SDMob: SDN-Based Mobility Management for IoT NetworksShow others and affiliations
2022 (English)In: Journal of Sensor and Actuator Networks, E-ISSN 2224-2708, Vol. 11, no 1, article id 8Article in journal (Refereed) Published
Abstract [en]
Internet-of-Things (IoT) applications are envisaged to evolve to support mobility of devices while providing quality of service in the system. To keep the connectivity of the constrained nodes upon topological changes, it is of vital importance to enhance the standard protocol stack, including the Routing Protocol for Lossy Low-power Networks (RPL), with accurate and real-time control decisions. We argue that devising a centralized mobility management solution based on a lightweight Software Defined Networking (SDN) controller provides seamless handoff with reasonable communication overhead. A centralized controller can exploit its global view of the network, computation capacity, and flexibility, to predict and significantly improve the responsiveness of the network. This approach requires the controller to be fed with the required input and to get involved in the distributed operation of the standard RPL. We present SDMob, which is a lightweight SDN-based mobility management architecture that integrates an external controller within a constrained IoT network. SDMob lifts the burden of computation-intensive filtering algorithms away from the resource-constrained nodes to achieve seamless handoffs upon nodes’ mobility. The current work extends our previous work, by supporting multiple mobile nodes, networks with a high density of anchors, and varying hop-distance from the controller, as well as harsh and realistic mobility patterns. Through analytical modeling and simulations, we show that SDMob outperforms the baseline RPL and the state-of-the-art ARMOR in terms of packet delivery ratio and end-to-end delay, with an adjustable and tolerable overhead. With SDMob, the network provides close to 100% packet delivery ratio (PDR) for a limited number of mobile nodes, and maintains sub-meter accuracy in localization under random mobility patterns and varying network topologies. © 2022 by the authors.
Place, publisher, year, edition, pages
MDPI , 2022. Vol. 11, no 1, article id 8
Keywords [en]
6LoWPAN, Contiki, COOJA, Internet of Things, Kalman filter, Localization, Mobility management, Particle filter, RPL, Software Defined Networking (SDN)
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:ri:diva-58501DOI: 10.3390/jsan11010008Scopus ID: 2-s2.0-85123551487OAI: oai:DiVA.org:ri-58501DiVA, id: diva2:1638962
Note
Funding details: 101007273, 876038; Funding details: Stiftelsen för Strategisk Forskning, SSF; Funding details: Vetenskapsrådet, VR; Funding details: Electronic Components and Systems for European Leadership, ECSEL; Funding text 1: This work was supported by the Swedish Foundation for Strategic Research via the FiC project, by the Swedish Research Council (Vetenskapsr?det) through the MobiFog starting grant, Vinnova by the GREENER project, the ECSEL Joint Undertaking (JU) projects InSecTT, and DAIS under grant agreement No.876038 and No.101007273.The authors would like to thank Aliasghar Mohammadsalehi for sharing his implementation of ARMOR.; Funding text 2: Funding: This work was supported by the Swedish Foundation for Strategic Research via the FiC project, by the Swedish Research Council (Vetenskapsrådet) through the MobiFog starting grant, Vinnova by the GREENER project, the ECSEL Joint Undertaking (JU) projects InSecTT, and DAIS under grant agreement No.876038 and No.101007273.
2022-02-182022-02-182022-02-18Bibliographically approved