sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: It is easy to show that the distance from p s sphere to q s sphere minus t is always less than p s sphere to a s sphere minus b if q wasinlockstepwith a.
Sentence 2: informally, ¯¯ ¯ this is because PQ < PA-1 and therefore PQ-1 -t< (PA -1) -1 -(l + b) < PA-1 -b.q s ¯¯update of its active set will always arrive before a s sphere enters p s the boot radius.
Relationship: entailment
Domain: Networks
Sentence 1: DIFFERENTIAL BANDWIDTH ALLOCA-TION By decoupling ef.ciency and fairness, XCP provides a .exible  (a) Time (seconds)  (c) Time (seconds)   (b) Time (seconds) (d) Time (seconds) framework for designing a variety of bandwidth allocation schemes.
Sentence 2: 10 the min-max fairness controller, described in §3, may be replaced by a controller that causes the .ows throughputs to converge to a different bandwidth allocation (e.g., weighted fair­ ness, proportional fairness, priority, etc).
Relationship: entailment
Domain: Networks
Sentence 1: In particular, strategies may be sorted in de­creasing order of e.ciency as Rate-Limit, Proportional­Keep-Lowest, Proportional, Proportional-Keep-Highest and Keep-Highest.
Sentence 2: removing bandwidth from strong ties can reduce the bandwidth consumption considerably while incurring a lower age than the one experienced at the same average bandwidth when re­moving weak ties.
Relationship: entailment
Domain: Networks
Sentence 1: We found that the success rate of VRR is less than 100% in our experiments because the link failure detection pro­tocol implemented does not always work.
Sentence 2: in theVRRimplementation,alinkisdisabledifthepercentage of received packet falls below a threshold, and re-enabled whenthereceptionratioisgreaterthanit,usinganexponen­tially weighted moving average (EWMA) .lter.
Relationship: entailment
Domain: Networks
Sentence 1: An exhaustive comparison is out of the qA jqE rithm R such that for all m.MqA and all m. scope of this work.
Sentence 2: mqE , 5there may be further communication at the E inter­ .. qA P(F (m,mjqE )= mqE+1) face to communicate the setAq to the adversary.
Relationship: entailment
Domain: Networks
Sentence 1: In addition, in our simulations we let the overlay graph topology change over time contrary to what we assumed in our model.
Sentence 2: we let users join and leave the peer-to-peer network according to the Law and Siu algo­rithm[9] which webrie.y outlinebelow; we referthe reader to[9] foramoredetaileddescription.
Relationship: entailment
Domain: Networks
Sentence 1: Here, the transmission time of the AP should not exceed the packetization interval because the wireless nodes need to send at least a packet within a packetization interval to keep their queues empty.
Sentence 2: xAP + t · P<i (5) Figure 4: Simulation topology Then, i - xAP P< (6) t Eqns 4 and 6 are plotted in Fig.
Relationship: entailment
Domain: Networks
Sentence 1: Be aware of the drawbacks and limitations of existing wireless network emulators, we aimed to design and implement a new one that is able to emulate network topology and mobility of mobile hosts.
Sentence 2: with a set of network parameters, EMWIN can map the target mobile wireless network to an emulation configuration in a laboratory private network, which consists of several emulator nodes and wireless devices if necessary.
Relationship: entailment
Domain: Networks
Sentence 1: For instance, in .gure 5, both sensors s1 and s3 satisfy the condition .1 - .2 =0, however sensor s2 satis.es the condition .2 - .1 = p. Figure 6: Avoiding Skinny Triangles Due to errors in angle measurements, sensors should be very careful in selecting the anchor pairs they use to localize themselves.
Sentence 2: a sensor should avoid using any anchor pair that forms with the sensor a skinny triangle.
Relationship: entailment
Domain: Networks
Sentence 1: We experienced that TinyNET represents a change of perspective with respect to the usual devel­opment of TinyOS applications, as it endows TinyOS de­velopers with the chance to follow the well known divide­and-conquer design strategy for complex systems.
Sentence 2: tinyNET allows to subdivide the development into many simpler independent parts, each to be handled sep­arately.
Relationship: entailment
Domain: Networks
Sentence 1: We observe that the short-term nonuniform access can funda­mentally alter the BEBA operations as assumed in the p­persistent scheme in the following aspects: 1) the short­term nonuniform access renders a lower probability of suc­cessful transmission compared to that obtained in the p­persistent scheme; 2) the probability of successful transmis­sion achieved by BEBA is less susceptible to the number of contending stations than that predicted by the p-persistent model.
Sentence 2: as the network size grows, the former falls at a much slower rate than the latter; and 3) the probabil­ity of collision experienced by BEBA is signi.cantly lower than that predicted by the p-persistent model.
Relationship: entailment
Domain: Networks
Sentence 1: Here dt(i, j)denotes the Euclidean distance between nodes i and j in time slot t, and r is the common transmission radius.
Sentence 2: a pair of nodes are neighbors if their distance is no larger than r. To further characterize a successful reception of a trans­mission, we consider the classical protocol model [20], i.e., a transmission from node i to node j is successful if for any time t within the duration of the transmission, dt(i, j) = r and each node i. except i with dt(i',j) = (1 + .
Relationship: entailment
Domain: Networks
Sentence 1: Available technologies, such as Platform Termi­nal Transmitter (PTT) and GPS tags [18], cannot hope to achieve these goals because their power demands conspire to make the tags useful for only single aspects of the study described above.
Sentence 2: they can either collect a hand­ful of daytime .xes at regular intervals over long-periods, or they can collect high-frequency movement data over short periods.
Relationship: entailment
Domain: Networks
Sentence 1: Then, the weight of edge (v, r) should satisfy: For vertex x: W1 +w(v, r)<w(x, y)+W2, For vertex y: W2 <w(x, y)+W1 +w(v, r).
Sentence 2: w2 - W1 - w(x, y)<w(v, r)<W2 - W1 +w(x, y), and there is a feasible choice for w(v, r).
Relationship: entailment
Domain: Networks
Sentence 1: The analysis of all possible combinations of .ow pairs provides instead the basis to evaluate the packet loss probability p (the other fundamental variable that we need to compute the throughput) of a node in an arbitrary topol­ogy.
Sentence 2: two-.ow scenarios are the building blocks that can be used to evaluate the collision probability of a transmitter in any net­work topology: a transmission on a link is successful if it does not collide with any other transmission on neighboring links.
Relationship: entailment
Domain: Networks
Sentence 1: Thus by Lemma 7.4, GoodExits(uVt)Choose max[(PossibleExits(uVt))S[for all tT1.
Sentence 2: as noted in Section 6, BestRoute(uVt)bestu(route(GoodExits(uVt)Vu)) bestu(route(S[Vu)) BestRoute(uVt)remains .xed for every node ufor all t T1.
Relationship: entailment
Domain: Networks
Sentence 1: An attacker could either be an outsider who wants to gain access to our data or services or a PN owner that has become a trusted member of a PN F. For each one of these cases we have to examine the respective threat trees.
Sentence 2: we should analyze the outsider threat tree (figure 1), which represents a usual attack process of an outsider (government agencies, industrial spies, etc) and then the unpredictable human factor threat tree (figure 2), which represents the involvement of a PN owner (might be a PN F member in the worst case) into the hacking procedure.
Relationship: entailment
Domain: Networks
Sentence 1: We use the same distinction but also consider the special case of the sink s neighbors [4], whose energy con­sumption pro.les are fundamentally different if the sink s radio is not duty-cycled (i.e., it is always on), as is often the case and as we assume throughout this paper.
Sentence 2: for sink neighbors the footprint of unicast transmissions, di ut, is typically three orders of magnitude smaller than for reg­ular nodes because tw (generally of the order of seconds) is replaced by the packet transmission time (of the order of ms).
Relationship: entailment
Domain: Networks
Sentence 1: Toaddprotection,FlexCastdesignsaratelessvideo codecbased on raptor codes [24] that allows the sender to protect bits in dif­ ferent distortion groups according to their relative importance.
Sentence 2: it has the property that if a particular group of bits is encodedwithmorebits,thenitsreconstructionerroriscorrespond­ingly lower after going through a noisy wireless channel.
Relationship: entailment
Domain: Networks
Sentence 1: Table 2 answers the second question: how different are the end­point information sites in different world regions?
Sentence 2: table 2 shows top entries for three different world regions we ex­plored (details provided in the next section).3 While some sites, e.g., projecthoneypot.org or robtex.com, show global presence, other top websites are completely divergent in different world regions.
Relationship: entailment
Domain: Networks
Sentence 1: While most of these components can borrow virtualization solutions from the wired network [5, 14, 16, 25, 28, 31] and desktop/server [15, 17] domains, the access network has to additionally deal with wireless resource virtualization, which is the focus of this paper.
Sentence 2: several unique challenges get introduced in the virtualization of wireless resources: (1) Unlike wired networks, co-existence of slices with bandwidth-based and resource-based reservations is not straight-forward since the bandwidth achieved by a slice from a given amount of re­sources varies with the channel quality of the users and the .ow scheduling policies.
Relationship: entailment
Domain: Networks
Sentence 1: Proof: Wlog, let w2nbr(v)be such that w=6u.
Sentence 2: then, by the shortest path property, we have cvu+Dud =Dvd<cvw+Dwd (12) This implies that Dvd;Dwd <1 (13) c vw and Dvd;Dud =1 (14) c vu Using equations (13) and (14), we get Dvd;DudDvd;Dwd (15) cc vuvw Using equation (15) and the fact that V(x)is a monotonically increas­ing linear function of x, we conclude that V(Dvd);V(Dud)V(Dvd);V(Dwd) (16) cc vuvw the force in the direction of uis maximum and positive.
Relationship: entailment
Domain: Networks
Sentence 1: in terms of link availability and available bandwidth).
Sentence 2: this project determined that for user downlink communications, such a system could support, in the 28 GHz frequency band, data rates of 60 Mb/s per cell for 99% of the time with a bandwidth of 12.5 MHz and up to 120 Mb/s per cell with a bandwidth of 25 MHz and clean air conditions.
Relationship: entailment
Domain: Networks
Sentence 1: In doing so, we have developed an infrastructure that allows this class of schedulers to be easily implemented and tested at Gb/s line rates.
Sentence 2: we have extended the ONL API to include functionality which provides ONL users the ability to place their own scheduler on the router, added measurement tools to the suite of standard router code that can run at up to a 100 µs granularity, and added flexible traffic generators which can produce Gb/s flows of any size packets with the additional ability to synchronize multiple generators to start flows to within 15 µs of one another.
Relationship: entailment
Domain: Networks
Sentence 1: The key difference between physical and service mobility is that while the first one attempts to continue the service uninterrupted even as the device (user) moves, the latter attempts continuous service experience even if this is consumed from a different device.
Sentence 2: (traditional) physical mobility puts a single user device at the center of a network/ system (made of cells, or different network types), and attempts to offer service continuity; service mobility, as conceived in this paper, puts user media at the center of a device/system (made of multiple devices, running possibly over several types of networks), and attempts to offer service continuity by moving media seamlessly from one device to another.
Relationship: entailment
Domain: Networks
Sentence 1: Other algorithms have attempted to minimize end-to-end delay mod- We also note that these results indirectly indicate that for any net­ work node v, the routes to destinations that are distant change much less frequently than routes to destinations that are close by.
Sentence 2: route .uctuations are con.ned to destinations that are close to vand thereby improves the stability of routes.
Relationship: entailment
Domain: Networks
Sentence 1: Extensive simulation using realistic classifiers and traffic traces shows that the proposed pipeline architecture outperforms HyperCut and B2PC schemes in classification speed by at least one order of magnitude, while with a similar storage requirement.
Sentence 2: with different types of classifiers of 4K rules, the proposed pipeline architecture is able to achieve a throughput between 19.5 Gbps and 91 Gbps.
Relationship: entailment
Domain: Networks
Sentence 1: Intuitively G j is the number of successfully- N utilized slots per time-slot unit in the entire network using the jth code-word assignment combination.
Sentence 2: if the information carried by a slot is called a packet, G j is the number of packets N successfully delivered in the entire network in an interval of time equivalent to a slot and using the jth code-word assignment combination.
Relationship: entailment
Domain: Networks
Sentence 1: Accordingly, the total buffer space which should be provided at the Internet gateway is given by n awndi packets, where n denotes the number of active TCP i=1 flows running through the Internet gateway.
Sentence 2: for a flow with a TCP data packet size of 1460 bytes and a receiver advertised window of 64 packets, we only need 187 Kbytes of buffer space for caching packets at the Internet gateway, which make up about 1.4 Mbytes for 15 flows.
Relationship: entailment
Domain: Networks
Sentence 1: Forwarding engines in many routers are designed to handle worst­case scenarios where all incoming packets have the minimum size.
Sentence 2: assume that a router can support a KLmin packets per second where L is the link speed in bytes per second; Kmin (typi­cally, Kmin = 40 bytes) is the minimum packet size; and a = 1is the ef.ciency factor.
Relationship: entailment
Domain: Networks
Sentence 1: Our work both corroborates known patterns of undesirable be­havior in P2P systems, and provides more insights into them.
Sentence 2: our .ndings on DDoS con.rm recent works where re­searchers showed the feasibility of exploiting P2P systems to launch DDoS attacks on the Internet [7, 9, 18, 30].
Relationship: entailment
Domain: Networks
Sentence 1: In this paper, we leverage an automated tool for .ngerprint construction to study novel scenarios for WiFi-based device-free localization training and testing that are di.cult to evaluate in a real environment.
Sentence 2: we examine the e.ect of changing the access points (AP) mounting location, AP technology upgrade, and outsider e.ect; on the accuracy of the localization system.
Relationship: entailment
Domain: Networks
Sentence 1: 4.3 Campaign to build the measurement database with DDP, NDDP and UDP scenarios As explained in Section 3.4, the idea was to obtain and store sets of RTT measurements performed at several fixed distances (4, 6, 9, 12 meters), including all the channel profiles for every distance.
Sentence 2: for every scenario (a given profile at a given distance) sets of 1000 RTT measurements were obtained.
Relationship: entailment
Domain: Networks
Sentence 1: In terms of data, instead of using BGP or traceroute data, our approach relies on the geographical location of end users or eyeballs (i.e.,, IP addresses) that are associated with an AS.
Sentence 2: the starting point of our work is a dataset consisting of the IP addresses of about 48 million users of three popular P2P applications that map to a total of 1233 eyeball ASes.
Relationship: entailment
Domain: Networks
Sentence 1: The membership adjustment algorithm works as follows: for any Meridian node M, we need to check each of its ring members Mi 0.4 0.2 to see whether the prediction ratio of the edge between M and Mi is within a safe range.
Sentence 2: if the prediction ratio of the edge is smaller than certain threshold ts or larger than another threshold tl, we need to place that corresponding node into rings not only based on the real measured delay but also based on the predicted delay.
Relationship: entailment
Domain: Networks
Sentence 1: In this work, we describe a new multivariate fore­casting technique that enables the NWS to automat­ically correlate monitor data from different sources, and to exploit that observed correlation to make bet­ter, longer-ranged forecasts.
Sentence 2: this new cor­relative method allows the NWS to combine infrequent and irregularly spaced expensive measurements (pos­sibly obtained through instrumentation) with regularly spaced, but far less intrusive probes to make predictions that would be far too expensive to generate with probes alone.
Relationship: entailment
Domain: Networks
Sentence 1: 3.3.1 Feature Extraction from Nodes In order to .nd patterns that nodes of a graph follow, we characterize the nodes with several features, so that each node becomes a multi-dimensional point.
Sentence 2: each node is summarized by a set of features extracted from its egonet (egonet of a node includes the node itself, its neigh­bors, and all the interactions between these nodes).
Relationship: entailment
Domain: Networks
Sentence 1: Although the total number of sen­sor nodes (N) in the network is large, the number of simultane­ous events that produce sensing data are limited.
Sentence 2: we as­sume that the number of source sensor nodes that actually produc­ing sensing data (i.e., the number of nodes sENwith T5>0) is not a large number.
Relationship: entailment
Domain: Networks
Sentence 1: 5.2 Evaluation Methodology In general, to compare the analytical and the simulation results, we use the .2 (Chi-Square) statistical test ([16]).
Sentence 2: for the performance metric of distribution of the number of infected nodes as a function of time, the range of integers from 1 to N is divided into k bins, where a bin is assigned a range of integers that correspond to the number of infected nodes at a particular time instance.
Relationship: entailment
Domain: Networks
Sentence 1: To make the problem of ex­tracting anomalies more challenging, we manually added to the candidate set .Fj .ows that had one of the three most frequent destination ports but had not been .agged by all histogram clones.
Sentence 2: the most popular destina­tion ports were port 80 that matched 252,069 .ows, port 9022 that matched 22,667 .ows, and port 25 that matched 22,659 .ows.
Relationship: entailment
Domain: Networks
Sentence 1: The valuations function of all nodes are policy consistent, the export functions of all the nodes but m obey consistent export, and the network has path veri.cation.
Sentence 2: then there is a BGP-compliant strategy for m that sets rm(·) = vm(·) and obeys all-or-nothing export (and therefore also consis­tent export), such that this strategy is optimal (utility-maximizing) for m. using the export-all rule is one such optimal strategy.
Relationship: entailment
Domain: Networks
Sentence 1: For example, we may decide to use MD5 or SHA1 for hashing blocks, while the hash function for the window is chosen such that it can be e.ciently rolled over the .le.
Sentence 2: for e.ciency reasons we need to be able to compute an updated hash value in constant time from the previous hash value whenever the window is shifted by one character, which is one of the main bene.ts of the hashes described in [18].
Relationship: entailment
Domain: Networks
Sentence 1: Afterthispoint, the number of movements is equal to m. However, until t = qlog2(m/m0) there are fewer movements under replication than under the multiple random walkers mechanism.
Sentence 2: under the latter mechanism mq log2(m/m0), while under the for- Llog2 (m/m0 ) 2i mer mechanism m0qi=0 movements take place, assuming that m/m0 is an integer power of 2.
Relationship: entailment
Domain: Networks
Sentence 1: InthesecondphaseBob receivesa message which comprises P OFDM symbols and uses an hypothesis test[14] todecideifthetransmissionisperformedbyAlice or Eve.
Sentence 2: let H be the estimate of the channel obtained by Bob on the pilots of the message according to (7), where now the average is done over P OFDM blocks.
Relationship: entailment
Domain: Networks
Sentence 1: It is therefore not possible to simply shift all sessions to the radio interface that would be most energy-ef.cient if fully utilised, without paying attention to the actual throughput rates of those sessions and detailed energy models for the inter­faces.
Sentence 2: we know that it is sometimes more energy­ef.cient to use one interface, sometimes it is better to use another interface, but how can we optimise MPTCP s .exible handover of .ows between interfaces to maximise those savings?
Relationship: entailment
Domain: Networks
Sentence 1: So at that point she gives up and sends the entire message using an error correcting code and incurs a constant blowup.
Sentence 2: say that for some .xed e > 0 she gives up when the block size is log1+e n. This means that the last phase before she gives up is i such that v n log n 2i = log1+e n ( ) 1 1 i = log n - + elog log n 2 2 The error threshold for this phase is 4n i+1 4= log1+2e n Let s analyze the cost of this algorithm.
Relationship: entailment
Domain: Networks
Sentence 1: Yet, in this case, he could keep zp(C1+.C ) entries at C1 +.C at the most, which is 1/z on the average.
Sentence 2: the energy he may gain in a stretch of any size C su.ces to keep, on average, 1/z counters at zpC at the most; .ushes in between only diminishing this energy.
Relationship: entailment
Domain: Networks
Sentence 1: In this work, we focus on the second approach, where the decision if a node can substitute another node is based on the consideration if the substituting node satisfies certain conditions.
Sentence 2: if a node N1 would like to change its state from passive to active and a neighbor node N2 would like to change its role from active to passive, this role changing can occur if and only if N2 is on a certain number of active paths of N1.
Relationship: entailment
Domain: Networks
Sentence 1: Furthermore, these features vary in a predictable manner as a function of the amount of traf.c car­ried in the OD .ow.
Sentence 2: we show quantitatively that the largest OD .ows in both networks are primarily deterministic and periodic; OD .ows of moderate strength are generally comprised of both bursts and noise comparatively; and the weakest OD .ows are primarily bursty (for Sprint-Europe) and primarily noise (for Abilene).
Relationship: entailment
Domain: Networks
Sentence 1: More precisely, denoted as T'(S) a minimum spanning tree of G'(S) and as MST (G'(S)) its cost, considering T'(S) rooted at the source station s, the heuristic directs the edges of T'(S) toward the leaves and sets the range r(x) of every internal station x of T'(S) with k children x1,...,xk in such a way that r(x)= ( · maxi=1,...,kdist(x, xi) ' .
Sentence 2: r is the range as­signment of minimum cost inducing the directed tree de­rived from T'(S) and is such that cost(r) : MST (G'(S)).
Relationship: entailment
Domain: Networks
Sentence 1: It is the topological anchor point for the MN s home network prefix and is the entity that manages the MN s binding state.
Sentence 2: it maintains the reachability state to the MN s address while it moves within the PMIPv6 domain  MAG: a functional entity that handles all mobility-related signaling on behalf of an MN attached to its access link.
Relationship: entailment