arXiv subjects

Admela Jukan

Publications and source records attributed to Admela Jukan.

At least 55 records · Page 3Linked to original sources

arXiv2021

Performance Analysis of MDPC and RS codes in Two-channel THz Communication Systems

We analyze whether a multidimensional parity check (MDPC) or a Reed-Solomon (RS) code in combination with an auxiliary channel can improve the throughput and extend the THz transmission distance. While channel quality is addressed by various coding approaches, and an effective THz system configuration is enabled by other approaches with additional channels, their combination is new with the potential for significant improvements in quality of the data transmission. Our specific solution is designed to correct data bits at the physical layer by using a low complexity erasure code (MDPC or RS), whereby original and parity data are transferred over two separate and parallel THz channels, including one main channel and one additional channel. The results are theoretically analyzed to see that our new solution can improve throughput, support higher modulation levels and transfer data over the longer distances with THz communications.

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arXiv2021

Benchmarking Buffer Size in IoT Devices Deploying REST HTTP

A few potential IoT communication protocols at the application layer have been proposed, including MQTT, CoAP and REST HTTP, with the latter being the protocol of choice for software developers due to its compatibility with the existing systems. We present a theoretical model of the expected buffer size on the REST HTTP client buffer in IoT devices under lossy wireless conditions, and validate the study experimentally. The results show that increasing the buffer size in IoT devices does not always improve performance in lossy environments, hence demonstrating the importance of benchmarking the buffer size in IoT systems deploying REST HTTP.

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arXiv2021

Benchmarking Various ML Solutions in Complex Intent-Based Network Management Systems

Intent-based networking (IBN) solutions to managing complex ICT systems have become one of the key enablers of intelligent and autonomous network management. As the number of machine learning (ML) techniques deployed in IBN increases, it becomes increasingly important to understand their expected performance. Whereas IBN concepts are generally specific to the use case envisioned, the underlying platforms are generally heterogenous, comprised of complex processing units, including CPU/GPU, CPU/FPGA and CPU/TPU combinations, which needs to be considered when running the ML techniques chosen. We focus on a case study of IBNs in the so-called ICT supply chain systems, where multiple ICT artifacts are integrated in one system based on heterogeneous hardware platforms. Here, we are interested in the problem of benchmarking the computational performance of ML technique defined by the intents. Our benchmarking method is based on collaborative filtering techniques, relying on ML-based methods like Singular Value Decomposition and Stochastic Gradient Descent, assuming initial lack of explicit knowledge about the expected number of operations, framework, or the device processing characteristics. We show that it is possible to engineer a practical IBN system with various ML techniques with an accurate estimated performance based on data from a few benchmarks only.

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arXiv2021

Improving THz Quality-of-Transmission with Systematic RLNC and Auxiliary Channels

In this paper, we propose a novel solution that can improve the quality of THz transmission with systematic random linear network coding (sRLNC) and a low-bitrate auxiliary channel. To minimize complexity of channel coding, we complement a generic low complexity FEC code by a low complexity sRLNC. To increase the overall throughput of THz transmission, we propose to send the native data and coding redundancy in parallel over 2 differently configured THz channels, i.e., over 1 high bit rate main channel and 1 low bit rate low error rate auxiliary channel. The results show, that the main THz channel supported by low bit rate auxiliary channel can use a higher level modulation format and sent over longer distances with a higher throughput.

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arXiv2021

Error Correction with Systematic RLNC in Multi-Channel THz Communication Systems

The terahertz (THz) frequency band (0.3-10THz) has the advantage of large available bandwidth and is a candidate to satisfy the ever increasing mobile traffic in wireless communications. However, the THz channels are often absorbed by molecules in the atmosphere, which can decrease the signal quality resulting in high bit error rate of received data. In this paper, we study the usage of systematic random linear network coding (sRLNC) for error correction in generic THz systems with with 2N parallel channels, whereby N main high-bitrate channels are used in parallel with N auxiliary channels with lower bit rate. The idea behind this approach is to use coded low-bit rate channels to carry redundant information from high-bit rate channels, and thus compensate for errors in THz transmission. The analytical results evaluate and compare the different scenarios of the THz system in term of the amount of coding redundancy, a code rate, transmission rate of auxiliary channels, the number of THz channels, the modulation format and transmission distance as required system configurations for a fault tolerant THz transmission.

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arXiv2021

The Role of Intent-Based Networking in ICT Supply Chains

The evolution towards Industry 4.0 is driving the need for innovative solutions in the area of network management, considering the complex, dynamic and heterogeneous nature of ICT supply chains. To this end, Intent-Based networking (IBN) which is already proven to evolve how network management is driven today, can be implemented as a solution to facilitate the management of large ICT supply chains. In this paper, we first present a comparison of the main architectural components of typical IBN systems and, then, we study the key engineering requirements when integrating IBN with ICT supply chain network systems while considering AI methods. We also propose a general architecture design that enables intent translation of ICT supply chain specifications into lower level policies, to finally show an example of how the access control is performed in a modeled ICT supply chain system.

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arXiv2021

Scaling Migrations and Replications of Virtual Network Functions based on Network Traffic Forecasting

Migration and replication of virtual network functions (VNFs) are well-known mechanisms to face dynamic resource requests in Internet Service Provider (ISP) edge networks. They are not only used to reallocate resources in carrier networks, but in case of excessive traffic churns also to offloading VNFs to third party cloud providers. We propose to study how traffic forecasting can help to reduce the number of required migrations and replications when the traffic dynamically changes in the network. We analyze and compare three scenarios for the VNF migrations and replications based on: (i) the current observed traffic demands only, (ii) specific maximum traffic demand value observed in the past, or (iii) predictive traffic values. For the prediction of traffic demand values, we use an LSTM model which is proven to be one of the most accurate methods in time series forecasting problems. Based the traffic prediction model, we then use a Mixed-Integer Linear Programming (MILP) model as well as a greedy algorithm to solve this optimization problem that considers migrations and replications of VNFs. The results show that LSTM-based traffic prediction can reduce the number of migrations up to 45\% when there is enough available resources to allocate replicas, while less cloud-based offloading is required compared to overprovisioning.

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arXiv2021

Engineering and Experimentally Benchmarking a Serverless Edge Computing System

Thanks to the latest advances in containerization, the serverless edge computing model is becoming close to reality. Serverless at the edge is expected to enable low latency applications with fast autoscaling mechanisms, all running on heterogeneous and resource-constrained devices. In this work, we engineer and experimentally benchmark a serverless edge computing system architecture. We deploy a decentralized edge computing platform for serverless applications providing processing, storage, and communication capabilities using only open-source software, running over heterogeneous resources (e.g., virtual machines, Raspberry Pis, or bare metal servers, etc). To achieve that, we provision an overlay-network based on Nebula network agnostic technology, running over private or public networks, and use K3s to provide hardware abstraction. We benchmark the system in terms of response times, throughput and scalability using different hardware devices connected through the public Internet. The results show that while serverless is feasible on heterogeneous devices showing a good performance on constrained devices, such as Raspberry Pis, the lack of support when determining computational power and network characterization leaves much room for improvement in edge environments.

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arXiv2021

Engineering an IoT-Edge-Cloud Computing System Architecture: Lessons Learnt from An Undergraduate Lab Course

With the rapid advances in IoT, edge and cloud computing solutions, it is critical to educate and train students in computer science and engineering in various aspects of IoT-edge-cloud (IoT-E-C) system architecture implementations. We outline the design and development of an undergraduate laboratory course that sets the goal of implementing various interfaces and communication protocols to connect IoT, edge and cloud computing systems and evaluating their performance. The lab setup is modular and based on open source tools. In the IoT context, it consists of low-cost processing platforms with various sensors and actuators. In the edge and cloud computing context, we implement and deploy single board computers and Firebase cloud solutions, respectively. The modular lab setup allows students to engineer and integrate various communication protocol solutions, including MQTT, COAP and HTTP. In addition to the system implementation, students can evaluate and benchmark the performance of the entire system.

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arXiv2021

An Experimental Study of Network Coded REST HTTP in Dynamic IoT Systems

REST HTTP is the communication protocol of choice for software developers today. In IoT systems with unreliable connectivity, however, a stateless protocol like REST HTTP needs to send a request message multiple times, and it only stops the retransmissions when an acknowledgement arrives at the sender. In our previous work, we studied the usage of random linear network coding (RLNC) for REST HTTP protocol to reducing the amount of unnecessarily retransmissions. In this paper, we experimentally validate the study and analyze REST HTTP with and without RLNC in a simple testbed in dynamic IoT systems. The measurements show notable improvements in bandwidth utilization in terms of reducing the retransmissions and delay when using network-coded REST HTTP.

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arXiv2021

Enhancing REST HTTP with Random Linear Network Coding in Dynamic Edge Computing Environments

The rising number of IoT devices is accelerating the research on new solutions that will be able to efficiently deal with unreliable connectivity in highly dynamic computing applications. To improve the overall performance in IoT applications, there are multiple communication solutions available, either proprietary or open source, all of which satisfy different communication requirements. Most commonly, for this kind of communication, developers choose REST HTTP protocol as a result of its ease of use and compatibility with the existing computing infrastructure. In applications where mobility and unreliable connectivity play a significant role, ensuring a reliable exchange of data with the stateless REST HTTP protocol completely depends on the developer itself. This often means resending multiple request messages when the connection fails, constantly trying to access the service until the connection reestablishes. In order to alleviate this problem, in this paper, we combine REST HTTP with random linear network coding (RLNC) to reduce the number of additional retransmissions. We show how using RLNC with REST HTTP requests can decrease the reconnection time by reducing the additional packet retransmissions in unreliable highly dynamic scenarios.

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arXiv2020

Increasing Transmission Distance in THz systems with Erasure Coding and Auxiliary Channels

We analyze whether the THz transmission distance can be extended with systematic linear network coding (sRLNC) and a low-bitrate additional channel. While various coding techniques have been proposed to mitigate issues of channel quality, and other techniques have used auxiliary channels to enable an effective THz transmission system configuration, their combination is new, and carries potential for significant improvements in transmission quality. Our specific solution is designed to complementing a generic low complexity FEC code by a low complexity erasure code (sRLNC), whereby channel coding is proposed to simultaneously send the native and coded data over two parallel channels, including one main THz channel and one auxiliary channel with comparably lower bitrate. We show theoretically that the proposed system can improve throughput, support higher modulation levels and transfer data over the longer distances with THz communications.

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arXiv2020

On Optimal Placement of Hybrid Service Function Chains (SFCs) of Virtual Machines and Containers in a Generic Edge-Cloud Continuum

Traditionally, Network Function Virtualization (NFV) has been implemented to run on Virtual Machines (VMs) in form of Virtual Network Functions (VNFs). More recently, the so-called Serverless Computing has gained traction in cloud computing, offering Function-as-a-Service (FaaS) platforms that make use of containerization techniques to deploy services. In contrast to VM-based VNFs, where resources are usually reserved and continuously running, FaaS can just be subsets of code implementing small functions allowing for event-driven, on-demand instantiations. Thus, a hybrid VM-Container based Service Function Chains (SFCs) are a natural evolution of NFV architecture. We study a novel problem of optimal placement of hybrid SFCs from an Internet Service Provider (ISP) point of view, whereby VNFs can be instantiated either over VMs or containers in a generic edge and cloud continuum. To this end, we propose a Mixed-Integer Linear Programming model as well as a heuristic solution to solve this optimization problem that considers three objectives unique to the specific VM and container deployment in a carrier network: operational costs for maintaining servers in the edge, costs of placing VNFs in third-party cloud providers and penalty costs applied when SLA agreements are violated in terms of end-to-end delay. We also propose 2-phases optimization process to analyze the effect on performance as a result of replications and migrations of VNFs. The model can be used to highlight scenarios where a combination of VMs and containers can provide most benefits from the monetary costs point of view.

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arXiv2020

Jamming-Aware Control Plane in Elastic Optical Networks

Physical layer security is essential in optical networks. In this paper, we study a jamming-aware control plane, in which a high power jamming attack exists in the network. The studied control plane considers that the jammed connections can be detected and avoided. We used a physical layer model, in which we embedded the additional jamming power, to evaluate different security in scenarios, such as a jamming-free scenario, jamming with an unaware controller, and jamming with an aware controller. The performance is analyzed in terms of the blocking rate and slots utilization. We analyze the impact of jamming attacks in the least used link and in the most used link on the network. The results demonstrates that the jamming avoidance by the control plane can reach performance near the not jammed scenario.

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arXiv2020

A Simple Reliability Analysis of Complex Service Function Chains (SFCs)

In the framework of Network Function Virtualization (NFV), the reliability of Service Function Chain (SFC), -- an end-to-end service is presented by a chain of virtual network functions (VNFs), is a complex function of placement, configuration and deployment requirements, both in hardware and software. Previous reliability analysis models cannot be directly applied to SFC because they do not consider aspects of system component sharing, heterogeneity of system components and their interdependency in case of failures. In this paper, we analyze service reliability of complex SFC configurations, including serial and parallel VNF chaining, as well as their related backup protection components. Our analysis is based on combinatorial analysis and a reduced binomial theorem, and this simple approach can be utilized to analyzing rather complex SFC configurations. We consider, for the first time, failure dependences among VNF components placed in data centers, racks, and servers. We show that our analysis can easily consider different VNF placement strategies in data center networks in arbitrary configurations and, thus, be effectively used for optimizations of the reliable SFC placement.

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arXiv2020

On Detecting and Preventing Jamming Attacks with Machine Learning in Optical Networks

Optical networks are prone to power jamming attacks intending service disruption. This paper presents a Machine Learning (ML) framework for detection and prevention of jamming attacks in optical networks. We evaluate various ML classifiers for detecting out-of-band jamming attacks with varying intensities. Numerical results show that artificial neural network is the fastest (10^6 detections per second) for inference and most accurate (~ 100 %) in detecting power jamming attacks as well as identifying the optical channels attacked. We also discuss and study a novel prevention mechanism when the system is under active jamming attacks. For this scenario, we propose a novel resource reallocation scheme that utilizes the statistical information of attack detection accuracy to lower the probability of successful jamming of lightpaths while minimizing lightpaths' reallocations. Simulation results show that the likelihood of jamming a lightpath reduces with increasing detection accuracy, and localization reduces the number of reallocations required

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arXiv2020

Engineering and Experimentally Benchmarking a Container-based Edge Computing System

While edge computing is envisioned to superbly serve latency sensitive applications, the implementation-based studies benchmarking its performance are few and far between. To address this gap, we engineer a modular edge cloud computing system architecture that is built on latest advances in containerization techniques, including Kafka, for data streaming, Docker, as application platform, and Firebase Cloud, as realtime database system. We benchmark the performance of the system in terms of scalability, resource utilization and latency by comparing three scenarios: cloud-only, edge-only and combined edge-cloud. The measurements show that edge-only solution outperforms other scenarios only when deployed with data located at one edge only, i.e., without edge computing wide data synchronization. In case of applications requiring data synchronization through the cloud, edge-cloud scales around a factor 10 times better than cloud-only, until certain number of concurrent users in the system, and above this point, cloud-only scales better. In terms of resource utilization, we observe that whereas the mean utilization increases linearly with the number of user requests, the maximum values for the memory and the network I/O heavily increase when with an increasing amount of data.

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arXiv2020

Embedding Jamming Attacks into Physical Layer Models in Optical Networks

Optical networks are prone to physical layer attacks, in particular the insertion of high jamming power. In this paper, we present a study of jamming attacks in elastic optical networks (EON) by embedding the jamming into the physical layer model, and we analyze its impact on the blocking probability and slots utilization. We evaluate our proposed model using a single link and a network topology and we show that for in-band-jamming, the slots utilization decreases with the increase of jamming power, and becomes null when the jamming power is higher than 3 dB, while for out-of-band jamming, the impact is maximal for a specific jamming power, 1.75 dB in our simulation. Considering multiple positions of attackers, we attained the highest blocking probability 32% for a specific jamming power 2 dB. We conclude that the impact of jamming depends on attacker positions as well as the jamming power.

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