sadat2307/MSciNLI huggingface dataset:
Domain: Networks
Sentence 1: Speci.cally, the contention window is set to the sum of the back­off intervals that were skipped when the GN is in possession of the medium.
Sentence 2: the contention window is set to CW =min(|.|×CWmin ,CWmax ), (10) where CW, CWmin ,and CWmax are the current, maximum, and the minimum contention window sizes, respectively.
Relationship: entailment
Domain: Networks
Sentence 1: The group or slice scheduler is con.gured to allocate re­sources (in terms of time slots) to each group in proportion to the percentage of users in the group.
Sentence 2: we de.ne the group scheduling approach as follows: Let N0 be the number of users in the normal group, and Nj be the number of users in each of the k deviant groups j, 1 : j : k. Let S be the total number of resource slots at a base station for a unit interval, and Sjexp be an exponentially weighted moving average of slots allocated to each group (including all .ows).
Relationship: entailment
Domain: Networks
Sentence 1: Using a recent result presented in [21], it can be shown that this power scaling is a necessary condition to achieve a high rate in worst-case networks.
Sentence 2: it was shown that if nodes transmitted at constant power, or if nodes transmit­ted at a power proportional to da when transmitting over adistance d, then atmosta constant number of nodes can transmit in parallel in worst-case networks.
Relationship: entailment
Domain: Networks
Sentence 1: CHARM obtains path loss information by leveraging the Reciprocity Theorem [14], which states: If the role of the transmitter and receiver are instantaneously interchanged, the signal transfer function between them remains unchanged.
Sentence 2: the instantaneous path loss between two nodes is the same in both directions and a transmitter can obtain the path loss to a receiver by measuring the path loss from the receiver to the transmitter.
Relationship: entailment
Domain: Networks
Sentence 1: [1,D], then again the attacker can determine j with the following algorithm: j =2 if and only if Esj (x)= Es1 (aq) for some q.
Sentence 2: by process of elimination, the attacker determines that j =2 because Esj (x)= Es1 (aq), 8The length, .,of yr,j should be chosen such that 2.
Relationship: entailment
Domain: Networks
Sentence 1: (2) jEJ: In wireless systems, the situation is different from what it is in their wired counterparts, notably with respect to the amount of bandwidth seen by the different flows at any given time.
Sentence 2: define Ci(t), i E jr, as the maximum goodput of flow i at epoch t. C,(t) can be intuitively viewed as the error free capacity seen by flow i should this latter be using the full capacity of the network C. should flow i transmit at rate C at time t including both useful data and redundancy (such as FEC) the good capacity perceived during such transmission would be Ci(t).
Relationship: entailment
Domain: Networks
Sentence 1: In our simulations MSs measure signal quality in every frame, that is, every 5 ms, which means that the Time-to-trigger timer may be started or stopped in 5 ms cycles.
Sentence 2: in spite of a short measurement cycle, it can be observed that oc­casionally the fast fading does not change the RSSI levels enough for the smallest Ttrig value, 0.05 s. despite the impact from fast fading, the RSSI level might    2 m/s, 0.05s TTT 2 m/s, 0.1s TTT 2 m/s, 0.25s TTT 2 m/s, 0.5s TTT 5 m/s, 0.05s TTT 5 m/s, 0.1s TTT 5 m/s, 0.25s TTT 5 m/s, 0.5s TTT 10 m/s, 0.05s TTT 10 m/s, 0.1s TTT 10 m/s, 0.25s TTT 10 m/s, 0.5s TTT 20 m/s, 0.05s TTT 20 m/s, 0.1s TTT 20 m/s, 0.25s TTT 20 m/s, 0.5s TTT   remain quite stable for a longer period of time than 0.05 s. If the Time-to-trigger timeisstarted, during the50 mstime the di.erence between compared channels might not change enough to prevent a possibly unnecessary handover trigger­ing.
Relationship: entailment
Domain: Networks
Sentence 1: In such a scenario, the basin of attraction of the (C, C) NE (i.e., the surface of the rectangle between the mixed NE and the (C, C) NE) is larger than that of the (D, D) NE.
Sentence 2: (C, C) would be the most likely NE in settings where players .nd their best response with an adaptive be­havior.
Relationship: entailment
Domain: Networks
Sentence 1: Total Candidate Candidatesdetected Candidates detected Anomalies Evaluated by Deviation Score by Holt-Winters 39 II 38 37 II In each case we were somewhat tolerant of discrepancies be- tween the anomaly timestamps in the journal's log entries and the times at which the automated methods reported anomalous network traffic.
Sentence 2: we allowed a discrepancy of as much as 1.5 hours since both automated techniques sometimes shift the report significantly from the time of the event's on- set.
Relationship: entailment
Domain: Networks
Sentence 1: CASE STUDY: WHERE SECURITY CLAIMS FAIL AND COMPROMISE EAP SECU-RITY In this section we present attacks that exploit special prop­erties of EAP systems to break EAP security claims.
Sentence 2: the attacks break the channel binding, protected ciphersuite negotiation and cryptographic bindings of EAP methods that claim to provide such security properties.
Relationship: entailment
Domain: Networks
Sentence 1: The way this signature is formulated with respect to the ACN follows.
Sentence 2: to introduce a mathematical notation for this behavior, let  denote the event that an IP packet was transmitted from port b on host a to port d on host c at time t .(a, b) represents the client address and port and (c, d) the server address and port (note: this di.ers from the tcpdump format).
Relationship: entailment
Domain: Networks
Sentence 1: A visual indication is given to the user to deploy a new relay when the highest running RSS average goes below a threshold, Sth.
Sentence 2: letting Si,j be the RSS mea­ surement from the ith replying node during the jth probe 0 -5 -10 period, deployment is triggered when N 1 max Si,j<Sth.
Relationship: entailment
Domain: Networks
Sentence 1: However, traditional compressive sensing algorithms are com­putationally infeasible to apply in this setting because A has as many columns as the number of nodes in the network (e.g., one million itemsinaWal-Mart store).Todevelopa practical solution, we exploit the sparsity in x to eliminate large chunks of columns in A.
Sentence 2: we hash the elements of x into buckets.
Relationship: entailment
Domain: Networks
Sentence 1: 2.1 If Hi* is empty, i.e., no other hops of the packet has been scheduled, set t = t0,where t0 is a reference time.
Sentence 2: 2.2 If Hi* is not empty, .nd h ' so that |h ' -h*|= minh.Hi* |h-h*|.h ' is the hop closest * to h* among all the scheduled hops of packet i.
Relationship: entailment
Domain: Networks
Sentence 1: Focusing on the design of power ef.cient op­tical networks in the context of CapEx minimized networks, the works that are the closest to ours are [16, 18, 19].
Sentence 2: in [16] the authors focus on two network architectures (IP-over-WDM with gray interfaces and IP-over-Optical Transport Network (OTN)-WDM), providing a break down of normalized power con­sumption over the IP equipment and OXCs/Electrical Cross-Connects (EXCs).
Relationship: entailment
Domain: Networks
Sentence 1: For some of our classi.ers and some of our algo­rithms and some .eld permutations, the running time occa­sionally exceeds one minute; fortunately, these cases can be ignored as they almost always result in poor compression.
Sentence 2: we can set a reasonable limit such as one minute or .ve minutes for running a compression algorithm and termi­nate the algorithm and discard the result for the given .eld permutation if it exceeds the given time limit.
Relationship: entailment
Domain: Networks
Sentence 1: = .D.Using the same bd,i, E[EPG] - E[EMG]isgiven by .D cPI s0 + [(cPR - PV )s0 +((c- 1)PR - cPV )s] >0, 1 - .D because PR » in practice.
Sentence 2: e[E * > PV PG] E[E * and the MG] when the AP transmits data with PMAX same bd,i * according to Props.
Relationship: entailment
Domain: Networks
Sentence 1: CONCLUSION The successful deployment of WiMAX as a BWA technology will be strongly dependent on how it will support multiple users and how it will be able to distribute multimedia applications such as VoIP, VoD and IPTV.
Sentence 2: the performance of video streams over WiMAX is an important challenge, both from the perspective of the Internet Service Provider (ISP), which wants to maximize revenue while keeping customers satisfied, and the customers, which want to have a good service level with the minimum cost.
Relationship: entailment
Domain: Networks
Sentence 1: We study the performance of the stable mobile path and the minimum hop mobile path when generated under different simulation time periods.
Sentence 2: we evaluate the number of route transitions and the average hop count when the minimum hop mobile path and stable mobile path are generated over simulation time periods of 1 to 1000 seconds, 1001 to 2000 seconds, 2001 to 3000 seconds, 3001 to 4000 seconds, 4001 to 5000 seconds.
Relationship: entailment
Domain: Networks
Sentence 1: Thus the problem can be formulated as follows: Maxi­mize T0 such that the average waiting time for broadcasting the .rst link change during an update interval is bounded.
Sentence 2: maximize T0 such that E(t0) = a,where a is the bound required on the mean value of the delay with which the update about the .rst detected change in an update interval is broadcasted.
Relationship: entailment
Domain: Networks
Sentence 1: This intuitionisincorrect,however,and causesbothfalsepositives and falsenegatives.Twodependent flowsmayalwaysoccurtogetherin thetrace,yethappensorarely(lowProb(X.Y))thattheirdepen­denceisnotidentified.Ontheotherhand,anunrelatedpairofflows canhaveahighjointprobability simplybecauseoneof the flowsis verypopular.
Sentence 2: we take an information-theoretic approach to identify statisti­callysignificantdependencies pairsofflowsthathavemuchhigher jointprobabilitiesthan merelydueto chance.we setup candidate rules ofthetype X .
Relationship: entailment
Domain: Networks
Sentence 1: 7.1 Routing for Delay-Insensitive Applications We extended the wireless package of the J-Sim Simulator [1], which implements the whole protocol stack of a sensor node, in or­der to simulate the characteristics of the underwater environment, as discussed in Section 4.
Sentence 2: we modeled the underwa­ter transmission loss, the propagation delay, and the physical layer characteristics of underwater receivers.
Relationship: entailment
Domain: Networks
Sentence 1: A routing solution can be considered a feasible solution only if all the through­put constraints speci.ed in the high-level speci.cation phase are satis.ed.
Sentence 2: the XY routing can be used, as well as a custom routing algorithm that performs a recur­sive iteration over the mapping solutions provided by the previous phase, computing all the possible routes from each source to its corresponding target, storing the throughput of all the connections and verifying that the maximum limit of throughput is not reached.
Relationship: entailment
Domain: Networks
Sentence 1: The longer paths in Valiant routing also have the disad­vantage of requiring the use of additional virtual channels to guarantee deadlock freedom.
Sentence 2: the Valiant routing variant for dragon.ies as described in [13], which we will call Valiant [Kim:2008] , requires 3 virtual channels (instead of 2 for shortest paths) for the L links and 2 virtual channels (instead of 1 for shortest path) for the R links, to guarantee deadlock freedom [2].
Relationship: entailment
Domain: Networks
Sentence 1: 6.1.5 Maximum Transmission Count (MTC) To improve packet delivery reliability, one common ap­proach is to retransmit lost packets.
Sentence 2: when a node sends a packet to its next-hop forwarder (or the base sta­tion), the node will keep transmitting the packet until an ACK is received or the packet has been transmitted up to a threshold number of times, which we call the maximum transmission count (MTC).
Relationship: entailment
Domain: Networks
Sentence 1: Although it might seem natural to set the DHCP lease time to about the time of a typical class period; however, in practice, usage patterns are highly variable.
Sentence 2: class periods are variable, wireless networks are deployed in many other parts of the campus (e.g., common areas), and the campus network must support an increasingly wider range of devices that use dynamic addressing (e.g., gaming consoles, phones).
Relationship: entailment
Domain: Networks
Sentence 1: They are subject to several constraints: Minimum and maximum power constraint: If PminGlk + N0 = ß, then vkl = 1.
Sentence 2: if the re­ceivedpower atthetransmitter oflink k is su.ciently large even when the transmitter of link l is using the minimum power level, then vkl should always equal to one.
Relationship: entailment
Domain: Networks
Sentence 1: Despite a wide range of work on this in the past, for example [4, 3, 13, 5, 8, 10], the classi.cation of network traf.c continues to be a challenge.
Sentence 2: network traf.c classi.cation is a complicated multi-factor system involving the mutual interaction of a range of networks, hosts, applications, and protocols.
Relationship: entailment
Domain: Networks
Sentence 1: Further analysis showed that the me­dian number of messages forwarded per node was similar, but some nodes transmitted disproportionately many mes­sages using BUBBLE, especially in Flunet/ SHED1, imply­ing high energy usage and potential bu.er over.ow at the over-utilized nodes.
Sentence 2: 25% of the nodes trans­mit over 45,000/22000 messages, using BUBBLE.
Relationship: entailment
Domain: Networks
Sentence 1: While previous work had modelled and ana­lyzed the broken incentive structure subjacent to for­warding tra.c from an economic perspective, work on re-feedback and congestion exposure [17] pioneered a practical means of alleviating the tussle surrounding re­source sharing.
Sentence 2: congestion exposure advo­cates the use of congestion volume, rather than through­put or tra.c volume, as the by-product by which the impact of tra.c should be assessed.
Relationship: entailment
Domain: Networks
Sentence 1: Note that the adaptive pacing algorithm aims at improving TCP performance in the wireless domain and thus has to be implemented at the entry point of a TCP connection into the wireless network.
Sentence 2: for connections spanning across wireless and wired networks we distinguish the two cases: (1) the TCP source is a wireless device and the TCP destination resides in the wired Internet; denoted as wireless-to-wired flows.
Relationship: entailment
Domain: Networks
Sentence 1: For ZE{I,S}, we will obtain a lower bound on Pr[iEZAk(i)] and show it to approach 1 as so.Let Xk(i)be a random variable assuming a value of 1 if the cross­ing line iis not k-covered, and 0 otherwise.
Sentence 2: xk(i)is an indicator of the event Ak(i).Let Xk ZXk(1) Xk(2)Xk(1Z1).Now, .
Relationship: entailment
Domain: Networks
Sentence 1: Note that the lifetime of a sensor node is the inverse of its normalized power dissipation.
Sentence 2: thus we can de.ne a utility function for sensor node i as a function of its normal­ized power dissipation zi.1 ß ß+1 Vi (zi)= zi (22) (ß +1) and the utility of sensor node i with respect to its normal­ized power dissipation is negative, and given by -i (zi).
Relationship: entailment
Domain: Networks
Sentence 1: The unweighted version of the problem, where the goal is to min­imize the number of Steiner nodes, is the special case of the weighted version where the terminals have weight 0 and the non-terminals have weight 1.
Sentence 2: in this paper, we present a 0.775d-approximation algo­rithm for the problem of computing a Steiner tree with min­imum total weight of the Steiner nodes for graph classes that admit spanning trees of maximum degree at most d. this yields a 3.875-approximation algorithm for unit disk graphs, an O(1/a2 )-approximation algorithm for a-unit disk graphs, and an O(A)-approximation algorithm for (A + 1)-claw-free graphs.
Relationship: entailment
Domain: Networks
Sentence 1: Consider a PoP with N core routers, numbered 1,...,N, each with L line cards having P ports each.
Sentence 2: the line cards across the various CRs are numbered 1,...,N· L. Similarly, the ports across the various CRs are numbered 1,...,N · L· P. the ports of the .rst CR are numbered 1,...,L· P, while the ports of the .rst line card of this CR are enumerated from 1,...,P. The ports of the second CR are numbered P·L+1,...,2·P·L, and so on.
Relationship: entailment
Domain: Networks
Sentence 1: Observed Structure of Addresses in IP Traffic Eddie Kohler* Jinyang Li t Vern Paxson* Scott Shenker*  *ICSI Center for Internet Research tMIT Lab for Computer Science kohler@icir.org, jinyang@lcs.mit.edu, {vern, shenker}@icir.org ABSTRACT This paper investigates the structure of addresses contained in IP traffic.
Sentence 2: we analyze the structural charac- teristics of destination IP addresses seen on Interuet links, considered as a subset of the address space.
Relationship: entailment
Domain: Networks
Sentence 1: Although most of prior works focus on caching proxies placed in the network (e.g., hierarchical caching proxies [18], caching proxy placement [21], and caching within 3G networks [20]), we emphasize that in cellular networks, caching on handsets is particularly important because it does not incur any network-related overhead.
Sentence 2: it eliminates data transmitted over the last-mile, i.e., the radio access network, which is known as the performance and resource bottleneck of a cellular network [31].
Relationship: entailment
Domain: Networks
Sentence 1: To explore these aspects, we refer to the application of economic models to the Radio Resource Management, an open .eld for research on which several contributions have appeared in the recent literature.
Sentence 2: the con­cept of utility functions and issues taken from game-theory have been employed to represent a tunable Quality of Ser­vice (QoS), for example obtained through variations of the terminal s data rate [4, 5].
Relationship: entailment
Domain: Networks
Sentence 1: However, the fpr describes the overall network per­formance only indirectly.
Sentence 2: in order to capture better the actual bandwidth consumption due to false positives, we in­troduce forwarding e.ciency asametrictoquantify the bandwidth overhead caused by sending packets through un­necessary links: #Links on shortest path tree fwe = (3) #Links during delivery  forwarding e.ciency is 100% if the packets strictly follow the shortest path tree for reaching the sub­scribers.
Relationship: entailment
Domain: Networks
Sentence 1: To execute a list of call branches, the system treats the call branches as sends followed by receives.
Sentence 2: the system acts as if the principal sends the message x * after guaranteeing the formulas F, * then recvs the message y and relies on the formulas .. the the runtime trust management system selects a branch, within which it can successfully guarantee the formulas F. It calls the associated subprotocol procedure f with the parameters x * instan­tiated using the values in the resulting extended runtime environ­ment.
Relationship: entailment
Domain: Networks
Sentence 1: [10], whether stability and .nite delivery times for all packets can be achieved against all adversaries of rate r=1.1 As discussed above,we show that for some sequences of packets injected at rate r= 1,it is impossible (even by an of­.ine scheduler) to have a .nite upper bound on the delivery times of all packets.
Sentence 2: an adversary that is commit­ted to have itself a schedule for the packets such that there is some .nite bound on the delivery times of all packets,is a weaker adversary than the rate-1 adversary.
Relationship: entailment
Domain: Networks
Sentence 1: The received signal is also represented as a stream of complex symbols spaced by the sampling interval T. These symbols differ, however,fromthetransmitted symbols, bothinamplitudeand phase.
Sentence 2: if the transmitted symbol is x[n] the received symbol can be approximated as: y[n]= Hx[n]+ w[n], (1) where H= he.
Relationship: entailment
Domain: Networks
Sentence 1: Several WBAN protocol proposals can be found in the literature, as well as studies of applicabil­ity of existing Wireless Sensor Network protocols to WBAN scenarios, see for example [7].
Sentence 2: [7] consider the IEEE 802.15.4 standard as reference, [3] mainly focus on re­ducing devices duty-cycle to save energy, while [4] proposes a Time Division Multiple Access (TDMA)-based Medium Ac­cess Control (MAC) protocol.
Relationship: entailment
Domain: Networks
Sentence 1: CONCLUSIONS Inthispaper wehave consideredthephysical-layertechnique developedin[9,10] toprovide authenticationbetweenAl­ice and Bob assuming a more general model for the attack employed by Eve.
Sentence 2: we provide the optimal Eve s strategyin the case of single attack and weperform an analytical computation of E[PMD] with respect to channel distribution.
Relationship: entailment
Domain: Networks
Sentence 1: Accordingly, the MPP decides to use PCF-enabled mode for next superframe if Q0 is larger than the queue threshold in the MPP, Q0, or if it receives a PCF-enabled mode request from its neighbor MPs.
Sentence 2: the MPP changes the op­eration mode from contention mode to PCF-enabled mode if Qi >Q i for i=0,1,2,··· ,n. (1) Let R be the channel bit rate and TCFP be the maximum operation time of the CFP.
Relationship: entailment
Domain: Networks
Sentence 1: In the following we prove that the backwards rewrite the­ory (SP , EP , R -1 ) is sound with respect to the forward BP rewrite theory (SP , EP , RF P ).
Sentence 2: we need to show that if we .nd a symbolic initial state S0 from a symbolic attack pattern S then, for any concrete initial state s0 such that S0 >.
Relationship: entailment
Domain: Networks
Sentence 1: The proposed context information set for the mobile network selection includes service requirements, user preferences, device capabilities, interface power consumption, user mobility, service criticality and end-to-end QoS (e2eQoS) prediction information.
Sentence 2: for providing the near-accurate estimate of the e2eQoS and minimizing power required at the mobile device to search all the available wireless networks, the QoS prediction context source located in the fixed network provides predictions on the availability of mobile networks and their estimated e2eQoS along the user s travel path.
Relationship: entailment
Domain: Networks
Sentence 1: The results clearly show the same trends as ob­served at hotspots in Figure 8(b).
Sentence 2: music is the leading application at locations corresponding to night hotspots even during the daytime as well; social networking istheleading applicationatlocations corresponding at noon hotspots even outside noon intervals; dating is the leading application at locations corresponding to evening hotspots even during non-evening periods.
Relationship: entailment
Domain: Networks
Sentence 1: Using the result of Palacios and Tetali [14], 0 one nk nkn B = can explicitly compute all the hitting times of such a chain.
Sentence 2: theorem 2.3 of [14] states 2 2(k-1) k-1 01 - 2 (1 -) nk nnk 2 0 0 2 nk 1 - 2 nk Summing over 0 = t * = T * - 1, T * -1 T * -1 E [.t* ] = (k - 1)cXY T Bt * XQ0, t* =0 t* =0 The rest of the proof is algebraic; we compute the eigen­value decomposition of matrix B and based on that, we eT * -1 establish the lower bound on E [.t* ].
Relationship: entailment
Domain: Networks
Sentence 1: This question is important because ranking autonomy and .ltering expressiveness re.ect the realities of how ASes spec­ify policies today, and little is known (beyond the results surveyed in Section 2) about the tradeoffs between autonomy and expres­siveness as far as routing stability is concerned, particularly under .ltering.
Sentence 2: our work is the .rst to develop necessary conditions for stability under realistic assumptions about autonomy and expressiveness and the .rst to derive necessary conditions for stability in policy routing.
Relationship: entailment