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The impact of load comparison errors on the power-of-[formula omitted] load balancing Perform. Eval. (IF 2.2) Pub Date : 2024-02-28 Sanidhay Bhambay, Arpan Mukhopadhyay, Thirupathaiah Vasantam
We consider a system with unit-rate servers where jobs arrive according a Poisson process with rate (). In the standard or Pod scheme with , for each incoming job, a dispatcher samples servers uniformly at random and sends the incoming job to the least loaded of the sampled servers. However, in practice, load comparisons may not always be accurate. In this paper, we analyse the effects of noisy load
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A dependence graph pattern mining method for processor performance analysis Perform. Eval. (IF 2.2) Pub Date : 2024-02-28 Yawen Zheng, Chenji Han, Tingting Zhang, Fuxin Zhang, Jian Wang
As the complexity of processor microarchitecture and applications increases, obtaining performance optimization knowledge, such as critical dependent chains, becomes more challenging. To tackle this issue, this paper employs pattern mining methods to analyze the critical path of processor micro-execution dependence graphs. We propose a high average utility pattern mining algorithm called Dependence
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Accelerating multi-tier storage cache simulations using knee detection Perform. Eval. (IF 2.2) Pub Date : 2024-02-27 Tyler Estro, Mário Antunes, Pranav Bhandari, Anshul Gandhi, Geoff Kuenning, Yifei Liu, Carl Waldspurger, Avani Wildani, Erez Zadok
Storage cache hierarchies include diverse topologies, assorted parameters and policies, and devices with varied performance characteristics. Simulation enables efficient exploration of their configuration space while avoiding expensive physical experiments. Miss Ratio Curves (MRCs) efficiently characterize the performance of a cache over a range of cache sizes, revealing “key points” for cache simulation
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Age of information minimization in hybrid cognitive radio networks under a timely throughput constraint Perform. Eval. (IF 2.2) Pub Date : 2024-02-23 Mohamed F. El-Sherif, Sherif I. Rabia, Ahmed H. Abd El-Malek, W.K. Zahra
Exchanging time-critical information is prevalent in various industrial applications where low latency and timely delivery are paramount. Through this work, we consider a cognitive radio network comprised of multiple secondary users with time-sensitive traffic, and they can access the licensed channel under the hybrid interweave/underlay scheme to enhance spectrum utilization. Traffic in the secondary
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Average delay analysis of soft deadline messages scheduled in the dynamic segment of FlexRay protocol Perform. Eval. (IF 2.2) Pub Date : 2024-01-30 Sunil Kumar P.R., Vinod V., Manjunath A.S.
The FlexRay communication protocol provides high bandwidth for supporting both hard deadline and soft deadline traffic in in-vehicle communication networks. In this paper, we carry out delay analysis of soft deadline traffic which is handled by the dynamic segment of FlexRay. We model the arrival of these messages as Poisson processes, and use queuing theory to evaluate the average delay that they
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On the sensitivity of stationary solutions of Markov regenerative processes Perform. Eval. (IF 2.2) Pub Date : 2024-01-29 Junjun Zheng, Hiroyuki Okamura, Tadashi Dohi
Markov regenerative process (MRGP) is favored for modeling and evaluating system dependability due to its high power and flexibility. However, its analysis presents challenges because of its inherent renewal nature. The embedded Markov chain (EMC) method offers a stationary solution to the MRGP, while the phase expansion approach delivers both stationary and transient solutions. From these solutions
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Towards the optimal dynamic size-aware dispatching Perform. Eval. (IF 2.2) Pub Date : 2024-01-26 Esa Hyytiä, Rhonda Righter
In this paper, we study dispatching systems that appear in manufacturing, service, healthcare systems, as well as, in various information, communication and computer systems. Such systems comprise a dispatcher and a pool of parallel servers, to which jobs are assigned upon arrival. A common objective is to minimize the mean waiting or response time. In large systems, due to the state-space explosion
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Decentralized fault tolerant source localization without sensor parameters in wireless sensor networks Perform. Eval. (IF 2.2) Pub Date : 2023-12-08 Akram Hussain, Yuan Luo
In this paper, we study the source (event) localization problem in decentralized wireless sensor networks (WSNs) under faulty sensor nodes without knowledge of the sensor parameters. Source localization has many applications, such as localizing WiFi hotspots and mobile users. Some works in the literature localize the source by utilizing the knowledge or estimates of the fault probability of each sensor
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Two families of indexable partially observable restless bandits and Whittle index computation Perform. Eval. (IF 2.2) Pub Date : 2023-12-02 Nima Akbarzadeh, Aditya Mahajan
We consider the restless bandits with general finite state space under partial observability with two observational models: first, the state of each bandit is not observable at all, and second, the state of each bandit is observable when it is selected. Under the assumption that the models satisfy a restart property, we prove that both models are indexable. For the first model, we derive a closed-form
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The effect of network delays on Distributed Ledgers based on Directed Acyclic Graphs: A mathematical model Perform. Eval. (IF 2.2) Pub Date : 2023-11-25 Navdeep Kumar, Alexandre Reiffers-Masson, Isabel Amigo, Santiago Ruano Rincón
We present a new stochastic model for the evolution of Directed Acyclic Graphs (DAG)-based distributed ledgers (DL), under the presence of heterogeneous delay. This model is used to analyse the performance metrics of the DL, showing in particular that the number of unapproved messages, in expectation, does not diverge to infinity, even under the presence of delay. We propose an analysis based on conveniently
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Editorial: Special issue on IFIP performance 2023 Perform. Eval. (IF 2.2) Pub Date : 2023-11-19
Abstract not available
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Marginal and joint distribution of inter-departure times for a PH/PH/c queue Perform. Eval. (IF 2.2) Pub Date : 2023-11-04 Ruth Sagron, Yoav Kerner
In this paper, we introduce the Laplace–Stieltjes transform (LST) of the inter-departure time distribution in a PH/PH/c queue, and the two-dimensional joint LST of two consecutive inter-departure times to construct their correlation structure. We exploit the properties of phase-type (PH) random variables, as well as the steady-state distribution of the underlying continuous-time Markov chain in a PH/PH/c
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Performance of the Gittins policy in the G/G/1 and G/G/k, with and without setup times Perform. Eval. (IF 2.2) Pub Date : 2023-10-29 Yige Hong, Ziv Scully
How should we schedule jobs to minimize mean queue length? In the preemptive M/G/1 queue, we know the optimal policy is the Gittins policy, which uses any available information about jobs’ remaining service times to dynamically prioritize jobs. For models more complex than the M/G/1, optimal scheduling is generally intractable. This leads us to ask: beyond the M/G/1, does Gittins still perform well
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ASIP tandem queues with consumption Perform. Eval. (IF 2.2) Pub Date : 2023-10-18 Yaron Yeger, Onno Boxma, Jacques Resing, Maria Vlasiou
The Asymmetric Inclusion Process (ASIP) tandem queue is a model of stations in series with a gate after each station. At a gate opening, all customers in that station instantaneously move to the next station unidirectionally. In our study, we enhance the ASIP model by introducing the capability for individual customers to independently move from one station to the next, and by allowing both individual
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Quality competition among internet service providers Perform. Eval. (IF 2.2) Pub Date : 2023-10-12 Simon Scherrer, Seyedali Tabaeiaghdaei, Adrian Perrig
Internet service providers (ISPs) have a variety of quality attributes that determine their attractiveness for data transmission, ranging from quality-of-service metrics such as jitter to security properties such as the presence of DDoS defense systems. ISPs should optimize these attributes in line with their profit objective, i.e., maximize revenue from attracted traffic while minimizing attribute-related
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POBO: Safe and optimal resource management for cloud microservices Perform. Eval. (IF 2.2) Pub Date : 2023-10-10 Hengquan Guo, Hongchen Cao, Jingzhu He, Xin Liu, Yuanming Shi
Resource management in microservices is challenging due to the uncertain latency–resource relationship, dynamic environment, and strict Service-Level Agreement (SLA) guarantees. This paper presents a Pessimistic and Optimistic Bayesian Optimization framework, named POBO, for safe and optimal resource configuration for microservice applications. POBO leverages Bayesian learning to estimate the uncertain
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Online convex optimization with switching cost and delayed gradients Perform. Eval. (IF 2.2) Pub Date : 2023-10-13 Spandan Senapati, Rahul Vaze
We consider the online convex optimization (OCO) problem with quadratic and linear switching cost in the limited information setting, where an online algorithm can choose its action using only gradient information about the previous objective function. For L-smooth and μ-strongly convex objective functions, we propose an online multiple gradient descent (OMGD) algorithm and show that its competitive
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The RESET and MARC techniques, with application to multiserver-job analysis Perform. Eval. (IF 2.2) Pub Date : 2023-10-11 Isaac Grosof, Yige Hong, Mor Harchol-Balter, Alan Scheller-Wolf
Multiserver-job (MSJ) systems, where jobs need to run concurrently across many servers, are increasingly common in practice. The default service ordering in many settings is First-Come First-Served (FCFS) service. Virtually all theoretical work on MSJ FCFS models focuses on characterizing the stability region, with almost nothing known about mean response time. We derive the first explicit characterization
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Minimizing age of information under arbitrary arrival model with arbitrary packet size Perform. Eval. (IF 2.2) Pub Date : 2023-10-10 Kumar Saurav, Rahul Vaze
We consider a single source–destination pair, where information updates (in short, updates) arrive at the source at arbitrary time instants. For each update, its size, i.e. the service time required for complete transmission to the destination, is also arbitrary. At any time, the source may choose which update to transmit, while incurring transmission cost that is proportional to the duration of transmission
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Fixed confidence community mode estimation Perform. Eval. (IF 2.2) Pub Date : 2023-10-12 Meera Pai, Nikhil Karamchandani, Jayakrishnan Nair
Our aim is to estimate the largest community (a.k.a., mode) in a population composed of multiple disjoint communities. This estimation is performed in a fixed confidence setting via sequential sampling of individuals with replacement. We consider two sampling models: (i) an identityless model, wherein only the community of each sampled individual is revealed, and (ii) an identity-based model, wherein
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Load balancing policies without feedback using timed replicas Perform. Eval. (IF 2.2) Pub Date : 2023-10-11 Rooji Jinan, Ajay Badita, Tejas Bodas, Parimal Parag
Dispatching policies such as join the shortest queue (JSQ), join the queue with smallest workload (JSW), and their power of two variants are used in load balancing systems where the instantaneous queue length or workload information at all queues or a subset of them can be queried. In situations where the dispatcher has an associated memory, one can minimize this query overhead by maintaining a list
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Robust fake-post detection against real-coloring adversaries Perform. Eval. (IF 2.2) Pub Date : 2023-10-10 Khushboo Agarwal, Veeraruna Kavitha
The viral propagation of fake posts on online social networks (OSNs) has become an alarming concern. The paper aims to design control mechanisms for fake post detection while negligibly affecting the propagation of real posts. Towards this, a warning mechanism based on crowd-signals was recently proposed, where all users actively declare the post as real or fake. In this paper, we consider a more realistic
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Simulation modeling of Zoom traffic on a campus network: A case study Perform. Eval. (IF 2.2) Pub Date : 2023-10-10 Mehdi Karamollahi, Carey Williamson, Martin Arlitt
In this paper, we develop a synthetic workload model for the Zoom network application based on empirical Zoom traffic measurements from a campus network. We then use this model in a simulation study of Zoom network traffic at the campus scale. The simulation results show that hybrid learning places a substantial load on the campus network. Additional simulation experiments investigate the potential
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Probabilistic indoor tracking of Bluetooth Low-Energy beacons Perform. Eval. (IF 2.2) Pub Date : 2023-10-05 F. Serhan Daniş, Cem Ersoy, A. Taylan Cemgil
We construct a practical and real-time probabilistic framework for fine target tracking. In our scenario, a Bluetooth Low-Energy (BLE) device navigating in the environment publishes BLE packets that are captured by stationary BLE sensors. The aim is to accurately estimate the live position of the BLE device emitting these packets. The framework is built upon a hidden Markov model (HMM), the components
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The saturated Multiserver Job Queuing Model with two classes of jobs: Exact and approximate results Perform. Eval. (IF 2.2) Pub Date : 2023-10-06 Diletta Olliaro, Marco Ajmone Marsan, Simonetta Balsamo, Andrea Marin
We consider a multiserver queue where jobs request for a varying number of servers for a random service time. The requested number of servers is assigned to each job following a First-In First-Out (FIFO) order. When the number of free servers is not sufficient to accommodate the next job in line, that job and any subsequent jobs in the queue are forced to wait. As a result, not all available servers
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WattScope: Non-intrusive application-level power disaggregation in datacenters Perform. Eval. (IF 2.2) Pub Date : 2023-10-05 Xiaoding Guan, Noman Bashir, David Irwin, Prashant Shenoy
Datacenter capacity is growing exponentially to satisfy the increasing demand for many emerging computationally-intensive applications, such as deep learning. This trend has led to concerns over datacenters’ increasing energy consumption and carbon footprint. The most basic prerequisite for optimizing a datacenter’s energy- and carbon-efficiency is accurately monitoring and attributing energy consumption
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A hardware-independent time estimation method for inference process of convolutional layers on GPU Perform. Eval. (IF 2.2) Pub Date : 2023-09-20 Chengzhen Meng, Hongjun Dai
Nowadays, various AI applications based on Convolutional Neural Networks (CNNs) are widely deployed on GPU-accelerated devices. However, due to the lack of visibility into GPU internal scheduling, accurately modeling the performance of CNN inference tasks or estimating the latency of CNN tasks that are executing or waiting on the GPU is challenging. This hurts the multi-model scheduling on multi-device
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On the regret of online edge service hosting Perform. Eval. (IF 2.2) Pub Date : 2023-09-11 R. Sri Prakash, Nikhil Karamchandani, Sharayu Moharir
We consider the problem of service hosting where a service provider can dynamically rent edge resources via short term contracts to ensure better quality of service to its customers. The service can also be partially hosted at the edge, in which case, customers’ requests can be partially served at the edge. The total cost incurred by the system is modeled as a combination of the rent cost, the service
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Modeling and performance analysis of hybrid systems by queues with setup time Perform. Eval. (IF 2.2) Pub Date : 2023-09-04 Mitsuki Sato, Kohei Kawamura, Ken’ichi Kawanishi, Tuan Phung-Duc
NFV (Network Functions Virtualization) is a technology to provide network services by applying virtualization. While the virtualization technology provides flexible architecture by itself, a specific environment where physical legacy equipment and virtualized machines coexist is also considered to meet a wide range of requirements from not only users but also service providers. Motivated by such hybrid
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Stability of a stochastic ring network Perform. Eval. (IF 2.2) Pub Date : 2023-08-28 Pieter Jacob Storm, Wouter Kager, Michel Mandjes, Sem Borst
In this paper we establish a necessary and sufficient stability condition for a stochastic ring network. Such networks naturally appear in a variety of applications within communication, computer, and road traffic systems. They typically involve multiple customer types and some form of priority structure to decide which customer receives service. These two system features tend to complicate the issue
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Efficient and accurate Lyapunov function-based truncation technique for multi-dimensional Markov chains with applications to discriminatory processor sharing and priority queues Perform. Eval. (IF 2.2) Pub Date : 2023-08-10 Gagan Somashekar, Mohammad Delasay, Anshul Gandhi
Online service providers aim to satisfy the tail performance requirements of customers through Service-Level Objectives (SLOs). One approach to ensure tail performance requirements is to model the service as a Markov chain and obtain its steady-state probability distribution. However, obtaining the distribution can be challenging, if not impossible, for certain types of Markov chains, such as those
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Resource allocation for URLLC and eMBB traffic in uplink wireless networks Perform. Eval. (IF 2.2) Pub Date : 2023-07-20 Duan-Shin Lee, Cheng-Shang Chang, Ruhui Zhang, Mao-Pin Lee
In this paper we consider two resource allocation problems of URLLC traffic and eMBB traffic in uplink 5G networks. We propose to divide frequencies into a common region and a grant-based region. Frequencies in the grant-based region can only be used by eMBB traffic, while frequencies in the common region can be used by eMBB traffic as well as URLLC traffic. In the first resource allocation problem
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CLC: A cross-level program characterization method Perform. Eval. (IF 2.2) Pub Date : 2023-07-20 Li Tang, Scott Pakin
Characterization of program execution plays a key role in performance improvement. There are numerous transformations applied to each step that a program takes on its lowering from source code to a compiler intermediate representation to machine language to microarchitecture-specific execution. The unpredictable benefit of each transformation step could lead a notionally superior algorithm to exhibit
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Secrecy performance analysis of UAV-based full-duplex two-way relay NOMA system Perform. Eval. (IF 2.2) Pub Date : 2023-07-13 Thanh Trung Nguyen, Van Toan Hoang, Manh Hoang Tran, T. Thanh Huyen Le, Xuan Nam Tran
In this paper, we investigate the secrecy performance of an unmanned aerial vehicle (UAV)-based full-duplex (FD) two-way relay non-orthogonal multiple access (TWR-NOMA) system with two terrestrial users and an eavesdropper. To ensure secure communications, a UAV acts as an aerial relay station, which not only forwards confidential information to legitimate users but also keeps emitting the jamming
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Optimizing recommendations under abandonment risks: Models and algorithms Perform. Eval. (IF 2.2) Pub Date : 2023-06-21 Xuchuang Wang, Hong Xie, Pinghui Wang, John C.S. Lui
User abandonment behaviors are quite common in recommendation applications such as online shopping recommendation and news recommendation. To maximize its total “reward” under the risk of user abandonment, the online platform needs to carefully optimize its recommendations for its users. Because inappropriate recommendations can lead to user abandoning the platform, which results in a short learning
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A loss queueing game for electric vehicle charging performance evaluation Perform. Eval. (IF 2.2) Pub Date : 2023-05-18 Alix Dupont, Yezekael Hayel, Tania Jiménez, Olivier Beaude, Jean-Baptiste Breal
The demand of electricity at the Charging Stations (CSs) by Electric Vehicle (EV) users is tremendously increasing. However, EV users still face limited resources at the CSs, both in terms of the number of parking spaces equipped with a charging point, and in terms of available power. This paper deals with the choice of a CS among two CSs by the EV users in a competitive environment. The stochastic
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An analysis of probabilistic forwarding of coded packets on random geometric graphs Perform. Eval. (IF 2.2) Pub Date : 2023-02-24 B.R. Vinay Kumar, Navin Kashyap, D. Yogeshwaran
We consider the problem of energy-efficient broadcasting on large ad-hoc networks. Ad-hoc networks are generally modelled using random geometric graphs (RGGs). Here, nodes are deployed uniformly in a square area around the origin, and any two nodes which are within Euclidean distance of 1 are assumed to be able to receive each other’s broadcast. A source node at the origin encodes k data packets of
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A learning-based scheme for channel allocation to vehicular users in wireless networks Perform. Eval. (IF 2.2) Pub Date : 2023-01-20 Thi Thuy Nga Nguyen, Olivier Brun, Balakrishna J. Prabhu
Resource allocation algorithms in wireless networks can require solving complex optimization problems at every decision epoch. For large scale networks, when decisions need to be taken on time scales of milliseconds, using standard convex optimization solvers for computing the optimum can be a time-consuming affair that may impair real-time decision making. In this paper, we propose to use Data-driven
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Adaptive Intelligent Tiering for modern storage systems Perform. Eval. (IF 2.2) Pub Date : 2023-01-20 Lu Pang, Anis Alazzawe, Madhurima Ray, Krishna Kant, Jeremy Swift
Enterprise systems routinely use tiered storage consisting of a hierarchy of storage devices that vary in speed and size. One key to obtaining good performance in such a hierarchy is to migrate data elements intelligently to the appropriate tier. For example, moving the most used data towards the fastest tier and the least used data towards the slowest tier. Tiering is typically done based on usage
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Stability analysis of two-class retrial systems with constant retrial rates and general service times Perform. Eval. (IF 2.2) Pub Date : 2023-01-05 Konstantin Avrachenkov, Evsey Morozov, Ruslana Nekrasova
We establish stability criterion for a two-class retrial system with Poisson inputs, general class-dependent service times and class-dependent constant retrial rates. We also characterize an interesting phenomenon of partial stability when one orbit is tight but the other orbit goes to infinity in probability. All theoretical results are illustrated by numerical experiments.
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Practical anonymization for data streams: z-anonymity and relation with k-anonymity Perform. Eval. (IF 2.2) Pub Date : 2022-12-29 Nikhil Jha, Luca Vassio, Martino Trevisan, Emilio Leonardi, Marco Mellia
With the advent of big data and the emergence of data markets, preserving individuals’ privacy has become of utmost importance. The classical response to this need is anonymization, i.e., sanitizing the information that, directly or indirectly, can allow users’ re-identification. Among the various approaches, k-anonymity provides a simple and easy-to-understand protection. However, k-anonymity is challenging
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Asymptotic optimality of speed-aware JSQ for heterogeneous service systems Perform. Eval. (IF 2.2) Pub Date : 2022-10-13 Sanidhay Bhambay, Arpan Mukhopadhyay
The Join-the-Shortest-Queue (JSQ) load-balancing scheme is known to minimise the average delay of jobs in homogeneous systems consisting of identical servers. However, it performs poorly in heterogeneous systems where servers have different processing rates. Finding a delay optimal scheme remains an open problem for heterogeneous systems. In this paper, we consider a speed-aware version of the JSQ
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Stability and average delay in delay tolerant networks with Poisson packet arrivals and buffered relay nodes Perform. Eval. (IF 2.2) Pub Date : 2022-09-29 Vineeth B.S., Chandramani Singh
We consider a single-source single-destination delay tolerant network (DTN) with Poisson packet arrivals. The source uses a store and forward protocol which makes multiple copies of a packet to relays which buffer them until delivery to the destination. We characterize the stability threshold, defined as the maximum value of arrival rate for which the source has finite average queue length, as a function
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I/O performance analysis of machine learning workloads on leadership scale supercomputer Perform. Eval. (IF 2.2) Pub Date : 2022-09-05 Ahmad Maroof Karimi, Arnab K. Paul, Feiyi Wang
The popularity of machine learning technologies and frameworks has led to an increasingly large number of machine learning workloads running on high-performance computing (HPC) clusters. The ML workflows are readily being adopted in diverse computational fields such as Biology, Physics, Materials, and Computer Science. The I/O behavior of the emerging ML workloads distinctly differs from the traditional
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Parameter estimation of Markov modulated fluid arrival processes Perform. Eval. (IF 2.2) Pub Date : 2022-09-05 Salah Al-Deen Almousa, Gábor Horváth, Miklós Telek
Markov modulated discrete arrival processes have a wide literature, including parameter estimation methods based on expectation–maximization (EM). In this paper, we investigate the adaptation of these EM based methods to Markov modulated fluid arrival processes (MMFAP), and conclude that only the generator matrix of the modulating Markov chain of MMFAPs can be approximated by EM based method. For the
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Strategic access in a Green IoT(Internet of Things) system with an unreliable server Perform. Eval. (IF 2.2) Pub Date : 2022-08-31 Kalpana Devarajan, Muthukrishnan Senthilkumar
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Low-complexity scheduling algorithms with constant queue length and throughput guarantees Perform. Eval. (IF 2.2) Pub Date : 2022-08-28 Subrahmanya Swamy Peruru, Aravind Srinivasan, Radha Krishna Ganti, Krishna Jagannathan
Distributed scheduling algorithms based on carrier sense multiple access (CSMA) are optimal in terms of the throughput and the steady-state queue lengths. However, they take a prohibitively long time to reach the steady-state, often exponential in the network size. Therefore for large networks that operate over a finite time horizon, apart from the guarantees on the steady-state queue lengths, performance
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Performance evaluation of tape library systems Perform. Eval. (IF 2.2) Pub Date : 2022-08-28 Ilias Iliadis, Linus Jordan, Mark Lantz, Slavisa Sarafijanovic
Magnetic tape provides a cost-effective way to retain the exponentially increasing volumes of data being produced. The low cost per gigabyte and the low energy consumption render tape a preferred option over hard disk drives and flash for infrequently accessed data. Assessing the performance of tape library systems is central to achieving appropriate storage provisioning and dimensioning. Performance
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Improving Massive Access to IoT Gateways Perform. Eval. (IF 2.2) Pub Date : 2022-08-18 Erol Gelenbe, Mert Nakıp, Tadeusz Czachórski
IoT networks handle incoming packets from large numbers of IoT Devices (IoTDs) to IoT Gateways. This can lead to the IoT Massive Access Problem that causes buffer overflow, large end-to-end delays and missed deadlines. This paper analyzes a novel traffic shaping method named the Quasi-Deterministic Traffic Policy (QDTP) that mitigates this problem by shaping the incoming traffic without increasing
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Service scheduling for random requests with fixed waiting costs Perform. Eval. (IF 2.2) Pub Date : 2022-06-16 Ramya Burra, Chandramani Singh, Joy Kuri
We study service scheduling problems in a slotted system in which agents arrive with service requests according to a Bernoulli process and have to leave within two slots after arrival, service costs are quadratic in service rates, and there is also a waiting cost. We consider fixed waiting costs. We frame the problem as an average cost Markov decision process. While the studied system is a linear system
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Performance evaluation of complex multi-thread applications through execution path analysis Perform. Eval. (IF 2.2) Pub Date : 2022-03-30 Majid Rezazadeh, Naser Ezzati-Jivan, Seyed Vahid Azhari, Michel R. Dagenais
The sporadic latency problems of multi-threaded applications remain a major concern for developers. A performance issue may be caused by internal factors such as an error in the code, inadequate database design or external factors such as thread imbalances, resource contention or system overload. In complex applications such as the Chromium browser, which is our focus in this paper, being able to collect
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Analysis of an optimal policy in dynamic bipartite matching models Perform. Eval. (IF 2.2) Pub Date : 2022-02-22 Arnaud Cadas, Josu Doncel, Ana Bušić
A dynamic bipartite matching model is given by a bipartite matching graph which determines the possible matchings between the various types of supply and demand items. Both supply and demand items arrive to the system according to a stochastic process. Matched pairs leave the system and the others wait in the queues, which induces a holding cost. We model this problem as a Markov Decision Process and
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Continuous approximations of discrete phase-type distributions and their applications to reliability models Perform. Eval. (IF 2.2) Pub Date : 2022-02-09 Qi-Ming He, Baoliang Liu, Haoran Wu
Using Erlangization, we construct two types of continuous phase-type (PH) random variables that approximate discrete PH-random variables and finite discrete random variables. The key idea of the method is to use Erlang random variables to approximate constants. The approximations have (i) explicit closed form PH-representations; (ii) a small set of parameters, (iii) the same mean as the original random
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Optimal pricing in multi server systems Perform. Eval. (IF 2.2) Pub Date : 2022-01-07 Ashok Krishnan K.S., Chandramani Singh, Siva Theja Maguluri, Parimal Parag
We study optimal service pricing in server farms where customers arrive according to a renewal process and have independent and identical (i.i.d.) exponential service times and i.i.d. valuations of the service. The service provider charges a time varying service fee aiming at maximizing its revenue rate. The customers that find free servers and service fees lesser than their valuation join for the
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On the quantum performance evaluation of two distributed quantum architectures Perform. Eval. (IF 2.2) Pub Date : 2021-10-13 Gayane Vardoyan, Matthew Skrzypczyk, Stephanie Wehner
Distributed quantum applications impose requirements on the quality of the quantum states that they consume. When analyzing architecture implementations of quantum hardware, characterizing this quality forms an important factor in understanding their performance. Fundamental characteristics of quantum hardware lead to inherent tradeoffs between the quality of states and traditional performance metrics