sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: SideCar expectsthe guesttomark and steerdisk commandpacketsto a sidecarthat can trackthese metrics.
Sentence 2: aguestcan deflateitsrequest ratebyonlysteering someofits commandpackets.Topreventthe guestfromdo­ing so, SideCar can sample allpackets and verifythat allthe requestpacketswereindeedmarkedtobe counted.
Relationship: contrasting
Domain: Networks
Sentence 1: The size of an anomaly then is the difference between the actual value and the modeled value, |zt - z t| where z t is the Fourier approximation of the OD .ow at time index t. We con.rmed that every OD .ow anomaly that we could visually isolate was also discovered by both these approaches.
Sentence 2: we did .nd several instances where both schemes mistakenly marked a moving average schemes) to identify single-timestep spikes, is that the scheme often mistakenly marks the time after a spike as an ad­ditional spike.
Relationship: contrasting
Domain: Networks
Sentence 1: This might be di.erent in scenarios with higher load, but as this requires an adaptation of control phase and data phase (the end-to-end delay for value of 1 2 3 4 5 6 Number of concurrent chains Figure 9: Comparison of end-to-end delay the initial JamTDMA packet and MAC-RSV solely depends on the slots available in the control phase), we leave the discussion of throughput optimization for further studies.
Sentence 2: when the end-to-end path is established, the delay is constant for this path.
Relationship: contrasting
Domain: Networks
Sentence 1: Finally, in terms of framing we note that the funneling-MAC uses the low power listening (LPL) algorithm and preamble technique proposed in B-MAC [3] to reduce energy consumption for sensor networks with low duty cycle.
Sentence 2: unlike B-MAC f-nodes do not need to transmit a long preamble in the LPL mode because their communications are synchronized by the superframe.
Relationship: contrasting
Domain: Networks
Sentence 1: Monitoring of User Generated Video Broadcasting Services Denny StohrDistributed Multimedia Stefan Wilk Distributed Multimedia Wolfgang EffelsbergDistributed Multimedia Systems Systems Systems Technische Universität Technische Universität Technische Universität Darmstadt, Germany dstohr@cs.tu­darmstadt.de Darmstadt, Germany swilk@cs.tu­darmstadt.de Darmstadt, Germany effelsberg@cs.tu­darmstadt.de ABSTRACT Mobile video broadcasting services o.er users the opportu­nity to instantly share content from their mobile handhelds to a large audience over the Internet.
Sentence 2: existing data caps in cellular network contracts and limitations in their up­load capabilities restrict the adoption of mobile video broad­casting services.
Relationship: contrasting
Domain: Networks
Sentence 1: We observe that when the .rst slice uses a simple round-robin scheduler, both clients in SLC 1 get similar airtime when channel quality is good for the mo­bile client.
Sentence 2: as the mobile client passes through the area with poor coverage, the airtime consumed by the mo­bile client increases, leading to a corresponding decrease in airtime available to the static client in SLC1.
Relationship: contrasting
Domain: Networks
Sentence 1: Although the size of the Hello packets may be reduced by using differential Hellos [24], the periodic packet over­head is still a concern.
Sentence 2: in situations when Hellos must be used for maintaining local neighborhood and to de­tect link failures (e.g., when the link layer cannot provide any feedback about link failures), incremental overhead for unidirectional link detection may not be very much.
Relationship: contrasting
Domain: Networks
Sentence 1: As a consequence AAAH cannot gen­erate AAA-Key as [10] proposes.
Sentence 2: instead, in our proposal, AAAH computes the AAA-Key as following: AAA-Key = KDF(MSK, AAA-Key-name) [10] does not de.ne any speci.c for­mat for AAA-Key-Name.
Relationship: contrasting
Domain: Networks
Sentence 1: It is a natural extension for wireless messaging service to integrate with messaging services over heterogeneous networks and provide a seamless and ubiquitous wireless data access.
Sentence 2: to reach this ubiquitous and seamless integration demands at least the following requirements: Heterogeneous connection: the messaging session should be seamless managed and user devices should have the capability to access among heterogeneous networks.
Relationship: contrasting
Domain: Networks
Sentence 1: By setting TRi = 8 every node in the network has direct access to the sink, thus expending a lot of energy of the nodes because of the long transmissions, however delay should be minimal since there is only one-hop transmissions.
Sentence 2: setting TRi to a small number will decrease communication cost a little but at the same time the data will take a long time to reach the sink.
Relationship: contrasting
Domain: Networks
Sentence 1: Moreover, in this case the business model is not yet clear, as operators would indeed o.oad tra.c, but also lose revenue as direct ad-hoc commu­nication would be di.cult to charge and privacy issues may arise.
Sentence 2: combining hotspot connectivity and multi­hop communications is an appealing answer to broadcasting geo-localized informations e.ciently.
Relationship: contrasting
Domain: Networks
Sentence 1: The combination of the uptime distribution (Figure 6) and the session length distribution (Figure 4) present an enlightening view of churn in P2P systems as follows: At any point of time, a majority of participating peers in the system are long-lived peers.
Sentence 2: the remaining small portion of short-lived peers join and leave the system at such a high rate that they constitute a relatively large portion of sessions.
Relationship: contrasting
Domain: Networks
Sentence 1: Of particular concern here would be architectures with the primary goal of improving performance properties such as path loss or de­lay.
Sentence 2: this is likely to be less of an issue for the (many) proposals that seek to add IP-level support for security, mobility, addressing, robustness, and so forth [2, 3, 7, 12, 13, 16, 17, 35 37].
Relationship: contrasting
Domain: Networks
Sentence 1: After a device has failed once, its failure probability de­creases by a factor of 1.5, and the probability contin­ues to decrease with subsequent failures indicating that it is favorable to consider repairing devices of this type when they fail.
Sentence 2: note that for some device gen­erations, repairs may not be as effective e.g., the proba­bility of failure likely increases with each subsequent re­pair for old devices close to their end-of-life as expected.
Relationship: contrasting
Domain: Networks
Sentence 1: Theories of Homomorphic Encryption, Uni.cation, and the Finite Variant Property * Fan Yang Santiago Escobar Catherine Meadows University of Illinois at DSIC-ELP, Naval Research Laboratory, Urbana-Champaign, USA Universitat Polit`ecnica de Val`encia, Washington DC, USA fanyang6@illinois.edu Spain meadows@itd.nrl.navy.mil sescobar@dsic.upv.es Jos´ e Meseguer University of Illinois at Urbana-Champaign, USA meseguer@illinois.edu Abstract Recent advances in the automated analysis of cryptographic proto­cols have aroused new interest in the practical application of uni­.cation modulo theories, especially theories that describe the al­gebraic properties of cryptosystems.
Sentence 2: this application re­quires uni.cation algorithms that can be easily implemented and easily extended to combinations of different theories of interest.
Relationship: contrasting
Domain: Networks
Sentence 1: In this design, each node s share of the medium is the same.A node with a good channel probably does not need the amount of share it gets, while another node with a bad channel would not be able to de­liver its data within its share.
Sentence 2: backscatter nodes inBuzz randomly collide in different time slots andkeep doing so until the reader signals that it has correctly received their data, as shown in Fig.
Relationship: contrasting
Domain: Networks
Sentence 1: v 49 msu 237 MI 3561 PL v 50 uky 10437 KY 209 PL 51 ac-uk 786 UK 3356 PL v  3.3 Validation of Bandwidth Bounds v 52 umich 237 MI 3561 PL v 53 cornell 26 NY 6395 RON v A number of groups have shown that packet trains can be used 54 lulea 2831 Sweden 1653 RON v 55 ana1 3549 CA 1239, 7018 RON v to estimate the available bandwidth of a network path [26, 18, 21].
Sentence 2: 56 ccicom 13649 UT 3356, 19092 RON v 57 ucsd 7377 CA 2152 RON the source has to carefully control the inter-packet gap, v 58 utah 17055 UT 210 RON and since Pathneck sends the probing packets back-to-back, it can- BW: measurements for bandwidth estimation; GE: measurements for general properties; ST: measurements for stability analysis; OV: measurements for overlay analysis; not, in general, measure the available bandwidth of a path.
Relationship: contrasting
Domain: Networks
Sentence 1: 6.3 The Effect of Remediation The drastic ampli.er reduction we saw was also evident in the number of ampli.ers seen per each victim IP, which also decreased by an order of magnitude across the ONP samples.
Sentence 2: we don t show this in a .gure, but the number of packets that the average ampli.er sends all victims has actually gone up by about an order of magnitude, to somewhat compensate for the reduced number of ampli.ers.
Relationship: contrasting
Domain: Networks
Sentence 1: Running a virtual router in unprivileged domain has unacceptable forwardingperfor­mance [16] but running it in privileged domain yields viable data planeperformance [15].
Sentence 2: letting a virtual net­work run directly in the privileged domain of the underlying hardware leads to less .exibility in customizing the virtual network,because a virtual network willbe limited to use a set of trustful elements to avoid jeopardizing the shared substrate.
Relationship: contrasting
Domain: Networks
Sentence 1: The victim s gateway cannot possibly .lter millions of .ows today s most sophisticated routers can accommodate up to tens of thousands of .lters [2].
Sentence 2: a sophisticated attack involves a large number of routers, which can share the .ltering load with the victim s gateway; and the closer we get to the attack sources, the larger the amount of .ltering resources that are available per attack source.
Relationship: contrasting
Domain: Networks
Sentence 1: MIN builds ATs using the nearest nodes from a speci.c group, which constructs ATs within a much fewer iterations both when ATs are constructed from scratch and when ATs are reconstructed after revoking faulty or compromised nodes.
Sentence 2: oPT incurs a lower operation cost (i.e., less transmissions to send one message to all the nodes in an AT) and a slower growth in the operation cost, while it takes longer and more messages to build ATs.
Relationship: contrasting
Domain: Networks
Sentence 1: For ZigBee nodes, we program the transmitter(s) to change its transmit power at each transmission by randomly select­ing one among four pre-de.ned transmit power levels, i.e., +4.5 dBm, -1.5 dBm, -6 dBm, and -10 dBm.
Sentence 2: we are unable to program the random power changes in WiFi nodes and hence, we simulate these power changes.
Relationship: contrasting
Domain: Networks
Sentence 1: (proved in [25]) tT (I) E[T]be_ tT_tT (II) ar(T)be_(I(ItT)e) e tTtTI (III) E[DT]ITI 2 tT (IV) ar(DT)b(etTI) tT (V) DTeT Remark: We can see that from Lemma 1(III) that DTis a bi­_tT_l ased estimator of ITIwith bias e'T 2.
Sentence 2: this bias is very small compared to the parameter ITI, since ITIis typically in millions and the tT(load factor) we are working with is no more than 0.7, resulting in a bias no more than 0.16.
Relationship: contrasting
Domain: Networks
Sentence 1: This is because the AP operates at the effective RSSI correspond­ing to the bottleneck client in the beam pattern in GREP d, which gives more room (in dB) for other clients with higher RSSI in the beam to cope with fading (including interference) losses.
Sentence 2: in GRASP 2 the AP is already operating at the effective RSSI that is socially optimal for all the clients in the beam (by .ne power splitting).
Relationship: contrasting
Domain: Networks
Sentence 1: The optimal solution may not completely eliminate inter-cell interference since interference below the noise power is often no longer considered the capacity-limiting factor.
Sentence 2: identifying the optimal solution is neither practical nor compatible with 802.11ac because (i) it is computationally intractable due to the lack of an analytical solution, and (ii) it has to be done in a centralized way with full channel knowledge of the entire MU-MIMO network.
Relationship: contrasting
Domain: Networks
Sentence 1: Equation(4)trans­lates that when the di.erence between two samples of the packetgrowthrateislessthan onepacket,thenthedetector considers that there was no signi.cant di.erence in ampli­tude, and hence it is not an indication of a change due to congestion.
Sentence 2: if the di.erence exceeds the thresholdof onepacket,thesignfunctiontakesthevalueof +1 to indicate a positive increase while it takes the value of -1 when the di.erence goes down below the threshold of one packet.
Relationship: contrasting
Domain: Networks
Sentence 1: 2.2 For the In-.ight-target Model Usually when users or Web sites want to make sure the pages are safe when .y from the server to the browser, they choose to use Hypertext Transfer Protocol Secure (HTTPS)[13], which provides end-to-end security by sym­metrically encrypting each document the user requested.
Sentence 2: this secure protocol also has some disadvantages.
Relationship: contrasting
Domain: Networks
Sentence 1: CCNx would likely su.er heavily due to the increased overhead of maintaining routing information; this would be further exacerbated by the complexity of routing on hierarchical identi.ers in an unstructured (changing) topology.
Sentence 2: approaches such as PSIRP or DONA would only be able to exploit this local caching if the local Rendezvous Point or Resolution Handler were accessible, thereby negating the greater po­tential resilience.
Relationship: contrasting
Domain: Networks
Sentence 1: To work around the limitations of current hardware, we implement a version of A-MACthat misappropriates addresses, violates standards, and abuses ac­knowledgments.
Sentence 2: the goal of our work is to demon­strate the power and performance bene.ts of the design; the underlying ideas are more principled than the hacks we em­ploy to accomplish this goal.
Relationship: contrasting
Domain: Networks
Sentence 1: Recent research has also produced mechanisms for esti­mating other important statistics such as the total number of .ows [4], the number of .ows of size 1 [1, 3], and the .rst and second moments of the FSD [5].
Sentence 2: such solutions are often restricted to producing estimates for onlythe com­plete population of .ows.
Relationship: contrasting
Domain: Networks
Sentence 1: The de­coding of these eleven tags can generally be categorized into two types.Certain tags hadavery good channel and were therefore im­mediately decoded from the .rst collision theyparticipated in, such as the two tags decoded in the very .rst time slot.
Sentence 2: other tags messages were uncovered as the belief on their data gradu­ally built up when the tags they collided with were decoded.
Relationship: contrasting
Domain: Networks
Sentence 1: According to the results presented by the authors, this approach is able to increase tra.c .ow in ur­ban areas by up to 60 % in comparison to traditional in­tersection management.
Sentence 2: their evaluation is based on optimistic and ideal assumptions, i.e., they neglected the existence of radio obstacles, and considered a perfect com­munications system based on which every broadcast message is received by every vehicle within a certain distance.
Relationship: contrasting
Domain: Networks
Sentence 1: These types of approaches might be straightforward and true if TCP application heavily depends on the fine-grain interaction, that is, heavy transactions between client and server like telnet session or FTP (File Transfer Protocol) control session.
Sentence 2: some of the Internet applications like e-mail or NetNews system was implemented by batch-oriented and was transmitted over intermittent connection, UUCP (Unix-to-Unix CoPy) dial-up for example.
Relationship: contrasting
Domain: Networks
Sentence 1: One could already deploy these mechanisms to implement a coopera­tion environment with most of the demanded features pro­posed in section 3.
Sentence 2: by doing so we would accept two major drawbacks: The cooperation environment would have to be hard-wired to the chosen persistency technology and the developers of the cooperative applications would need to know about all technical aspects of the object dis­tribution and replication in order to implement the desired behavior.
Relationship: contrasting
Domain: Networks
Sentence 1: Given an ex­plicit MACaddress identi.er, it is trivial to associate packets with their transmitting device.
Sentence 2: even without explicit network identi.ers, it has been demonstrated that otherimplicitly identifying informa- Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.
Relationship: contrasting
Domain: Networks
Sentence 1: This algorithm function stipulates that at the beginning, a node broadcasts the request message to its neighbors with probability 1 for the first k hops and with probability p for the rest; if a node with n neighbors receives a message and does not broadcast it, but then does not receive the message from at least m neighbors within a reasonable timeout period, it broadcasts the message to all its neighbors with probability 1.
Sentence 2: we discovered some critical issues for a broadcasting message with probability p on the relation of n neighbors in GOSSIP3(p,k,m).
Relationship: contrasting
Domain: Networks
Sentence 1: When the network is not very congested, their delay constraints can be easily satis.ed.
Sentence 2: when the network is persistently congested which is un­common in our dataset, adopters behave the same as non-adopters, 0 RTT between UE and Market Proxy (ms) Figure 17: The impact of the delay between UEs and the mar­ket proxy.
Relationship: contrasting
Domain: Networks
Sentence 1: Generated Orthogonal Sequence (GOS) [8] is a pioneer­ing work, which generates an orthogonal sequence of length N(N+1) based on the random permutations of {1, 2, ·· · ,N}.
Sentence 2: gOS is limited to the scenario where all chan­nels are not occupied by PUs and all users can access them.
Relationship: contrasting
Domain: Networks
Sentence 1: Median attacks over our sample period only lasted approximately 40 seconds in the samples since mid February, and about half or a quarter of that in previous samples.
Sentence 2: the 95th percentile duration attacks lasted about six and a half hours in the January 10th sample and have been declining since, with 50 minutes being the 95th percentile duration in the later April samples.
Relationship: contrasting
Domain: Networks
Sentence 1: Since such unexpected tra.c is likely to be dropped by the destinations themselves, classi.cation inac­curacy is not a show-stopper.
Sentence 2: it implies that if deep packet inspection capable .rewalls are available, then policies must be de.ned to forward all tra.c to them, rather than allowing tra.c to skip .rewalls based on their 5-tuples.
Relationship: contrasting
Domain: Networks
Sentence 1: We define a failure as the event that occurs when a system or compo­nent isunabletoperformitsrequiredfunctionformorethan.. s. Asexpected,mostfailuresaresmall insize(e.g.,...
Sentence 2: of network devicefailures involve < .devices and... of networkdevicefail­ures involve < .. devices) while large correlated failures are rare (e.g.,thelargestcorrelatedfailure involved... switches).downtimescanbesignificant:...offailuresare resolvedin..min, ...in< .hr,.....in< .day,but.....last> ..days.
Relationship: contrasting
Domain: Networks
Sentence 1: Thus, we can use a compressive sensing solution to ef.ciently re­cover x with a small number of linear combinations.
Sentence 2: traditional compressive sensing algorithms are com­putationally infeasible to apply in this setting because A has as many columns as the number of nodes in the network (e.g., one million itemsinaWal-Mart store).Todevelopa practical solution, we exploit the sparsity in x to eliminate large chunks of columns in A.
Relationship: contrasting
Domain: Networks
Sentence 1: Instead of taking into account these complex timing-dependencies between di.er­ent nodes sending in white spaces, we assume that in any (small enough) time-interval of duration t, the probability that a transmitting node returns to the control channel is .ret(Q)=(N - Q) · t/Tmax.
Sentence 2: the proba­bility that in a time-interval t, there is at least one successful handshake on the control channel can be approximated as psuc(Q) · t µsuc(Q)= .
Relationship: contrasting
Domain: Networks
Sentence 1: The moti­vation is that, even when the number of neighboring APs is large, at most 3 or 4 access points are targets of the hand­o.s [9]; it is likely that a similar motivation applies for ICNs, since the movement of users is the cause for mobility in both cases.
Sentence 2: the application of such an idea for support­ing mobility in ICNs is di.erent due to the di.erent nature of the problem: in ICNs the objective is to forward to mo­biles items that match their subscriptions, whereas in [9] the objective is to proactively send a mobile s context to neigh­boring access points in order to reduce association delay.
Relationship: contrasting
Domain: Networks
Sentence 1: The solu­tion of the MIP tells us how many copies of each video are needed and where each copy should be placed so as to minimize the total network bandwidth consump­tion.
Sentence 2: due to the scale of the problem, we .nd that eventhelinearprogramming(LP) relaxation of ourMIPistoolargeforo.-the-shelf software(e.g., CPLEX)to .nd an optimal solution within a reasonable time.
Relationship: contrasting
Domain: Networks
Sentence 1: This is expected, since vehicles (c) 10:00 am -3:00 pm(d) Zoom leaving one cell necessarily move to an adjacent cell, gener­ating large .ows between close-by cells.
Sentence 2: it is more interesting to note that there exist several macroscopic .ows 1.0 2.5 1.0 5 0.5 0.5 4 of vehicles among distant cells (i.e., from 1 km up to 4 km 2 0.0 0.0 away) and that involve hundreds of cars per hour.
Relationship: contrasting