sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: We measure the severity of triangle inequality violations as fol­lows: for each node pair, we ask what the shortest path is between the two that passes through a third node.
Sentence 2: for all pairs of Relative Path Length Figure 2: Severity of triangle inequality violations: the cumula­tive distribution of mink(d(i, k)+ d(k, j))/d(i, j) over all pairs i, j. nodes i and j, we compare d(i, j) with mink(d(i, k)+ d(k, j)).
Relationship: entailment
Domain: Networks
Sentence 1: Hence, it becomes important to construct a good mesh so that good quality trees may be produced.
Sentence 2: we attempt to ensure the fol- lowing properties: (i) the shortest path delay between any pair of members along the mesh is at most K times the uni- cast delay between them, where K is a small constant and (ii) each member has a limited number of neighbors in the mesh which does not exceed a given (per-member) bound chosen to reflect the bandwidth of the member's connection to the Internet.
Relationship: entailment
Domain: Networks
Sentence 1: (14) j06 =j Dove-tailing DRFQ (§5.5) and memoryless DRFQ (§5.4) are thus special cases of bounded DRFQ.
Sentence 2: when = 1, the functions B1 and B2 reduce to functions F and S as in the previous section, and bounded DRFQ becomes equivalent to dove-tailing DRFQ.
Relationship: entailment
Domain: Networks
Sentence 1: T as a linear weighted sum of the values at­tained by each feature where the weights are given by ßj for each feature j .
Sentence 2: f : yi = j.F ßj xj + ß0 we use the LASSO, also known as L1-regularized Linear Regression [18], where an additional constraint on each feature allows us to obtain a model with lower test prediction errors than the non-regularized linear regression since some variables can be adaptively shrunk towards lower values.
Relationship: entailment
Domain: Networks
Sentence 1: for the network G. A multicast rate vector .S bits/sec is feasible if there is a spatial and temporal scheme for scheduling transmissions such that by operating the network in a multi-hop fashion and buffering at intermediate nodes when awaiting transmission, every node vi can send .i bits/sec average to its chosen k - 1 destination nodes.
Sentence 2: there is a T< 8 such that in every time interval (with unit seconds) [(i - 1) · T,i · T ], every node vi .S can send T · .i bits to its corresponding k - 1 receivers Ui.
Relationship: entailment
Domain: Networks
Sentence 1: We select the .rst such un­scheduled packet or buffer cell, whichever occurs .rst, i.e., on a smaller wavelength.
Sentence 2: if it is an unscheduled buffer cell on wave­length i, then based on the construction algorithm, any packet on a wavelength between wavelengths 1 and min{i+ d,W} (which is the largest wavelength i can be converted to), cannot be sched­uled to buffer cells on a wavelength larger than i.all of these packets are scheduled to buffer cells on wavelength ior smaller, but there is still a buffer cell on wavelength ithat cannot be used.
Relationship: entailment
Domain: Networks
Sentence 1: Then, equations (3) and (5) become -ad = z0 , i.e.
Sentence 2: dmin = 6z0 d (6) a -a 6D min and thus, 6Lbd 6Lb 1 × when dCS < Dmin (7) = 2 2 d a a Te = ( 6z d ) ( 6z ) 0 0 Te increases as the communication distance d decreases as predicted in [8].
Relationship: entailment
Domain: Networks
Sentence 1: While we could not simul-taneously examine different beamforming sizes and different CSI estimation frequencies in real time, we have collected traces of the channel coefficients and emulated the channel offline.
Sentence 2: we replay the channel using the recorded traces but assume dif-ferent beamforming sizes (2 and 4), and different CSI estimation frequencies (10 ms and 100 ms).
Relationship: entailment
Domain: Networks
Sentence 1: In SQoS, however, this authentication is integrated with a mech­anism that prevents excessive .ooding.
Sentence 2: since QoS-Guided Route Discovery requires a .ood of the network and hence provides a means for an attacker to perform a Denial-of-Service attack (consuming all network resources), a secure ad hoc network routing protocol must enforce limits on the frequency at which each node can initiate such .ooding.
Relationship: entailment
Domain: Networks
Sentence 1: As we can see in the above equation, the characteristic of the ISI terms depends on the results of the relation mod(lk - l, Np).
Sentence 2: as we will see in the simulations, the ISI e.ect cannot reduce necessarily by increasing the number of PN sequences, especially, for Np << L. In the remainder of this paper, to simplify the theoretical analysis, we assume orthogonal PN sequences.
Relationship: entailment
Domain: Networks
Sentence 1: The subgraph eccentricity of bi with respect to bj (represented as SEcc(bi,bj ) ) is de.ned as the eccentricity of bi with respect to only the nodes in SG(bi,bj ).
Sentence 2: sEcc(bi,bj )= Maxbx ESG(bi ,bj ) (Dist(bi,bx)).
Relationship: entailment
Domain: Networks
Sentence 1: In particular, we de.ne the capacity C(n) of the net­work as the supremum of all rates .
Sentence 2: (n) that are uniformly achievable by all sources in the network, multiplied by their number n. the capacity is the supremum of all achievable aggregate throughputs, under the requirement that source nodes create tra.c with the same rate.
Relationship: entailment
Domain: Networks
Sentence 1: The main motive here is to .nd a balance between 3G and WiFi connectivity in densely populated areas.
Sentence 2: to supportthegrowing needfor mobile connectivity,theop­erators have to massively overprovision their 3G networks, or otherwise o.oad some of the tra.c to WiFi networks, saving this way money from 3G network extensions and im­plicitly increasing their revenue.
Relationship: entailment
Domain: Networks
Sentence 1: While a number of studies have analyzed short-term unfairness due to various aspects of the wireless medium ranging from channel errors to contention, (see [1, 5, 6] for example), none accurately characterize the time scale in which 802.11 stations alternate domination in SIS scenarios.
Sentence 2: in our analysis of the SIS group, we model short-term unfairness of IEEE 802.11 with and without RTS/CTS, derive the behavior of the .ows from the collision probability, analyze the transient behavior of the system, and accurately predict the time­scale of this unfairness as a function of key system parameters.
Relationship: entailment
Domain: Networks
Sentence 1: It would be useful to be able to use these capabilities in the decentralized environment, but this will require signi.cant further investigation to see how well the assumptions of the centralized model can carry over to the decentralized case.
Sentence 2: there would need to be some mechanism by which the members of the mesh confer­ence can agree about who has control over the conference and is authorized to make these decisions.
Relationship: entailment
Domain: Networks
Sentence 1: The target actual uplink rate * indicates the ideal value of RTi, a user s actual transmission rate per time slot, at which its service QoS requirements are fulfilled, while the Margin Factor (MFi) determines acceptable bounds of its actual achieved throughput deviations with respect to the target actual rate.
Sentence 2: a RT user s margin factor determines the minimum acceptable levels of its expected actual throughput (i.e.
Relationship: entailment
Domain: Networks
Sentence 1: In this paper, we consider the following question: can we design a compact routing scheme for this problem?
Sentence 2: when the condition that packets route along shortest paths is relaxed to allow some bounded stretch (where the stretch |p(u,v)| of path p(u, v)from node u to node v is de.ned as , d(u,v) where d(u, v) is the length of the shortest u-v path), can routing tables be constructed that use sublinear space at every node?
Relationship: entailment
Domain: Networks
Sentence 1: The core can clas­sify all the packets heading towards the congested link into multiple .ows according to buckets (IP buckets or main buckets), inbound interfaces and the boundary routers from which they enter the core.
Sentence 2: each .ow can be characterized by the attribute vector (bucket, interface, boundary router), which we refer to as a virtual port ; de­ 1 b ,··· ,x U b be the bit rates tio of 16, if all these packets are puzzle solutions, a puz-note these ports 1,··· ,U.Let x zle router needs 88MB memory to keep all the client nonce these ports demand, let r 1 c ,··· ,r U c be the rates of computa­ 1 b ,··· ,r U b denote the bit sequences within a nonce period of 20 seconds.
Relationship: entailment
Domain: Networks
Sentence 1: Indeed, a lower bound of the number of downloads D from the central server is: XX XX D = Ni,j 1Ni,j>0 + j.C i |C j .i where the equality holds for in.nite-capacity caches.Without caching, PP the number of downloads from the central server is ji Ni,j , and,hence,caching reducestheloadatthe serverbyafactor a: a = µ · 1 - 1 S « with P P P P µ = j.C i Ni,j P j P i Ni,j and S = j.C i Ni,j P j.C P i 1Ni,j>0 .
Sentence 2: µ is the fraction of updates needed in subnets cov­ered by caches and S is simply the mean number of updates per subnetover subnetsthat deploycaches.Asimilar approach canbe used to derive the bene.t in terms of bytes.
Relationship: entailment
Domain: Networks
Sentence 1: (9) i.Bt The second constraint ensures that a packet is processed at a con­sistent rate across resources.
Sentence 2: for a backlogged .ow i and its head-of-line packet at time t, let tt i,r be its packet processing time on resource r, and t t r ri = arg max i,r (10) Table 1: Main notations used in the .uid model.
Relationship: entailment
Domain: Networks
Sentence 1: 8.3 Exploiting Physical Layer Information In recent years, researchers have started to exploit the .ne-grained physical layer information to improve the per­formance of both categories.
Sentence 2: pinLoc [20] ap­plies high resolution CSI .ngerprints to combat the instabil­ity RSSI .ngerprint, at the cost of higher complexity in con­structing a .ngerprint map.
Relationship: entailment
Domain: Networks
Sentence 1: The strategy proposed here allows increas­ing the ef.ciency of the channel by increasing the length of the transmitted train, without compromising on the packet error rate, i.e., keeping the transmitted packets short.
Sentence 2: we de­couple the effect of the packet size from the choice of the length of the train, i.e., the number of consecutive packets transmitted back­to-back by a node: while the former determines the packet error rate, the latter can be increased as needed to increase the channel ef.ciency.
Relationship: entailment
Domain: Networks
Sentence 1: INTRODUCTION A VANET (Vehicular Ad-hoc NETwork) is an ad-hoc network that allows providing communications among nearby vehicles with the primary goal of improving traffic conditions.
Sentence 2: it is a kind of MANET (Mobile Ad-Hoc NETwork), where devices are vehicles and the ad-hoc network is formed spontaneously by nodes in movement.
Relationship: entailment
Domain: Networks
Sentence 1: To cope with this situation, throughout the 2nd phase of the algorithm we exploit pricing to bring about a Pareto improvement in integrated network s performance via cells load balancing.
Sentence 2: our intention is to take advantage of the pricing­based algorithms for solving individual cell s resource allocation optimization problems (EORA_NSA) to shape incoming users behavior, in terms of different access networks cells selection towards improving the performance from an integrated system viewpoint (NCS_ NSA).
Relationship: entailment
Domain: Networks
Sentence 1: Edman and Yener also used their setup, based on USRP2 software de­.ned radios,1 to attempt toimpersonatelaptop-based nodes.
Sentence 2: by recording many 802.11b frames, they trained their software de.ned radio attacker to reproduce the mod­ulation attributes (e.g., average phase error and frequency o.set) of the legitimate laptop-based nodes.
Relationship: entailment
Domain: Networks
Sentence 1: In addition, apart from feasibility, the first experience in the system usage has exhibited efficient and scalable performance for the implemented mechanisms to support mobility.
Sentence 2: the tracing and discovery service has shown good scalability while increasing the number of mobile entities involved, mainly due to the delegation and distribution of registering duties over all involved places, without forcing to maintain a centralized and strictly consistent naming service.
Relationship: entailment
Domain: Networks
Sentence 1: 7.6 Non-monotonic algebra As an example of an algebra that is not monotone consider the algebra of the previous section but with the ordering of the set W being inverse-lexicographic, instead of lexico­graphic.
Sentence 2: (x1,n1)(x2,n2) if and only if n1 <n2, or n1 = n2 and x1 = x2.
Relationship: entailment
Domain: Networks
Sentence 1: Instead of attempt­ing to embed all the nodes in a global Cartesian-space based on RTT measurements, Netvigator performs local clustering for proximity estimation.
Sentence 2: one scheme Netviga­tor [29] uses to estimate latency from a node X to another node Y is based on MIN-SUM formulation: latency(X, Y )=min {d(X, l)+ d(Y, l)}, l.L where L is the set of landmarks and milestones and d(X, l) denotes the measured latency from node X to l. In the S3 architecture, distributed Netvigator uses web service interfaces of sensor pods to con.gure periodic invoca­tions of traceroute sensor from each machine to chosen land­mark nodes.
Relationship: entailment
Domain: Networks
Sentence 1: 5.3 Results In this section, we quantify the effectiveness of using multivari­ate, network-wide analysis of routing updates to detect network disruptions that might otherwise be missed.
Sentence 2: we .nd the following: (1) the subspace method detects every documented link and node failure on the Abilene backbone network and nearly two-thirds of documented failures on Abilene peering links; (2) the amount of routing data that must be processed to successfully iden­tify network disruptions are reasonable, suggesting that our tech­niques could ultimately be incorporated into an online detection system; and (3) though speci.c parameters in the subspace method are tunable, the technique works well for a wide range of settings.
Relationship: entailment
Domain: Networks
Sentence 1: This paper presents analytical results that shed light on the latency of oppor­tunistic forwarding in wireless networks with duty cycling.
Sentence 2: we give approximation formulas and bounds for the expected latency of opportunistic forwarding in pres­ence of duty cycling for general .nite network topologies, and an exact formula for a speci.c regular network topology that captures some common sensor network deployment sce­narios.
Relationship: entailment
Domain: Networks
Sentence 1: We know from the design of MRSCBF that elements are inserted into SCBF i with sampling probability pi.
Sentence 2: to .nd out the number of occurrences of x from the observation T,we use the principle of MLE, i.e., we would like to .nd f that maximizes Pr(F = f|T).F = argmax Pr(F = f|T).
Relationship: entailment
Domain: Networks
Sentence 1: of L Aquila DIEI/DEWS L Aquila, Italy fabio.graziosi@univaq.it ABSTRACT In this paper, a general framework for performance evalu­ation of cooperative spectrum sensing methods over realis­tic propagation environments is proposed.
Sentence 2: the framework accounts for correlated Log Normal shadowing in both sensing and reporting channels, and yields simple and easy to use formulas for computing the Detection Probabil­ity of a distributed network of secondary users using Amplify and Forward (AF) relying for data reporting to the fusion center.
Relationship: entailment
Domain: Networks
Sentence 1: SETTINGPARAMETERS In the following analysis, our goal is to choose a sampling rate p, and stash size W that will maximize the expected number of delay samples that we extract from FineComb.
Sentence 2: we would like to maximize the expected number of packets that are hashed to usefulbuckets, so that we can estimate delay as accurately as pos­sible.
Relationship: entailment
Domain: Networks
Sentence 1: The reason for this is that a high-performance DTN can overwhelm the slower wide area link causing packet loss.
Sentence 2: the set of applications that run on a DTN is typically limited to parallel data transfer applications like GridFTP or FDT.17 user-agent applications associated with general-purpose computing and business productivity (e.g., email clients, document editors, media players) are not installed.
Relationship: entailment
Domain: Networks
Sentence 1: Our proposed system, ISPY, exploits a key observation about IP pre.x hijacking: due to the rich connectivity of the ASes in the Internet, a pre.x hijack almost always pollutes a signi.cant percentage of the ASes, i.e., those ASes will route any packet destined to the hijacked pre.x to the attacker s network, as opposed to the victim s network.
Sentence 2: when a pre.x hijack is ongoing, the victim s network will experience failure in probing a large number of networks, as the probe reply will be routed to the attacker s network.
Relationship: entailment
Domain: Networks
Sentence 1: In the late 1990s, a larger series of projects from various parts of the world further addressed key issues related to stratospheric telecommunications, including the design of efficient wireless communications systems, the study of radio propagation and potential interference with terrestrial and satellite systems and the development of modular communication payloads.
Sentence 2: among the multiple initiatives, European projects FP5 HeliNet [4] and FP6 CAPANINA [5] addressed these issues through the investigation of the means for HAPs to deliver broadband services.
Relationship: entailment
Domain: Networks
Sentence 1: In the .rst set of experiments, we aim to achieve the min­imum live latencies in both the server push and no push cases.
Sentence 2: since segment duration is the major source of live latency, we con.gure it as a small number (i.e., 1 sec) in both cases, and we compare the two cases in terms of the live latency and the request overhead (i.e., request rate).
Relationship: entailment
Domain: Networks
Sentence 1: Identifying Persistent Items Over a Fixed Window: Devise a space-e.cient algorithm that takes as input a prespeci.ed window W = S1 n and a persistence thresh­old a, and at the end of observing the stream, returns the set of all items that are a-persistent.
Sentence 2: the algorithm will report every item that is a-persistent in W and will not report any item that is not a-persistent.
Relationship: entailment
Domain: Networks
Sentence 1: {vj | ij (t) }, and a subset of the =Øedges Ei(t)={ejk(t)|vj ,vk .V i(t)}.
Sentence 2: we de.ne the subgraph Ci(t)=G(Vi(t),Ei(t))as the component within which vertex vi lies at time t. the component Ci(t)is the graph representing the portion of the network that vehicle ican reach via multi-hop communication at time t. The size of the component, Si(t)= IVi(t)I, is the number of nodes that belong to it.
Relationship: entailment
Domain: Networks
Sentence 1: (k1,k3,k2), but P.(k1,k2,k3)= P.(k3,k2,k1).
Sentence 2: in the following .gure, we illustrate properties Pd, d = 0,..., 4, calculated for a given graph G of size 4, where for simplicity, values of all distributions P are the total numbers of corresponding subgraphs, i.e., P (2, 3) = 2 means Generalizing, we de.ne the dK-distributions to be degree correlations within non-isomorphic simple connected subgra­phs of size d and the dK-series Pd to be the series of prop­erties constraining the graph s dK-distribution to the same form as in a given graph G. Pd tells us how groups of d-nodes with degrees k1, ..., kd interconnect.
Relationship: entailment
Domain: Networks
Sentence 1: EVOLVING DYNAMICS OF IPV4 AND IPV6 INFRASTRUCTURE Continuing to explore our hypothesis that a maturing IPv6 network should look more like the IPv4 network, we compare the evolution of routing dynamics in IPv4 and IPv6.
Sentence 2: we focus on the evolution of update churn, correlation between the update churn seen from dif­ferent vantage points, path exploration, and convergence times in IPv4 and IPv6.
Relationship: entailment
Domain: Networks
Sentence 1: In order to solve such a problem and make the TEMP IP solution more reliable, in Section 3.3 we introduced a new approach based on the SIP presence model for determining the correct TEMP IP.
Sentence 2: with the help of other STAs we are able to .nd a TEMP IP with no time constraints without adding to the total handoff time and therefore reducing to zero the risk of having a duplicate IP address.
Relationship: entailment
Domain: Networks
Sentence 1: In this paper, we try to bridge this gap by introducing a fully distributed, randomized protocol called TWIN for building a dominating set in logarithmic time, w.h.p.1, in a wireless multi-hop network based on more realistic radio propagation and interference models with respect to those commonly usedin thedistributed algorithms community.
Sentence 2: we assume radio wave propagation obeys a cost­based generalization of the log-distance path loss model, which can be used to resemble a close approximation of the well-knownlog-normal shadowing model.
Relationship: entailment
Domain: Networks
Sentence 1: Further, because of 802.11 randomjitters,thetwocollisionsarelikely to have different offsets, i.e.,.1 .= .2.SaythattheAP cancomputethese offsets(asexplained in §5.1), the AP can then .nd a chunk of bits that experience inter­ference in one collision but is interference-free in the other, such aschunk1inFig.
Sentence 2: 2.AZigZagAP usesthischunkto bootstrapits decoder.sincechunk1isinterference-freeinthe .rst collision, the AP can decode it using a standard decoder.
Relationship: entailment
Domain: Networks
Sentence 1: This recovery strategy has extensively been studied in unit disk and quasi unit disk graphs.
Sentence 2: a unit disk graph connects any two nodes if and only if their Euclidean distance is less or equal to a unique sending radius r. the transmission area of each device v is a circle with center v and a unique radius r. The class of quasi unit disk graphs extends the concept of unit disk graphs by allowing a limited variation of the transmission area of each device; it may be of any shape provided that its boundary lies within a minimum and maximum circle while the ratio over the minimum and v maximum circle radii is limited by 2 [1, 16].
Relationship: entailment
Domain: Networks
Sentence 1: To reflect the two main properties of radio irregularity, namely non-isotropic and continuous variation, we adjust the value of path loss models in Equation 1 based on DOI values, resulting in the following formula: Received Signal Strength = Sending Power DOI Adjusted Path Loss + Fading (2) DOI Adjusted Path Loss = Path Loss × Ki (3) Here Ki is a coefficient to represent the difference in path loss in different directions.
Sentence 2: ki is the ith degree coefficient, which is calculated in the following way: .
Relationship: entailment
Domain: Networks
Sentence 1: For example, node Ni will have a distinctive secret key SK(C, Ni ) with node Nj SK(C, N j ), so that Ni cannot decrypt the encrypted messages SK(C, N j )[MSG] of Nj, vice versa.
Sentence 2: when a secret key becomes a unique evidence for a specified entity, the unique secret key also acts as a means of authentication.
Relationship: entailment
Domain: Networks
Sentence 1: Types of operations: We subject Maple to 3 types of operations: (1) augments, where Maple evaluates a policy, augments the trace tree, generates .ow table updates, and installs the updates at switches; (2) lookups, where Maple handles a packet by looking up the cached answer in the trace tree; and (3) invalidations, where Maple inval­idates part of the trace tree and deletes rules generated for those subtrees.
Sentence 2: we evaluate host invalidations, which are caused by host mobility and remove all leaf nodes related to a moved host, and port invalidations, which support topology up­dates and remove any leaf node whose action uses a given port.
Relationship: entailment