sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: Tempus uses our novel mixed-packing covering solvers, which have the following distinc­tive features: (a) they have smaller memory footprint compared to running an LPsolver at each timestep, and perhaps more impor­tantly, (b) they conserve computation.
Sentence 2: since the cumula­tive effect of the online optimization across all timesteps allocates only as much network flow as the offline LP, the total computational cost should be similar; i.e., the running time when added up across all timesteps equals the runntime of the offline LP; and hence the per timestep running time is much smaller.
Relationship: entailment
Domain: Networks
Sentence 1: Basedontheseobservations,fora network-wideNIDSwe implementthe coordinationchecksforthedifferentmodules as early as possible.
Sentence 2: for modules such as HTTP, IRC, andLogin, we add the checksin the event engine, and for modules suchasScan,TFTP,Blaster, andSYNFlood we add the checksin thepolicy scripts.
Relationship: entailment
Domain: Networks
Sentence 1: However, the solution to this problem shows (see Section 5) that although the network capacity (i.e., the sum of bit rates over all nodes) is maximized, there exists a severe bias in the rate allocation among the nodes.
Sentence 2: those nodes that consume the least amount of power on their data path toward the base-station will be allocated with much more bit rates than other nodes in the network.
Relationship: entailment
Domain: Networks
Sentence 1: The relative influence between the heuristic information and the pheromone levels is controlled using parameters D and E. While an ant is visiting node i, Ni represents the set of neighborhood nodes that are not yet visited from node i.
Sentence 2: the probability of choosing a node j while at node i, is defined by the following equation: DE ­Wij .Kij DE if j N ° ¦Wig .K i ig p ® g Ni (5) ij ° 0 otherwise ¯ for the considered RWA problem this paper uses two visibilities.
Relationship: entailment
Domain: Networks
Sentence 1: However, as speci.cations (or languages for de.ning speci­.cations) become more complex, another kind of correctness should be considered: how can a designer have con.dence that the speci.cation (or collection of speci.cations in multi­ple models) he de.nes is an accurate re.ection of his intuitive and practical expectations regarding the correct behavior of the software?
Sentence 2: we are interested in some con­.rmation, from the perspective of a speci.cation s designer, that the speci.cation of a system correctly captures the be­havior and requirements that the designer believes that it possesses.
Relationship: entailment
Domain: Networks
Sentence 1: between pathwidth [20] and pathlength [8].
Sentence 2: for any n, we describe an n × n matrix M, and a labeling L of the nodes of any n-node graph G, such that greedy routing in (G, (M, L)) per­ v forms in O(min{ps(G) · log2 n, n}) expected num­ber of steps, where ps(G) denotes the pathshape of G. This result has many important corollaries.
Relationship: entailment
Domain: Networks
Sentence 1: Yet the causal relationship between routing changes and degraded data plane performance has not been established.
Sentence 2: very little is known about (1) how routing changes re­sult in degraded end-to-end path performance in the .rst place, and (2) how factors such as topological properties, routing policies, and iBGP con.gurations affect the extent to which such routing events can cause performance degradation.
Relationship: entailment
Domain: Networks
Sentence 1: Since every tag has exactly one representative bit in each partition of Vt, we may be able to use one of the partitions to carry the order information.
Sentence 2: if there is a partition P * whose number of ones is equal to the number of tags encoded in Vt, we know that there must be a one-to-one mapping between these tags and the 1 bits in P *.
Relationship: entailment
Domain: Networks
Sentence 1: Our experience with extending the userver to use the AIO API illustrates sev­eral new aspects that should be factored in when developing AIO-based applications.
Sentence 2: the use of an AIO model necessitates additional steps for registering and de­registering (and, therefore, managing) bu.er memory, sim­pli.es the application by eliminating the need to handle par­tially completed operations, exposes new considerations in the sequencing of the application s socket operations, and enables applications to process events and issue operations using application-speci.c policies to improve resource man­agement and performance.
Relationship: entailment
Domain: Networks
Sentence 1: The lab also points out issues in the interaction between intradomain and interdomain routing that are di.cult to reproduce without real routing software.
Sentence 2: bGP only selects a route as best if a recursive lookup on the next-hop succeeds, i.e., the path to reach the next hop is known by static routes or some IGP protocol, as stated in [39].
Relationship: entailment
Domain: Networks
Sentence 1: 3.2 Results for general graphs We now present a randomized O(log n)-approximation for general graphs in the multicast model, based on the tech­nique of embedding arbitrary metrics into tree metrics [1, 7, 13].
Sentence 2: we .rst use the 2-HST (hierarchically well-separated tree) construction of Fakcharoenphol et al [7], which O(log n)-probabilistically approximates the metric d over the given graph.
Relationship: entailment
Domain: Networks
Sentence 1: Inthis sense,thetra.cpatterngenerated towardsthe network of theMNOin thetwo above scenarios(i.e,Wi-Fi or femtocells) is the same.
Sentence 2: all tra.c generated by theuserwhen outsidecoverage of aWi-Fi accesspoint(or a femtocell) is sent to the network of the MNO as usual.
Relationship: entailment
Domain: Networks
Sentence 1: First, it prepares a DTLS record specifying the actual response data as payload, and referring to the record header structure depicted in Figure 4.
Sentence 2: the listener node r: i) .lls the 5 octet Truncated Sequence Number .eld with the sequence number value stored in the write group connec­tion state C SW associated to sender node s, before incrementing s it; and ii) .lls the 1 octet GroupID .eld with the group identi.er I DG.
Relationship: entailment
Domain: Networks
Sentence 1: 2.3 Safety and Determinism Previous work has noted that because BGP makes best-path de­cisions based on local policy, certain sets of policies can result in routing con.gurations with no stable solution [16, 20].
Sentence 2: one AS may change its choice for a best route to a destination and read­vertise that change to its neighbors, which will cause neighbors to change their choices for best routes, which will in turn affect the original AS s choice for a best route, and so forth.
Relationship: entailment
Domain: Networks
Sentence 1: Albeit the similarity to shooter localization (e.g., [16]), positioning radio source indoors can be fundamentally different from locating acous­tic source outdoors: the former has its speci.c challenges given the complicated indoor structures and the totally dif­ferent signal propagation features between sound and radio signal.
Sentence 2: we may not afford to deploy a network sensing system given the reason discussed earlier.
Relationship: entailment
Domain: Networks
Sentence 1: In [7], the capacity of wireless ad-hoc networks with IEEE 802.11 is assessed with simple mathematical derivations and simulations.
Sentence 2: it is found that in principle, in a chain topology, the maximum throughput between the end points in the absence of other traffic is a fraction of 0.25 of the nominal net (i.e., without overhead) WLAN bandwith.
Relationship: entailment
Domain: Networks
Sentence 1: Unlike in other sections, in Figures10 13, we normalizethepro.t of alltheplotsinthegraphs tothehighest observedpro.t.
Sentence 2: pmax inthese .gures is not the maximumpro.t of eachplot, but the maximumpro.t of theplot withhighestpro.tinthe .gure.Normalizingby thehigh­est observed pro.t allows us to show how changing the parameter .
Relationship: entailment
Domain: Networks
Sentence 1: 1Speci.cally, for a given time t, where t is the seconds part of a 32-bit UNIX times­tamp in UTC, and an expiration interval of 2n, the corresponding key ID i =(t >> n)&#38; 0xF.
Sentence 2: the key ID is the last 4 bits of t after removal of the lower n bits; the key ID changes every 2n seconds.
Relationship: entailment
Domain: Networks
Sentence 1: Main contribution (part 1): The .rst .nding reported in this paper is that some of the largest Internet Exchange Points (IXPs) in Europe (i. e., AMS-IX in Amsterdam, DE-CIX in Frankfurt, LINX in London) do indeed serve as the kind of vantage points we are looking for.
Sentence 2: our detailed analysis of 17 contiguous weeks of complete sFlow measurements from one of the largest European IXPs reveals that in addition to being a critical part of the European portion of the Internet, this IXP also plays a global role, seeing traf.c from a large fraction of the Internet.
Relationship: entailment
Domain: Networks
Sentence 1: On the other hand, the transition zone is shallow on channel 6.
Sentence 2: about 23 % of all trans­mitter pairs achieve a cumulated TXR between 100 PPS and 140 PPS, whereas this region only contains 4-6 % of the (a) With CRC/PHY errors (trials 1.34-1.57) (b) Without CRC/PHY errors (trials 1.66-1.69) Figure 5: Relative TXR loss for all transmitter pairs, ordered according to ascending (interference­free) PSR, on channel 14 with and without process­ing of CRC/PHY corrupted frames.
Relationship: entailment
Domain: Networks
Sentence 1: Considering all the above three factors, we propose IDCC, which uses traffic-based probabilistic caching, intra-domain advertisement, intra-domain cooperation and content hierarchical caching to improve caching performance.
Sentence 2: iDCC scheme uses the following strategies: Probabilistic caching: Probability caching can reduce cache redundancy, at the same time, guarantee the cache time.
Relationship: entailment
Domain: Networks
Sentence 1: Mallory waits until the user enters to the same website, and since browsers re-use connections, the browser will send the user s requests over the victim-connection, allowing Mallory to in­ject a spoofed web-page in response.
Sentence 2: mallory can learn user credentials by spoo.ng the homepage of web­sites, which often do not invoke SSL until the user presses a log-on link; this is done by injecting a spoofed homepage where the log-on link points to Mallory s site.
Relationship: entailment
Domain: Networks
Sentence 1: Given an action pro.le S(S1,,Sn), the set s{(k,i): 1:k:n,iESk}is called the pair set for S. Given a function f:IkSk., the corresponding set function, fs,of fis a 1 set function of the form .where {(k,i):1: k:n,1:i:m}and fs(s)f(S).
Sentence 2: fs(K)f((A1,A2,,An))if Aj{i:(j,i)EK}.
Relationship: entailment
Domain: Networks
Sentence 1: 3.1 Hop-limited shortest-path trees As explained in Section 1, we refer to the shortest-path tree formed by nodes within a certain number of hops (say n hops) from the root as hop-limited shortest-path tree.
Sentence 2: we use the term n-hop shortest-path tree for re­ferring to the hop-limited shortest-path tree that is made of nodes within n hops from the root.
Relationship: entailment
Domain: Networks
Sentence 1: When the MD-Like algorithm is considered, the correlation be­tween packets affects the packet loss PMF, which is an impor­tant parameter in the FEC optimization.
Sentence 2: a two-state Markov model, which corresponds to a Gilbert-Elliot channel, char­acterizes the channel by a good" state (G) and a bad" state (B), the probability that k packets are lost for a channel with K corre­lated packet is [16] PK (k)= PK (k|G)P (G)+PK (k|B)P (B) (4) where PK (k|G)(PK (k|B)) is the probability of having k cor­rupted packets when the channel is in the good" ( bad") state, and P (G)(P (B)) is the probability of being in the good" ( bad") state.
Relationship: entailment
Domain: Networks
Sentence 1: This is partially because CDNs have emerged only for about ten years and have became prevalent only recently as video, im­age, and other User Generated Content (UGC) has become dominant sources of tra.c on the Internet and way passed the capacity that content publishers can handle by them­selves.
Sentence 2: no caching schemes have been designed particularly for CDNs in prior literature, to the best of our knowledge.
Relationship: entailment
Domain: Networks
Sentence 1: However, even if a node ends up the game paying some money to be part of a network which makes it content, this situation is still preferable to not joining the network, as this would drive down the utility function of the node to -M (we recall that M is much larger than the due payment and the edge weights).
Sentence 2: if we assume that every node in the network accepts to join the computed net­work topology T only if T makes it content, it is easy to see that our proposed framework satis.es individual rationality: it is rational for any sel.sh node u to take part in the game, since the outcome of the game can only increase u s utility6 .
Relationship: entailment
Domain: Networks
Sentence 1: Each facility provides some common utility level to all its users, which depends onthenumberofusers, and .nally eachplayergets thesumoverusedfacilities oftheutilitylevelsthattheselat­ter provide.
Sentence 2: the larger the number of players who use a facility, the lower the common utility level that they attain from that facility (monotonicity).
Relationship: entailment
Domain: Networks
Sentence 1: If node vk+1 receives the packet and node vk doesn t, then node vk+1 forwards the packet with cost Cvk+1 .
Sentence 2: if both vk+1 and vk receive the packet, then node vk forwards the packet with cost Cvk .node vk forwards data only if both node vk and vk+1 receive the packet.
Relationship: entailment
Domain: Networks
Sentence 1: A simple and feasible method for solving this problem is to allocate each terminal to one concentrator without exceeds the capacity of any concentrator.
Sentence 2: we use a vector of integers:  (1) Where X(t)=c means that terminal t is allocated to the concentrator c, and 1 = X(t) = M, 1 = t = N. whole terminals must be assigned to one concentrator, and  (2) It means that the capacity of one concentrator must not be exceeded by the capacity requirements of the terminals assigned to that concentrator.
Relationship: entailment
Domain: Networks
Sentence 1: Such restrictions might be the subnetwork that consists of all the OC48 links, all the links with available capac- ity over some timescale, or all the links with delay be- low an appropriate threshold.
Sentence 2: using explicit MPLS routing, different families of shortest paths are maintained in the network; traditional shortest paths, and shortest paths over different restrictions of the net- work  2.
Relationship: entailment
Domain: Networks
Sentence 1: It is easy to see = that for .l .e, we have = L(d, x, r,p,l)= L(d, r,l)+ xepe(l) L(d,r,e) * = L(d, r,l)+ cece pe(l) = L(d, r,l)+ L(d, r,e)p * e(l).
Sentence 2: l(d, x,r,p,l) is the same as the link load on l when pro­tection routing pe * is used to reroute traf.c traversing thefailed link e, which is no larger than cl by assumption.
Relationship: entailment
Domain: Networks
Sentence 1: In Case A, the handover latency delay that occurs is very small as 100Mbps, 2-20ms  the overlapping region is larger.
Sentence 2: the SMMP avoids 100Mbps, 2-20ms  Domain Address 100Mbps, 2-20ms MAP Domain Address 2.0.0 the handover latency delay by preparing the T_Addr in advance.
Relationship: entailment
Domain: Networks
Sentence 1: Since not all attacks are created equal, it is of paramount im­portance for network administrators to be aware of the status of the network infrastructure, the relevance of each attack with respect to the goals of the organization under attack, and also the most likely next steps of the attackers.
Sentence 2: the last capability, attack prediction, is of the most importance and value to the network ad­ministrators, as it enables them to provision the required actions to stop the attack and/or minimize its damage to the network s assets.
Relationship: entailment
Domain: Networks
Sentence 1: In [20] it has been proven that the class of position-based scheduling policies, i.e., those policies in which the selection of the transmission con.guration pS(t) is driven only by the vector of instantaneous nodes positions X(t), achieves the maximum network capacity.
Sentence 2: in this work we consider the following position­ based scheduling policy, which complies with the conditions im­ posed by the protocol interference model: De.nition 1.
Relationship: entailment
Domain: Networks
Sentence 1: CONCURRENCY In this and the following section, we analyze the impli- Clearly, the lookup algorithm presented in Section 4 does cations of mobile nodes.
Sentence 2: this section focuses not support lazy publishing in its second phase, where the on the publish algorithm, through which every node keeps lookup request follows the level pointers in order to .nd a its level pointers up to date when it moves.
Relationship: entailment
Domain: Networks
Sentence 1: 3.2 The GUIDE End-System In close consultation with the TIC, we considered a wide range of devices for use as the GUIDE end-system.
Sentence 2: we considered pen-based tablet PCs, such as the Fujitsu Stylistic and TeamPad, Windows CE based machines, such as the Casio Cassiopeia, and other PDAs such as the Apple Newton.
Relationship: entailment
Domain: Networks
Sentence 1: We call identifiers of an encoded symbol algorithmic, because they are all produced according to an algorithm that must be known to the entities participating in the communication while all other entities can remain agnostic to this algorithmic relationship.
Sentence 2: subscribers utilize the same algorithm to extract meaningful information out of the identifier, which will be later used to decode the initial content, while intermediary caches can utilize the statistical uniqueness of symbols identifiers to possibly replay cached symbols.
Relationship: entailment
Domain: Networks
Sentence 1: When apacket withpayload x and .ow identi.er f arrives at time t, for each row r, a position in the ma­trixgiven by(r, (hr (f)+h ' r(x))modC)is determined.
Sentence 2: the .ow hash is used to obtain a base position in each row, whilethepacketpayload shashdeterminesano.setto thatpositioninthe range[0,k - 1].
Relationship: entailment
Domain: Networks
Sentence 1: In Figure 3, we show the expectation of the normalized number of tickets observed for a network, as a function of the normalized entropy binned in units of 0.33.
Sentence 2: low, medium, and high heterogeneity refer, respectively, to normalized entropy in the range [0, 0.33), [0.33, 0.66), and [0.66, 1].
Relationship: entailment
Domain: Networks
Sentence 1: If a Black Hole node uses instead a directional antenna (electronically steerable or sec­torized), then it can fool its upstream node by beam-forming as illustrated in Figure 4(b).
Sentence 2: the Black Hole node will beam-form a fake j to k transmission such that i incorrectly in­fers that k has received the packet.1 This issue will be increasingly critical as such technologies become widely deployed.
Relationship: entailment
Domain: Networks
Sentence 1: [1] shown by analysis of the IEEE 802.11 Distributed Coordinate Func­tion (DC F )that the individual throughput qj obtained by all the ST As served by AP j is of the form: 1 qj = mj (2) 1 wip j p=1 Note that the objective function we have considered in this paper is to maximize the aggregate throughput.
Sentence 2: the ag­gregate throughput is de.ned here as the logarithmic sum of the individual throughput obtained by the ST As from their respective serving AP s. aggregate through­ .n put is equal to the quantity j=1 mj ln(qj ).
Relationship: entailment
Domain: Networks
Sentence 1: The last phase of the design .ow is the recon.gurations minimization phase, in which all the temporary placement solutions sets will be compared in order to .nd an optimal placement for each application that minimizes the recon.g­urations needed to pass from one application to the subse­quent one.
Sentence 2: this phase tries to .nd a set of placement solutions (one for each application) in which the maximum number of computational and communication elements shared among di.erent applications is physically placed in the same recon.gurable regions across the maxi­mum number of applications.
Relationship: entailment
Domain: Networks
Sentence 1: The result of this is that the effective receive window of the connection, from application to application, is the minimum of the TCP and allSSH receivewindows.
Sentence 2: rWINe = MIN(RWINtcp, RWINssh)[11] Figure 2 illustrates the disparity between the SSH and required TCP receive windows (as dictated by BDP) in hypothetical 1Gb/s networks of varying lengths.
Relationship: entailment
Domain: Networks
Sentence 1: Therefore, we consider adversarial models similar to anti-censorship so­lutions such as Telex [49], Cirripede [23] and Decoy Rout­ing [25].
Sentence 2: the censor is able to block access to Tor s publicly listed routers, and to detect certain patterns in Tor s tra.c and hence block them [18].
Relationship: entailment
Domain: Networks
Sentence 1: 5.2.2 Varying Work.ows We now look at Baraat s performance under the di.erent work.ows described in Figure 1 in §2.
Sentence 2: we examine three work.ows (i) a two-level partition aggregate work.ow where requests arrive in an online fashion, (ii) the storage retrieval scenario used for our testbed experiments where tasks have parallel work.ows and request arrival is online, and (iii) a data-parallel application where tasks have a parallel work.ow and there is a batch of jobs to execute.
Relationship: entailment
Domain: Networks
Sentence 1: To reduce the complexity we propose a method for obtaining the bit epoch by processing the matrix A at different chip offsets and then solving the Lagrangian problem once at the chosen bit epoch rather than N times.
Sentence 2: using equation (1) and the definition of the matrix A and assuming E{|ci|2}=1, the un­normalized diagonal elements of A maintain a constant value which can be expressed as follows *2 a =E rr {}=K +N (2) kk kk p while the off-diagonal elements akn , where k and n are the matrix element indices, can be expressed as follows KK K pp p {* LLEbb L{ ss a = E rr } = {}ss = E bb } kn kn jkin jkin ik in ik in j 1 i=1 i=1 = (3) The final form of the equation can be found using the observation that E{bjkbin}=0 if icj because two bits of the two different users j and i are independent.
Relationship: entailment
Domain: Networks
Sentence 1: Using Your Smartphone to Detect and Map Heterogeneous Networks and Devices in the Home George NychisSrinivasan Seshan Peter Steenkiste Adaptrum Carnegie Mellon University Carnegie Mellon University george@adaptrum.com srini@cs.cmu.edu prs@cs.cmu.edu ABSTRACT Heterogeneity in the wireless spectrum is an increasing problem which breaks down coordination and exacerbates wireless interfer­ence.
Sentence 2: this is a growing problem in the home: hetero­geneity is increasing, yet there is a lack of tools and expertise in the home to gather the necessary information about its RF environment to combat this issue.
Relationship: entailment
Domain: Networks
Sentence 1: From the results shown in Figure 3 we can see that even with a small cache size of type B proxy, e.g., approximately equal to 380,000 blocks resulting in a total cache capacity of 500,000 blocks in the tree topology, we can achieve the same byte-hit ratio with the one of the simple topology with a total capacity of 1,200,000 blocks.
Sentence 2: the tree topology achieves the same byte hit ratio with the simple topology with a 58% reduction in the overall cache capacity in the system.
Relationship: entailment