%%% -*-BibTeX-*-
%%% ====================================================================
%%%  BibTeX-file{
%%%     author          = "Nelson H. F. Beebe",
%%%     version         = "1.01",
%%%     date            = "14 October 2017",
%%%     time            = "10:27:10 MDT",
%%%     filename        = "tompecs.bib",
%%%     address         = "University of Utah
%%%                        Department of Mathematics, 110 LCB
%%%                        155 S 1400 E RM 233
%%%                        Salt Lake City, UT 84112-0090
%%%                        USA",
%%%     telephone       = "+1 801 581 5254",
%%%     FAX             = "+1 801 581 4148",
%%%     URL             = "http://www.math.utah.edu/~beebe",
%%%     checksum        = "01660 1666 9361 88369",
%%%     email           = "beebe at math.utah.edu, beebe at acm.org,
%%%                        beebe at computer.org (Internet)",
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%%%     keywords        = "ACM Transactions on Modeling and Performance
%%%                        Evaluation of Computing Systems (TOMPECS);
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%%%                        ACM Transactions on Modeling and Performance
%%%                        Evaluation of Computing Systems (TOMPECS)
%%%                        (CODEN ????, ISSN 2376-3639 (print),
%%%                        2376-3647 (electronic)).  The journal appears
%%%                        quarterly, and publication began with volume
%%%                        1, number 1, in March 2016.
%%%
%%%                        At version 1.01, the COMPLETE journal
%%%                        coverage looked like this:
%%%
%%%                             2016 (  26)    2017 (   6)
%%%
%%%                             Article:         32
%%%
%%%                             Total entries:   32
%%%
%%%                        The journal Web page can be found at:
%%%
%%%                            http://tompecs.acm.org/
%%%
%%%
%%%                            http://dl.acm.org/pub.cfm?id=J1525
%%%
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%%%                        text of recent articles in PDF form.
%%%
%%%                        The initial draft was extracted from the ACM
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%%%                        with credit, so article abstracts, keywords,
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%%%                        available.  Article reviews have been
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%%%                        been clarified.
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%%% ====================================================================
%%% Acknowledgement abbreviations:

@String{ack-nhfb = "Nelson H. F. Beebe,
University of Utah,
Department of Mathematics, 110 LCB,
155 S 1400 E RM 233,
Salt Lake City, UT 84112-0090, USA,
Tel: +1 801 581 5254,
FAX: +1 801 581 4148,
e-mail: \path|beebe@math.utah.edu|,
\path|beebe@acm.org|,
\path|beebe@computer.org| (Internet),
URL: \path|http://www.math.utah.edu/~beebe/|"}


%%% ====================================================================
%%% Journal abbreviations:

@String{j-TOMPECS               = "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)"}


%%% ====================================================================
%%% Bibliography entries:

@Article{Towsley:2016:I,
author =       "Don Towsley and Carey Williamson",
title =        "Introduction",
journal =      j-TOMPECS,
volume =       "1",
number =       "1",
pages =        "1:1--1:1",
month =        mar,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2893179",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:29:10 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2893179",
acknowledgement = ack-nhfb,
articleno =    "1",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Lashgar:2016:ESM,
title =        "Employing Software-Managed Caches in {OpenACC}:
Opportunities and Benefits",
journal =      j-TOMPECS,
volume =       "1",
number =       "1",
pages =        "2:1--2:34",
month =        mar,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2798724",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:29:10 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2798724",
abstract =     "The OpenACC programming model has been developed to
simplify accelerator programming and improve
investigate the main limitations faced by OpenACC in
harnessing all capabilities of GPU-like accelerators.
We build on our findings and discuss the opportunity to
exploit a software-managed cache as (i) a fast
communication medium and (ii) a cache for data reuse.
To this end, we propose a new directive and
communication model for OpenACC. Investigating several
benchmarks, we show that the proposed directive can
improve performance up to $2.54 \times$, and at the
cost of minor programming effort.",
acknowledgement = ack-nhfb,
articleno =    "2",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Zhang:2016:VSL,
author =       "Deli Zhang and Jeremiah Wilke and Gilbert Hendry and
Damian Dechev",
title =        "Validating the Simulation of Large-Scale Parallel
Applications Using Statistical Characteristics",
journal =      j-TOMPECS,
volume =       "1",
number =       "1",
pages =        "3:1--3:22",
month =        mar,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2809778",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:29:10 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2809778",
abstract =     "Simulation is a widely adopted method to analyze and
predict the performance of large-scale parallel
applications. Validating the hardware model is highly
important for complex simulations with a large number
of parameters. Common practice involves calculating the
percent error between the projected and the real
execution time of a benchmark program. However, in a
high-dimensional parameter space, this coarse-grained
approach often suffers from parameter insensitivity,
which may not be known a priori. Moreover, the
traditional approach cannot be applied to the
validation of software models, such as application
skeletons used in online simulations. In this work, we
present a methodology and a toolset for validating both
hardware and software models by quantitatively
comparing fine-grained statistical characteristics
obtained from execution traces. Although statistical
information has been used in tasks like performance
optimization, this is the first attempt to apply it to
simulation validation. Our experimental results show
that the proposed evaluation approach offers
significant improvement in fidelity when compared to
evaluation using total execution time, and the proposed
metrics serve as reliable criteria that progress toward
automating the simulation tuning process.",
acknowledgement = ack-nhfb,
articleno =    "3",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Roos:2016:DDE,
author =       "Stefanie Roos and Thorsten Strufe",
title =        "Dealing with Dead Ends: Efficient Routing in
Darknets",
journal =      j-TOMPECS,
volume =       "1",
number =       "1",
pages =        "4:1--4:30",
month =        mar,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2809779",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:29:10 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2809779",
abstract =     "Darknets, membership-concealing peer-to-peer networks,
suffer from high message delivery delays due to
insufficient routing strategies. They form topologies
restricted to a subgraph of the social network of their
users by limiting connections to peers with a mutual
trust relationship in real life. Whereas centralized,
highly successful social networking services entail a
privacy loss of their users, Darknets at higher
performance represent an optimal private and
censorship-resistant communication substrate for social
applications. Decentralized routing so far has been
analyzed under the assumption that the network
resembles a perfect lattice structure. Freenet,
currently the only widely used Darknet, attempts to
approximate this structure by embedding the social
graph into a metric space. Considering the resulting
distortion, the common greedy routing algorithm is
adapted to account for local optima. Yet the impact of
thus suggest a model integrating inaccuracies in the
embedding. In the context of this model, we show that
the Freenet routing algorithm cannot achieve polylog
performance. Consequently, we design NextBestOnce, a
provable poylog algorithm based only on information
about neighbors. Furthermore, we show that the routing
length of NextBestOnce is further decreased by more
than a constant factor if neighbor-of-neighbor
information is included in the decision process.",
acknowledgement = ack-nhfb,
articleno =    "4",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Izagirre:2016:STA,
author =       "A. Izagirre and U. Ayesta and I. M. Verloop",
title =        "Sojourn Time Approximations for a Discriminatory
Processor Sharing Queue",
journal =      j-TOMPECS,
volume =       "1",
number =       "1",
pages =        "5:1--5:31",
month =        mar,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2812807",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:29:10 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2812807",
abstract =     "We study a multiclass time-sharing discipline with
relative priorities known as discriminatory processor
sharing (DPS), which provides a natural framework to
model service differentiation in systems. The analysis
of DPS is extremely challenging, and analytical results
are scarce. We develop closed-form approximations for
the mean conditional (on the service requirement) and
unconditional sojourn times. The main benefits of the
approximations lie in its simplicity, the fact that it
applies for general service requirements with finite
second moments, and that it provides insights into the
dependency of the performance on the system parameters.
We show that the approximation for the mean conditional
and unconditional sojourn time of a customer is
decreasing as its relative priority increases. We also
show that the approximation is exact in various
scenarios, and that it is uniformly bounded in the
second moments of the service requirements. Finally, we
numerically illustrate that the approximation for
exponential, hyperexponential, and Pareto service
requirements is accurate across a broad range of
parameters.",
acknowledgement = ack-nhfb,
articleno =    "5",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Harrison:2016:EPT,
author =       "Peter G. Harrison and Naresh M. Patel and William J.
Knottenbelt",
title =        "Energy--Performance Trade-Offs via the {EP} Queue",
journal =      j-TOMPECS,
volume =       "1",
number =       "2",
pages =        "6:1--6:31",
month =        jun,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2818726",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2818726",
abstract =     "We introduce the EP queue -- a significant
generalization of the M B / G /1 queue that has
state-dependent service time probability distributions
and incorporates power-up for first arrivals and
power-down for idle periods. We derive exact results
for the busy-time and response-time distributions. From
these, we derive power consumption metrics during
nonidle periods and overall response time metrics,
which together provide a single measure of the
trade-off between energy and performance. We illustrate
these trade-offs for some policies and show how
numerical results can provide insights into system
behavior. The EP queue has application to storage
systems, especially hard disks, and other data-center
components such as compute servers, networking, and
even hyperconverged infrastructure.",
acknowledgement = ack-nhfb,
articleno =    "6",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Tavakkol:2016:PED,
author =       "Arash Tavakkol and Pooyan Mehrvarzy and Mohammad
title =        "Performance Evaluation of Dynamic Page Allocation
Strategies in {SSDs}",
journal =      j-TOMPECS,
volume =       "1",
number =       "2",
pages =        "7:1--7:33",
month =        jun,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2829974",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2829974",
abstract =     "Solid-state drives (SSDs) with tens of NAND flash
chips and highly parallel architectures are widely used
in enterprise and client storage systems. As any write
operation in NAND flash is preceded by a slow erase
operation, an out-of-place update mechanism is used to
distribute writes through SSD storage space to postpone
erase operations as far as possible. SSD controllers
use a mapping table along with a specific allocation
strategy to map logical host addresses to physical page
addresses within storage space. The allocation strategy
is further responsible for accelerating I/O operations
through better striping of physical addresses over SSD
parallel resources. Proposals already exist for using
static logical-to-physical address mapping that does
not balance the I/O traffic load within the SSD, and
its efficiency highly depends on access patterns. A
more balanced distribution of I/O operations is to
alternate resource allocation in a round-robin manner
irrespective of logical addresses. The number of
resources that can be dynamically allocated in this
fashion is defined as the degree of freedom, and to the
best of our knowledge, there has been no research thus
far to show what happens if different degrees of
explores the possibility of using dynamic resource
allocation and identifies key design opportunities that
it presents to improve SSD performance. Specifically,
using steady-state analysis of SSDs, we show that
dynamism helps to mitigate performance and endurance
experiments indicate that midrange/high-end SSDs with
dynamic allocation can provide I/O operations per
second (IOPS) improvement of up to 3.3x/9.6x, response
time improvement of up to 56\%/32\%, and about
88\%/96\% average reduction in the standard deviation
of erase counts of NAND flash blocks.",
acknowledgement = ack-nhfb,
articleno =    "7",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Chang:2016:CRA,
author =       "Cheng-Shang Chang and Jay Cheng and Tien-Ke Huang and
Duan-Shin Lee and Cheng-Yu Chen",
title =        "Coding Rate Analysis of Forbidden Overlap Codes in
High-Speed Buses",
journal =      j-TOMPECS,
volume =       "1",
number =       "2",
pages =        "8:1--8:25",
month =        jun,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2846091",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2846091",
abstract =     "One of the main problems in deep submicron designs of
high-speed buses is propagation delay due to the
crosstalk effect. To alleviate the crosstalk effect,
there are several types of crosstalk avoidance codes
the coding rates of forbidden overlap codes (FOCs) that
avoid 010 $\to$ 101'' transition and 101 $\to$
010'' transition on any three adjacent wires in a bus.
We first compute the maximum achievable coding rate of
FOCs and the maximum coding rate of memoryless FOCs.
Our numerical results show that there is a significant
gap between the maximum coding rate of memoryless FOCs
and the maximum achievable rate. We then analyze the
coding rates of FOCs generated from the bit-stuffing
algorithm. Our worst-case analysis yields a tight lower
bound of the coding rate of the bit-stuffing algorithm.
Under the assumption of Bernoulli inputs, we use a
Markov chain model to compute the coding rate of a bus
with n wires under the bit-stuffing algorithm. The main
difficulty of solving such a Markov chain model is that
the number of states grows exponentially with respect
to the number of wires n. To tackle the problem of the
curse of dimensionality, we derive an approximate
analysis that leads to a recursive closed-form formula
for the coding rate over the n th wire. Our
approximations match extremely well with the numerical
results from solving the original Markov chain for $n \leq 10$ and the simulation results for $n \leq 3000$. Our analysis of coding rates of FOCs could be
propagation delay and coding rate among various
crosstalk avoidance codes in the literature. In
comparison with the forbidden transition codes (FTCs)
that have shorter propagation delay than that of FOCs,
our numerical results show that the coding rates of
FOCs are much higher than those of FTCs.",
acknowledgement = ack-nhfb,
articleno =    "8",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Bermolen:2016:ETP,
author =       "Paola Bermolen and Matthieu Jonckheere and Federico
Larroca and Pascal Moyal",
title =        "Estimating the Transmission Probability in Wireless
Networks with Configuration Models",
journal =      j-TOMPECS,
volume =       "1",
number =       "2",
pages =        "9:1--9:23",
month =        jun,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2858795",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2858795",
abstract =     "We propose a new methodology to estimate the
probability of successful transmissions for random
access scheduling in wireless networks, in particular
those using Carrier Sense Multiple Access (CSMA).
Instead of focusing on spatial configurations of users,
we model the interference between users as a random
graph. Using configuration models for random graphs, we
show how the properties of the medium access mechanism
are captured by some deterministic differential
equations when the size of the graph gets large.
Performance indicators such as the probability of
connection of a given node can then be efficiently
computed from these equations. We also perform
simulations to illustrate the results on different
types of random graphs. Even on spatial structures,
these estimates get very accurate as soon as the
variance of the interference is not negligible.",
acknowledgement = ack-nhfb,
articleno =    "9",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Yan:2016:PAF,
author =       "Feng Yan and Xenia Mountrouidou and Alma Riska and
Evgenia Smirni",
title =        "{PREFiguRE}: An Analytic Framework for {HDD}
Management",
journal =      j-TOMPECS,
volume =       "1",
number =       "3",
pages =        "10:1--10:27",
month =        may,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2872331",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2872331",
abstract =     "Low disk drive utilization suggests that placing the
drive into a power saving mode during idle times may
decrease power consumption. We present PREFiguRE, a
robust framework that aims at harvesting future idle
intervals for power savings while meeting strict
quality constraints: first, it contains potential
delays in serving IO requests that occur during power
savings since the time to bring up the disk is not
negligible, and second, it ensures that the power
saving mechanism is triggered a few times only, such
that the disk wear-out due to powering up and down does
not compromise the disk's lifetime. PREFiguRE is based
on an analytic methodology that uses the histogram of
idle times to determine schedules for power saving
modes as a function of the preceding constraints.
PREFiguRE facilitates analysis for the evaluation of
the trade-offs between power savings and quality
targets for the current workload. Extensive
experimentation on a set of enterprise storage traces
illustrates PREFiguRE's effectiveness to consistently
achieve high power savings without undermining disk
reliability and performance.",
acknowledgement = ack-nhfb,
articleno =    "10",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Antunes:2016:EFD,
author =       "Nelson Antunes and Vladas Pipiras",
title =        "Estimation of Flow Distributions from Sampled
Traffic",
journal =      j-TOMPECS,
volume =       "1",
number =       "3",
pages =        "11:1--11:28",
month =        may,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2891106",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2891106",
abstract =     "This work addresses the problem of estimating the
distributions of packet flow sizes and durations under
several methods of sampling packets. Two approaches,
one based on inversion and the other on asymptotics,
are considered. For the duration distribution, in
particular, both approaches require modeling the
structure of flows, with the duration distribution
being characterized in terms of the IATs (interarrival
times between packets) and size distributions of a
flow. The inversion of the flow IAT distribution from
sampled flow quantities, along with the inversion of
the flow size distribution (already used in the
literature) allows estimating the flow duration
distribution. Motivated by the limitations of the
inversion approach in estimating the distribution tails
for some sampling methods, an asymptotic approach is
developed to estimate directly the distribution tails
of flow durations and sizes from sampled quantities.
The adequacy of both approaches to estimate the flow
distributions is checked against two real Internet
traces.",
acknowledgement = ack-nhfb,
articleno =    "11",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Garetto:2016:UAP,
author =       "Michele Garetto and Emilio Leonardi and Valentina
Martina",
title =        "A Unified Approach to the Performance Analysis of
Caching Systems",
journal =      j-TOMPECS,
volume =       "1",
number =       "3",
pages =        "12:1--12:28",
month =        may,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2896380",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2896380",
abstract =     "We propose a unified methodology to analyze the
performance of caches (both isolated and
interconnected), by extending and generalizing a
decoupling technique originally known as Che's
approximation, which provides very accurate results at
low computational cost. We consider several caching
policies (including a very attractive one, called k
-LRU), taking into account the effects of temporal
locality. In the case of interconnected caches, our
approach allows us to do better than the Poisson
approximation commonly adopted in prior work. Our
results, validated against simulations and trace-driven
experiments, provide interesting insights into the
performance of caching systems.",
acknowledgement = ack-nhfb,
articleno =    "12",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Xie:2016:DAI,
author =       "Hong Xie and John C. S. Lui and Don Towsley",
title =        "Design and Analysis of Incentive and Reputation
Mechanisms for Online Crowdsourcing Systems",
journal =      j-TOMPECS,
volume =       "1",
number =       "3",
pages =        "13:1--13:27",
month =        may,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2897510",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:54 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2897510",
abstract =     "Today, online crowdsourcing services like Amazon
Mechanical Turk, UpWork, and Yahoo! Answers are gaining
in popularity. For such online services, it is
important to attract workers'' to provide
high-quality solutions to the tasks'' outsourced by
requesters.'' The challenge is that workers have
different skill sets and can provide different amounts
incentive and reputation mechanisms to solicit
high-quality solutions from workers. Our incentive
mechanism allows multiple workers to solve a task,
splits the reward among workers based on requester
evaluations of the solution quality, and guarantees
that high-skilled workers provide high-quality
solutions. However, our incentive mechanism suffers the
potential risk that a requester will eventually
collects low-quality solutions due to fundamental
limitations in task assigning accuracy. Our reputation
mechanism ensures that low-skilled workers do not
provide low-quality solutions by tracking workers'
historical contributions and penalizing those workers
having poor reputations. We show that by coupling our
reputation mechanism with our incentive mechanism, a
requester can collect at least one high-quality
solution. We present an optimization framework to
select parameters for our reputation mechanism. We show
that there is a trade-off between system efficiency
(i.e., the number of tasks that can be solved for a
given reward) and revenue (i.e., the amount of
transaction fees), and we present the optimal trade-off
curve between system efficiency and revenue. We
demonstrate the applicability and effectiveness of our
mechanisms through experiments using a real-world
dataset from UpWork. We infer model parameters from
this data, use them to determine proper rewards, and
select the parameters of our incentive and reputation
mechanisms for UpWork. Experimental results show that
our incentive and reputation mechanisms achieve 98.82\%
of the maximum system efficiency while only sacrificing
4\% of revenue.",
acknowledgement = ack-nhfb,
articleno =    "13",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

title =        "Scheduling Storms and Streams in the Cloud",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "14:1--14:28",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2904080",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2904080",
abstract =     "Motivated by emerging big streaming data processing
we investigate the problem of scheduling graphs over a
large cluster of servers. Each graph is a job, where
nodes represent compute tasks and edges indicate data
flows between these compute tasks. Jobs (graphs) arrive
randomly over time and, upon completion, leave the
system. When a job arrives, the scheduler needs to
partition the graph and distribute it over the servers
to satisfy load balancing and cost considerations.
Specifically, neighboring compute tasks in the graph
that are mapped to different servers incur load on the
network; thus a mapping of the jobs among the servers
incurs a cost that is proportional to the number of
broken edges.'' We propose a low-complexity
randomized scheduling algorithm that, without service
preemptions, stabilizes the system with graph
arrivals/departures; more importantly, it allows a
smooth tradeoff between minimizing average partitioning
cost and average queue lengths. Interestingly, to avoid
service preemptions, our approach does not rely on a
Gibbs sampler; instead, we show that the corresponding
limiting invariant measure has an interpretation
stemming from a loss system.",
acknowledgement = ack-nhfb,
articleno =    "14",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

author =       "Alessandro Vittorio Papadopoulos and Ahmed Ali-Eldin
and Karl-Erik {\AA}rz{\'e}n and Johan Tordsson and Erik
Elmroth",
title =        "{PEAS}: A Performance Evaluation Framework for
Auto-Scaling Strategies in Cloud Applications",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "15:1--15:31",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2930659",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2930659",
abstract =     "Numerous auto-scaling strategies have been proposed in
the past few years for improving various Quality of
Service (QoS) indicators of cloud applications, for
example, response time and throughput, by adapting the
amount of resources assigned to the application to meet
the workload demand. However, the evaluation of a
proposed auto-scaler is usually achieved through
experiments under specific conditions and seldom
includes extensive testing to account for uncertainties
in the workloads and unexpected behaviors of the
system. These tests by no means can provide guarantees
about the behavior of the system in general conditions.
framework for Auto-Scaling (PEAS) strategies in the
presence of uncertainties. The evaluation is formulated
as a chance constrained optimization problem, which is
solved using scenario theory. The adoption of such a
technique allows one to give probabilistic guarantees
of the obtainable performance. Six different
auto-scaling strategies have been selected from the
literature for extensive test evaluation and compared
using the proposed framework. We build a discrete event
simulator and parameterize it based on real
experiments. Using the simulator, each auto-scaler's
performance is evaluated using 796 distinct real
workload traces from projects hosted on the Wikimedia
foundations' servers, and their performance is compared
using PEAS. The evaluation is carried out using
different performance metrics, highlighting the
flexibility of the framework, while providing
probabilistic bounds on the evaluation and the
performance of the algorithms. Our results highlight
the problem of generalizing the conclusions of the
original published studies and show that based on the
evaluation criteria, a controller can be shown to be
better than other controllers.",
acknowledgement = ack-nhfb,
articleno =    "15",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Fricker:2016:AOS,
author =       "Christine Fricker and Fabrice Guillemin and Philippe
Robert and Guilherme Thompson",
the Framework of Fog Computing",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "16:1--16:18",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2950047",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2950047",
abstract =     "In the context of fog computing, we consider a simple
case where data centers are installed at the edge of
the network and assume that if a request arrives at an
overloaded data center, then it is forwarded to a
neighboring data center with some probability. Data
centers are assumed to have a large number of servers,
and traffic at some of them is assumed to cause
saturation. In this case, the other data centers may
help to cope with this saturation regime by accepting
some of the rejected requests. Our aim is to
qualitatively estimate the gain achieved via
cooperation between neighboring data centers. After
proving some convergence results related to the scaling
limits of loss systems for the process describing the
number of free servers at both data centers, we show
that the performance of the system can be expressed in
terms of the invariant distribution of a random walk in
the quarter plane. By using and developing existing
results in the technical literature, explicit formulas
for the blocking rates of such a system are derived.",
acknowledgement = ack-nhfb,
articleno =    "16",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{DeCicco:2016:CTA,
author =       "Luca {De Cicco} and Yixi Gong and Dario Rossi and
Emilio Leonardi",
title =        "A Control-Theoretic Analysis of Low-Priority
Congestion Control Reprioritization under {AQM}",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "17:1--17:33",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2934652",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2934652",
abstract =     "Recently, a negative interplay has been shown to arise
when scheduling/Active Queue Management (AQM)
techniques and low-priority congestion control
protocols are used together; namely, AQM resets the
relative level of priority among congestion control
protocols. This work explores this issue by carrying
out a control-theoretic analysis of the dynamical
system to prove some fundamental properties that fully
characterize the reprioritization phenomenon. In
particular, (i) we provide the closed-form solution of
the equilibrium in the open loop (i.e., fixing a target
loss probability p ); (ii) we provide a stability
analysis and a characterization of the reprioritization
phenomenon when closing the loop with AQM (i.e., that
dynamically adjusts the system loss probability). Our
results are important as the characterization of the
reprioritization phenomenon is not only quantitatively
accurate for the specific protocols and AQM considered
but also qualitatively accurate for a broader range of
congestion control protocol and AQM combinations.
Finally, while we find a sufficient condition to avoid
the reprioritization phenomenon, we also show, at the
same time, such conditions to be likely impractical:
Therefore, we propose a simple and practical
system-level solution that is able to reinstate
priorities among protocols.",
acknowledgement = ack-nhfb,
articleno =    "17",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Zhang:2016:TIM,
author =       "Linquan Zhang and Shaolei Ren and Chuan Wu and
Zongpeng Li",
title =        "A Truthful Incentive Mechanism for Emergency Demand
Response in Geo-Distributed Colocation Data Centers",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "18:1--18:23",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2950046",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2950046",
abstract =     "Data centers are key participants in demand response
programs, including emergency demand response (EDR), in
which the grid coordinates consumers of large amounts
of electricity for demand reduction in emergency
situations to prevent major economic losses. While
existing literature concentrates on owner-operated data
centers, this work studies EDR in geo-distributed
multitenant colocation data centers in which servers
are owned and managed by individual tenants. EDR in
colocation data centers is significantly more
challenging due to lack of incentives to reduce energy
consumption by tenants who control their servers and
are typically on fixed power contracts with the
colocation operator. Consequently, to achieve demand
reduction goals set by the EDR program, the operator
has to rely on the highly expensive and/or
environmentally unfriendly on-site energy
backup/generation. To reduce cost and environmental
impact, an efficient incentive mechanism is therefore
needed, motivating tenants' voluntary energy reduction
in the case of EDR. This work proposes a novel
incentive mechanism, Truth-DR, which leverages a
reverse auction to provide monetary remuneration to
tenants according to their agreed energy reduction.
Truth-DR is computationally efficient, truthful, and
achieves 2-approximation in colocation-wide social
cost. Trace-driven simulations verify the efficacy of
the proposed auction mechanism.",
acknowledgement = ack-nhfb,
articleno =    "18",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Fu:2016:FPP,
author =       "Yongquan Fu and Ernst Biersack",
title =        "False-Positive Probability and Compression
Optimization for Tree-Structured {Bloom} Filters",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "19:1--19:39",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2940324",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/datacompression.bib;
http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2940324",
abstract =     "Bloom filters are frequently used to to check the
membership of an item in a set. However, Bloom filters
face a dilemma: the transmission bandwidth and the
accuracy cannot be optimized simultaneously. This
dilemma is particularly severe for transmitting Bloom
filters to remote nodes when the network bandwidth is
limited. We propose a novel Bloom filter called
BloomTree that consists of a tree-structured
organization of smaller Bloom filters, each using a set
of independent hash functions. BloomTree spreads items
across levels that are compressed to reduce the
transmission bandwidth need. We show how to find
optimal configurations for BloomTree and investigate in
detail by how much BloomTree outperforms the standard
Bloom filter or the compressed Bloom filter. Finally,
we use the intersection of BloomTrees to predict the
set intersection, decreasing the false-positive
probabilities by several orders of magnitude compared
to both the compressed Bloom filter and the standard
Bloom filter.",
acknowledgement = ack-nhfb,
articleno =    "19",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Anonymous:2016:LR,
author =       "Anonymous",
title =        "List of Reviewers",
journal =      j-TOMPECS,
volume =       "1",
number =       "4",
pages =        "20:1--20:2",
month =        sep,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2989212",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2989212",
acknowledgement = ack-nhfb,
articleno =    "20",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Molka:2016:CAW,
author =       "Karsten Molka and Giuliano Casale",
title =        "Contention-Aware Workload Placement for In-Memory
Databases in Cloud Environments",
journal =      j-TOMPECS,
volume =       "2",
number =       "1",
pages =        "1:1--1:29",
month =        nov,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2961888",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2961888",
abstract =     "Big data processing is driven by new types of
performance modeling to efficiently optimize workload
placement for such systems. In particular, we propose
novel response time approximations for in-memory
databases based on fork-join queuing models and
contention probabilities to model variable threading
levels and per-class memory occupation under analytical
workloads. We combine these approximations with a
nonlinear optimization methodology that seeks optimal
load dispatching probabilities in order to minimize
memory swapping and resource utilization. We compare
our approach with state-of-the-art response time
approximations using real data from an SAP HANA
in-memory system and show that our models markedly
improve accuracy over existing approaches, at similar
computational costs.",
acknowledgement = ack-nhfb,
articleno =    "1",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Vergara:2016:FIC,
author =       "Ekhiotz Jon Vergara and Simin Nadjm-Tehrani and Mikael
Asplund",
title =        "Fairness and Incentive Considerations in Energy
Apportionment Policies",
journal =      j-TOMPECS,
volume =       "2",
number =       "1",
pages =        "2:1--2:29",
month =        nov,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2970816",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2970816",
abstract =     "The energy consumption of a system is determined by
the system component usage patterns and interactions
between the coexisting entities and resources. Energy
accounting plays an essential role in revealing the
contribution of each entity to the total consumption
and for energy management. Unfortunately, energy
accounting inherits the apportionment problem of
accounting in general, which does not have a general
cooperative game theory, which is commonly used in cost
allocation problems to study the energy apportionment
problem, that is, the problem of prescribing the actual
energy consumption of a system to the consuming
entities (e.g., applications, processes, or users of
the system). We identify five relevant fairness
properties for energy apportionment and present a
detailed categorisation and analysis of eight
previously proposed energy apportionment policies from
different fields in computer and communication systems.
In addition, we propose two novel energy apportionment
policies based on cooperative game theory that provide
strong fairness notion and a rich incentive structure.
Our comparative analysis in terms of the identified
five fairness properties as well as information
requirement and computational complexity shows that
there is a tradeoff between fairness and the other
evaluation criteria. We provide guidelines to select an
energy apportionment policy depending on the purpose of
the apportionment and the characteristics of the
system.",
acknowledgement = ack-nhfb,
articleno =    "2",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Nasiriani:2016:FAC,
author =       "Neda Nasiriani and Cheng Wang and George Kesidis and
Bhuvan Urgaonkar and Lydia Y. Chen and Robert Birke",
title =        "On Fair Attribution of Costs Under Peak-Based Pricing
to Cloud Tenants",
journal =      j-TOMPECS,
volume =       "2",
number =       "1",
pages =        "3:1--3:28",
month =        nov,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2970815",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2970815",
abstract =     "The costs incurred by cloud providers towards
operating their data centers are often determined in
large part by their peak demands. The pricing schemes
currently used by cloud providers to recoup these costs
from their tenants, however, do not distinguish tenants
based on their contributions to the cloud's overall
peak demand. Using the concrete example of peak-based
pricing as employed by many electric utility companies,
we show that this gap'' may lead to unfair
attribution of costs to the tenants. Simple
enhancements of existing cloud pricing (e.g., analogous
to the coincident peak pricing (CPP) used by some
shortcomings and suffer from short-term unfairness and
undesirable oscillatory price-vs.-demand relationships
offered to tenants. To overcome these shortcomings, we
define an alternative pricing scheme to more fairly
distribute a cloud's costs among its tenants. We
demonstrate the efficacy of our scheme under
price-sensitive tenant demand response using a
combination of (i) extensive empirical evaluation with
recent workloads from commercial data centers operated
by IBM and (ii) analytical [modeling] through
non-cooperative game theory for a special case of
tenant demand model.",
acknowledgement = ack-nhfb,
articleno =    "3",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Nain:2016:FDD,
author =       "Philippe Nain and Don Towsley",
title =        "File Dissemination in Dynamic Graphs: The Case of
Independent and Correlated Links in Series",
journal =      j-TOMPECS,
volume =       "2",
number =       "1",
pages =        "4:1--4:23",
month =        nov,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2981344",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2981344",
a file across N communication links subject to
stochastic changes in the sending rate of each link.
Each link's sending rate is modeled by a finite-state
Markov process. Two cases, one where links evolve
independently of one another ( N mutually independent
Markov processes) and the second where their behaviors
are dependent (these N Markov processes are not
mutually independent), are considered. A particular
instance where the above is encountered is ad hoc
delay/tolerant networks where links are subject to
intermittent unavailability.",
acknowledgement = ack-nhfb,
articleno =    "4",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Liu:2016:SSS,
author =       "Qingyun Liu and Xiaohan Zhao and Walter Willinger and
Xiao Wang and Ben Y. Zhao and Haitao Zheng",
title =        "Self-Similarity in Social Network Dynamics",
journal =      j-TOMPECS,
volume =       "2",
number =       "1",
pages =        "5:1--5:26",
month =        nov,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2994142",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2994142",
abstract =     "Analyzing and modeling social network dynamics are key
to accurately predicting resource needs and system
behavior in online social networks. The presence of
statistical scaling properties, that is,
self-similarity, is critical for determining how to
model network dynamics. In this work, we study the role
that self-similarity scaling plays in a social network
edge creation (that is, links created between users)
process, through analysis of two detailed, time-stamped
traces, a 199 million edge trace over 2 years in the
Renren social network, and 876K interactions in a
4-year trace of Facebook. Using wavelet-based analysis,
we find that the edge creation process in both networks
is consistent with self-similarity scaling, once we
account for periodic user activity that makes edge
creation process non-stationary. Using these findings,
we build a complete model of social network dynamics
that combines temporal and spatial components.
Specifically, the temporal behavior of our model
reflects self-similar scaling properties, and accounts
for certain deterministic non-stationary features. The
spatial side accounts for observed long-term graph
properties, such as graph distance shrinkage and local
declustering. We validate our model against network
dynamics in Renren and Facebook datasets, and show that
it succeeds in producing desired properties in both
temporal patterns and graph structural features.",
acknowledgement = ack-nhfb,
articleno =    "5",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Krishnasamy:2016:DSR,
author =       "Subhashini Krishnasamy and Rajat Sen and Sanjay
Shakkottai and Sewoong Oh",
journal =      j-TOMPECS,
volume =       "2",
number =       "1",
pages =        "6:1--6:29",
month =        nov,
year =         "2016",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2988543",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:55 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2988543",
abstract =     "With the vast number of items, Web pages, and news
from which to choose, online services and customers
both benefit tremendously from personalized recommender
systems. Such systems additionally provide great
ads alongside genuine recommendations. We consider a
biased recommendation system in which such ads are
displayed without any tags (disguised as genuine
recommendations), rendering them indistinguishable to a
single user. We ask whether it is possible for a small
subset of collaborating users to detect such bias. We
propose an algorithm that can detect this type of bias
through statistical analysis on the collaborating
users' feedback. The algorithm requires only binary
information indicating whether a user was satisfied
with each of the recommended item or not. This makes
the algorithm widely appealing to real-world issues
such as identification of search engine bias and
pharmaceutical lobbying. We prove that the proposed
algorithm detects the bias with high probability for a
broad class of recommendation systems when a sufficient
number of users provides feedback on a sufficient
number of recommendations. We provide extensive
simulations with real datasets and practical
recommender systems, which confirm the trade-offs in
the theoretical guarantees.",
acknowledgement = ack-nhfb,
articleno =    "6",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Petsas:2017:MMA,
author =       "Thanasis Petsas and Antonis Papadogiannakis and
Michalis Polychronakis and Evangelos P. Markatos and
Thomas Karagiannis",
title =        "Measurement, Modeling, and Analysis of the Mobile App
Ecosystem",
journal =      j-TOMPECS,
volume =       "2",
number =       "2",
pages =        "7:1--7:33",
month =        may,
year =         "2017",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/2993419",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:56 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=2993419",
abstract =     "Mobile applications (apps) have been gaining
popularity due to the advances in mobile technologies
and the large increase in the number of mobile users.
Consequently, several app distribution platforms, which
updating software applications in modern mobile
devices, have recently emerged. To better understand
development strategies in this rapidly evolving mobile
app ecosystem, we systematically monitored and analyzed
four popular third-party Android app marketplaces. Our
study focuses on measuring, analyzing, and modeling the
app popularity distribution and explores how pricing
and revenue strategies affect app popularity and
developers' income. Our results indicate that unlike
web and peer-to-peer file sharing workloads, the app
popularity distribution deviates from commonly observed
Zipf-like models. We verify that these deviations can
we refer to as the clustering effect. We validate the
existence of this effect by revealing a strong temporal
these observations, we propose a new formal clustering
demonstrate that it closely fits measured data.
Moreover, we observe that paid apps follow a different
popularity distribution than free apps and show how
free apps with an ad-based revenue strategy may result
in higher financial benefits than paid apps. We believe
that this study can be useful to appstore designers for
improving content delivery and recommendation systems,
as well as to app developers for selecting proper
pricing policies to increase their income.",
acknowledgement = ack-nhfb,
articleno =    "7",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Yi:2017:CDC,
author =       "Xiaomeng Yi and Fangming Liu and Di Niu and Hai Jin
and John C. S. Lui",
title =        "{Cocoa}: Dynamic Container-Based Group Buying
Strategies for Cloud Computing",
journal =      j-TOMPECS,
volume =       "2",
number =       "2",
pages =        "8:1--8:31",
month =        may,
year =         "2017",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/3022876",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:56 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib;
http://www.math.utah.edu/pub/tex/bib/virtual-machines.bib",
URL =          "http://dl.acm.org/citation.cfm?id=3022876",
abstract =     "Although the Infrastructure-as-a-Service (IaaS) cloud
offers diverse instance types to users, a significant
portion of cloud users, especially those with small and
short demands, cannot find an instance type that
exactly fits their needs or fully utilize purchased
instance-hours. In the meantime, cloud service
providers are also faced with the challenge to
consolidate small, short jobs, which exhibit strong
dynamics, to effectively improve resource utilization.
To handle such inefficiencies and improve cloud
resource utilization, we propose Cocoa (COmputing in
COntAiners), a novel group buying mechanism that
organizes jobs with complementary resource demands into
groups and allocates them to group buying deals
predefined by cloud providers. Each group buying deal
offers a resource pool for all the jobs in the deal,
which can be implemented as either a virtual machine or
a physical server. By running each user job on a
virtualized container, our mechanism allows flexible
resource sharing among different users in the same
group buying deal, while improving resource utilization
for cloud providers. To organize jobs with varied
resource demands and durations into groups, we model
the initial static group organization as a
variable-sized vector bin packing problem, and the
subsequent dynamic group organization problem as an
online multidimensional knapsack problem. Through
extensive simulations driven by a large amount of real
usage traces from a Google cluster, we evaluate the
potential cost reduction achieved by Cocoa. We show
that through the effective combination and interaction
of the proposed static and dynamic group organization
strategies, Cocoa greatly outperforms the existing
the feasibility of group buying in cloud computing.",
acknowledgement = ack-nhfb,
articleno =    "8",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Liu:2017:ECE,
author =       "Yu-Hang Liu and Xian-He Sun",
title =        "Evaluating the Combined Effect of Memory Capacity and
Concurrency for Many-Core Chip Design",
journal =      j-TOMPECS,
volume =       "2",
number =       "2",
pages =        "9:1--9:25",
month =        may,
year =         "2017",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/3038915",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:56 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=3038915",
abstract =     "Modern memory systems are structured under hierarchy
and concurrency. The combined impact of hierarchy and
concurrency, however, is application dependent and
2 -Bound, a data-driven analytical model that serves
the purpose of optimizing many-core design. C 2 -Bound
considers both memory capacity and data access
concurrency. It utilizes the combined power of the
newly proposed latency model, concurrent average memory
access time, and the well-known memory-bounded speedup
model (Sun-Ni's law) to facilitate computing tasks.
Compared to traditional chip designs that lack the
notion of memory capacity and concurrency, the C 2
-Bound model finds that memory bound factors
significantly impact the optimal number of cores as
well as their optimal silicon area allocations,
especially for data-intensive applications with a
non-parallelizable sequential portion. Therefore, our
model is valuable to the design of next-generation
many-core architectures that target big data
processing, where working sets are usually larger than
the conventional scientific computing. These findings
are evidenced by our detailed simulations, which show,
with C 2 -Bound, the design space of chip design can be
narrowed down significantly up to four orders of
magnitude. C 2 -Bound analytic results can be either
used in reconfigurable hardware environments or, by
software designers, applied to scheduling,
partitioning, and allocating resources among diverse
applications.",
acknowledgement = ack-nhfb,
articleno =    "9",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Simhon:2017:ARG,
author =       "Eran Simhon and David Starobinski",
journal =      j-TOMPECS,
volume =       "2",
number =       "2",
pages =        "10:1--10:21",
month =        may,
year =         "2017",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/3053046",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:56 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=3053046",
abstract =     "Advance reservation (AR) services form a pillar of
several branches of the economy, including
transportation, lodging, dining, and, more recently,
cloud computing. In this work, we use game theory to
analyze a slotted AR system in which customers differ
in their lead times. For each given time slot, the
number of customers requesting service is a random
variable following a general probability distribution.
Based on statistical information, the customers decide
whether or not to make an advance reservation of server
resources in future slots for a fee. We prove that only
two types of equilibria are possible: either none of
the customers makes AR or only customers with lead time
greater than some threshold make AR. Our analysis
further shows that the fee that maximizes the
provider's profit may lead to other equilibria, one of
which yields zero profit. In order to prevent ending up
with no profit, the provider can elect to advertise a
lower fee yielding a guaranteed but smaller profit. We
refer to the ratio of the maximum possible profit to
the maximum guaranteed profit as the price of
conservatism. When the number of customers is a Poisson
random variable, we prove that the price of
conservatism is one in the single-server case, but can
be arbitrarily high in a many-server system.",
acknowledgement = ack-nhfb,
articleno =    "10",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Kelley:2017:OMA,
author =       "Jaimie Kelley and Christopher Stewart and Nathaniel
Morris and Devesh Tiwari and Yuxiong He and Sameh
Elnikety",
title =        "Obtaining and Managing Answer Quality for Online
Data-Intensive Services",
journal =      j-TOMPECS,
volume =       "2",
number =       "2",
pages =        "11:1--11:31",
month =        may,
year =         "2017",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/3055280",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:56 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=3055280",
abstract =     "Online data-intensive (OLDI) services use anytime
algorithms to compute over large amounts of data and
respond quickly. Interactive response times are a
priority, so OLDI services parallelize query execution
across distributed software components and return best
effort answers based on the data so far processed.
Omitted data from slow components could lead to better
could be is difficult. We propose Ubora, a design
approach to measure the effect of slow-running
components on the quality of answers. Ubora randomly
samples online queries and executes them a second time.
The first online execution omits data from slow
components and provides interactive answers. The second
execution uses mature results from intermediate
components completed after the online execution
finishes. Ubora uses memoization to speed up mature
executions by replaying network messages exchanged
between components. Our systems-level implementation
works for a wide range of services, including
Hadoop/Yarn, Apache Lucene, the EasyRec Recommendation
Engine, and the OpenEphyra question-answering system.
Ubora computes answer quality with more mature
executions per second than competing approaches that do
not use memoization. With Ubora, we show that answer
quality is effective at guiding online admission
control. While achieving the same answer quality on
higher peak throughput on low-priority queries than a
competing controller guided by the rate of timeouts.",
acknowledgement = ack-nhfb,
articleno =    "11",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}

@Article{Joshi:2017:ERT,
author =       "Gauri Joshi and Emina Soljanin and Gregory Wornell",
title =        "Efficient Redundancy Techniques for Latency Reduction
in Cloud Systems",
journal =      j-TOMPECS,
volume =       "2",
number =       "2",
pages =        "12:1--12:30",
month =        may,
year =         "2017",
CODEN =        "????",
DOI =          "https://doi.org/10.1145/3055281",
ISSN =         "2376-3639 (print), 2376-3647 (electronic)",
ISSN-L =       "2376-3639",
bibdate =      "Thu Jun 15 12:19:56 MDT 2017",
bibsource =    "http://www.math.utah.edu/pub/tex/bib/tompecs.bib",
URL =          "http://dl.acm.org/citation.cfm?id=3055281",
abstract =     "In cloud computing systems, assigning a task to
multiple servers and waiting for the earliest copy to
finish is an effective method to combat the variability
in response time of individual servers and reduce
latency. But adding redundancy may result in higher
cost of computing resources, as well as an increase in
queueing delay due to higher traffic load. This work
helps in understanding when and how redundancy gives a
cost-efficient reduction in latency. For a general task
service time distribution, we compare different
redundancy strategies in terms of the number of
redundant tasks and the time when they are issued and
canceled. We get the insight that the log-concavity of
the task service time creates a dichotomy of when
adding redundancy helps. If the service time
distribution is log-convex (i.e., log of the tail
probability is convex), then adding maximum redundancy
reduces both latency and cost. And if it is log-concave
(i.e., log of the tail probability is concave), then
less redundancy, and early cancellation of redundant
tasks is more effective. Using these insights, we
design a general redundancy strategy that achieves a
good latency-cost trade-off for an arbitrary service
time distribution. This work also generalizes and
extends some results in the analysis of fork-join
queues.",
acknowledgement = ack-nhfb,
articleno =    "12",
fjournal =     "ACM Transactions on Modeling and Performance
Evaluation of Computing Systems (TOMPECS)",
journal-URL =  "http://dl.acm.org/pub.cfm?id=J1525",
}