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Publications (10 of 97) Show all publications
Bhamare, D., Kassler, A., Vestin, J., Khoshkholghi, M. A. & Taheri, J. (2019). IntOpt: In-Band Network Telemetry Optimization for NFV Service Chain Monitoring. In: 2019 IEEE International Conference on Communications (ICC) Próceedings: . Paper presented at IEEE ICC 2019: IEEE International Conference on Communications 2019 Shanghai, China 20-24 May.
Open this publication in new window or tab >>IntOpt: In-Band Network Telemetry Optimization for NFV Service Chain Monitoring
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2019 (English)In: 2019 IEEE International Conference on Communications (ICC) Próceedings, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Managing and scaling virtual network function(VNF) service chains require the collection and analysis ofnetwork statistics and states in real time. Existing networkfunction virtualization (NFV) monitoring frameworks either donot have the capabilities to express the range of telemetryitems needed to perform management or do not scale tolarge traffic volumes and rates. We present IntOpt, a scalableand expressive telemetry system designed for flexible VNFservice chain network monitoring using active probing. IntOptallows to specify monitoring requirements for individual servicechain, which are mapped to telemetry item collection jobsthat fetch the required telemetry items from P4 (programmingprotocol-independent packet processors) programmable dataplaneelements. In our approach, the SDN controller creates theminimal number of monitoring flows to monitor the deployedservice chains as per their telemetry demands in the network.We propose a simulated annealing based random greedy metaheuristic(SARG) to minimize the overhead due to activeprobing and collection of telemetry items. Using P4-FPGA, webenchmark the overhead for telemetry collection and compareour simulated annealing based approach with a na¨ıve approachwhile optimally deploying telemetry collection probes. Ournumerical evaluation shows that the proposed approach canreduce the monitoring overhead by 39% and the total delays by57%. Such optimization may as well enable existing expressivemonitoring frameworks to scale for larger real-time networks.

Keywords
In-band Network Telemetry, Monitoring, P4, Service Function Chain, Software Defined Networks
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-74631 (URN)10.1109/ICC.2019.8761722 (DOI)978-1-5386-8089-6 (ISBN)978-1-5386-8088-9 (ISBN)
Conference
IEEE ICC 2019: IEEE International Conference on Communications 2019 Shanghai, China 20-24 May
Projects
HITS, 4707
Funder
Knowledge Foundation
Available from: 2019-09-04 Created: 2019-09-04 Last updated: 2019-09-19Bibliographically approved
Nguyen, V.-G., Carlsson, A., Grinnemo, K.-J., Cheng, J., Taheri, J. & Brunström, A. (2019). On the Use of 5G for Inter-substation GOOSE Transmission in Smart Grid. In: Proceedings of the Fifteenth Swedish National Computer Workshop (SNCNW), Luleå, Sweden. June 2019: . Paper presented at 15th Swedish National Computer Networking Workshop SNCNW 2019. 4-5 juni, 2019. Luleå, Sweden..
Open this publication in new window or tab >>On the Use of 5G for Inter-substation GOOSE Transmission in Smart Grid
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2019 (English)In: Proceedings of the Fifteenth Swedish National Computer Workshop (SNCNW), Luleå, Sweden. June 2019, 2019Conference paper, Oral presentation only (Refereed)
Abstract [en]

Protection and automation in a smart grid environmentoften have stringent real-time communication requirementsbetween devices within a substation as well as between distantlylocated substations. The Generic Object Oriented SubstationEvent (GOOSE) messaging service has been proposed to achievethis goal as it allows to transfer time-critical information within afew milliseconds. However, the transmission of GOOSE messagesare often limited to a small Local Area Network (LAN).In this paper, we propose the use of the fifth generation ofmobile networks (5G) as a means to transport GOOSE messagesin a large scale smart grid environment. The end-to-end delay ismeasured between GOOSE devices over an 5G network with thefocus on the core network using the Open5GCore platform in alab environment. Although there is a lack of a real radio accessnetwork, the experimental results confirm that the delay withinthe rest of the 5G network is small enough for it to be feasiblefor inter-substation GOOSE transmissions.

National Category
Telecommunications
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-72435 (URN)
Conference
15th Swedish National Computer Networking Workshop SNCNW 2019. 4-5 juni, 2019. Luleå, Sweden.
Projects
HITS, 4707
Funder
Knowledge Foundation
Available from: 2019-06-12 Created: 2019-06-12 Last updated: 2019-07-17Bibliographically approved
Khoshkholghi, M. A., Taheri, J., Bhamare, D. & Kassler, A. (2019). Optimized Service Chain Placement Using Genetic Algorithm. In: Christian Jacquenet, Filip De Turck, Prosper Chemouil, Flavio Esposito, Olivier Festor, Walter Cerroni, Stefano Secci (Ed.), Proceedings of the 2019 IEEE Conference on Network Softwarization NetSoft 2019, Unleasing the Power of Network Softwarization: . Paper presented at Network Softwarization (NetSoft), IEEE Conference on 24-28 June Paris, France. IEEE
Open this publication in new window or tab >>Optimized Service Chain Placement Using Genetic Algorithm
2019 (English)In: Proceedings of the 2019 IEEE Conference on Network Softwarization NetSoft 2019, Unleasing the Power of Network Softwarization / [ed] Christian Jacquenet, Filip De Turck, Prosper Chemouil, Flavio Esposito, Olivier Festor, Walter Cerroni, Stefano Secci, IEEE, 2019Conference paper (Refereed)
Abstract [en]

Network Function Virtualization (NFV) is anemerging technology to consolidate network functions onto highvolume storages, servers and switches located anywhere in thenetwork. Virtual Network Functions (VNFs) are chainedtogether to provide a specific network service. Therefore, aneffective service chain placement strategy is required tooptimize the resource allocation and consequently to reduce theoperating cost of the substrate network. To this end, we proposefour genetic-based algorithms using roulette wheel andtournament selection techniques in order to place service chainsconsidering two different placement strategies. Since mappingof service chains sequentially (One-at-a-time strategy) may leadto suboptimal placement, we also propose Simultaneous strategythat places all service chains at the same time to improveperformance. Our goal in this work is to reduce deployment costof VNFs while satisfying constraints. We consider Geantnetwork as the substrate network along with its characteristicsextracted from SndLib. The proposed algorithms are able toplace service chains with any type of service graph. Theperformance benefits of the proposed algorithms arehighlighted through extensive simulations.

Place, publisher, year, edition, pages
IEEE, 2019
Keywords
Network Function Virtualization, Optimization, Genetic Algorithm, Service Chain Placement
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-74619 (URN)10.1109/NETSOFT.2019.8806644 (DOI)978-1-5386-9376-6 (ISBN)978-1-5386-9377-3 (ISBN)
Conference
Network Softwarization (NetSoft), IEEE Conference on 24-28 June Paris, France
Projects
HITS, 4707
Funder
Knowledge Foundation
Available from: 2019-09-04 Created: 2019-09-04 Last updated: 2019-09-04
Fazio, M., Ranjan, R., Girolami, M., Taheri, J., Dustdar, S. & Villari, M. (2018). A Note on the Convergence of IoT, Edge, and Cloud Computing in Smart Cities. IEEE Cloud Computing, 5(5), 22-24
Open this publication in new window or tab >>A Note on the Convergence of IoT, Edge, and Cloud Computing in Smart Cities
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2018 (English)In: IEEE Cloud Computing, ISSN 2325-6095, Vol. 5, no 5, p. 22-24Article in journal (Refereed) Published
Abstract [en]

The purpose of the special issue is to cover all aspects of design and implementation, as well as deployment and evaluation of solutions aimed at the osmotic convergence of IoT, edge, and cloud computing, with specific reference to the smart cities application scenario.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70068 (URN)10.1109/MCC.2018.053711663 (DOI)000447944400004 ()
Available from: 2018-11-08 Created: 2018-11-08 Last updated: 2019-03-14Bibliographically approved
Gokan Khan, M., Taheri, J., Kassler, A. & Darula, M. (2018). Automated Analysis and Profiling of VirtualNetwork Functions: the NFV-Inspector Approach. In: 2018 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN): . Paper presented at IEEE Conference on Network Function Virtulization and Software defined Networks, Verona, Italy, 27-29 November 2018. IEEE
Open this publication in new window or tab >>Automated Analysis and Profiling of VirtualNetwork Functions: the NFV-Inspector Approach
2018 (English)In: 2018 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), IEEE, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Discovering insights about Virtual Network Function (VNFs) resource demand characteristics will enable cloud vendors to optimize their underlying Network Function Virtualization (NFV) system orchestration and dramatically mitigate CapEx and OpEx spendings. However, analyzing large-scale NFV systems, especially in mobile network environments, is a challenging task and requires tailor-made approaches for each particular application. In this demo, we showcase NFV-Inspector, an open source and extensible VNF analysis platform that is capable of systematically benchmark and profile NFV deployments. Based on its pluggable framework, NFV-Inspector classifies VNFs resource demand characteristics and correlate their Key Performance Indicators (KPIs) with system-level Quality of Service (QoS) measurements. 

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Classification, Network Function Virtualization, Platform, Profiling, Quality of Service
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-71388 (URN)10.1109/NFV-SDN.2018.8725697 (DOI)000475896900023 ()978-1-5386-8281-4 (ISBN)978-1-5386-8282-1 (ISBN)
Conference
IEEE Conference on Network Function Virtulization and Software defined Networks, Verona, Italy, 27-29 November 2018
Projects
NFV Optimizer, 5276
Funder
Knowledge Foundation, 20160182
Note

Available from: 2019-02-28 Created: 2019-02-28 Last updated: 2019-08-06Bibliographically approved
Taheri, J. (Ed.). (2018). Big Data and Software Defined Networks (1ed.). London: The Institution of Engineering and Technology
Open this publication in new window or tab >>Big Data and Software Defined Networks
2018 (English)Collection (editor) (Refereed)
Place, publisher, year, edition, pages
London: The Institution of Engineering and Technology, 2018. p. 504 Edition: 1
Keywords
bandwidth allocation; software defined networking; information analysis; resource allocation; Big Data; message passing
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-67208 (URN)10.1049/PBPC015E (DOI)978-1-78561-304-3 (ISBN)978-1-78561-305-0 (ISBN)
Available from: 2018-04-27 Created: 2018-04-27 Last updated: 2018-06-25Bibliographically approved
Cho, D., Bastani, S., Taheri, J. & Zomaya, A. Y. (2018). Big Data helps SDN to optimize its controllers (1ed.). In: Javid Taheri (Ed.), Big Data and Software Defined Networks: (pp. 389-408). London: The Institution of Engineering and Technology
Open this publication in new window or tab >>Big Data helps SDN to optimize its controllers
2018 (English)In: Big Data and Software Defined Networks / [ed] Javid Taheri, London: The Institution of Engineering and Technology , 2018, 1, p. 389-408Chapter in book (Refereed)
Abstract [en]

In this chapter, we first discuss the basic features and recent issues of the SDN control plane, notably the controller element. Then, we present feasible ideas to address the SDN controller-related problems using Big Data analytics techniques. Accordingly, we propose that Big Data can help various aspects of the SDN controller to address scalability issue and resiliency problem. Furthermore, we proposed six applicable scenarios for optimizing the SDN controller using the Big Data analytics: (i) controller scale-up/out against network traffic concentration, (ii) controller scale-in for reduced energy usage, (iii) backup controller placement for fault tolerance and high availability, (iv) creating backup paths to improve fault tolerance, (v) controller placement for low latency between controllers and switches, and (vi) flow rule aggregation to reduce the SDN controller's traffic. Although real-world practices on optimizing SDN controllers using Big Data are absent in the literature, we expect scenarios we highlighted in this chapter to be highly applicable to optimize the SDN controller in the future.

Place, publisher, year, edition, pages
London: The Institution of Engineering and Technology, 2018 Edition: 1
Keywords
telecommunication traffic; computer network reliability; Big Data; fault tolerance; data analysis; software defined networking
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-67215 (URN)10.1049/PBPC015E_ch19 (DOI)978-1-78561-304-3 (ISBN)978-1-78561-305-0 (ISBN)
Available from: 2018-04-27 Created: 2018-04-27 Last updated: 2018-06-26Bibliographically approved
Deng, S., Xiang, Z., Yin, J., Taheri, J. & Zomaya, A. Y. (2018). Composition-Driven IoT Service Provisioning in Distributed Edges. IEEE Access, 6, 54258-54269
Open this publication in new window or tab >>Composition-Driven IoT Service Provisioning in Distributed Edges
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2018 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 6, p. 54258-54269Article in journal (Refereed) Published
Abstract [en]

The increasing number of Internet of Thing (IoT) devices and services makes it convenient for people to sense the real world and makes optimal decisions or complete complex tasks with them. However, the latency brought by unstable wireless networks and computation failures caused by constrained resources limit the development of IoT. A popular approach to solve this problem is to establish an IoT service provision system based on a mobile edge computing (MEC) model. In the MEC model, plenty of edge servers are placed with access points via wireless networks. With the help of cached services on edge servers, the latency can be reduced, and the computation can be offloaded. The cache services must be carefully selected so that many requests can by satisfied without overloading resources in edge servers. This paper proposes an optimized service cache policy by taking advantage of the composability of services to improve the performance of service provision systems. We conduct a series of experiments to evaluate the performance of our approach. The result shows that our approach can improve the average response time of these IoT services.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Mobile edge computing, Internet of Thing, service provisioning, service composition
National Category
Computer and Information Sciences
Research subject
Mathematics; Computer Science
Identifiers
urn:nbn:se:kau:diva-70056 (URN)10.1109/ACCESS.2018.2871475 (DOI)000448016000001 ()
Available from: 2018-11-07 Created: 2018-11-07 Last updated: 2018-11-23Bibliographically approved
Casas, I., Taheri, J., Ranjan, R., Wang, L. & Zomaya, A. (2018). GA-ETI: An enhanced genetic algorithm for the scheduling of scientific workflows in cloud environments. Journal of Computational Science, 26, 318-331
Open this publication in new window or tab >>GA-ETI: An enhanced genetic algorithm for the scheduling of scientific workflows in cloud environments
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2018 (English)In: Journal of Computational Science, ISSN 1877-7503, E-ISSN 1877-7511, Vol. 26, p. 318-331Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Cloud computing; Scientific workflow; Scheduling algorithms; Genetic algorithm; Virtual machine
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-45845 (URN)10.1016/j.jocs.2016.08.007 (DOI)000438001600033 ()
Available from: 2016-09-12 Created: 2016-09-12 Last updated: 2018-08-16Bibliographically approved
Nguyen, V.-G., Grinnemo, K.-J., Taheri, J. & Brunström, A. (2018). Load balancing for a Virtual and Distributed MME using Weighted Round Robin. In: The Fourteenth Swedish National Computer Networking Workshop (SNCNW), Karlskrona, Sweden. May 2018: . Paper presented at The Fourteenth Swedish National Computer Networking Workshop (SNCNW).
Open this publication in new window or tab >>Load balancing for a Virtual and Distributed MME using Weighted Round Robin
2018 (English)In: The Fourteenth Swedish National Computer Networking Workshop (SNCNW), Karlskrona, Sweden. May 2018, 2018Conference paper, Published paper (Other academic)
Abstract [en]

In this paper, we aim at tackling the scalability ofthe Mobility Management Entity (MME) which is one of the key control plane entities of the 4G Evolved Packet Core (EPC). One of the solutions to this problem is to virtualize the MME by adopting the Network Function Virtualization (NFV) technology and deploy it as a pool of virtualized instances (vMMEs) with a frontend load balancer. Although several designs have been proposed, a large part of them does not consider the load balancing aspect. To this end, we propose using a Weighted Round Robin (WRR) algorithm for balancing signaling load in a MME architecture. We implement and compare its performance to two currently used algorithms: random and round robin. Experimental results show that the WRR algorithm can significantly reduce the control plane latency as compared to the other two schemes.

National Category
Telecommunications
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-70608 (URN)
Conference
The Fourteenth Swedish National Computer Networking Workshop (SNCNW)
Projects
High Quality Networked Services in a Mobile World (HITS)
Funder
Knowledge Foundation
Available from: 2018-12-22 Created: 2018-12-22 Last updated: 2019-06-17
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9194-010X

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