Karl-Johan Grinnemo

My research centers on the analysis, design, and optimization of transport services and quality of service in IP-based computer and cellular networks, with a particular focus on low-latency, high-throughput, and highly reliable communication. Motivated by the escalating demands on contemporary 4G, 5G, and next-generation cellular networks, I address the support of services with stringent performance requirements, including mission-critical and soft real-time applications.
A central aspect of my research examines multi-connectivity solutions, congestion control, and network slicing as essential mechanisms for fulfilling these requirements. I have contributed to the design of policy-based architectures for network slicing, which facilitate coordinated control across the network and end hosts to optimize transport behavior and resource utilization. This work encompasses the development of mechanisms that extend slice awareness to user equipment, enabling the dynamic adaptation of transport protocols based on slice characteristics. As a sub-project leader within the DRIVE (Data-driven Latency-sensitive Mobile Services for a Digitalized Society) research initiative, I focus on developing transport and tunneling frameworks for latency-sensitive services, including multipath-based solutions that support flexible scheduling of multiple data flows over shared tunnels and enable differentiated performance objectives.
My research further encompasses edge computing and mobile edge–cloud architectures, focusing on service placement, task offloading, and scheduling challenges. I have formulated these problems using optimization-based models, such as mixed-integer linear programming, to minimize end-to-end latency and enhance overall system efficiency. Beyond offline optimization, my recent work investigates online and adaptive methods that leverage heuristic techniques and machine learning, including reinforcement learning and sequential decision-making, to address dynamic and large-scale environments.
With the emergence of 5G, my research has increasingly concentrated on the Cellular Internet of Things (CIoT), with a particular emphasis on NB-IoT. A primary objective is to analyze and optimize the trade-offs among energy consumption, latency, and reliability across diverse network configurations. I have contributed to the development of simulation tools and experimental studies that assess the impact of protocol parameters and network configurations on CIoT device energy efficiency. More recently, my work has shown that machine learning techniques can automatically configure NB-IoT devices in 4G and 5G networks, substantially reducing power consumption while maintaining service performance.
Overall, my research seeks to deliver principled, data-driven solutions that enhance the efficiency, robustness, and performance of future cellular and IP-based networks, encompassing transport protocols, edge computing, and energy-efficient IoT systems.

I possess extensive teaching experience spanning the first-, second-, and third-cycle levels, primarily at Karlstad University, where I have been active since 2010. After my promotion to Senior Lecturer in 2015, I have consistently contributed to teaching, course development, examination, and supervision across a broad spectrum of subjects in computer science and computer engineering. Additionally, during 2009–2010, I served as Acting Senior Lecturer at KTH Royal Institute of Technology.
At Karlstad University, I have served as course responsible and lecturer for several undergraduate and graduate courses in core computer science areas, including computer networking, distributed systems, operating systems, programming, databases, and machine learning. In recent years, my teaching has focused on advanced, research-oriented graduate courses such as Advanced Communication Networks, Advanced Wireless Networks and Systems, and Introduction to Machine Learning, where I have overseen course design, examinations, and quality assurance. I have also managed large undergraduate courses, notably Computer Networking I and Operating Systems, over multiple years.
At the doctoral level, I have taught and lectured in Ph.D. courses and seminars in computer networking, and have also served as an assistant teacher in individualized doctoral courses. I regularly supervise and examine bachelor’s and master’s theses, including degree projects in computer engineering, and possess extensive experience as both thesis advisor and examiner across all academic cycles.
Earlier in my career at Karlstad University, I held roles as lecturer, assistant teacher, and lab assistant across a wide range of undergraduate courses, which provided broad pedagogical experience in teaching foundational topics and conducting hands-on laboratory instruction. This progression has given me a comprehensive understanding of curriculum coherence and student learning trajectories from introductory programming to advanced research-level topics.
During my appointment at KTH Royal Institute of Technology, I served as course responsible and lecturer for undergraduate and graduate courses in networking, communication systems, and Internet security, which further strengthened my experience in diverse academic environments.
Overall, my teaching portfolio reflects sustained engagement, increasing responsibility, and pedagogical breadth across academic levels, with a particular emphasis on networking, distributed systems, and emerging communication technologies.

I work in close collaboration with a number of highly reputable Swedish universities and research institutes, including MDU, KTH, and RISE, on various projects that have received national funding. Additionally, I partner with multiple esteemed European universities and institutes on diverse projects that receive funding from the EU. Some of the universities and institutes I work with include the University of Oslo, Simula, University of Malaga, University of Athens, Fraunhofer FOKUS, and FH Munster, among others. My aim is to leverage these partnerships to advance my research and development efforts and stay at the forefront of innovation in my research fields.

I received my Ph.D. in Computer Science from Karlstad University in June 2006. Prior to and alongside my doctoral studies, I built a solid industrial background through long-term employment at Ericsson, where I worked as a systems engineer and software designer on large-scale telecom systems. My early work included development of quality assurance and production support systems, as well as participation in Ericsson’s early Internet-related initiatives such as WAP, Bluetooth, and distributed office solutions. In the early 2000s, I worked with SS7 signaling stacks and prestudy activities related to carrier-grade telephony systems, experiences that strongly influenced my later academic research.

My doctoral research focused on transport services for soft real-time applications in IP networks, with particular emphasis on transport-layer reliability, redundancy, and availability for signaling traffic (SIGTRAN). After completing my Ph.D., I held a six-month postdoctoral position at the Department of Computer Science at Karlstad University, during which I continued my research in close collaboration with Ericsson Research in Aachen on telephone signaling over IP and SCTP. This period also included a cooperative research effort with Universitat Politècnica de Catalunya (UPC) in Barcelona on the use of SCTP in mobile networks.

In 2007, I returned to industry as a consultant at Tieto (formerly TietoEnator) in Karlstad, while remaining actively engaged in academic research as an adjunct researcher. At Tieto, I worked extensively on prestudies, system design, and implementation in projects for Ericsson, primarily within the Ericsson Connectivity Packet Platform (CPP). My work included development of SCTP functionality, alarm mechanisms, and evaluations of SCTP offload engines and fault-tolerant signaling solutions for LTE-era telecom systems. These activities maintained a strong alignment between my industrial work and academic research interests.

Between Fall 2009 and Fall 2010, I took leave from Tieto to serve as an acting senior lecturer at the School of Information and Communication Technology at the KTH Royal Institute of Technology. During this period, I initiated and led the research project Smart Session Management for Multihomed SCTP (SCTP SmartSwitch), in collaboration with Karlstad University and Ericsson Research in Kista. The project aimed to extend SCTP’s failover and changeover mechanisms with intelligent session management to support real-time and interactive applications, as well as mobile terminals with intermittent connectivity.

In Fall 2010, I was appointed to a four-year tenure-track position at Karlstad University as an Associate Senior Lecturer. My research during this period resulted in approximately ten publications and the development of an SCTP-based mobility management framework for smartphones and tablets enabling sub-second vertical handovers between 3G and Wi-Fi networks, as well as a generic SCTP-based session layer for mobility support in mobile delay-tolerant networks.

I became a Senior Lecturer at Karlstad University in 2014 and was awarded the title of Associate Professor (Swedish Docent) in Computer Science in 2016. I have authored or co-authored over 100 peer-reviewed conference and journal publications and am a Senior Member of the IEEE.

The following ten publications have been selected to provide a representative overview of my research over the past five years. The selection is based on: (i) publication in internationally established, peer-reviewed journals and conferences, (ii) relevance to my main research directions during this period, and (iii) the contributions’ connection to current and emerging communication systems, in particular low-latency and high-performance transport, L4S architecture, 5G and 6G networks, and the Cellular Internet of Things (CIoT).

The publications reflect both methodological contributions (analysis, measurement, and protocol development) and application-oriented studies of configuration, energy efficiency, and AI-based optimization in modern mobile networks.

Selected publications (2020–2025)

1. Boru Oljira, D., Grinnemo, K.-J., Brunstrom, A. and Taheri, J.
   Validating the Sharing Behavior and Latency Characteristics of the L4S Architecture. ACM SIGCOMM Computer Communication Review, vol. 50, no. 2, pp. 15–21, 2020.
2. Haile, H., Grinnemo, K.-J., Hurtig, P., Ferlin, S. and Brunstrom, A. End-to-End Congestion Control Approaches for High Throughput and Low Delay in 4G/5G Cellular Networks. Computer Networks, Elsevier, vol. 186, 2021.
3. Rabitsch, A., Grinnemo, K.-J., Brunstrom, A., Abrahamsson, H., Abdesslem, F. B. and Ahlgren, B. Utilizing Multi-Connectivity to Reduce Latency and Enhance Availability for Vehicle-to-Infrastructure Communication. IEEE Transactions on Mobile Computing, vol. 21, no. 5, pp. 1874–1891, 2022.
4. Haile, H., Grinnemo, K.-J., Hurtig, P. and Brunstrom, A.
   RBBR: A Receiver-Driven BBR in QUIC for Low-Latency in Cellular Networks. IEEE Access, vol. 10, pp. 18707–18719, 2022.
5. Abbas, M. T., Grinnemo, K.-J., Eklund, J., Brunstrom, A., Alfredsson, S., Rajiullah, M., Caso, G., Kousias, K. and Alay, Ö.
   Energy-Saving Solutions for Cellular Internet of Things – A Survey. IEEE Access, vol. 10, pp. 62073–62096, 2022.
6. Rico, D., Grinnemo, K.-J., Brunstrom, A. and Merino, P.
   Performance Analysis of the Multi-connection Tactile Internet Protocol over 5G. Journal of Network and Systems Management, Springer, vol. 31, no. 3, 2023.
7. Abbas, M. T., Grinnemo, K.-J., Brunstrom, A., Jörke, P., Eklund, J., Alfredsson, S., Rajiullah, M. and Wietfeld, C. Evaluating the Impact of Pre-configured Uplink Resources in NB-IoT. Sensors, MDPI, vol. 24, no. 17:5706, 2024.
8. Abbas, M. T., Grinnemo, K.-J., Ferré, G., Laurent, P., Alfredsson, S., Rajiullah, M. and Eklund, J. Towards Zero-Energy: Navigating the Future with 6G in Cellular Internet of Things. Journal of Networking and Computer Applications, Elsevier, vol. 230, 2024.
9. Memarian, M., Kassler, A., Grinnemo, K.-J., Laki, S., Pongracz, G. and Forsman, J. Utilizing Hybrid P4 Solutions to Enhance 5G gNB with Data Plane Programmability. IFIP Wireless and Mobile Networking Conference, 2024.
10. Abbas, M. T., Li, Y., Grinnemo, K.-J., Brunstrom, A., Eklund, J. and Rajiullah, M. Dynamic NB-IoT Configuration: A Machine Learning-Driven Optimization Framework. IEEE Internet of Things Journal, vol. 12, no. 19, pp. 40098–40114, 2025.