Amir Taherkordi

University of Oslo · Department of Informatics

Variational Autoencoders (VAEs), as a form of deep generative model, have been widely used in recent years, and shown great great peformance in a number of different domains, including image generation and anomaly detection, etc.. This paper aims to explore neural network model compression method based on VAE. The experiment uses different neural n...

Adopting serverless computing to edge networks benefits end-users from the pay-as-you-use billing model and flexible scaling of applications. This paradigm extends the boundaries of edge computing and remarkably improves the quality of services. However, due to the heterogeneous nature of computing and bandwidth resources in edge networks, it is ch...

The Industrial Internet of Things (IIoT) has revolutionized industrial sectors with enhanced connectivity, data exchange, and predictive maintenance. However, it faces various challenges from non-IID data distributions and communication overheads, to the consistency and privacy of prediction models for maintenance. Federated Learning (FL) has been...

To solve the security problems of the moving robot system in the fog network of the Industrial Internet of Things (IIoT), this paper presents a privacy‐preserving data integration scheme in the moving robot system. First, a novel data collection enhancement algorithm is proposed to enhance the image effects, and a k‐anonymous location and data priv...

With the rapid development of Mobile Edge Computing (MEC) technology, the computationally intensive requests of end devices can be offloaded to MEC servers directly, which equipped at the edge of wireless networks. Through offloading, the performances such as the execution delay as well as the energy consumption can be effectively improved, which c...

Internet of Vehicles (IoV) has attracted global research interests across extensive applications. Due to the significant increase in the number of vehicles accessing the Internet, there are several challenges in designing efficient task offloading and data caching strategies to improve the utilization of the network resource and provide the users w...

The rapid development of the Internet of Vehicles (IoV) along with the emergence of intelligent applications have put forward higher requirements for massive task offloading. Even though Mobile Edge Computing (MEC) can diminish network transmission delay and ease network congestion, the constrained heterogeneous resources of a single edge server an...

In case the spatial shape of the feature maps of the teacher in feature-based knowledge distillation (KD) is significantly greater than the student model, first, they cannot be compared directly. Second, the knowledge of these complex feature maps cannot be quite apprehensible for the student. This paper proposed a new KD, in which Tucker decomposi...

With the explosive growth of various connected devices and the supported services, the satellite-aerial-terrestrial network (SATN) can fulfill the requirements of the increasing data traffic with enlarged coverage and enhanced capacity. In particular, utilizing multiple unmanned aerial vehicles (UAVs) as relays in SATN holds great promise for bring...

Vehicle-to-Everything (V2X) communication is receiving growing attention from industry and academia as multiple pilot projects explore its capabilities and feasibility. With about 50\% of global road vehicle exports coming from the European Union (EU), and within the context of EU legislation around security and data protection, V2X initiatives mus...

Vehicle-to-Everything (V2X) communication is receiving growing attention from industry and academia as multiple pilot projects explore its capabilities and feasibility. With about 50% of global road vehicle exports coming from the European Union (EU), and within the context of EU legislation around security and data protection, V2X initiatives must...

Running computer vision applications, such as 3-D simultaneous localization and mapping (SLAM), on mobile devices requires low-latency responses and a massive amount of computation. Edge computing has been introduced to move Cloud features closer to end users, providing necessary computing and network resources for end devices. The heterogeneous ed...

Internet of Things (IoT) systems are rightly receiving considerable interest for many real-world applications, from in-body networks to satellite networks. Such a massivescale system generates a considerable amount of traffic data, making IoT systems a distributed data source generator. For many reasons, such as the functionality of IoT application...

According to the recent studies on feature-based knowledge distillation (KD), a student model will not be able to imitate a teacher’s behavior properly if there is a high variance between the inner layers of the teacher and those of the student in terms of spatial shapes. This paper proposes a hypothesis that breaking down the knowledge of feature...

Nowadays, due to the exponential and continuous expansion of new paradigms such as Internet of Things (IoT), Internet of Vehicles (IoV) and 6G, the world is witnessing a tremendous and sharp increase of network traffic. In such large‐scale, heterogeneous, and complex networks, the volume of transferred data, as big data, is considered a challenge c...

The fifth generation (5G) communication network has been developed rapidly in the past few years, which provides substantial bandwidth capacities and higher quality of service (QoS). 5G technology commercialization includes mobile edge computing and communication technologies. The increasing deployment of mobile edge computing empowered 5G infrastr...

Modern networks generate a massive amount of traffic data streams. Analysing this data is essential for various purposes, such as network resources management and cyber-security analysis. There is an urgent need for data analytic methods that can perform network data processing in an online manner based on the arrival of new data. Online machine le...

Predicting traffic flow plays an important role in reducing traffic congestion and improving transportation efficiency for smart cities. Traffic Flow Prediction (TFP) in the smart city requires efficient models, highly reliable networks, and data privacy. As traffic data, traffic trajectory can be transformed into a graph representation, so as to m...

Digital Twins are increasingly being introduced for smart manufacturing systems to improve the efficiency of the main disciplines of such systems. Formal techniques, such as graphs, are a common way of describing Digital Twin models, allowing broad types of tools to provide Digital Twin based services such as fault detection in production lines. Ob...

Network Traffic Classification (NTC) has become an important feature in various network management operations, e.g., Quality of Service (QoS) provisioning and security services. Machine Learning (ML) algorithms as a popular approach for NTC can promise reasonable accuracy in classification and deal with encrypted traffic. However, ML-based NTC tech...

The accurate detection of the mobile context information of public transportation vehicles and their passengers is a key feature to realize intelligent transportation systems. A topical example is in-vehicle presence detection that can, e.g., be used to ticket passengers automatically. Unfortunately, most existing solutions in this field suffer fro...

In smart grids, the large-scale integration of distributed renewable energy resources has enabled the provisioning of alternative sources of supply. Peer-to-peer (P2P) energy trading among local households is becoming an emerging technique that benefits both energy prosumers and operators. Since conventional energy supply is still needed to help fi...

Network Traffic Classification (NTC) has become an important component in a wide variety of network management operations, e.g., Quality of Service (QoS) provisioning and security purposes. Machine Learning (ML) algorithms as a common approach for NTC methods can achieve reasonable accuracy and handle encrypted traffic. However, ML-based NTC techni...

Wireless body area networks (WBANs) collect health‐related vital signs of human body and provide real‐time and continuous healthy and physical recreation services. Mobile edge computing (MEC) and blockchain technology can significantly improve the quality of service, security, and privacy protection in WBANs. In this paper, we propose an improved c...

Quality of Service (QoS) provisioning is based on various network management techniques including resource management and medium access control (MAC). Various techniques have been introduced to automate networking decisions, particularly at the MAC layer. Deep reinforcement learning (DRL), as a solution to sequential decision making problems, is a...

Network traffic classification (NTC) has attracted considerable attention in recent years. The importance of traffic classification stems from the fact that data traffic in modern networks is extremely complex and ever-evolving in different aspects, e.g. volume, velocity, and variety. The inherent security requirements of Internet-based application...

Internet of Things (IoT) refers to a system of interconnected heterogeneous smart devices communicating without human intervention. A significant portion of existing IoT networks is under the umbrella of ad-hoc and quasi ad-hoc networks. Ad-hoc based IoT networks suffer from the lack of resource-rich network infrastructures that are able to perform...

Modern communication systems and networks, e.g., Internet of Things (IoT) and cellular networks, generate a massive and heterogeneous amount of traffic data. In such networks, the traditional network management techniques for monitoring and data analytics face some challenges and issues, e.g., accuracy, and effective processing of big data in a rea...

Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over networks that support device-to-device (D2D) communication, e.g., D2D-enabled cellular networks and WiFi-Direct. In these ad-hoc types of IoT networks, efficient topology manag...

In this article, we present a wireless powered mobile-edge computing system consisting of a hybrid access point and multiple cooperative fogs, where the users in each cooperative fog can share communication and computation resources to improve their computation performance. Based on the classic time-division-multiple-access protocol, we propose a h...

Fog computing plays a crucial role in future smart city applications, enabling services running along the cloud-to-thing continuum with low latency and high quality of service (QoS) requirements. However, the mobility of end users in smart city systems can result in considerable network performance and QoS degradation, hence interrupting fog servic...

Wireless Sensor Networks (WSNs) typically include thousands of resource-constrained sensors to monitor their surroundings, collect information and transfer data to remote machines for further processing. Although WSNs are considered highly flexible ad-hoc networks, network management has been among fundamental challenges to address in these types o...

Wireless Body Area Network (WBAN) as one of the primary Internet of Things (IoT) provides real time and continuous healthcare monitoring and has been widely deployed to improve the quality of peoples’ life. In edge-enabled WBANs, intensive computing tasks could be offloaded to Mobile Edge Computing (MEC) servers, guaranteeing that the massive amoun...

With the rapid evolution of the Internet of Things (IoT) and the growth of IoT-generated data, cloud computing platforms have been widely used to store and process this type of data. However, cloud computing cannot handle rapidly emerging smart applications with latency-sensitive, high throughput, and high availability and reliability requirements,...

Fog computing, which provides low-latency computing services at the network edge, is an enabler for the next generation Internet of Things (IoT) systems. In scenarios such as smart cities, multiple applications are simultaneously deployed and distributed across the Cloud and fog nodes, offering various IoT-based services. Moreover, each application...

Proximity Service (ProSe), using the geographic location and device information by considering the proximity of mobile devices, enriches the services we use to interact with people and things around us. ProSe has been used in mobile social networks in proximity (MSNP), and also in smart home and building automation (Google Home). To enable ProSe in...

Thanks to its decentralized structure and immutability, blockchain technology has the potential to address relevant security and privacy challenges in the Internet of Things (IoT). In particular, by hosting and executing smart contracts, blockchain allows secure, flexible, and traceable message communication between IoT devices. The unique characte...

The convergence of Internet of Things (IoT) and the Cloud has significantly facilitated the provision and management of services in large-scale applications, such as smart cities. With a huge number of IoT services accessible through clouds, it is very important to model and expose cloud-based IoT services in an efficient manner, promising easy and...

Cloud computing has been recognized as the de facto utility computing standard for hosting and delivering services over the Internet. Cloud platforms are being rapidly adopted by business owners and end-users thanks to its many benefits to traditional computing models such as cost saving, scalability, unlimited storage, anytime anywhere access, bet...

Clouds offer flexible and economically attractive compute and storage solutions for enterprises. However, the effectiveness of cloud computing for high-performance computing (HPC) systems still remains questionable. When clouds are deployed on lossless interconnection networks, like InfiniBand (IB), challenges related to load-balancing, low-overhea...

Mobile Cyber-Physical Systems (mCPS) consist of cooperating units that often operate in an unpredictably changing environment. Thus, they need to adapt quickly to varying spatial and temporal conditions during operation, e.g., to avoid collisions. The control software of the mobile units has to reflect this complex dynamics, and traditional device-...

Mobile Edge Computing (MEC) is an emergent architecture where cloud computing services are extended to the edge of networks leveraging mobile base stations. As a promising edge technology, it can be applied to mobile, wireless and wireline scenarios, using software and hardware platforms, located at the network edge in the vicinity of end-users. ME...

Fog computing is mainly proposed for IoT applications that are geospatially distributed, large-scale, and latency sensitive. This poses new research challenges in real-time and scalable provisioning of IoT services distributed across Fog-Cloud computing platforms. Data-centric IoT services, as a dominant type of IoT services in large-scale deployme...

Autonomous systems have become more and more important in today's transport sector. They often operate in dynamic environments in which unpredictable events may occur at any time. These events may affect the safe operation of vehicles, calling for highly efficient control software technologies to reason about and react on their appearance. A crucia...

The large-scale deployments of Internet of Things (IoT) systems have introduced several new challenges in terms of processing their data. The massive amount of IoT-generated data requires design solutions to speed up data processing, scale up with the data volume and improve data adaptability and extensibility. Beyond existing techniques for IoT da...

IoT applications are essentially characterized by their highly dynamic nature, in which the configurations of both network and software systems may change. In the context of IoT software services, modifications can occur during application lifespan due to updates and amendments. Hence, third-party applications and services depending on the changed...

The applications of Cyber-Physical Systems (CPSs) in large scale, mobile and distributed systems, such as transportation and healthcare systems, foster the development of novel cross-CPS applications. Services, in such applications, enable the emergence of multiple end-to-end cyber-physical scenarios, formed dynamically based on their demands, e.g....

The capabilities of Cyber-Physical Systems (CPSs) are increasingly being extended towards new composite services deployed across a range of smart sensing and controlling devices. These services enable the emergence of multiple end-to-end cyber-physical scenarios, formed dynamically based on their demands, e.g., disaster recovery systems. In such sc...

Nowadays, the computational devices are everywhere. In malls, offices, streets, cars, and even homes, we can find devices providing and consuming functionality to improve the user satisfaction. These devices include sensors that provide information about the environment state (e.g., temperature, occupancy, light levels), service providers (e.g., In...

The challenge of designing and programming Wireless Sensor Network (WSN) applications has gained increasing attention in recent years. While most existing programming models for WSNs share the same goal of improving software modularity, there exists a gap between the structural software design patterns offered by them and the high-level description...

Wireless reprogramming of sensor nodes is a critical requirement in long-lived wireless sensor networks (WSNs) addressing several concerns, such as fixing bugs, upgrading the operating system and applications, and adapting applications behavior according to the physical environment. In such resource-poor platforms, the ability to efficiently delimi...

The (future) Internet of Things (IoT), with service composition point of view, raises additional challenges especially with respect to handling the scale, dynamicity and heterogeneity of the target networking environment. Therefore, the services offered by IoT resources can not be composed by simply extending existing Service Oriented Architecture...

Wireless sensor networks (WSNs) are being extensively deployed today in various monitoring and control applications by enabling rapid deployments at low cost and with high flexibility. However, high-level software development is still one of the major challenges to wide-spread WSN adoption. The success of high-level programming approaches in WSNs i...

The use of resource-constrained devices, such as smartphones, PDAs, Tablet PCs, and Wireless Sensor Networks (WSNs) is spreading rapidly in the business community and our daily life. Accessing services from such devices is very common in ubiquitous environments, but mechanisms to describe, implement and distribute these services remain a major chal...

The use of resource-constrained devices, such as smartphones, PDAs, Tablet PCs, and Wireless Sensor Networks (WSNs) is spreading rapidly in the business community and our daily life. Accessing services from such devices is very common in ubiquitous environments, but mechanisms to describe, implement and distribute these services remain a major chal...

One of the recent trends in networking has been concentrated on realizing all-IP mobile networks, together with new Internet applications and services. For the next generation of all-IP mobile networks, one of the challenging issues is mobility management. The contribution of this chapter is multifold. First, the state of the art in mobility manage...

Next-generation sensor applications require system software and middleware that can be dynamically adapted to meet resource constraints on sensor nodes, as well as application-specific requirements. The reflective middleware model has emerged as a de facto standard to attain inspection and adaptation in dynamic software systems. However, prior refl...

The increasing number of distributed applications over Wireless Sensor Networks (WSNs) in ubiquitous environments raises the need for high-level mechanisms to distribute sensor services and integrate them in modern IT systems. Existing work in this area mostly focuses on low-level networking issues, and fails to provide high-level and off-the-shelf...

The success of high-level programming models in Wireless Sensor Networks (WSNs) is heavily dependent on factors such as ease of programming, code well-structuring, degree of code reusability, and required software development effort. Component-based programming has been recognized as an effective approach to meet such requirements. Most of componen...

More and more home devices are equipped with advanced computational capabilities to improve the user satisfaction (e.g., programmable heating system, Internet TV). Although these devices exhibit communication capabilities, their integration into a larger home monitoring system remains a challenging task, partly due to the strong heterogeneity of te...

Purpose – The purpose of this paper is to describe the required functionalities on providing Internet connectivity and mobility management for mobile ad-hoc networks (MANETs), present discovered problems such as inconsistent contexts, and provide the corresponding solutions. It also provides a hybrid metric for the load-balance of intra/inter-MANET...

Context-aware environments are being populated with Wireless Sensor Networks (WSNs), observing sensory context elements, and adapting their behavior accordingly. Although adaptation has been known as a common approach for addressing context-awareness, the resource-scarceness of WSNs raises the requirements for lightweight adaptations. The related w...