sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: Design and Implementation of a Framework for Persistent Identi.cation and Communication in Emerging Networks * Joud S. Khoury Henry Jerez Luca De Cicco jkhoury@ece.unm.edu hjerez@cnri.reston.va.us ldecicco@gmail.com ABSTRACT The Internet Protocol (IP) is currently used to provide inter­networking among heterogeneous access networks.
Sentence 2: the evolution of and the innovation within these networks is greatly hindered by the geographical and topological rigid­ness of the protocol implementation that hinders the sup­port for .exible unstructured communication paradigms.
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Domain: Networks
Sentence 1: The decreases in the loss window size is slight congestion has occurred in the network, and the given by loss window size is decreased by approximately (1-()× cwnd = { dwnd (where 0 <( < 1).
Sentence 2: when a packet cwnd (duplicateACKpackets) loss is detected by means of a timeout, it is concluded 2 (1) that serious congestion has occurred in the network, and 1.
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Domain: Networks
Sentence 1: Such new metrics can, in principle, be used with any detector that learns their normal trend from time series data and .ags bins which deviate from that trend.
Sentence 2: we develop a new method which is fundamentally di.erent from time series approaches used by Kalman [26], Wavelet [2], or PCA [13], because it does not require training from normal tra.c data, and thus is immune to data-poisoning.
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Domain: Networks
Sentence 1: Table 6 shows the duty cycle of ZiSense is 5.14%, which is just 22.1% larger than the of.ce environment.
Sentence 2: comparing with the of.ce environment, the serious interference leads to 100.7%, 125.2% and 141.7% more energy consumption for BoX-MAC-2, AEDP and A-MAC separately.
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Domain: Networks
Sentence 1: Interoperability: The user agent will need to support redirection and not change the Contact header re­ceived from the anycast servers.
Sentence 2: it is often the case that SIP clients do not support redirection due to poor implementation or for policy reasons as redirection could be used for fraud when a user is lured to call a free number but then gets directed to a costly number for example.
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Domain: Networks
Sentence 1: For low-distance threshold val­ues (5 meters), we see that the external adversary has a TPR comparable to the case where no community infor­mation is extracted (for most weight functions).
Sentence 2: the FPR values are signi.cantly di.erent: The false-positive rate for friends and classmates relationships is three to four times lower when using community structure than when not.
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Domain: Networks
Sentence 1: The alternate approach like Content Distribution Net­work (CDN) is also widely studied and deployed in the current Internet services (e.g., Akamai, Limelight) [13, 16].
Sentence 2: due to lacking of collaboration of multi­ple CDN service providers, CDN approach has limita­tion on how to place their services and contents to sup­port users [5].
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Domain: Networks
Sentence 1: Figures 2(a) and 2(b) show perfectly posi­tively correlated link pairs for two different cases; when both the links have same PRR and when they have different PRRs.
Sentence 2: if the second link s transmissions that fail are a subset of transmissions that succeed on the .rst link, then a node maximizes the chances of every packet making progress.
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Domain: Networks
Sentence 1: (u)-(u)]+ sup0=u=s[A2 .ß2(u) -A2* (u)] .
Sentence 2: if we want to prove the concatenation property for weak stochastic ser­vice curve, we need to prove [(A1 .ß1) .ß2(s) -A2* (s)] = [A1 .ß1(s) -A1* (s)] + [A2 .ß2(s) -A2* (s)] for all s =0, which is di.cult to obtain and does not hold in general.
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Domain: Networks
Sentence 1: This resource planning at .rst glance may seem similartotheplanningthatwasperformedinproviding plain old telephony services(POTS) with resources(phone circuits) statistically shared by multiple users.
Sentence 2: in this network the number of users is smaller and the cost of alineisfargreater, making accurateplanningfar more crit­ical.
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Domain: Networks
Sentence 1: We see that  Table 2: Ef.Cuts Average Memory Reduction over HyperCuts as the classi.er size increases within each classi.er type (ACL, FW, or IPC), HiCuts and HyperCuts memory requirements grow quickly (the Y axis is log scale) and vary widely across classi.er types.
Sentence 2: ef.Cuts memory requirements are almost con­stant across classi.er types and sizes.
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Domain: Networks
Sentence 1: The DTLS approach ex­hibits an overall larger memory footprint because DTLS (i) involves more messages than HIP and (ii) requires SHA2 while HIP-PSK only uses AES-CMAC.
Sentence 2: for key management, HIP adds slightly more overhead, as it requires the de.nition and handling of new parameter types whereas in DTLS the required information can simply be carried in the payload.
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Domain: Networks
Sentence 1: Anysendthatexeedsthehandler'slaneallowaneis fagged.Thehekisroughly220linesofode.Muhof thisodedealswithprintingoutpreisetextual.bak traes"fortheinter­proeduralpaththatausedthe problempathlengthandbranhingomplexitymake thisfeatureruialfordiagnosingerrors.
Sentence 2: forstraight­lineodewithoutfuntionpointers,this extensionisonservativeandsound:whilethereexist orrethandlersitwouldrejet,anyhandlerthatsatis­fesitannotexeeditsbuferquota.Mosthandlersft thismodel,andareaepted.thereareafew handlersthatuseloopsorreursion.Cylesreateprob­lemsforstatianalysissine,ingeneral,itisimpossible todeterminehowmanyiterationsayleanause.
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Domain: Networks
Sentence 1: When the bottle­neck queue is 8 packets, the packet loss ratio is about 2.0% and FS-ATs can get more throughput than Reno,because of the retransmission control of FS-ATs; however, FS-AT loses the throughput when there are enough queue in the bottle­neck nodes.
Sentence 2: fS-ATmax can maintain the fairness between Reno.
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Domain: Networks
Sentence 1: FQandStopItperform exactlythe same,becauseinthese collud­ing attacks,theyboth resorttoper-senderfairqueuing toprotecta legitimate user s traf.c.
Sentence 2: unexpectedly, we note that they provide legitimate users less throughput than attackers even when the user traf.c is long-running TCP.
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Domain: Networks
Sentence 1: The simulation of the radio propagation is based on theoretical data and validated with empirical mea­sures, and it does not need to know the exact location of the buildings since it approximates them by using the streets width.
Sentence 2: unlike our proposal, the CORNER algo­rithm implies very complex calculations and it is only valid for Manhattan-based topologies where the streets are ar­ranged orthogonally.
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Domain: Networks
Sentence 1: Indeed, suppose that one of the honest stations switches from wh to ws, its bandwidth share becoming bs(N, xNE(R) + 1).
Sentence 2: by (14) and (15), its perceived bandwidth share then becomes bC, meaning a payoff decrease: the station now obtains a less-than-required bandwidth share "in exchange for" increased power expenditure.
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Domain: Networks
Sentence 1: Forthemidandlong-rangeradios,bothofwhichsavedenergylocally,compressingwiththeS-LZW-MC16-BWTalgorithmsavesanaverageof9.9%moreenergyateachhopthanS-LZW-MC32andanaveragefactorof2.04Xoverall.
Sentence 2: 5.2 Replacing BWT in Structured Datasets Tothispoint,wehaveassumedthatweknowverylittleaboutthedatawearetryingtocompress.ifwecanidentifyasimple,reversiblewaytoreorderthedata,wecouldsurpassthegainsobtainedwithBWTatareduceden­ergycost.
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Domain: Networks
Sentence 1: The server sends the .rst couple tens of seconds of video as fast as possible, then it rate-limits the transfer based on the video encoding rate to minimize wasted network capacity if a user cancels the rest of the video.
Sentence 2: for most video downloaded in In­dia, there is little or no di.erence between the throttled and un-throttled data rates because there is little or no surplus network capacity above the video encoding rate.
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Domain: Networks
Sentence 1: We note that their analysis only con­sider links secured by preloaded keys, and hence the fraction of  6.2 Connectivity As shown in Section 2.1, RKP and SRKP require high density deployments to ensure the entire sensor network is securely con­nected with high probability.
Sentence 2: gKE ensures that any two neighboring sensors are able to establish a path key, regardless of the sensor density or distribution, as long as the sensor network is physically connected.
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Domain: Networks
Sentence 1: Thus, even though Tree Bitmap guarantees O(1) route-update cost, in the worst case its memory management scheme can add an over­head of more than 100 memory accesses to any route-update due to compaction operations.
Sentence 2: we use only 1-bit trie nodes without compression, ensuring that all nodes have the same size across all levels and all stages.
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Domain: Networks
Sentence 1: We have chosen it because it has been used in many previous routing studies (for example, [11, 12]), it is used in capacity planning decisions by ISPs, and it may well be correlated with other metrics of interest, such as loss rate.
Sentence 2: we also believe that the techniques we have introduced here can be extended to incorporate other relevant performance metrics, such as end-to-end delay.
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Domain: Networks
Sentence 1: In Figure 4, the first mutation takes effect in router S. Therefore, the bulk transfer changes the path from S to router 4 instead of going trough the congested router 1.
Sentence 2: we think that a single mutation on the first router before the congested router is not enough, because of the possibility that the router 4 would choose the router 1 as the next hop.
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Domain: Networks
Sentence 1: Our discussion so far has implicitly as­sumed router-level redundancy, i.e., that the code running in par­allel would be the operating system and entire protocol suite of a single router.
Sentence 2: our architecture also enables two ad­ditional forms of redundancy: network-level redundancy, where entire virtual networks are run in parallel, and process-level re­dundancy, where individual routing processes and threads running inside a router implementation are replicated.
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Domain: Networks
Sentence 1: The receiver-oriented orchestration of transmissions de­sired for MPR can be accomplished using contention-based or scheduling approaches.
Sentence 2: we advocate a design consisting of establishing transmission schedules by means of distributed elections of the information .ows that should be o.ered to the channel during the time slots of the sched­ule, together with opportunistic reservations of time slots after they are acquired through election.
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Domain: Networks
Sentence 1: Joe et al proposed to use tra.c class to estimate the en­ergy consumption for prediction of mobile terminal lifetime in available networks [3].
Sentence 2: the experiments we per­formed for this paper suggest that more .ne-grained esti­mation of tra.c is necessary due to the large di.erences between tra.c load inside each tra.c class, as discussed in Section 4.3.
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Domain: Networks
Sentence 1: When a packet is lost or the length of the queue is more then limit L, the probability pm is incremented.
Sentence 2: when the link is idle or the queue is empty the probability is decre­ 10 0 1.0Mbps 1.5Mbps 2.0Mbps 2.5Mbps 3.0Mbps 3.5Mbps Speed of the link Figure 4: Average Queue in AVQW experiments setting differ­ent link speed mented.
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Domain: Networks
Sentence 1: More formally, we want to maximize: a* TB a* TB log( ) + log(min ( ,(1 - a) * TA,B)) 2 2 Due to space constraints, we refer readers to [4] for de­tailed derivation of the optimal a.
Sentence 2: we show that either a =0.5 or a= 2TA,B/(TB +2TA,B), so the optimal ais the one that maximizes the throughput.
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Domain: Networks
Sentence 1: RC(u, i), once that rank for all next-hop nodes that have paths to d becomes equal to or greater than the number of credits assigned for that batch at 350 that node, the node distributes its credits to next-hop nodes in a fashion similar to Algorithm 1.
Sentence 2: this time the 300 node only focuses on one session i, and the credits that are assigned are real not virtual credits.
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Domain: Networks
Sentence 1: Indeed, while the forwarding rate reported in recent virtual router work (e.g., the rate for minimum-sized packets of roughly 700kpps in [6] or [7]) is signi.cantly better than that origi­nally achieved in VINI [5], it is still rather low for practical applications in a real network.
Sentence 2: on many occasions over the last few years, we have heard people assert that for routers to go fast, they would need dedicated forwarding hardware, with the various camps pushing the case for Network Processors, FPGAs, and various forms of of.oad engines; usually such pitches include graphs showing the sorry state of software forwarding.
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Domain: Networks
Sentence 1: Consequently, if exponential (and Weibull) distribu­tions are close, but imperfect, models of user behavior, they might be accepted with a small number of data points but rejected when we supply a large number of data points (i.e., enough data points for the test to detect the di.erence).
Sentence 2: the di.erence could be to a fundamental di.erence in user behavior between the two datasets.
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Domain: Networks
Sentence 1: Hence it is also hard for cryptanalysts to correlate the route pseudonyms established on top of the cryptographic onions.
Sentence 2: an unbounded eavesdropper can trace on-demand routes by exploring other data .elds in RREQ/RREP packets: (i) RREP packets with the same prdest .eld are likely on the same route.
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Domain: Networks
Sentence 1: Not letting the adversary pick the session ID (which corre­sponds to a replication index in CryptoVerif s process calcu­lus), on the other hand, restricts the adversary s capabilities.
Sentence 2: since the number of sessions is polynomial (in the security parameter), a non-negligible advantage of winning an attack game for a two-phase adversary as in [21] implies a non-negligible advantage for the adversary we described above.
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Domain: Networks
Sentence 1: For this scenario, binary exponential backoff performs worse than the other 95   Summary and Future Work State-of-the-art multiple access protocols for shared chan- nel wireless networks often lack a well-defined notion of fair- ness, and provide somewhat ad hoc mechanisms for achiev- ing fairness among contending flows.
Sentence 2: as shared channel wireless networks move from the academic domain to the commercial domain, these environments must sup-port network-level quality of service and service differen- tiation, which translates to MAC layer weighted fairness.
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Domain: Networks
Sentence 1: This data shuffle pattern arises in large scale sorts, mergesandjoinoperations inthedatacenter.
Sentence 2: wechosethistest because,in our interactionswithapplicationdevelopers, welearned thatmanyuse suchoperations withcaution,becausethe operations arehighlyexpensive intoday sdatacenternetwork.data shuffles are required, and, if data shuffles can be efficiently sup­ported, it could have large impact on the overall algorithmic and data storage strategy.
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Domain: Networks
Sentence 1: Further, since the bene.t of reuse outweighs the diversity gain in static envi­ronments, even CSMA is better than DAS.
Sentence 2: as we vary the number of mobile clients in the network, the per­formance ofbothnetMIMO andCSMA start todegrade;the degradation for netMIMO being especially severe.
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Domain: Networks
Sentence 1: In the proposed scheme, the throughput of femtocells shown in Figure 6 is greatly enhanced because the femtocells interfere less with the macrocell users than in the comparison schemes.
Sentence 2: in the FFR-3 and NoFFR-3 schemes, the sub­carriers are randomly assigned to the femtcells regardless of the sub-carriers used by the macrocell users.
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Domain: Networks
Sentence 1: A THEORY FORMULTI-INSTANCE ROUTING Although a considerable body of research has been devoted to the correctness of routing, most prior work concentrated on the be­haviors of one speci.c routing protocol (e.g., RIP, OSPF, or BGP) at a time.
Sentence 2: this section presents a general framework to study routing properties across multiple routing protocol instances.
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Domain: Networks
Sentence 1: At large loss rates, highly asymmetric loss patterns cause this method to disregard a poten- tially good path because the reverse direction of that path has a high loss rate.
Sentence 2: the benefits of avoiding the high loss rate path seem to outweigh the cost of missing one good link, but we in- tend to remedy this problem soon by explicitly estimating one-way loss rates.
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Domain: Networks
Sentence 1: References values are taken from a ZigBee node im- On the one hand, with CMSA, presented .gures show that the failure anticipation window size has any impact on theprovided networkdysfunctiontime,giventhatit canbe considered as CPMS-NB with a single expected failure win­dow.
Sentence 2: since they use the same heuristic, CPMS-NB and CMSA give the same robot scheduling so­lution and consequently the same network dysfunction time with a small size of expected failures window.
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Domain: Networks
Sentence 1: Note that by ensuring that the next stage PM s tail pointer is always equal to its own head pointer, a PM can guarantee that all the downstream PMs in the pip-eline are accessing blocks of data that do not overlap with its own data window.
Sentence 2: when several PMs work in parallel at a same pipeline stage, their tail pointers must be shared , that is data gets released to all these PMs simultaneously.
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Domain: Networks
Sentence 1: Micciancio and Panjwani [40] con­sidered the case where the adversary adaptively chose the formal messages to be computationally interpreted, the necessary security of the encryption scheme still corresponded to security against pas­sive adversaries.
Sentence 2: we have given a static program anal­ysis [32] and a type system [35] that work directly in the computa­tional model, handling programs containing symmetric encryption.
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Domain: Networks
Sentence 1: Packets were distributed according to their proximity to each AP: in the CY group, Y/T and T/C s packets were generally observed, since they were involved in  Figure 4: Layer-4 TCP/UDP packet ratio compari­ son -CY group (APs-B, C, D) Figure 5: Layer-4 TCP/UDP packet ratio compari­son -Berth group (APs-E, F, G) loading/unloading containers there, meanwhile in the Berth group, Y/T and C/C s packets were generally observed, but we found no more interesting results on layer-4 analysis.
Sentence 2: in the analysis of OSI layer-2, we found more in- teresting results, as shown in Figure 6, which illustrates the MAC frame retransmission ratio.
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Domain: Networks
Sentence 1: The mules in this simulation only positively affected the results, as they have no energy and memory constraints.
Sentence 2: even if all the three simulated approaches have large advantage compared to traditional sensor networking, as they do not rely on the end-to-end connection assumption, the mobility-assisted forwarding require the assistants (the mule in our simulation), while PROSAN comes for free with people mobility.
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Domain: Networks
Sentence 1: To avoid such periodic transmissions from synchronizing with one another, which would result in un­due collisions of signal packets, the neighbor protocol adds random jitters to the interval value between signal packet #Signals n 10 10 1 transmissions.
Sentence 2: because of the randomness of signal packet trans­ missions, it is still possible for a signal sent by a node to 100 100 0 collide with signals sent by some of its two-hop neighbors.
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Domain: Networks
Sentence 1: Equivalent functionality could be obtained if all the cluster resources in the system ran a distributed .le system that supports caching AFS [18], for example.
Sentence 2: given that in a wide-area computing envi­ronment these cluster resources are typically owned by independent entities and operated in di.erent admin­istrative domains, this approach is not always feasible, and operating system-and .le system-independent ap­proaches must be investigated.
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Domain: Networks
Sentence 1: Figure 3 Reactive RO between LMAs 4.5.2 Proactive In the proactive synchronization strategy, a proLMA receives a BU from the MR and sends an ePBU to the priLMA, just as before.
Sentence 2: during the final step when the priLMA sends the (positive) ePBA to the proLMA, the priLMA also sends ePBUs to all the other LMAs in the Extended Home Network.
Relationship: contrasting
Domain: Networks
Sentence 1: [33] empirically established the basic probe size as64KBforthe NetworkWeather Service (NWS).Theyusedthe connection pair to predict the throughput of data transfer on NWS and focused on only the connection pair where the probe size was 64 KB and data size was 16 MB.
Sentence 2: theyselected the size of the connection pair empirically and generated connection pairs in limited networks, so the probe size might be inappropriate for other networks.
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Domain: Networks
Sentence 1: In particular, the problem of scheduling transmissions ef­.ciently given certain interference constraints have been ad­dressed in several papers and algorithms to solve this prob­lem have been proposed [13, 21, 3, 19, 1, 17, 4].
Sentence 2: permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.
Relationship: contrasting
Domain: Networks
Sentence 1: 6 (a), when the tra.c rate is low, DutyCon con­ 0.3 0.2 0.2 0.1 0.1 0 10-1 requirement (s) 0 100 200 time(s) 300 400 Figure 7: Average delay and average queue length varying delay requirements trols the average delay very close to the desired requirement.
Sentence 2: as the tra.c load becomes heavier, neither Duty-Con nor U-MAC have e.ective control of the average delay.
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Domain: Networks
Sentence 1: The inaccuracy in the end timestamp may be caused by delays from wait­ing until a .ow export packet or cache .lls, or by lingering out-of-order packets2 [7].
Sentence 2: .ow start timestamps appear to accurately re.ect the .rst packet of a .ow (al­lowing us to use them in calculating the inter-connection times).
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Domain: Networks
Sentence 1: This is for the simple reason that with many error-prone nodes on any individual route, it is almost a cer­tainty that some node along any particular route will fail.
Sentence 2: this is will not be simple to achieve, for two main reasons: One is computational complexity: searching a large space of possible routes (derived from having a large number of nodes with high density) may prove computationally prohibitive for low complexity devices like our micro-routers.
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