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Mobile Publish/Subscribe System for Intelligent Transport Systems over a Cloud Environment
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science. (Distributed Systems and Communications Research Group (DISCO))
Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Computer Science. (DISCO)ORCID iD: 0000-0002-9446-8143
Croatia.
Croatia.
2014 (English)In: 2014 International Conference on Cloud and Autonomic Computing (ICCAC 2014): Proceedings of a meeting held 8-12 September 2014, London, United Kingdom, IEEE Press, 2014, p. 187-195Conference paper, Published paper (Refereed)
Abstract [en]

With the advent of Smart Cities, public transport authorities are more and more interested in Intelligent Transport System (ITS) applications that allow to process a large amount of static and real time data in order to make public transport smarter. However, deploying such applications in a large scale distributed environment is challenging and requires an automated, scalable, flexible, elastic, loosely-coupled communication models in order to dynamically link information providers and consumers. To this end, Publish/Subscribe (Pub/Sub) systems offer an asynchronous, dynamic, decoupled interaction scheme that is perfectly suitable for developing up-to-date, large-scale distributed applications within the ITS domain. In addition, cloud computing offers computational resources as services to utility driven model regardless of considering geographical locations in a scalable, elastic, fault tolerant and cost-effective way. In this work, we build an ITS application “Real-time Public Transit Tracking” on top of a Mobile Pub/Sub System (MoPS), and deploy it over an open source cloud platform, OpenStack, in order to achieve high performance and flexible management. We conduct a set of experiments to evaluate the performance of the implemented ITS application in terms of scalability, resource usage, and efficiency of the underlying matching algorithm under automated mobility of the subscribers. Our experimental results show that the ITS application can handle a large number of subscribers and publishers with proper reliability and negligible notification delay under real-time constraints. Further, we present a measurement study to characterize the impact of different workloads on the performance of OpenStack.

Place, publisher, year, edition, pages
IEEE Press, 2014. p. 187-195
Keyword [en]
Publish/Subscribe System; Mobility; Cloud Computing; OpenStack; Intelligent Transport System (ITS)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kau:diva-35387DOI: 10.1109/ICCAC.2014.15ISI: 000370731000024ISBN: 9781479958429 (print)OAI: oai:DiVA.org:kau-35387DiVA, id: diva2:795154
Conference
The IEEE International Conference on Cloud and Autonomic Computing 8-12 sept London UK (CAC 2014)
Available from: 2015-03-13 Created: 2015-03-13 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Architectural Evolution of Intelligent Transport Systems (ITS) using Cloud Computing
Open this publication in new window or tab >>Architectural Evolution of Intelligent Transport Systems (ITS) using Cloud Computing
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

With the advent of Smart Cities, Intelligent Transport System (ITS) has become an efficient way of offering an accessible, safe, and sustainable transportation system. Utilizing advances in Information and Communication Technology (ICT), ITS can maximize the capacity of existing transportation system without building new infrastructure. However, in spite of these technical feasibilities and significant performance-cost ratios, the deployment of ITS is limited in the real world because of several challenges associated with its architectural design.

This thesis studies how to design a highly flexible and deployable architecture for ITS, which can utilize the recent technologies such as - cloud computing and the publish/subscribe communication model. In particular, our aim is to offer an ITS infrastructure which provides the opportunity for transport authorities to allocate on-demand computing resources through virtualization technology, and supports a wide range of ITS applications. We propose to use an Infrastructure as a Service (IaaS) model to host large-scale ITS applications for transport authorities in the cloud, which reduces infrastructure cost, improves management flexibility and also ensures better resource utilization. Moreover, we use a publish/subscribe system as a building block for developing a low latency ITS application, which is a promising technology for designing scalable and distributed applications within the ITS domain. Although cloud-based architectures provide the flexibility of adding, removing or moving ITS services within the underlying physical infrastructure, it may be difficult to provide the required quality of service (QoS) which decrease application productivity and customer satisfaction, leading to revenue losses. Therefore, we investigate the impact of service mobility on related QoS in the cloud-based infrastructure. We investigate different strategies to improve performance of a low latency ITS application during service mobility such as utilizing multiple paths to spread network traffic, or deploying recent queue management schemes.

Evaluation results from a private cloud testbed using OpenStack show that our proposed architecture is suitable for hosting ITS applications which have stringent performance requirements in terms of scalability, QoS and latency.

Abstract [en]

Baksidestext:

Intelligent Transport System (ITS) can utilize advances in Information and Communication Technology (ICT) and maximize the capacity of existing transportation systems without building new infrastructure. However, in spite of these technical feasibilities and significant performance-cost ratios, the deployment of ITS is limited in the real world because of several challenges associated with its architectural design.  This thesis studies how to design an efficient deployable architecture for ITS, which can utilize the advantages of cloud computing and the publish/subscribe communication model. In particular, our aim is to offer an ITS infrastructure which provides the opportunity for transport authorities to allocate on-demand computing resources through virtualization technology, and supports a wide range of ITS applications. We propose to use an Infrastructure as a Service (IaaS) model to host large-scale ITS applications, and to use a publish/subscribe system as a building block for developing a low latency ITS application. We investigate different strategies to improve performance of an ITS application during service mobility such as utilizing multiple paths to spread network traffic, or deploying recent queue management schemes.

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2015. p. 24
Series
Karlstad University Studies, ISSN 1403-8099 ; 2015:21
Keyword
ITS, cloud computing, OpenStack, virtualization, asynchronous communication, publish/subscribe system, scalability, distributed architecture, QoS, latency.
National Category
Engineering and Technology
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-35719 (URN)978-91-7063-635-6 (ISBN)
Presentation
2015-05-22, 21A 342, Karlstads universitet, Karlstad, 09:15 (English)
Opponent
Supervisors
Note

Artikel 4 Network Centric Performance Improvement for Live VM Migration finns i avhandlingen som manuskript. Nu publicerat konferenspaper. 

Available from: 2015-04-30 Created: 2015-03-27 Last updated: 2016-09-21Bibliographically approved
2. Cost- and Performance-Aware Resource Management in Cloud Infrastructures
Open this publication in new window or tab >>Cost- and Performance-Aware Resource Management in Cloud Infrastructures
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

High availability, cost effectiveness and ease of application deployment have accelerated the adoption rate of cloud computing. This fast proliferation of cloud computing promotes the rapid development of large-scale infrastructures. However, large cloud datacenters (DCs) require infrastructure, design, deployment, scalability and reliability and need better management techniques to achieve sustainable design benefits. Resources inside cloud infrastructures often operate at low utilization, rarely exceeding 20-30%, which increases the operational cost significantly, especially due to energy consumption. To reduce operational cost without affecting quality of service (QoS) requirements, cloud applications should be allocated just enough resources to minimize their completion time or to maximize utilization. 

The focus of this thesis is to enable resource-efficient and performance-aware cloud infrastructures by addressing above mentioned cost and performance related challenges. In particular, we propose algorithms, techniques, and deployment strategies for improving the dynamic allocation of virtual machines (VMs) into physical machines (PMs). 

For minimizing the operational cost, we mainly focus on optimizing energy consumption of PMs by applying dynamic VM consolidation methods. To make VM consolidation techniques more efficient, we propose to utilize multiple paths to spread traffic and deploy recent queue management schemes which can maximize network resource utilization and reduce both downtime and migration time for live migration techniques. In addition, a dynamic resource allocation scheme is presented to distribute workloads among geographically dispersed DCs considering their location based time varying costs due to e.g. carbon emission or bandwidth provision. For optimizing performance level objectives, we focus on interference among applications contending in shared resources and propose a novel VM consolidation scheme considering sensitivity of the VMs to their demanded resources. Further, to investigate the impact of uncertain parameters on cloud resource allocation and applications’ QoS such as unpredictable variations in demand, we develop an optimization model based on the theory of robust optimization. Furthermore, in order to handle the scalability issues in the context of large scale infrastructures, a robust and fast Tabu Search algorithm is designed and evaluated.

Abstract [en]

High availability, cost effectiveness and ease of application deployment have accelerated the adoption rate of cloud computing. This fast proliferation of cloud computing promotes the rapid development of large-scale infrastructures. However, large cloud datacenters (DCs) require infrastructure, design, deployment, scalability and reliability and need better management techniques to achieve sustainable design benefits. Resources inside cloud infrastructures often operate at low utilization, rarely exceeding 20-30%, which increases the operational cost significantly, especially due to energy consumption. To reduce operational cost without affecting quality of service (QoS) requirements, cloud applications should be allocated just enough resources to minimize their completion time or to maximize utilization. 

The focus of this thesis is to enable resource-efficient and performance-aware cloud infrastructures by addressing above mentioned cost and performance related challenges. In particular, we propose algorithms, techniques, and deployment strategies for improving the dynamic allocation of virtual machines (VMs) into physical machines (PMs).

Place, publisher, year, edition, pages
Karlstad: Karlstads universitet, 2017. p. 252
Series
Karlstad University Studies, ISSN 1403-8099 ; 2017:21
Keyword
Cloud Computing, OpenStack, Robust Optimization, Latency, Tabu Search, Resource Management, Resource Contention, QoS
National Category
Communication Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-48482 (URN)978-91-7063-783-4 (ISBN)978-91-7063-784-1 (ISBN)
Public defence
2017-06-21, 21A342 (Eva Erikssonsalen), Universitetsgatan 2, 651 88 Karlstad, Karlstad, 10:30 (English)
Opponent
Supervisors
Note

Paper 8 "Robust optimization for energy-efficient virtual machine consolidation in modern datacenters" ingick i avhandlingen som manuskript, nu publicerad. 

Paper 5 "Cost- and Performance-Aware Resource Management in Cloud Infrastructures" ingick i avhandlingen som manuskript nu konferensbidrag

Available from: 2017-05-19 Created: 2017-05-04 Last updated: 2018-05-15Bibliographically approved

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Nasim, RobayetKassler, Andreas

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