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IoT Networking Resource Allocation and Cooperation
Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The Internet of Things (IoT) promises that "anything that can be connected, will be connected". It comprises of Information and Communication Technologies that interconnect billions of physical and visual things with some "basic" intelligence. The emerging IoT services will be able to react with minimal human intervention and further contribute to the big data era that requires real-time, ultrareliable, ubiquitous, scalable, and heterogeneous operation.

This thesis is the result of our investigations on problems dealing with the evolution of such technologies. First, we explore the potential of using relay i.e., intermediate, nodes that assist users to transmit their packets in a a cellular network. Paper I provides insights into how adapting the cooperation of the relay's receiver and transmitter optimizes the network-wide throughput while the relay's queue stability is guaranteed.

The next part of the thesis copes with the resource allocation of services on IoT devices equipped with multiple network interfaces. The resources are heterogeneous and can be split among dierent interfaces. Additionally, they are not interchangeable. In paper II, we develop optimization models for this resource allocation problem, prove the complexity of the models, and derive results that give intuition into the problems. Moreover, we propose algorithms that approximate the optimal solution and show under which circumstances this is possible.

Finally, in paper III, we present a resource allocation problem specically for smart cities services. In comparison to the previous problem denition, resources are of one type but the IoT network device can oer capacities that vary over time. Furthermore, services have a tolerance regarding their preferred scheduling, namely, their allocation over time. We parametrize each service with a pricing function to indicate its tolerance to be served at the beginning of the scheduling window. We prove that the problem is computationally hard and provide numerical results to gain insight into how different pricing weight functions impact the allocations' distribution within the scheduling window.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. , 20 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1785
National Category
Communication Systems Telecommunications Computer Engineering Computer Science Computer Systems
Identifiers
URN: urn:nbn:se:liu:diva-139891Local ID: LiU-TEK-LIC-2017ISBN: 9789176854617 (print)OAI: oai:DiVA.org:liu-139891DiVA: diva2:1134728
Supervisors
Funder
EU, FP7, Seventh Framework Programme, FP7/2007-2013: Grant 609094 (RERUM), 612361 (SOrBet), 324515 (MESH-WISE), 645705 (DECADE), 318992 (WINDOW)
Available from: 2017-08-21 Created: 2017-08-21 Last updated: 2017-08-21Bibliographically approved
List of papers
1. Probabilistic Cooperation of a Full-Duplex Relay in Random Access Networks
Open this publication in new window or tab >>Probabilistic Cooperation of a Full-Duplex Relay in Random Access Networks
2017 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 5, 7394-7404 p.Article in journal (Refereed) Published
Abstract [en]

In this paper, we analyze the probabilistic cooperation of a full-duplex relay in a multiuser random-access network. The relay is equipped with on/off modes for the receiver and the transmitter independently. These modes are modeled as probabilities by which the receiver and the transmitter are activated. We provide analytical expressions for the performance of the relay queue, such as arrival and service rates, stability conditions, and the average queue size. We optimize the relays operation setup to maximize the network-wide throughput while, simultaneously, we keep the relays queue stable and lower the relays receptions and transmissions. Furthermore, we study the effect of the SINR threshold and the self-interference coefficient on the per-user and network-wide throughput. For low SINR threshold, we show under which circumstances it is beneficial to switch off the relay completely, or switch off the relays receiver only.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2017
Keyword
Cooperative communication; relays; relay networks; multiaccess communication; multiple access interference; internet of things (IoT); internet; wireless sensor networks (WSNs); body sensor networks (BSNs)
National Category
Computer Systems
Identifiers
urn:nbn:se:liu:diva-139423 (URN)10.1109/ACCESS.2016.2642540 (DOI)000403140800053 ()
Note

Funding Agencies|European Union [609094, 612361]

Available from: 2017-08-07 Created: 2017-08-07 Last updated: 2017-08-21
2. Allocation of Heterogeneous Resources of an IoT Device to Flexible Services
Open this publication in new window or tab >>Allocation of Heterogeneous Resources of an IoT Device to Flexible Services
Show others...
2016 (English)In: IEEE Internet of Things Journal, ISSN 2327-4662, Vol. 3, no 5, 691-700 p.Article in journal (Refereed) Published
Abstract [en]

Internet-of-Things (IoT) devices can be equipped with multiple heterogeneous network interfaces. An overwhelmingly large amount of services may demand some or all of these interfaces available resources. Herein, we present a precise mathematical formulation of assigning services to interfaces with heterogeneous resources in one or more rounds. For reasonable instance sizes, the presented formulation produces optimal solutions for this computationally hard problem. We prove the NP-completeness of the problem and develop two algorithms to approximate the optimal solution for big instance sizes. The first algorithm allocates the most demanding service requirements first, considering the average cost of interfaces resources. The second one calculates the demanding resource shares and allocates the most demanding of them first by choosing randomly among equally demanding shares. Finally, we provide simulation results giving insight into services splitting over different interfaces for both cases.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2016
Keyword
Internet of Things (IoT); mixed integer linear programming; network interfaces; optimization; resource management; scheduling algorithms
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-135000 (URN)10.1109/JIOT.2016.2535163 (DOI)000393047800006 ()
Note

Funding Agencies|Excellence Center at Linkoping-Lund in Information Technology; European Union [324515, 612316, 609094]

Available from: 2017-03-06 Created: 2017-03-06 Last updated: 2017-08-21Bibliographically approved

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