sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: {1,2,...,K}, t xi(t)-xj(t)= nxi(0) - xj(0) exp n-s(u)du.
Sentence 2: (44) yi(t) yj(t))0 ) by subtracting the right-and left-hand sides of the i-th and the j-thODEin(22), wehavethat d (xi(t)-xj(t))= -(xi(t)-xj(t))(s(t)-xi(t)-xj(t)).
Relationship: contrasting
Domain: Networks
Sentence 1: The use of servers or caches owned by the content distribution system is ruled out due by the need to decentralize control in peer-to-peer systems (either in an attempt to evade responsibility for redistribution of copyrighted material or because of a desire to build scalable ad-hoc communities without central administration).
Sentence 2: if storage can be shared within a community in a scalable, ad-hoc manner, and without assigning responsibility for the stored data to the operator of the resource, then peer-to-peer architectures can use such storage to optimize their performance and efficiency without compromising their goals.
Relationship: contrasting
Domain: Networks
Sentence 1: In these protocols, collision-free transmission schedules are generated by disseminating probe messages within at most two hops, and as a result, nodes are able to recognize potential competitors for a simultaneous transmission, and act accordingly.
Sentence 2: it is worth noting that, the cor­rectness of the above protocols is based on the assumption that the network topology remains static during the time when the transmission schedules are generated and used.
Relationship: contrasting
Domain: Networks
Sentence 1: In order to decode the data transmission, the receiver .rst detects the .ashes, and then instead of reading the erroneous bits from the symbols that were .ashed, the receiver erases them.
Sentence 2: instead of causing bit errors due to concurrent control messaging, Flashback exploits the fact that .ashes are easily detectable to con­vert them to bit erasures.
Relationship: entailment
Domain: Networks
Sentence 1: While the methods we employ are somehow inspired by the large amount of expertise that has been gathered in terrestrial radio networks, there is still a lot of ground to cover to devise methods to implement ef.cient broadcasting, given the peculiar underwater channel features.
Sentence 2: we devise a way to leverage the bandwidth distance relationship in order to re­duce the number of transmissions required to complete the broad­cast, with the further goal of minimizing both the overall energy consumed and the total time it takes to complete the broadcast.
Relationship: entailment
Domain: Networks
Sentence 1: Weexamineseveral dimensionsofdevice contactsin orderto better understand the observed dichotomy, and we study the  time nonstationarity due to human synchrony with the time of day.
Sentence 2: we provide evidence that there exist real-world cases in which return time of a mobile device to its frequently visited site follows the same dichotomy as that of the inter-contact time between devices.
Relationship: entailment
Domain: Networks
Sentence 1: INTRODUCTION This paper is concerned with network architecture, the fundamental tenets that underpin the actual design of the network.
Sentence 2: we are interested in the architecture of 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 profit or commercial advantage and that copies bear this notice and the full citation on the first page.
Relationship: entailment
Domain: Networks
Sentence 1: If a user has not acted to capture this information, and it appears that his machine is infested with malware, regulation could permit (or require) that his serving ISP log his traffic.
Sentence 2: regulation could define that the penalty for failure to self-protect is loss of privacy, which is a punishment that might fit the crime, as opposed to more draconian alternatives such a total disconnection or quarantine.
Relationship: entailment
Domain: Networks
Sentence 1: It follows from the de.nition of the entropy that H(D1, D2) = 2H(D), but for the uncorrelated network H(D1, D2) = - pe(k, l) log pe(k, l) kl = - pe(k)pe(l) log pe(k) - pe(k)pe(l) log pe(l) kl kl = - pe(k) log pe(k) - pe(l) log pe(l) = 2H(D).
Sentence 2: kl the Markov property maximizes the mutual informa­tion of joint degree distribution pe(k, l).
Relationship: entailment
Domain: Networks
Sentence 1: The latter is clearly a better choice if one seeks to optimize the throughput of the entire path from Ato E. The .rst contribution of this paper is a new rate-selection al­gorithm called modrate that seeks to jointly optimize individual link bitrate selections with network-wide overhearing opportuni­ties.
Sentence 2: as opposed to selecting bitrates in a link-local fashion based only upon a packet s next hop, modrate selects the bitrate that minimizes a packet s expected number of transmissions along a path to its eventual destination assuming that any overhear­ing can be pro.tably exploited.
Relationship: entailment
Domain: Networks
Sentence 1: 6.7 Secrecy Capacity Based Formulation Although we have adopted a packet loss/interception ap­proachinthispaper,the resultsareeasily extended toguar­antee a given secrecy rate for all links that are active in a given time slot.
Sentence 2: conditioned on the fading gains, the e.ective transmitter-receiver-eavesdropper chan­nel for each link is a Gaussian wiretap channel.
Relationship: entailment
Domain: Networks
Sentence 1: INTRODUCTION In the immediate aftermath of 9/11 events in New York City, the Internet was used to facilitate communication between family members and friends, as the phone network was overwhelmed1.It does not require a great leap of faith to imagine using the Internet as a communication medium for crisis and emergency response teams.
Sentence 2: the network could be used to carry communications between widely dispersed static sites (e.g., various federal, state, and city agencies) and (semi-) roaming stations and users.
Relationship: entailment
Domain: Networks
Sentence 1: Conversely, if v> Vcut, the argument of F(x) is negative and increasing in absolute value with d, meaning that 1 -F(x) will increase in d.When v = Vcut, the argument in F(x)is 0, and the detection probability slightly varies around 0.5.
Sentence 2: s3 ideal algorithm as d approaches Vcut = 1 .Lemma 1.
Relationship: entailment
Domain: Networks
Sentence 1: [1,D], then the attacker can trivially determine j with the following algorithm: x = aq without loss of generality; and j =1 if Esj (x)= Es1 (x),otherwise j =2.
Sentence 2: if x matches one of the certi.cates it has for V1 and V2, then all the attacker needs to do is match Esj (x) to either Es1 (x) or Es2 (x).
Relationship: entailment
Domain: Networks
Sentence 1: 3.1.2 High-Fidelity Measurement The key insight and capability of how minProbe achieves high-.delity is from its direct access to the /I/ characters in the physical layer.
Sentence 2: minProbe can measure (count) and generate (insert or remove) an exact number of /I/ characters between each subsequent probe packet to measure the relative time elapsed between packets or gen­erate a desired interpacket gap.
Relationship: entailment
Domain: Networks
Sentence 1: These results are based on a version of the forecaster we have im­plemented that automatically computes the empirical CDF for each forecast incrementally, based on all pre­vious measurement data.
Sentence 2: the forecaster learns 0.16 Univariate Forecaster MAE Percentage 0.15 0.14 0.13 0.12 0.11 0.1 0.09 0.08 0.07 0.06 0.05 HTTP measurements every X minutes Figure 6.
Relationship: entailment
Domain: Networks
Sentence 1: Since then, a number of solutions have been proposed to achieve the upper bounds in various set­tings.
Sentence 2: [6] showed that by an e.cient backbone­peripheral routing scheme (analogously called highway sys­ 1v n tem ) and a two-stage TDMA scheme, O( )is achievable feasible states, and consequently the capacity of CSMA net­  works.
Relationship: entailment
Domain: Networks
Sentence 1: 7.2 Individual Attacker/Victim Activity One of the unique aspects of our datasets from these two sites is that they offer us a level of detail that is not present in some of our higher level global datasets.
Sentence 2: we are able to examine .ow and packet level details that offer additional insight about the activity of individual attackers and victims as well as validate our global datasets.
Relationship: entailment
Domain: Networks
Sentence 1: Inotherwords,people with the same general application a.liations show highly skewed and biased group behavior towards a single application at the considered hotspots.
Sentence 2: social networking is the dominant application among those at noon hotspots; musicamong thoseat nighthotspots; e-mail among thoseat o.cehotspots; anddating among thoseat eveninghotspots.
Relationship: entailment
Domain: Networks
Sentence 1: CONCLUSION In this paper, we have introduced a signaling game ap­proach for power control in wireless networks in which the signal sent by player I to player II may be accurate or mis­leading.
Sentence 2: we have showed that, at the equilib­rium, player I always performs better than player II except in situations where player II does not believe in the received signal either the received signal is accurate or misleading.
Relationship: entailment
Domain: Networks
Sentence 1: 3.3 The closed loop control scheme Our goal is to design a bandwidth allocation algorithm to bound service delay of real-time .ows.
Sentence 2: our for­mal objective is to design a control law that would drive the queuing delay ti, experienced by each frame going through the ith queue, to a desired target value tiT ; this value repre­sents the QoS level requested by the DEV associated to the queue.
Relationship: entailment
Domain: Networks
Sentence 1: ), and moreprecisely strictisotonicity  These properties are easy to establish, and indeed are already establishedby combining resultsfrom[18,14,19].
Sentence 2: they are suf­.cient conditionsfor some resultsin[18], related to the notion of lightestpath.Severalnotionsof lightestpatharede.ned(S-lightest pathand L-lightest path)in[18],butdueto strictisotonicityofthe ML-OLSRalgebra,they are equivalent, and arede.ned asfollow: Alightest path P between two nodes u and v, is apathbe­tweenu, v,withtheminimumcost w(P) withrespecttoorder  ifP is alightestpathbetween u, and v, any otherpath Qbetweenthe same nodes veri.esw(P) .w(Q)   One major result of[18] isthat whentheproperties of mono­tonicityand strictisotonicity areveri.ed, onelightestpathisfound by a thegeneralization ofDijkstra s algorithm(Fig.
Relationship: entailment
Domain: Networks
Sentence 1: Inthebest case, ourapproachisfasterthanRE2 andPCRE by one to two orders of magnitude.
Sentence 2: we make the following contributions: We propose a new approach to tag capturing groups in a regular expression, and extend Thompson s NFA construc­tion approach to convert a regular expression with capturing groups to a tagged-NFA.
Relationship: entailment
Domain: Networks
Sentence 1: However, the ac­tual amount of this packet drop depends on the tra.c load, bandwidth resources and the transmission conditions, and this amount may become unacceptable if the tra.c load is not regulated.
Sentence 2: an e.cient admission control framework is required to ensure that su.cient amount of resources are available to meet the packet drop constraints of the admitted session.
Relationship: entailment
Domain: Networks
Sentence 1: It is worth to notice that Am >l0 and AM >l4.
Sentence 2: (a) Received rate r(t), video level l(t), and available bandwidth b(t) (c) Frame rate f(t) Figure 9: QAC adaptive video streaming response to a step change of available bandwidth at t = 50s we are interested in assessing the responsive­ness of the adaptation algorithms in matching the available bandwidth choosing the adequate video level l(t).
Relationship: entailment
Domain: Networks
Sentence 1: 4.1 Average Transmission Rate: No-RelayNetwork (OT ) For networks with no relay, the average transmission rate (OT ) can be computed as follows L L.8 LT k=1 Figure 3: Relaying Region of a Relay ui.UT NN 1 1 (a) OT = lim .ui (k)C(duiB) N L = lim C(duiB ) .ui (k) L.8 TL to the main cell.
Sentence 2: the relays partition the cell ui.UT k=1 N 1 1 into Nr sectors with the central angle of 2p each.
Relationship: entailment
Domain: Networks
Sentence 1: Though our routing algorithm is clearly sub-optimal in a static-node environment (wherein signi.­cant routing overhead for a type of distance-vector algorithm may be justi.ed), in simulation studies it rapidly responded to network volatility maintaining good delay and through­put performance with a comparable amount of (ANT) over­head, that itself required little in the way of computation and no specialized hardware.
Sentence 2: for additional overhead, the algorithm showed good minimum energy per­formance which is an important factor of maximizing net­work lifetime.
Relationship: entailment
Domain: Networks
Sentence 1: On the contrary, a DIFS idle time, two SIFS time, and ACK is unavoidable for one frame transmission for the legacy DCF.
Sentence 2: only stations which belong to head group need to wait a DIFS idle time and the AP could send a block ACK frame to acknowledge all the previous transmissions of all group slots at the end of grouping cycle for our GB-DCF+ , instead of transmitting one ACK frame per transmission for the legacy DCF.
Relationship: entailment
Domain: Networks
Sentence 1: The daemon is the fundamental building block of PINL, implementing all the functionality that we have described so far in the previous sections and exposing the NELO interface to the entities.
Sentence 2: we have used libpcap to bypass the IP layemr both when sending and receiving PI packets; libpcap listens on all the interfaces that are con.gured and captures all inbound frames that are either PI packets, Dis­covery packets or ARP packets by inspecting the MAC type .eld within a frame.
Relationship: entailment
Domain: Networks
Sentence 1: To this extend, this paper, which reports measure­ments from a .xed WiMAX testbed in Oulu, Finland, adds to our knowledge about real-world WiMAX performance us­ing o.-the-shelf hardware.
Sentence 2: we evaluate voice over IP (VoIP) perfor­mance over .xed WiMAX using synthetic tra.c genera­tion.
Relationship: entailment
Domain: Networks
Sentence 1: Speci.cally, the measured noise levels with the jammer exhibit a much lower variation (the time series curve is almost .at) in Fig­ure 5(c) compared to noise levels when the jammer is not present in Figures 5(a) and (b).
Sentence 2: the baseline scenario with no communicator, Figure 5(a), has a much higher variation.
Relationship: entailment
Domain: Networks
Sentence 1: Specifically, extra bandwidth (due to idle flows) will not be allocated to backlogged flows that are waiting to be served in the basic channel; instead, we will give spatial reuse higher priority.
Sentence 2: the slot allocated to an idle flow in the basic channel will not be allocated to another backlogged flow in the basic channel; it will be shared among multiple concurrent trans- mitting nodes (that belong to a flow-dependent maximum independent set).
Relationship: entailment
Domain: Networks
Sentence 1: Although the idea of building the interconnect of a multiproces­sor computer system in the form of a honeycomb spherical graph is still in its infancy, people have known about and used such graphs to discretize the sphere in the numerical weather prediction com­munity for many years; see, e.g., [3], [8], and [10].
Sentence 2: the model developed by the Deutscher Wetterdienst (DWD) is an ex­ample of an operational meteorological code that implements the dual of a honeycomb graph with icosahedral symmetry (see [7]).
Relationship: entailment
Domain: Networks
Sentence 1: The downside to our two key design decisions using general-purpose servers and parallelizing router functionality is that they make it dif.cult for our router to offer the strict performance guarantees that hardware routers have tradi­tionally offered.
Sentence 2: packet reordering (considered unde­sirable due to its potential impact on TCP throughput) and latency are two fronts on which a software router may fundamentally have to offer more relaxed performance guarantees.
Relationship: entailment
Domain: Networks
Sentence 1: For each, we give an example in which removing the constraint results in an un­bounded price of anarchy, meaning that the result of nodes acting rationally but sel.shly is arbitrarily worse than the result of a cen­tralized, optimal computation.
Sentence 2: local decisions us­ ing a BGP-compatible protocol may not .nd a welfare-maximizing i j. route allocation if one or more of the constraints are not satis.ed.
Relationship: entailment
Domain: Networks
Sentence 1: Taking the path in Lemma 1 {n~,..., nl} that obeys the ordering criteria, we show that if some node n~ changes its successor to ni to some other node mj along the path {mj,..., ml, ni ), which is in order, that the ordering criteria is obeyed.
Sentence 2: ni c rnj it c ~ nl c , n. tc Snnl (tnl ) < snnl , n, , or Snnl (tni ) = Snnm~ (t~.
Relationship: entailment
Domain: Networks
Sentence 1: We therefore have an operation 8 that can reconstruct a label from adjacent con.gu­rations, and we insist on consistency: the equation (lI 8 lE ) I s = lI II (lE IE s) must be valid for all label and metric values.
Sentence 2: we can reconstruct a label l = lI 8 lE from bits of con.guration data ' at each end of a link, and the metric s= l I s will always be the ' same as .rst computing w = lE IE s and then s= lI II w. The type of w is W , which corresponds to the data type that is shared over the wire by the vectoring protocol; this may not be equal to the algebra s metric type S. In this paper we will not concern ourselves with algebraic prop­erties of routing algebras that are associated with correct usage of various algorithms.
Relationship: entailment
Domain: Networks
Sentence 1: * * In this game, the strategies (s1, ..., s )are a Nash equilibrium n * if, for each player i, si is (at least tied for) player i s best re­ * sponse to the strategies speci.ed for the n-1 other players, (s1, **** * ..., s s ..., s ).
Sentence 2: s solves maxsi.Si ..., i-1, i+1, ni ui(s1, * ** si-1, si,si+1, ..., s ).
Relationship: entailment
Domain: Networks
Sentence 1: When proving the deniability property of protocol .E ,the PA-1 notion is therefore too weak to represent the common situation in which multiple copies of the protocol are run concurrently since in this case the attacker does have access to valid ciphertexts created by other parties.
Sentence 2: in the case of protocol .E the attacker may replay such ciphertexts in a communication with the owner of pk with­out knowing the encrypted plaintext.
Relationship: entailment
Domain: Networks
Sentence 1: To support implicit state management, we extended Bro s table and set data structures to support per-element timeouts of three dif­ferent .avors: creation, write, and read.
Sentence 2: for a given table (or set), the user can specify in the policy script a timeout associ­ated with each element which expires T seconds after any of: the element s creation; the last time the element was updated; or the last time the element was accessed.
Relationship: entailment
Domain: Networks
Sentence 1: Wk is a k-stage Erlang random variable with mean E[W]=2.ke and a is given by: 4.ne 2n a == > 1 E[Wk] k It is easy to see that P(Wk > 4.ne) .
Sentence 2: 0 for large n. all n nodes are discovered by the .log2 n.-th phase w.h.p.
Relationship: entailment
Domain: Networks
Sentence 1: However, with the increasing deployment of mesh and ad-hoc networks and new paradigms such as smart environments [1] for both professional and consumer applications, network mobility (as opposed to terminal mobility) will soon become commonplace.
Sentence 2: such a scenario will be an intrinsic feature of Body Area Networks (BANs) where the whole network is attached to the body which is in constant movement and interaction with the environment.
Relationship: entailment
Domain: Networks
Sentence 1: First, we show that this large IXP exhibits a surprisingly rich peering fabric in support of the many business objectives of its members.
Sentence 2: in terms of AS links of the peer-peer type that are typically established among member AS pairs we show that this IXP has close to 400 members which have established some 67 % (or more than 50,000) of all possible such peerings and use them for exchanging some 10 PB of IP traf.c daily.
Relationship: entailment
Domain: Networks
Sentence 1: We consider a simpli.ed propagation model in which r is the radio range of a station.1 Let s denote the physical area (size) of the network and T(·)represent a region of the plane satisfying cer­tain geometric conditions.
Sentence 2: t(A)indicates the region ¯ within radio range of station Aand T(AnB)represents the region within radio range of Bbut outside that of A.
Relationship: entailment
Domain: Networks
Sentence 1: Nonetheless, WSNs are naturallydependentonhow nodes aredistributed in the sensor .eld, since several tasks are a.ected by nodes location, such as clustering [10, 17], data routing [11], lo­calization algorithms[16,24],informationfusion[15],data agregation[7,21,25,26], and tasksthatdepends on spatial data correlation [9, 14, 22].
Sentence 2: in this paper, we will explore the impact of nodes distribution on data aggre­gation performed by clustering algorithms.
Relationship: entailment
Domain: Networks
Sentence 1: In our evalua­tion, we de.ne a stability function f = |a n ß|/|ß|, where a and  6.2 Dirty data In order to evaluate our scheme in identifying and removing dirty data, we synthetically inject some dirty data into both the SNMP link loads and the sampled NetFlow measurement.
Sentence 2: we introduce two types of dirty data in SNMP link loads.
Relationship: entailment
Domain: Networks
Sentence 1: The horizontal line corresponds (BER Block)/(BER Gray) 100 10-1 10-2 -30 -35 -40 -45 -50 -55 -60 -65 -70 RSSI Figure 8: Variation in BER gains at different bit-positions with Block relative to Gray with varying RSSI, and with PHY con­ speci.c constellation maps to improve the performance of media applications in a natural way.
Sentence 2: we focus on video streams in which content is par­titioned into multiple classes, and each class has a different levels of importance in correct decoding of the stream.
Relationship: entailment
Domain: Networks
Sentence 1: To achieve this, the following rule is used: Rule 3: xy - Down turns are not allowed in an odd xy-plane and Up -xy turns are not allowed in an even xy-plane.
Sentence 2: packets travelling upward cannot enter and even xy-plane (turn North, East, South or West) and pack­ets travelling within an odd xy-plane cannot leave this plane through the downward direction.
Relationship: entailment
Domain: Networks
Sentence 1: For example, the routing table information used by DQS queue can be directly acquired from the routing a) VBR-TCP b) CBR-UDP 300 70 250 65 200 60 150Goodput(Kbps) 55 100 50 50 45 0 2 4 6 8 10 40 2 4 6 8 10 Path length(n) Path length(n) Figure 1: Goodput for static chain topology layer.
Sentence 2: the routing layer provides an interface to the DQS queue, which belongs to di.erent layers.
Relationship: entailment
Domain: Networks
Sentence 1: In this paper, we show that much faster packet classi.ers are attainable with a careful design aimed at GPU hardware architec­tures.
Sentence 2: our design incorporates several GPU-speci.c features, including (1) memory accesses are always coalesced to signi.cantly reduce latency to off-chip memory; (2) on-chip SRAM memory is heavily utilized and shared among threads to speed up rule matching; and (3) all available GPU cores are exploited to their full extent, i.e., 100% occupancy is guaranteed.
Relationship: entailment