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Analysis and Evaluation of Routing in Large-Scale Delay Tolerant Networks
, Ph.D. Dissertation Sharif University of Technology ; Movaghar, Ali (Supervisor) ; Entezari Maleki, Reza (Co-Supervisor)
Abstract
Delay-tolerant networks refer to the networks that lack stable end-to-end paths due to the high mobility of nodes. In order to tackle the intermittent connections, nodes of delay-tolerant networks store the data packets and carry them. Nodes forward data packets according to routing protocols once they enter each other's communication range. In order to increase the probability of delivery, several or many copies of a packet can be disseminated in the network. Over the past years, various routing protocols have been proposed for delay-tolerant networks. These protocols differ from each other in the number of copies that are disseminated in the network or the information used to make routing...
A probabilistic task scheduling method for grid environments
, Article Future Generation Computer Systems ; Volume 28, Issue 3 , 2012 , Pages 513-524 ; 0167739X (ISSN) ; Movaghar, A ; Sharif University of Technology
2012
Abstract
This paper presents a probabilistic task scheduling method to minimize the overall mean response time of the tasks submitted to the grid computing environments. Minimum mean response time of a given task can be obtained by finding a subset of appropriate computational resources to service the task. To achieve this, a discrete time Markov chain (DTMC) representing the task scheduling process within the grid environment is constructed. The connection probabilities between the nodes representing the grid managers and resources can be considered as transition probabilities of the obtained DTMC. Knowing the mean response times of the managers and resources, and finding fundamental matrix of the...
Availability modeling of grid computing environments using SANs
, Article 2011 International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2011, 15 September 2011 through 17 September 2011, Split, Hvar, Dubrovnik ; 2011 , Pages 403-408 ; 9789532900262 (ISBN) ; Movaghar, A ; Sharif University of Technology
2011
Abstract
In this paper, the availability of the Resource Management System (RMS) and computational resources distributed within grid computing environments is studied. Since the RMS acts as a heart of the grid environments, the unavailability of this system can render the entire environment to the inoperable phase. Furthermore, the unavailability of the grid resources may result in degradation of the performance of the grid. Therefore, considering the great importance of the availability issue in grid computing environments, the Stochastic Activity Networks (SANs) are exploited to model and evaluate the availability of grid environments. The proposed SAN models the failure of the resource management...
A genetic-based scheduling algorithm to minimize the makespan of the grid applications
, Article Communications in Computer and Information Science, 13 December 2010 through 15 December 2010 ; Volume 121 CCIS , December , 2010 , Pages 22-31 ; 18650929 (ISSN) ; 9783642176241 (ISBN) ; Movaghar, A ; Sharif University of Technology
2010
Abstract
Task scheduling algorithms in grid environments strive to maximize the overall throughput of the grid. In order to maximize the throughput of the grid environments, the makespan of the grid tasks should be minimized. In this paper, a new task scheduling algorithm is proposed to assign tasks to the grid resources with goal of minimizing the total makespan of the tasks. The algorithm uses the genetic approach to find the suitable assignment within grid resources. The experimental results obtained from applying the proposed algorithm to schedule independent tasks within grid environments demonstrate the applicability of the algorithm in achieving schedules with comparatively lower makespan in...
Performance and power modeling and evaluation of virtualized servers in IaaS clouds
, Article Information Sciences ; Volume 394-395 , 2017 , Pages 106-122 ; 00200255 (ISSN) ; Sousa, L ; Movaghar, A ; Sharif University of Technology
Elsevier Inc
2017
Abstract
In this paper, Stochastic Activity Networks (SANs) are exploited to model and evaluate the power consumption and performance of virtualized servers in cloud computing. The proposed SAN models the physical servers in three different power consumption and provisioning delay modes, switching the status of the servers according to the workload of the corresponding cluster if required. The Dynamic Voltage and Frequency Scaling (DVFS) technique is considered in the proposed model for dynamically controlling the supply voltage and clock frequency of CPUs. Thus, Virtual Machines (VMs) on top a physical server can be divided into several power consumption and processing speed groups. According to the...
Performance Modeling and Evaluation of MapReduce Applications
, Ph.D. Dissertation Sharif University of Technology ; Movaghar Rahimabadi, Ali (Supervisor) ; Entezari Maleki, Reza (Co-Supervisor)
Abstract
Businesses are dependent on mining of their Big Data more than ever and configuring clusters and frameworks to reach the best performance is still one of the challenges. An accurate performance prediction of the Big Data application helps reduce costs and SLA-violations with better tuning of the configuration parameters. Among the Big Data frameworks, Hadoop, Tez, and Apache Spark are the widely used and popular ones, with the MapReduce and graph-based workflows, usually running on top of the YARN cluster. While a great number of attempts have been made to predict the execution time of Big Data applications, to the best of our knowledge, none of them considered multiple simultaneous YARN...
Performability evaluation of grid environments using stochastic reward nets
, Article IEEE Transactions on Dependable and Secure Computing ; Volume 12, Issue 2 , 2015 , Pages 204-216 ; 15455971 (ISSN) ; Trivedi, K. S ; Movaghar, A ; Sharif University of Technology
2015
Abstract
In this paper, performance of grid computing environment is studied in the presence of failure-repair of the resources. To achieve this, in the first step, each of the grid resource is individually modeled using Stochastic Reward Nets (SRNs), and mean response time of the resource for grid tasks is computed as a performance measure. In individual models, three different scheduling schemes called random selection, non-preemptive priority, and preemptive priority are considered to simultaneously schedule local and grid tasks to the processors of a single resource. In the next step, single resource models are combined to shape an entire grid environment. Since the number of the resources in a...
Performability Modeling and Analysis in Grid Computing
, Ph.D. Dissertation Sharif University of Technology ; Movaghar Rahimabadi, Ali (Supervisor)
Abstract
In this thesis, three different mathematical models named Markov Reward Model (MRM), Stochastic Reward Net (SRN) and Stochastic Activity Network (SAN) are used to model and evaluate the performability of grid computing environments consisting of many grid resources. The proposed models consider the arriving and servicing process of grid tasks inside a resource together with the failure-repair behavior of processors of the resource. Since the proposed MRM cannot be extended to model a grid environment with some realistic assumptions, we switch to use SRNs in modeling a single grid resource with more number of processors. Although the proposed SRN models for a single grid resource can...
Performance aware scheduling considering resource availability in grid computing
, Article Engineering with Computers ; Volume 33, Issue 2 , 2017 , Pages 191-206 ; 01770667 (ISSN) ; Bagheri, M ; Mehri, S ; Movaghar, A ; Sharif University of Technology
Springer London
2017
Abstract
This paper presents a mathematical model using Stochastic Activity Networks (SANs) to model a grid resource, and compute the throughput of a resource in servicing grid tasks, wherein the failure–repair behavior of the processors inside the resource is taken into account. The proposed SAN models the structural behavior of a grid resource and evaluates the combined performance and availability measure of the resource. Afterwards, the curve fitting technique is used to find a suitable function fitted to the throughput of a resource for grid tasks. Having this function and the size of each grid job based on its tasks, an algorithm is proposed to compute the makespan of each available resource to...
IDS modelling and evaluation in WANETs against black/grey-hole attacks using stochastic models
, Article International Journal of Ad Hoc and Ubiquitous Computing ; Volume 27, Issue 3 , 2018 , Pages 171-186 ; 17438225 (ISSN) ; Gharib, M ; Khosravi, M ; Movaghar, A ; Sharif University of Technology
Inderscience Enterprises Ltd
2018
Abstract
The aim of this paper is to model and evaluate the performance of intrusion detection systems (IDSs) facing black-hole and grey-hole attacks within wireless ad hoc networks (WANETs). The main performance metric of an IDS in a WANET can be defined as the mean time required for the IDS to detect an attack. To evaluate this measure, two types of stochastic models are used in this paper. In the first step, two different continuous time Markov chains (CTMCs) are proposed to model the attacks, and then, the method of computing the mean time to attack detection is presented. Since the number of states in the proposed CTMCs grows rapidly with increasing the number of intermediate nodes and the...
Computation offloading strategy for autonomous vehicles
, Article 27th International Computer Conference, Computer Society of Iran, CSICC 2022, 23 February 2022 through 24 February 2022 ; 2022 ; 9781665480277 (ISBN) ; Karimian Aliabadi, S ; Entezari Maleki, R ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2022
Abstract
Vehicular edge computing is a progressing technology which provides processing resources to the internet of vehicles using the edge servers deployed at roadside units. Vehicles take advantage by offloading their computationintensive tasks to this infrastructure. However, concerning time-sensitive applications and the high mobility of vehicles, cost-efficient task offloading is still a challenge. This paper establishes a computation offloading strategy based on deep Q-learning algorithm for vehicular edge computing networks. To jointly minimize the system cost including offloading failure rate and the total energy consumption of the offloading process, the vehicle tasks offloading problem is...
A hybrid genetic algorithm and variable neighborhood search for task scheduling problem in grid environment
, Article Procedia Engineering ; Volume 29 , 2012 , Pages 3808-3814 ; 18777058 (ISSN) ; Khodadadi, F ; Entezari Maleki, R ; Movaghar, A ; Sharif University of Technology
2012
Abstract
This paper addresses scheduling problem of independent tasks in the market-based grid environment. In market-based grids, resource providers can charge users based on the amount of resource requested by them. In this case, scheduling algorithms should consider users' willingness to execute their applications in most economical manner. As a solution to this problem, a hybrid genetic algorithm and variable neighborhood search is presented to reduce overall cost of task executions without noticeable increment in system makespan. Simulation results show that our algorithm performs much better than other algorithms in terms of cost of task executions. Considering the negative correlation between...
Availability modeling in redundant OpenStack private clouds
, Article Software - Practice and Experience ; Volume 51, Issue 6 , 2021 , Pages 1218-1241 ; 00380644 (ISSN) ; Ataie, E ; Entezari Maleki, R ; Movaghar, A ; Sharif University of Technology
John Wiley and Sons Ltd
2021
Abstract
In cloud computing services, high availability is one of the quality of service requirements which is necessary to maintain customer confidence. High availability systems can be built by applying redundant nodes and multiple clusters in order to cope with software and hardware failures. Due to cloud computing complexity, dependability analysis of the cloud may require combining state-based and nonstate-based modeling techniques. This article proposes a hierarchical model combining reliability block diagrams and continuous time Markov chains to evaluate the availability of OpenStack private clouds, by considering different scenarios. The steady-state availability, downtime, and cost are used...
Scalable performance analysis of epidemic routing considering skewed location visiting preferences
, Article 27th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, MASCOTS 2019, 22 October 2019 through 25 October 2019 ; Volume 2019-October , 2019 , Pages 201-213 ; 15267539 (ISSN); 9781728149509 (ISBN) ; Dalili Yazdi, A ; Entezari Maleki, R ; Sousa, L ; Movaghar, A ; Sharif University of Technology
IEEE Computer Society
2019
Abstract
This paper investigates the performance of epidemic routing, in mobile social networks (MSNs), which makes use of the store-carry-forward paradigm for communication. Real-life mobility traces show that people have skewed location visiting preferences, with some places visited frequently and some others infrequently. In order to model epidemic routing in MSNs, we first analyze the time taken for a node to meet the first node belonging to a set of nodes restricted to move in a specific subarea. Afterwards, a monolithic stochastic reward net (SRN) is proposed to evaluate the delivery delay and the average number of transmissions under epidemic routing by considering skewed location visiting...
Analytical composite performance models for Big Data applications
, Article Journal of Network and Computer Applications ; Volume 142 , 2019 , Pages 63-75 ; 10848045 (ISSN) ; Ardagna, D ; Entezari Maleki, R ; Gianniti, E ; Movaghar, A ; Sharif University of Technology
Academic Press
2019
Abstract
Recent years witnessed a steep rise in data generation and, consequently, the widespread adoption of software solutions able to support data-intensive applications. Many companies currently engage in data-intensive processes, however, fully embracing a data-driven paradigm is still cumbersome, and establishing a production-ready and fine-tuned deployment is time-consuming. This situation calls for innovative models and techniques to streamline the process of deployment configuration for Big Data applications. Moreover, many companies are using Cloud deployed clusters, which represent a cost-effective alternative to installation on premises. Accurate and fast prediction of the execution time...
Modeling and evaluation of multi-hop wireless networks using SRNs
, Article IEEE Transactions on Network Science and Engineering ; Volume 8, Issue 1 , 2021 , Pages 662-679 ; 23274697 (ISSN) ; Gharib, M ; Rezaei, S ; Trivedi, K. S ; Movaghar, A ; Sharif University of Technology
IEEE Computer Society
2021
Abstract
As multi-hop wireless networks are attracting more attention, the need to evaluate their performance becomes essential. In order to evaluate the performance metrics of multi-hop wireless networks, including sending and receiving rates of a node as well as the collision probability, a model based on Stochastic Reward Nets (SRNs) is proposed. The proposed SRN models a typical node in such networks, considered as a general template to be applied to any wireless node. The SRN model of a single node is designed to take transmission effects of all neighboring nodes into account, while ignoring the ones whose transmission has no effect on the node under-study. Applying the proposed SRN to each node...
Modeling epidemic routing: capturing frequently visited locations while preserving scalability
, Article IEEE Transactions on Vehicular Technology ; Volume 70, Issue 3 , 2021 , Pages 2713-2727 ; 00189545 (ISSN) ; Dalili Yazdi, A ; Entezari Maleki, R ; Sousa, L ; Movaghar, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
This paper investigates the performance of epidemic routing in mobile social networks considering several communities which are frequently visited by nodes. To this end, a monolithic Stochastic Reward Net (SRN) is proposed to evaluate the delivery delay and the average number of transmissions under epidemic routing by considering skewed location visiting preferences. This model is not scalable enough, in terms of the number of nodes and frequently visited locations. In order to achieve higher scalability, the folding technique is applied to the monolithic model, and an approximate folded SRN is proposed to evaluate performance of epidemic routing. Discrete-event simulation is used to...
Modeling and evaluation of service composition in commercial multiclouds using timed colored petri nets
, Article IEEE Transactions on Systems, Man, and Cybernetics: Systems ; 2017 ; 21682216 (ISSN) ; Etesami, S. E ; Ghorbani, N ; Akhavan Niaki, A ; Sousa, L ; Movaghar, A ; Sharif University of Technology
2017
Abstract
The increasing demand for Web services encourages commercial cloud service providers to publish their own services with various functional and nonfunctional capabilities in different cloud platforms. The aggregation of atomic services from multiple service repositories is the main idea of the service composition concept in multiclouds. The cloud Web service composition is a suitable way for satisfying users' complex requests by integrating services from different clouds in order to create a new value-added composite service. The time required to serve a composite service by a multicloud environment is an important parameter, which depends on different factors, ranging from the service...
Modeling and evaluation of service composition in commercial multiclouds using timed colored petri nets
, Article IEEE Transactions on Systems, Man, and Cybernetics: Systems ; Volume 50, Issue 3 , 2020 , Pages 947-961 ; Etesami, S. E ; Ghorbani, N ; Akhavan Niaki, A ; Sousa, L ; Movaghar, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
The increasing demand for Web services encourages commercial cloud service providers to publish their own services with various functional and nonfunctional capabilities in different cloud platforms. The aggregation of atomic services from multiple service repositories is the main idea of the service composition concept in multiclouds. The cloud Web service composition is a suitable way for satisfying users' complex requests by integrating services from different clouds in order to create a new value-added composite service. The time required to serve a composite service by a multicloud environment is an important parameter, which depends on different factors, ranging from the service...
Fixed-point iteration approach to spark scalable performance modeling and evaluation
, Article IEEE Transactions on Cloud Computing ; 2021 ; 21687161 (ISSN) ; Aseman Manzar, M ; Entezari Maleki, R ; Ardagna, D ; Egger, B ; Movaghar, A ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2021
Abstract
Companies depend on mining data to grow their business more than ever. To achieve optimal performance of Big Data analytics workloads, a careful configuration of the cluster and the employed software framework is required. The lack of flexible and accurate performance models, however, render this a challenging task. This paper fills this gap by presenting accurate performance prediction models based on Stochastic Activity Networks (SANs). In contrast to existing work, the presented models consider multiple work queues, a critical feature to achieve high accuracy in realistic usage scenarios. We first introduce a monolithic analytical model for a multi-queue YARN cluster running DAG-based Big...