sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: In the case where all the .ows have a common RTT or have a small RTT di.erence, VCP achieves a near-even dis­tribution of the capacity among the competing .ows (refer to Figure 8).
Sentence 2: when the .ows have signi.cantly di.er­ent RTTs, VCP does not distribute the bandwidth fairly be­tween the .ows that have huge RTT variation (with through­put ratio of up to 5).
Relationship: contrasting
Domain: Networks
Sentence 1: DTHR2 can improve the throughput performance with re­ spect to DT, for example in Scenarios 2 and 3.
Sentence 2: qMFLC outperforms the other schemes in Scenarios 1 and 2, we neither believe nor expect that this is true for all pos­ sible scenarios; for example, if the direct link S D is much stronger than the rest, we expect DT to do best; and if this link essentially does not exist (e.ectively creating a line net­ work as seen in Scenario 3) DFLS (i.e., routing) does better than all others schemes.
Relationship: contrasting
Domain: Networks
Sentence 1: First, for the ISM band case, none of the access points interfered with each other, while for the DTV whitespaces, several access points interfered with each other, with the number of neighbors as high as 4 in some cases.
Sentence 2: the spectral ef.ciency in the whitespaces (typi­cally > 2.5) is much higher than the spectral ef.ciency in the ISM band (typically close to 1).
Relationship: contrasting
Domain: Networks
Sentence 1: Storm s Overnet Protocol: Storm bots connected to the Over­net network used the same ID space, message types, and seman­tics as the other clients, and earlier version of the Storm was con­nected with Overnet, which has been used for old eDonkey clients.
Sentence 2: after Storm started encrypting traf.c using the Vigenère cipher, it has been disconnected from Overnet, forming a sepa­rate network.
Relationship: contrasting
Domain: Networks
Sentence 1: [2] are one ofthe .rsttohighlightthe challenges of independentWLANscoexistence.UsingdatafromexistingWLAN deployments, they study the impact of interference on client per­formance.In[5],Ergin etal.provide experimental and simulation results of similar unplanned WLANdeployments.
Sentence 2: they assume a single collision domain for all the WLANs and do not capturethe unfairnessthat arises over multiple collisiondomains.
Relationship: contrasting
Domain: Networks
Sentence 1: If a Trigger Point is met, S-CSCF sends the request to the AS associated with the Trigger Point to invoke it; on receiving the response from the AS, S-CSCF starts to evaluate the next iFC, until all iFCs are finished evaluating.
Sentence 2: this service invocation mechanism, which is based on sequential evaluation of iFCs, has not clarified the detailed implementation mechanism for integrated services, which concerns multiple service capabilities that are correlated with each other.
Relationship: contrasting
Domain: Networks
Sentence 1: While the above-mentioned report advocates the use of PBR in vehicular highway scenarios, it does not answer the question of how the beaconing interval should be set.
Sentence 2: it indicates the trade-off between a low beaconing interval resulting in high position accuracy at the expense of high network load and a high beaconing interval saving network load, but leading to an unclear picture of the neighborhood.
Relationship: contrasting
Domain: Networks
Sentence 1: With paid peering determined by Nash bargaining solution, it is preferred by both ISPs with peering of low level and medium level.
Sentence 2: the peering of high level still has much uncertainfactors causedby free-riding.We also proposed a regime equilibria analysis with BNE theory, ., and ch cAB = ., which is of the low level, we can get the = ..
Relationship: contrasting
Domain: Networks
Sentence 1: i.e., 1(622 - 64)/15l =38 hosts, in the proposed ESnet, Proposed ESnet Topology; Poisson Sources; At LANL Router TCP congestion-control really kicks in and adversely mod­ 1 ulates the application traf.c.
Sentence 2: over this proposed 0.9 ESnet, the adverse modulation by TCP is even more pro­nounced than in the current ESnet, i.e., the measured c.o.v.
Relationship: contrasting
Domain: Networks
Sentence 1: While the top plot in that figure shows the traffic rate process (all TCP) over the whole measurement period (i.e., 48 observation periods), the middle plot states that periods 23 and 31 have been identified as interesting by WIND.
Sentence 2: upon closer inspection, the fact that the energy function corresponding to period 31 is almost flat turns out to be an artifact of the very low traffic load dur­ing this period (see top plot).
Relationship: contrasting
Domain: Networks
Sentence 1: If this is the case,thenthepeer cannot now(i.e.in round t)receive any unit c t-k such that t -k+m = t +1 or k = m -1.
Sentence 2: re2 entails precisely that when we reach any round m = t = T + m all peers who still have not received unit c t-m arematched with the otherhalfofthepopulation, so to ultimately receive such a unit, that will no longer be distributed throughout the whole streaming.
Relationship: contrasting
Domain: Networks
Sentence 1: Us­ing either rule-based or machine learning based approaches [1, 2], application classes are commonly attributed to .ow records on the basis of the reported TCP/UDP port numbers, sometimes in con­junction with traf.c features such as total packets, bytes, duration, or combinations thereof.
Sentence 2: the performance of such ap­proaches often degrades when these .ow measurements are either inaccurate or incomplete.
Relationship: contrasting
Domain: Networks
Sentence 1: Additionally, it is di.cult to guarantee distinct per-QVPN delay violation probabilities with EDF due to strong interactions among QVPNs sharing a link.
Sentence 2: rate-based schedulers, such as the one we use, provide explicit performance isola­tion among QVPNs and are especially suited to guarantee QVPN-speci.c delay violation probabilities.
Relationship: contrasting
Domain: Networks
Sentence 1: The probe rate model (PRM) is based on the concept of self-induced congestion; informally, if one sends probe tra.c at a rate lower than the available bandwidth along the path, then the arrival rate of probe tra.c at the receiver will match their rate at the sender.
Sentence 2: if the probe tra.c is sent at a rate higher than the available bandwidth, then queues will build up inside the network and the probe tra.c will be delayed.
Relationship: contrasting
Domain: Networks
Sentence 1: The price goes up with more CPU sockets: $87 in a dual-socket machine7 and $183 in a quad-socket machine8.
Sentence 2: installing a cheap GPU (the price ranges from $50 to 6$240 per Core i7 920 processor (2.66 GHz, 4 cores) 7$925 per Xeon X5550 processor (2.66 GHz, 4 cores) 8$2190 per Xeon E7540 processor (2.00 GHz, 6 cores) $500) into a free PCIe slot does not require extra cost.
Relationship: contrasting
Domain: Networks
Sentence 1: In practice, localization using NLOS radio signals could be inaccurate, such as at X; con­sequently, di may not indicate the magnitude of the error in ri .
Sentence 2: as can be seen from Figure 1(a), di of some (or all) beacons should be associated with di >.i, since the signal propagation circles cannot intersect at a point.
Relationship: contrasting
Domain: Networks
Sentence 1: We have E(k(t)) = t · E(p, rT ) and V ar(k(t)) = t · V ar(p, rT ) .
Sentence 2: lemma 4 is scarcely useful in estimating P ro­b(Start(d,¯t¯)), since it gives little information on how close random variable k(t) is to its expected value.
Relationship: contrasting
Domain: Networks
Sentence 1: INTRODUCTION With advances in wireless communication and wide spread of multimedia applications, there is a growing need to provide quality of service (QoS) support to multimedia traffic in wireless networks.
Sentence 2: qoS provision in wireless LANs is a challenging task due to the varying wireless channel bandwidth which is determined by the number of users in the network, the users mobility, channel interference and physical layer auto-rate adaptation (e.g., IEEE 802.11a/b/g [3, 4, 5] which support multiple modulation schemes).
Relationship: contrasting
Domain: Networks
Sentence 1: of Technology Carnegie Mellon University ABSTRACT Using entropy of tra.c distributions has been shown to aid a wide variety of network monitoring applications such as anomaly detection, clustering to reveal interesting patterns, and tra.c classi.cation.
Sentence 2: realizing this potential bene.t in practice requires accurate algorithms that can op­erate on high-speed links, with low CPU and memory re­quirements.
Relationship: contrasting
Domain: Networks
Sentence 1: With more than two IDSs we can also analyze the the majority rule, which can initially be thought to be the operating point in the LRT ensemble that minimizes the expected cost function for t greater than any likelihood with a minority of alarms and smaller than any likelihood with a majority of alarms (max {l(001),l(010),l(100)} <t< min {l(011),l(101),l(110)}).
Sentence 2: the partial order shown in Figure 6(b) shows that in this case the above equation might not always hold.
Relationship: contrasting
Domain: Networks
Sentence 1: For example, if a user requests a video transcoding + face recognition service, the service compo­sition layer will check if there exist instances of video transcoding and face recognition services, such that the output media format of the former can be accepted by the latter.
Sentence 2: if all face recognition services can only accept the input media format of the transcoding service, the service composition layer may suggest the user to switch the order between the two services.
Relationship: contrasting
Domain: Networks
Sentence 1: In state of the art models, if a node has started with low energy, or has lost a large portion of its battery re­serves during multiple transmissions, it still has to abide by the general rule that is identical for all nodes.
Sentence 2: it is of importance to the network how the aggregate remaining energy is distributed among nodes, as nodes with critically low remaining energy will compromise the long-run perfor­mance of the network.
Relationship: contrasting
Domain: Networks
Sentence 1: This illustrates the trade o. between sampling rate and classi.cation speed.
Sentence 2: we choose to operate at a point in the design space that increases the true positive rate at the expense of being less accurate in the detection of non-conversation because the cost, from a user s perspective, of being wrong when detect­ing a conversation is larger than the cost of being wrong when detecting non-conversation.
Relationship: contrasting
Domain: Networks
Sentence 1: IP Packet Distribution on Wireless Access Route Combining IEEE802.11/802.16 Links for Improvement of Application Performance Yasuhisa Takizawa Faculty of Environmental and Urban Engineering, Kansai University Osaka, Japan takizawa@kansai-u.ac.jp ABSTRACT The expansion and diversi.cation of wireless communication are proceeding rapidly with the di.usion of cellular phones, WiFi and WiMAX.
Sentence 2: concern is increasing that the growth of wireless systems will exhaust .nite wireless re­sources.
Relationship: contrasting
Domain: Networks
Sentence 1: Notice that in [5, 10] an ~2((d2/log d) log n) lower bound is proved.
Sentence 2: in what follows, we describe the protocol MULTI-BROAD-A(n,d): It assumes that nodes know the maximum in-degree d and 260 the network size n. when d and/or n are not known, we can adopt the same dovetail technique introduced in [10].
Relationship: contrasting
Domain: Networks
Sentence 1: Therefore, irre­spective of channel width, modulation 24 OFDM coding (24 Mbps at 20 MHz using 16-QAM, 1/2 rate encoder) carries the same 96 data bits per symbol.
Sentence 2: since symbol lengths are different across channel widths, modulation 24 coding scheme gives 6 Mbps at 5 MHz, 12 Mbps at 10 MHz, 24 Mbps at 20 MHz, and 48 Mbps at 40 MHz.
Relationship: contrasting
Domain: Networks
Sentence 1: Given the real­time capability of the underlying simulation engine (QualNet or equivalence), we can replace anyLN(any connected subgraph of a reasonable size in the entire network topology) with an equivalent SVNrunning on the simulation engine at real time, or vice versa.
Sentence 2: for wireless networks, due to node mobility and wire­less signal propagation, two neighboring SVNs may have to ex­change environmental discrete simulation events(inparticular,node mobility and wireless signal propagation events) to deliver correct simulation results.
Relationship: contrasting
Domain: Networks
Sentence 1: As we require, for ex­ample, O(n log3 n) random walks executed in parallel, where each random walk traverses O(log4 n) nodes, we get that in the worst case a single node needs to handle O(n log3 n) tokens given that all random walks traversed this node.
Sentence 2: when the graph is a good expander, we argue that the probability of such an event is rather negligible.
Relationship: contrasting
Domain: Networks
Sentence 1: )r. (9) Knowing that the most e.cient route a message can take from a node to the BS is the one along the direction axis with equidistant hops of distances dchar, the minimum energy rate Plink-min that can be achieved is given as: ' Plink-min(D)= Kopt · Prelay(dchar), (10) where D is the total distance to the BS.
Sentence 2: in a ran­domly deployed sensor network, the power consumed in a link of distance D ' = D with intervening nodes deviating from the direction axis can be formulated as: K ' Plink(D )= K Prelay(ci · dchar).
Relationship: contrasting
Domain: Networks
Sentence 1: Because feature information is represented by a much smaller amount of data, it is possible to actually transmit the feature information of the received frame sequence back to the sender, which can then compare it to that of the original video and evaluate its quality.
Sentence 2: such a solution is still inadequate for our purpose, not only because it requires modifying the video client to perform fea­ture extraction, but more important because we need to estimate the quality of video transmission over multiple paths in parallel.
Relationship: contrasting
Domain: Networks
Sentence 1: In the case where k =1, the d-hop k-datacoveragequeryis similar to .nding a d-hop dominating set in wireless ad hoc net­works[2];however,thereare substantialdi.erencesamong the two problems.
Sentence 2: [2] proposed a heuristic that can handle only the maximization of one dimension, i.e., of the sensor ID.DaCoNhandlesdata ofthe sensor andthere­fore it is able to handle multidimensional values of di.erent semantics (maximization, minimization or combination of them, etc).
Relationship: contrasting
Domain: Networks
Sentence 1: This is manifested by the reducing gap between the two curves, demonstrating the reduced power of recalibrating the NetFlow estimate by the noisy SNMP link loads.
Sentence 2: we .nd that once the SNMP mea­surement is not extremely distorted (e.g., a = 0.05), our scheme always has an observable improvement in comparison to raw Net-Flow traf.c matrix (the horizontal line in Figure 3(b)).
Relationship: contrasting
Domain: Networks
Sentence 1: There are other such con.gurations, for example, com­plete subgraphs (cliques), odd cycles, etc.
Sentence 2: a complete char­acterization of these forbidden subgraphs is not possible.6 the key point is to note that the ILP constraints in Table 2 are both necessary and su.cient for any net­work graph.
Relationship: contrasting
Domain: Networks
Sentence 1: For example, in IEEE 802.11b (operates in the unlicensed ISM band at 2.4 GHz) though there are 14 channels available, due to inter-channel inter­ference, only 3 of them (1, 6 and 11) can be considered to be non-overlapping [9].
Sentence 2: often a denser de­ployment of AP s is required for increasing the capacity and coverage of the W LAN s. Thus when more and more AP s are installed in a relatively small geographic area, the cov­erage areas of the AP s are likely to overlap causing the co­channel interference.
Relationship: contrasting
Domain: Networks
Sentence 1: 3.2 Trust-aware Routing Protocol As soon as the candidate selection procedure is done ac­cording to the above-mentioned algorithm, the source node starts sending data packets towards the destination and can­didate nodes will be responsible to cooperatively forward packets to reach the destination.
Sentence 2: it should be no­ticed that there may also be some nodes in the network which act as uncooperative nodes and decide to sel.shly or maliciously attack the system, for example, by dropping re­ceived data packets.
Relationship: contrasting
Domain: Networks
Sentence 1: Mitigating starvation in Wireless Ad hoc Networks: Multi-channel MAC and Power Control Duc Ngoc Minh Dang Department of Computer Engineering Kyung Hee University, Korea dnmduc@khu.ac.kr  Phuong Luu Vo Department of Computer Engineering Kyung Hee University, Korea phuongvo@khu.ac.kr Choong Seon Hong Department of Computer Engineering Kyung Hee University, Korea cshong@khu.ac.kr Chi Kwang Hwang Department of Computer Engineering Kyung Hee University, Korea chikwang16@khu.ac.kr ABSTRACT The IEEE 802.11 DCF (Distributed Coordination Function) is based on CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance).
Sentence 2: the CSMA-based random access protocol can cause serious unfairness or .ow starva­tion.
Relationship: contrasting
Domain: Networks
Sentence 1: Since there is no subscriber in D3 (Group(CD)= null), RP3 will not send an IP multicast packet.
Sentence 2: it will send the COPSS Multicast packet downstream (through B324 and B43 to RP4) according to the ST. At the same time, RP3 encapsulates the packet into an Interest using RN(CD), i.e., RP1, and forwards it accord­ing to the FIB.
Relationship: contrasting
Domain: Networks
Sentence 1: Recently researchers have explored mechanisms that assign .ne grained spectrum blocks on the basis of traf.c demands.
Sentence 2: most of these mechanisms, such as DSAP [7], Jello [15], SWIFT [22], WhiteFi [6] and DIMSUMnet [17] are designed for non-802.11 systems and focus on deriving elegant algorithms for spectrum allocation that are primarily evaluated using network simulations or small-scale prototype implementation on software de.ned radios.
Relationship: contrasting
Domain: Networks
Sentence 1: The intuition behind this algorithm is the following: Ideally, during the short sequence a sample s[n] should correspond to the sample s[n + 16] due to its cyclic property.
Sentence 2: if noise and a frequency o.set are introduced, this is no longer the case, and s[n] s[n + 16] is not a real number, as in the idealized case.
Relationship: contrasting
Domain: Networks
Sentence 1: Hence, instead of mapping an FQDN to a location­dependent identi.er to an IP address with DNS, the resolu­tion system maps the authority .eld to the public key (or 2Of course, there may be additional .elds within the author­ity .eld.
Sentence 2: as they are not commonly used and not essential for the current discussion, we ignore them in the rest of this paper.
Relationship: contrasting
Domain: Networks
Sentence 1: However, this will also require a mechanism for detecting when partitions merge, and each ARPrequest will have to be .ooded through the entire ad hoc network (since the network is now considered to be a single link for ARPpurposes).
Sentence 2: the proposed Weak DAD scheme behaves similar to the scheme in [3] in that both may delay duplicate detection until it becomes necessary to ensure correct behavior.
Relationship: contrasting
Domain: Networks
Sentence 1: ForHSDPA,85% of thepackets havelowerdelays compared toUMTSdue to thefaster retransmis­sion mechanism.
Sentence 2: the other15% of thepackets have even longerdelays thanUMTS.This resultisdue to thefact thatUMTS has .xed errorrateswhichleadstomorestableperformance,while HSDPAchannel variancehas strong effect on the end-to-enddelay.
Relationship: contrasting
Domain: Networks
Sentence 1: In particular, since the quality of the original scal­able stream Sin is higher than the quality of the down­transcaled stream Sout over the range [Rmin_in , Rmax_in], then it should be clear that clients with access bandwidth that falls within this range can benefit from the higher quality (original) scalable stream Sin.
Sentence 2: clients with access bandwidth less than the original base­layer bitrate Rmin_in, can only use the down-transcaled bit­stream.
Relationship: contrasting
Domain: Networks
Sentence 1: We are inter­ested in the problem of Constrained Hierarchical Aggregate Classi.cation: Under the weight balance constraint, among 5Note that in this simple example, s1 can send the numbers of 1s and 0s picked by its children (together with itself) to achieve better consensus compared with sending the majority voting result only.
Sentence 2: this solution cannot work for the decision aggregation problem where only clustering results are available.
Relationship: contrasting
Domain: Networks
Sentence 1: We also compare with WiT­ Maximum Available Power (W) 5 2000M based on their speci.cation sheet.
Sentence 2: we cannot com­ pare with the UW prototype since [29, 30] do not provide informa­ tion about how they address orientation for phone charging.9 4 We note that since the compared schemes do not support the same distance, we could not .x one distance and compare all schemes.
Relationship: contrasting
Domain: Networks
Sentence 1: Note that it has already been shown that the Max-Weight is throughput optimal for time-varying channels [23] and joint scheduling and conges­tion control algorithms based on the optimization decomp o­sition, e.g., [2], are utility optimal by selecting the schedules over time, both of which essentially track the channel con­ditions quickly.
Sentence 2: a similar channel adaptation for CSMA algorithms may not be feasible for the following two reasons.
Relationship: contrasting
Domain: Networks
Sentence 1: Note that the TTL-limited and tailgat­ingprobepackets mostly obtainpacketdelay and delay variation, whereasthepacketpairand train mostly ob­tain packet dispersion.
Sentence 2: tRIO uses packet pairstoobtaindelayvariationfor computing asymmet­ric capacity of a round-trip path and does not over­whelm the bottleneck link.
Relationship: contrasting
Domain: Networks
Sentence 1: 5.1 Linear Predictors Moving Average (MA): Given a time series X,the one­step n-order MA (n-MA)predictor is: i X 1 Xi+1 = Xk n k=i-n+1 where Xi is the predicted value and Xi is the actual (ob­served) value at time i.If n is too small, the predictor can­not smooth out the noise in the underlying measurements.
Sentence 2: if n is too large the predictor cannot aptly adapt to non-stationarities (e.g., level shifts due to load variations or routing changes).
Relationship: contrasting
Domain: Networks
Sentence 1: @chalmers.se ferrari@tik.ee.ethz.ch zimmerling@tik.ee.ethz.ch ABSTRACT An important building block for low-power wireless systems is to e.ciently share and process data among all devices in a network.
Sentence 2: current approaches typically split such all-to-all interactions into sequential collection, processing, and dissemination phases, thus handling them ine.ciently.
Relationship: contrasting
Domain: Networks
Sentence 1: A number of mechanisms has been de­signed in the literature (e.g., [6, 22, 24]) for soliciting the truthful cost declaration from sel.sh agents so that a certain optimal routing structure could be built to connect the source node and destination node(s).
Sentence 2: several results (e.g., [9,11,19,25]) con­centrated on ensuring that intermediate nodes will indeed forward the data packets.
Relationship: contrasting