sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: ASK-BAN: Authenticated Secret Key Extraction Utilizing Channel Characteristics for Body Area Networks  Lu Shi, Jiawei Yuan, Shucheng Yu Department of Computer Science University of Arkansas at Little Rock Little Rock, AR 72204 {lxshi, jxyuan, sxyu1}@ualr.edu ABSTRACT Recently there has been an increasing interest on bootstrap­ping security for wireless networks merely using physical layer characteristics.
Sentence 2: the focus has been on two fundamental security issues -device authentication and se­cret key extraction.
Relationship: entailment
Domain: Networks
Sentence 1: The schedule needs to decide, at each time, the resource share allocated to each backlogged .ow.
Sentence 2: let Bt be the set of .ows that are backlogged at time t. Let ai,r t be the fraction (share) of resource r allocated to .ow i at time t. The .uid schedule determines, at each time t, the resource allocation ai,r t for each backlogged .ow i and each resource r. Two constraints must be satis.ed when making resource alloca­tion decisions.
Relationship: entailment
Domain: Networks
Sentence 1: We envision minProbe to be deployed in an architecture where a separate control plane manages a rich set of mid­dlebox functionalities with event trigger support(e.g [9]).
Sentence 2: we believe the separation of measurement hard­ware and production hardware enables high-.delity mea­surement in high-speed networks (and in real-time) that is di.cult to achieve otherwise.
Relationship: entailment
Domain: Networks
Sentence 1: For every node X in the shaded area, which is a neighbor Figure 1: I sends a packet to J, but J drops it.
Sentence 2: of both I and J, X will detect the dropping and will reduce their reputation value of J by a, RX (J) = RX (J) - a, X n N(J) n N(I) Here a = f(i, j), where i is the number of hops the packet has traveled, j is the number of packets dropping by J ob­served by X (j applies to source routing protocols, such as Dynamic Source Routing (DSR) [1], and does not apply to reactive routing algorithms, such as AODV [3]).
Relationship: entailment
Domain: Networks
Sentence 1: From the preceding we can see that, this selection depends on the total weight w, of all applications of user u that we associate with the technology.
Sentence 2: for tech­nology l, the best base station would be given by j * l(w) = arg max ln( sj ) , (6) Wj +w j.Jl where we have explicitly shown that dependence of jl * (w) on w, the total weight of all applications of user u that is associated with technology l. To this end, for each technology l, we de.ne the function Gl(w) as sj Gl(w) = maxln( ) .
Relationship: entailment
Domain: Networks
Sentence 1: However, though in a simpli.ed form, the considered MAC scheme captures the fundamental aspects of location-dependent contention inher­ent to multi-hop environments, which is due to di.erences in the number of contending nodes at both endpoints of each communication link.
Sentence 2: in this study we are more concerned on modeling the link capacity degradation due to location-dependent contention, rather than precisely incorporating in the analysis all the features of the IEEE 802.11 MAC protocol.
Relationship: entailment
Domain: Networks
Sentence 1: Prior studies [4, 11] also consider the geographical distance between the client hosts and their DNS resolvers and report different results.
Sentence 2: [11] observes shorter distances between FDNSes and RDNSes, with 60% of clients to be within 17 miles from their re­solvers, while [4] reports fewer client-resolver pairs at the low dis­tance range, with only 25% of pairs being within 500 miles from each other, and also fewer extremely distant pairs, with just 5% of pairs more than 2000 miles apart.
Relationship: entailment
Domain: Networks
Sentence 1: Additionally, the one factor that seems to bear the most responsibil­ity for IPv6 performance lagging behind that of IPv4, i.e., the use of less e.cient paths (hypothesis H2), is one that can hopefully be remedied through focused but relatively standard measures, namely, peering parity be­tween IPv6 and IPv4.
Sentence 2: the single most e.ective way to put IPv6 and IPv4 on an equal footing may well be to ensure peering parity.
Relationship: entailment
Domain: Networks
Sentence 1: Let ira_import(l, v)[R] denote the set of updates after applying the implicit import policy of v on edge l. Every edge has an implicit import policy that discards a routing update when the receiving BGP speaker's AS already ap- pears in the AS path; this is essential to avoid introducing a cycle in the AS path.
Sentence 2: if a(v) E r.as_path, then ira_import(l, v)[{r}] = {}; otherwise im_import(l, v)[{r}] = {r}.
Relationship: entailment
Domain: Networks
Sentence 1: The ExtInterface module [16] cmtSendAllVariant Parameter Functionality allowCMT Enable/Disable CMT cmtUseSFR Enable/Disable SFR cmtUseDAC Enable/Disable DAC cmtCUCVariant Congestion Window Update Strategy Path Selection Policy smallestLastTransmission Default Setting false true true pseudoCumAckV2 Table 1: CMT Parameters for the SCTP Module allows for connecting simulated IP nodes to real network in­terfaces.
Sentence 2: simulated applications on IP nodes can communicate with real applications on real IP endpoints in the Internet.
Relationship: entailment
Domain: Networks
Sentence 1: Reduced State Fair Queuing for Edge and Core Routers Ramana Rao Kompella and George Varghese University of California, San Diego {ramana,varghese}@cs.ucsd.edu ABSTRACT Despite many years of research, fair queuing still faces a number of implementation challenges in high speed routers.
Sentence 2: in spite of proposals such as DiffServ, the state needs for even simple schedulers are still large for heavily channelized core routers and for edge routers.
Relationship: entailment
Domain: Networks
Sentence 1: sult, we envision ScrambleSuit to be used by, amongst other protocols, Tor and VPN to tackle the GFW s most recent censorship upgrades.
Sentence 2: scrambleSuit exhibits the following four features: Pseudo-random payload: To an observer, ScrambleSuit s entire tra.c is computationally indistinguishable from randomness.
Relationship: entailment
Domain: Networks
Sentence 1: Based on the near-optimal solution to the idealized problem OPT-ub, we return to the original problem TPP by incorpo­rating non-zero traveling time for the WCV.
Sentence 2: we determine the traveling path in TPP by .nding the shortest Hamiltonian cycle to connect all the logical points that have  1A simpler version of bundling WPT and MBS problem was stud­ied in [11], where the traveling path for the WCV was assumed to be given apriori.
Relationship: entailment
Domain: Networks
Sentence 1: Thesecondtechniqueismorecomplex andis motivatedby our observationthatthe rule-graph consists of highly clustered components that are connected by weak edges, i.e., rules withlow statisticalsignificance.
Sentence 2: hence, we apply spectral partitioning[..]to the rule-graph,to remove such weak edgesbe­tween strongly connectedcomponents.if Aisthe adja­cency matrix of the rule-graph, where each matrix entryis the sig­nificance score of the corresponding rule, we recursivelypartition 0.09% 100s HotSpot-2 ­ 0.02% 57s HotSpot-1 ­ 2.29% Enterprise 399s 1.61% LabEnterprise 368s 23.8% LabAccess 1556s -0.3 -0.2 -0.1 0 0 500 1000 1500 2000 Fraction of Trace Duration Time to Mine for Rules (s) Figure .
Relationship: entailment
Domain: Networks
Sentence 1: The con­structed tree T(G)embeds the connectivity of the network and ensures that sampling a node according to a given dis­tributioncanbedonewith alogarithmicnumberofhops.
Sentence 2: supple requiresabootstrapphasewhere T(G)is constructed using a cost metric propagated in 1-hop ..... messages.
Relationship: entailment
Domain: Networks
Sentence 1: In this topology, node 4 is a hidden terminal for the transmission from node 1 to node 2.
Sentence 2: node 4 can neither receive the RTS/CTS handshake between node 1 and node 2 nor sense the data transmission from node 1 to node 2, since node 1 is out of the sensing range of node 4.
Relationship: entailment
Domain: Networks
Sentence 1: The ac­curacy quickly improves to within a fraction of a centimeter as the algorithm overlays the partitions obtained from consecutive moves of the robot.
Sentence 2: since outliers are more likely to occur when the pair of distances being compared have a small difference, RF-Compass sets a prede.ned threshold eand decides that tag Tk P is closer to tag Ti R than to Tj R only if mTP ,TR = (1-e) · mTP ,TR, where mTP ,TR is the ki kj ki DTW distances measured between tags Tk P and Ti R [49].
Relationship: entailment
Domain: Networks
Sentence 1: For each server S, if it receives data from a client C, the data is forwarded to all the other clients and other servers connected to itself (server S).
Sentence 2: if server S receives data from other servers, the data is forwarded only to the clients di­rectly connected to S. a client connected to S transmits a packet to another client connected to S in two hops via S, and transmits a packet to another client con­nected to another server S' in three hops via S and S'.
Relationship: entailment
Domain: Networks
Sentence 1: MI C RO B E N C H M A R K We start with a microbenchmark experiment to provide insights into the working of the system.
Sentence 2: to better understand the capabilities and properties of RF-IDraw s trajectory tracing, we let a user write the word "clear" using the RFID on his hand, in the 5×6 m 2 VICON room.
Relationship: entailment
Domain: Networks
Sentence 1: We argue that this is not possible in this particu­lar instance much more so than other challenging future scenarios, because the challenge itself constrains the resources available to deploy new devices, systems, and infrastructure.
Sentence 2: to build new infrastructure takes up-front energy the energy to manufac­ture, deploy, operate, and maintain the devices, and as well as the .nancial resources to do so [22].
Relationship: entailment
Domain: Networks
Sentence 1: Our general strategy in pursuing these goals is under­stand the big things .rst.
Sentence 2: for each of the dimen­sions listed above, we pick the most salient contributors to that dimension and delve into them enough to under­stand their next degree of structure, and then repeat the process, perhaps delving further if the given contributor re­mains dominant even when broken down into components, or perhaps turning to a different high-level contributor at this point.
Relationship: entailment
Domain: Networks
Sentence 1: PRELIMINARIES To simplify the presentation, we do not distinguish be­tween publishers and subscribers.
Sentence 2: in order to publish data on a topic t, a node has .rst to subscribe to t. We model the nodes subscriptions formally as follows: Given a set of nodes V and a set of topics T, we de.ne an interest function over V ×T to be a Boolean-valued function over domain V × T. Subsequently, given an interest func­tion Int ,we say that a node v is interested in a topic t i. Int (v, t)= true.
Relationship: entailment
Domain: Networks
Sentence 1: This experiment shows that limiters rely upon up-to-date sum­maries of global information, and these summaries may become stale when delayed or dropped by the network.
Sentence 2: our concern lies with stale under-estimates that cause the system to overshoot the global rate; a completely disconnected system due to either congestion, failure, or attack could over-subscribe the global limit by a factor of N. We can avoid these scenarios by ini­tializing limiters with the number of peers, N, and running a light­weight membership protocol [24] to monitor the current number of connected peers.
Relationship: entailment
Domain: Networks
Sentence 1: Node degree constraint: One of the basic requirements for re­siliency that all ISPs require is that every node in the network has at least two independent paths to route traf.c originating at the node.
Sentence 2: the degree of all the nodes added into the network should be at least 2.  n+g X M ' i,j =2.ki .i = n +1,n +2, ..., n + g j=1 SD time constraint: For an ISP it is important to ensure that the network performance experienced by customers connected to the nodes in the original network does not deteriorate.
Relationship: entailment
Domain: Networks
Sentence 1: To support multimedia services [9] in such wired-cum-wireless environment, there is a need to develop an efficient differential scheme for the congestion control protocol such that the protocol is able to correctly tell the packet loss caused by the wireless channel from that caused by the network congestion.
Sentence 2: a proper differential scheme can help the congestion protocol to avoid blindly reducing the sending rate in the present of packet loss which not relative to the network congestion.
Relationship: entailment
Domain: Networks
Sentence 1: Similar to the TCP analysis in single cell WLAN [7, 8, 18], to cope with the problem complexity, we adopt the fol­lowing assumptions: A1) The last hop wireless link is the bottleneck link of a TCP downlink .ow; A2) The wireless channel is error-free; A3) The RTT between all APs and remote .le servers are the same.
Sentence 2: tCP RTT bias does not occur between the tra.c sources and APs.
Relationship: entailment
Domain: Networks
Sentence 1: Furthermore, CoSaMP can toler­ate certain noises mixed in Y , and the path vector can be recov­ered even some misclassi.ed packets are included.
Sentence 2: coSaMP could recover s if the number of correctly classi.ed pack­ets is greater than Ml = ck log( N k ) when c = 1.5 according to recent study [5].
Relationship: entailment
Domain: Networks
Sentence 1: SecureArray makes no assumptions about the type of antenna that the attacker uses.
Sentence 2: the system is de­signed to be effective in the presence of an attacker equipped with omnidirectional antenna, directional antenna (such as the Pringles can antennas famously used in past high-pro.le WiFi security breaches [19]), or even a phased array of antennas capable of se­lectively beamforming and nulling transmissions to arbitrary sets of 802.11 receivers on a per-packet basis.
Relationship: entailment
Domain: Networks
Sentence 1: As an example, using the results in Fig.2 and Fig.4 it is possible to obtain an indication on the pair (CB/N, CF /N) to be selected for planning accounting for both UL-UL and DL-DL interference scenarios.
Sentence 2: .xing an outage target of 1%, from graph in Fig.2 we obtain CB/N =8.5 dB and CF /N = 12 dB as an acceptable pair for the UL-UL situation.
Relationship: entailment
Domain: Networks
Sentence 1: If we assume that in this speci.c case the user is not charged for using the WiFi connection, and therefore the overall due fee is proportional to the amount of time that he spends in the GPRS network, a suitable handover policy can be chosen according to his willingness to pay.
Sentence 2: for a given communication session, let us de.ne the following cost function: .n C = TN i · cN i (h) (1) i=1 where TN i is the sum of the permanence intervals spent by the user in the i-th access network and cN i (h) is the fee per unit of time (second) that the operator of the i-th access network charges to the user.
Relationship: entailment
Domain: Networks
Sentence 1: Our work provides new insights into the imple­mentation of the 802.11 standard in commodity hardware.
Sentence 2: we present a new method to measure clock skew, rather, a more precise clock to measure it against;  an attack that spoofs the clock skew of a fake AP to mimic that of a real one, thereby rendering the two indistinguishableby the methodsproposedpreviously;  additional parameters to measure authenticity of the skew, enabling detection and mitigation of spoo.ng;   clock skewarithmetic,that enablesanetworkprovider topublish skews ofAPsinthe networkindependent of client stations.
Relationship: entailment
Domain: Networks
Sentence 1: More speci.cally, it is noted that wireless users belong to a larger social environment and as such, their movement behavior is subject to several location dependent sociological constraints (in addition to speed lim­its and speci.c walkways, as described in [1]).
Sentence 2: on any given day, each user may visit a list of places of some social importance (which we referred to as hubs in [8]) in some probabilistic manner, creating what we refer to in this paper as a mobility pro.le .
Relationship: entailment
Domain: Networks
Sentence 1: We say that the transfer is level if for any pair of outputs j1 and j2, B( j1) + x(+, j1) < B( j2) + x(+, j2) - 1 implies that x(+, j1) = min{ST, B(+, j1)}.
Sentence 2: whenever the output queue level at some output j1 is more than one less than that of another (following a transfer phase), it s implies there is no way to increase the level at j1.
Relationship: entailment
Domain: Networks
Sentence 1: What we now have asked instead is: how can we measure how this vertical handover will in.uence the behavior of running applications?
Sentence 2: what is the application-level cost of the very same network layer vertical handover, which may be very diverse depending on how it will impact on the application and the protocol it uses to manage end-to-end data .ows (UDP, TCP, RTP, HTTP, FTP, etc.).
Relationship: entailment
Domain: Networks
Sentence 1: Mobile wireless users have become a common sight across the world, and have motivated the need for further evolv­ing the Internet protocols and infrastructures, originally in­tended for .xed users, into new realizations capable of sup­porting portable and even mobile users at various speeds and across many geographical areas [10].
Sentence 2: with mobile users comes the need for user tracking protocols that work seamlessly for all roaming needs and application char­acteristics.
Relationship: entailment
Domain: Networks
Sentence 1: Aformal spec­i.cation of ourheuristic canbefoundinFigure3 where we assume that theSRSes are represented usingACLs.3 Intuitively, we can extract policy units from the SRS matrix ob­tainedabovebyidentifyinggroups of source addressesforwhichthe subnet-level reachability sets are equivalent.
Sentence 2: we de­composethe subnet-level reachability setscorrespondingto a source subnet(i.e.
Relationship: entailment
Domain: Networks
Sentence 1: L indicates that this probe has a loss mark.
Sentence 2: we further de.ne Fk to be the set of the virtual probes experiencing the maximum queuing delay, Qk, at link k.Fk = {t | Dtk = Qk}.We assume that the queuing delay for a probe taking the last available position at router k is Qk.
Relationship: entailment
Domain: Networks
Sentence 1: From Lemma 1 and Figure 1, we know that both µ0(t)and µc(t) are monotonic continuous functions of t. (µ0(t)is increasing in t and µc(t)is decreasing in t.) Since they are monotonic and continuous, both these functions have unique inverses, denoted by g0() and gc() respectively.
Sentence 2: g0 (µ0(t)) = t and gc (µc(t)) = t. Theorem 2.
Relationship: entailment
Domain: Networks
Sentence 1: For instance, with k = 2 the BCCs shrink to around 50% of the nodes, whereas with k = 3 they shrink to about the 25%.
Sentence 2: the similarity measure based on the size of the intersection of the PNLs generates an all-or-nothing effect that makes it hard to gain any insight on the social structure that underlies our datasets.
Relationship: entailment
Domain: Networks
Sentence 1: By simi­larly decomposing region O2 into smaller regions O21, O22, O23 and O24, we may now describe a more re.ned STAC policy, where M v1 is accessible at location O21 but not O22, and thus the user must move its physical location with an appropriate time period to O22 in order to access M v2, and hence resume access to M v.  3.2.2 Complex access policies and their representa­tions by FA The example of object M v just described gives insight into the power of STAC.
Sentence 2: a STAC system can perform complex access control by decomposing objects into object atoms and suitably associating smaller region atoms with these ob jects.
Relationship: entailment
Domain: Networks
Sentence 1: For our detection mechanism, we consider that a negativetrend occurs wheneverthetrendfactor reaches a value lower than -0.5.
Sentence 2: for a given detec­tionwindow,whenthenumberofnegativedi.erencesin am­plitude is more than the half of the possible number of sign changes,thereisahighpotentialthatthesignalis undergo­ing a decrease as a consequence of an incipient congestion.
Relationship: entailment
Domain: Networks
Sentence 1: We implement an unequal error protection (UEP) scheme that relies on forward error correction (FEC) channel coding supported by a proper unequal distribution of the transmission power (UPD) among JPWL coding units.
Sentence 2: we show that an appropriate combination of Reed-Solomon (RS) coding and UPD on the image data, can greatly improve the average PSNR of the reconstructed frames, in case of transmission over wireless channels with both sparse and packet error statistics, such as those provided by satellite broadcasting and Wireless MAN standards as WiMAX..
Relationship: entailment
Domain: Networks
Sentence 1: Although under the setting of mixed mobility rates, our experiments suggest that all three protocol are less e.cient than in the case of uniform speeds, we are happy to report than our mobility sensitive approach manages to select the best strategy among the available choices.
Sentence 2: if we make sure that the mobile nodes are able to use routing protocols that are suitable to the actual mobility rates, then MSA will manage to pick the one that best suits the actual network conditions.
Relationship: entailment
Domain: Networks
Sentence 1: Thus, an appropriate choice of the pricing policy is key for the provider to obtain good system performance.
Sentence 2: the pricing strategy should be able to regulate Mbps s -1 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65 0.7 Instant revenue 1 0.5 0 Mean throughput achieved by satisfied users 1 0.5 0 a l Figure 7: Dynamics in high congestion situation  the users access in order to prevent users from achieving dissatisfactory service due to congestion.
Relationship: entailment
Domain: Networks
Sentence 1: In this article, Penrose proved that if n is high enough, then with high probability, if one starts with an empty graph (i.e., only isolated nodes) and adds the corresponding links as r0 increases, the resulting graph becomes k connected at the momentitachieves a minimumdegree dmin of k.So, for k = 1, the network becomes connected at the moment where r0 is large enough to achieve dmin(G) > 0 with high probability.
Sentence 2: p (G is k connected) = P (dmin = k) (20) for P (dmin = k) almost one.
Relationship: entailment
Domain: Networks
Sentence 1: Satisfaction is a specif­ically introduced quantity that grows proportionally to the goodness of the results returned by each queried peer [15].
Sentence 2: we compared the routing strategies presented in Section 3.4 together with the Global IP-based (GIP) policy, which is a variation of the Global (G) mechanism: A direct connection is established between the current peer and the peer chosen for the following step, avoiding the hops needed to reach it in the original network topology.
Relationship: entailment
Domain: Networks
Sentence 1: Rate-Caution: If the RA algorithm without Rate-Caution would increase the rate by amount V (there was no congestion in the net­work), with Rate-Caution that value is: RX.Y - BX.Y V' = V · max1 - C ,Cmin BX.Y where C and Cmin are two constants.
Sentence 2: v' decreases as the .ow s current rate increases further above its guarantee.
Relationship: entailment
Domain: Networks
Sentence 1: Further, (d) for 1 = d = 3, the average correlation qt is exactly the probability that at time t, a randomly selected pair of nodes at distance d play C.Thus for 1 = d = 3 and * (d) t = t , the evolution of qt is similar to the evolution of the pairwise correlation in an in.nite k-regular tree.
Sentence 2: using (15), (12), and (13), for 1 = d = 3 and t = t * ,wehave: (d) 2 (d) 2 (d-1) 2(k - 1) (d+1) q=(1 - )qq+ q, tt-1 + t-1 t-1 n nk nk (16) Since at time 0, a random pair of neighbors play C, (0) (1) (d) we have q=2/n, q=2/(nk),and q=0,for 00 0 d = 2.
Relationship: entailment