Change search
Link to record
Permanent link

Direct link
BETA
Publications (10 of 94) Show all publications
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
Show others...
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
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
Show others...
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
Show others...
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
Show others...
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
Oljira, D. B., Grinnemo, K.-J., Taheri, J. & Brunström, A. (2018). MDTCP: Towards a Practical Multipath Transport Protocol for Telco Cloud Datacenters. In: 9th International Conference on the Network of the Future (NOF): . Paper presented at 9th International Conference on the Network of the Future (NOF)19-21 nov 2018 (pp. 9-16). IEEE
Open this publication in new window or tab >>MDTCP: Towards a Practical Multipath Transport Protocol for Telco Cloud Datacenters
2018 (English)In: 9th International Conference on the Network of the Future (NOF), IEEE, 2018, p. 9-16Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Network congestion, MPTCP, ECN, TCP, 5G, Telco cloud, NFV, latency, cloud, datacenter
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-67241 (URN)10.1109/NOF.2018.8598129 (DOI)000458801700002 ()978-1-5386-8503-7 (ISBN)
Conference
9th International Conference on the Network of the Future (NOF)19-21 nov 2018
Projects
HITS
Available from: 2018-04-30 Created: 2018-04-30 Last updated: 2019-03-14Bibliographically approved
Gokan Khan, M., Bastani, S., Taheri, J., Kassler, A. & Deng, S. (2018). NFV-Inspector: A Systematic Approach to Profile and Analyze Virtual Network Functions. In: 2018 IEEE 7th International Conference on Cloud Networking (CloudNet): . Paper presented at 7th IEEE International Conference on Cloud Networking, CloudNet 2018, 22 October 2018 through 24 October 2018 (pp. 1-7). IEEE
Open this publication in new window or tab >>NFV-Inspector: A Systematic Approach to Profile and Analyze Virtual Network Functions
Show others...
2018 (English)In: 2018 IEEE 7th International Conference on Cloud Networking (CloudNet), IEEE, 2018, p. 1-7Conference paper, Published paper (Refereed)
Abstract [en]

Network Function Virtualization (NFV) focuses on decoupling network functions from proprietary hardware (i.e., middleboxes) by leveraging virtualization technology. Combining it with Software Defined Networking (SDN) enables us to chain network services much easier and faster. The main idea of using these technologies is to consolidate several Virtual Network Functions (VNFs) into a fewer number of commodity servers to reduce costs, increase VNFs fluidity and improve resource efficiency. However, the resource allocation and placement of VNFs in the network is a multifaceted decision problem that depends on many factors, including VNFs resource demand characteristics, arrival rate, configuration of underlying infrastructure, available resources and agreed Quality of Services (QoS) in Service Level Agreements (SLAs). This paper presents a bottom-up open-source NFV analysis platform (NFV-Inspector) to (1) systematically profile and classify VNFs based on resource capacities, traffic demand rate, underlying system properties, placement of VNFs in the network, etc. and (2) extract/calculate the correlation among the QoS metrics and resource utilization of VNFs. We evaluated our approach using an emulated virtual Evolved Packet Core platform (Open5GCore) to showcase how complex relation among various NFV service chains can be systematically profiled and analyzed.

Place, publisher, year, edition, pages
IEEE, 2018
Series
IEEE International Conference on Cloud Networking, ISSN 2374-3239
Keywords
Classification, Network Function Virtualization, Profiling, Quality of Service, Software Defined Networking, Classification (of information), Open source software, Open systems, Outsourcing, Transfer functions, Virtual reality, Decoupling network, Evolved packet cores, Resource efficiencies, Resource utilizations, Service level agreement (SLAs), Software defined networking (SDN), Virtualization technologies
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:kau:diva-71277 (URN)10.1109/CloudNet.2018.8549333 (DOI)000465081600016 ()2-s2.0-85060215258 (Scopus ID)9781538668313 (ISBN)
Conference
7th IEEE International Conference on Cloud Networking, CloudNet 2018, 22 October 2018 through 24 October 2018
Projects
NFV Optimizer, 5276
Funder
Knowledge Foundation, 20160182
Available from: 2019-02-21 Created: 2019-02-21 Last updated: 2019-07-03Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-9194-010X

Search in DiVA

Show all publications