the bandwidth availability when the instantaneous queue length decreases, and informs the TCP sources by proportionally increasing the suggested window value for each of them.
Relationship: entailment
Domain: Networks
Sentence 1: (2) Tmu + Tu At the end of this time, the mobile will have become reach­able if either Xu elapsed .rst (with probability Tmu/(Tmu + Tu)), or Xmu elapsed .rst and the new BS whose coverage area the mobile entered is reachable (which has probability Tr/(Tu + Tr).
Sentence 2: the total probability that the mobile will be reachable after the time min(Xu, Xmu) is « « Tmu Tr Tu pr = + .
Relationship: entailment
Domain: Networks
Sentence 1: Therefore, to calculate the value of ResidualAirTimei[n], we let each node explicitly exchange the perceived channel status with the nodes within its carrier-sensing range.
Sentence 2: we let each node broadcast its BusyPeriod table as a BUSY_PERIOD_REPORT message on the control channel to its carrier-sensing neighbors every Tbx seconds, where Tbx is referred to as the busy period exchange interval.
Relationship: entailment
Domain: Networks
Sentence 1: The Duration/ID .eld of the MAC header of each multicast data frame has to be modi.ed.
Sentence 2: the virtual carrier-sense mechanism provided by the MAC should take into account the extra delay for multicast ac­ Figure 4: Receiver side of a 802.11 WLAN board Goodput[Kbps] 800 700 600 500 400 300 200 knowledgements.
Relationship: entailment
Domain: Networks
Sentence 1: =(.1,.2, ··· ,.n-1,.n) (or generally .S ) bits/sec is feasible if there is a spatial and temporal scheme for scheduling transmissions such that by operating the network in a multi-hop fashion and buffering at intermediate nodes when awaiting trans­mission, every node vi can send .i bits/sec average to its chosen k - 1 destination nodes.
Sentence 2: there is a T< 8 such that in every time interval (with unit seconds) [(i-1)·T,i·T ], every node can send T · .i bits to its corresponding k - 1 receivers.
Relationship: entailment
Domain: Networks
Sentence 1: Constraints (4), (5), and (6) express conservation of .ows [16], i.e., each source generates a .ow, which is collected by an actor.
Sentence 2: constraint (4) guarantees that a source node generates a .ow on the tree of the selected actor, and only on that one; while non-source nodes do not generate any .ow.
Relationship: entailment
Domain: Networks
Sentence 1: To this purpose we implement a modi.ed version of the L-IDM driver be­havior, whereby some drivers brake and slow down.
Sentence 2: one third of the drivers, when approaching the braking platoon (i.e., in the 100 m of road preceding the critical point), decelerate uni­formly, down to a speed no lower than 70% of the average speed of the simulation (e.g., 90 km/h for the 130 km/h scenario).
Relationship: entailment
Domain: Networks
Sentence 1: In this section, we argue that this fact happens by no chance, but it is a consequence of the triangular inequality argument, which, although not valid as far as energy is con­cerned, turns out to hold (under certain assumptions) for multi-hop interference.
Sentence 2: assume that the radio coverage area is a perfect circle, and that nodes are randomly, densely distributed.we model the distribution of nodes in (2-dimensional) space according to the Poisson process with given density parame­ter ..In this scenario, let N(S) denote the number of nodes in the surface S,and let µ(S) denote the measure (i.e., area) of S;then -.µ(S) (.µ(S))k Prob(N(S)= k)= e .
Relationship: entailment
Domain: Networks
Sentence 1: Several studies report on the rapid growth of this market; the market for network secu­rity appliances alone was estimated to be 6 billion dollars in 2010 and expected to rise to 10 billion in 2016 [8].
Sentence 2: middleboxes are critical part of today s networks and it is reasonable to expect that they will remain so for the foreseeable future.
Relationship: entailment
Domain: Networks
Sentence 1: Discussion The directory service is designed for easy de­ployability on the Internet today while guaranteeing at least as much security as is currently obtained from the X.509 PKI used in TLS.
Sentence 2: a client C checks an X.509 cer­ti.cate chain leading to the long-term public key for server S, in the same way that web browsers today check such chains.
Relationship: entailment
Domain: Networks
Sentence 1: Then, we present qualitative examples highlighting the bene­.ts arising from assigning encoding and decoding responsibilities across a collection of routers in an intelligent, coordinated fashion.
Sentence 2: we show how this: (1) leads to ef.cient memory us­age, (2) ensures RE-related tasks can be performed at full capacity, and (3) enables incremental deployment.
Relationship: entailment
Domain: Networks
Sentence 1: While at high density the performance of both approaches is comparable, we see that at low den­sities BVR performs much better than greedy geographic routing with true positions.
Sentence 2: while the suc­cess rate of the greedy routing is about 61%, the success rate of BVR reaches 80% with 30 beacons, and 90% with 40 beacons.
Relationship: entailment
Domain: Networks
Sentence 1: In our experiments, TransCom can reduce the client access latency by 2-3 times and improve the video playback quality by 2-20 times compared with the thin-client sys­tems.
Sentence 2: we .nd that when the number of clients is small (= 4 in our setup), thin-client systems can achieve lower client latencies than TransCom since the servers perform all com­puting tasks.
Relationship: entailment