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Wolfgang Kellerer

Publications and source records attributed to Wolfgang Kellerer.

At least 73 records · Page 4Linked to original sources

Boost Your CotS IEEE 802.15.4 Network with Inter-Slot Interference Cancellation for Industrial IoT

The current cellular standardization for 5G is working towards wireless advances to enable further productivity for industrial automation. However, this development will take several years. Meanwhile, the capabilities of the currently available standards should be pushed to their limits. To this end, in this work, we present results from the first inter-slot successive interference cancellation testbed using commercial off the shelf IEEE 802.15.4 sensors. Through our implementation, we have measured a throughput of $0.72$ packets per slot which doubles the currently used contention-based access, Slotted ALOHA, with a limit of $0.36$ packets per slot. The hardware effects of the boards, which degrade the successive interference cancellation performance from the theoretical limit of $1$ packet per slot, are modeled and validated through measurements. We also propose a model that can be used to calculate the expected successive interference cancellation throughput with the specific hardware available in a factory. Furthermore, our proposed model should replace the perfect physical layer assumptions for researchers to design new MAC algorithms taking practical limitations into account.

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Joint Cross-layer Optimization in Real-Time Networked Control Systems

Networked control system (NCS) refer to a set of control loops that are closed over a communication network. In this article, the joint operation of control and networking for NCS is investigated wherein the network serves the sensor-to-controller communication links for multiple stochastic linear time-invariant (LTI) sub-systems. The sensors sample packets based on the observed plant state, which they send over a shared multi-hop network. The network has limited communication resources, which need to be assigned to competing links to support proper control loop operation. In this set-up, we formulate an optimization problem to minimize the weighted-sum linear-quadratic-Gaussian (LQG) cost of all loops, taking into account the admissible sampling, control, congestion control and scheduling policies. Under some mild assumptions on the sampling frequencies of the control loops and the communication network, we find the joint optimal solution to be given by a certainty equivalence control with threshold-based sampling policy, as well as a back-pressure type scheduler with a simple pass-through congestion control. The interface between network and control loops is identified to be the buffer state of the sensor node, which can be interpreted as network price for sampling a packet from control perspective. We validate our theoretical claims by simulating NCSs comprising of multiple LTI stochastic control loops communicating over a two-hop cellular network.

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P4BFT: Hardware-Accelerated Byzantine-Resilient Network Control Plane

Byzantine Fault Tolerance (BFT) enables correct operation of distributed, i.e., replicated applications in the face of malicious take-over and faulty/buggy individual instances. Recently, BFT designs have gained traction in the context of Software Defined Networking (SDN). In SDN, controller replicas are distributed and their state replicated for high availability purposes. Malicious controller replicas, however, may destabilize the control plane and manipulate the data plane, thus motivating the BFT requirement. Nonetheless, deploying BFT in practice comes at a disadvantage of increased traffic load stemming from replicated controllers, as well as a requirement for proprietary switch functionalities, thus putting strain on switches' control plane where particular BFT actions must be executed in software. P4BFT leverages an optimal strategy to decrease the total amount of messages transmitted to switches that are the configuration targets of SDN controllers. It does so by means of message comparison and deduction of correct messages in the determined optimal locations in the data plane. In terms of the incurred control plane load, our P4-based data plane extensions outperform the existing solutions by ~33.2% and ~40.2% on average, in random 128-switch and Fat-Tree/Internet2 topologies, respectively. To validate the correctness and performance gains of P4BFT, we deploy bmv2 and Netronome Agilio SmartNIC-based topologies. The advantages of P4BFT can thus be reproduced both with software switches and "commodity" P4-enabled hardware. A hardware-accelerated controller packet comparison procedure results in an average 96.4% decrease in processing delay per request compared to existing software approaches.

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Transmission Power Control for Remote State Estimation in Industrial Wireless Sensor Networks

Novel low-power wireless technologies and IoT applications open the door to the Industrial Internet of Things (IIoT). In this new paradigm, Wireless Sensor Networks (WSNs) must fulfil, despite energy and transmission power limitations, the challenging communication requirements of advanced manufacturing processes and technologies. In industrial networks, this is possible thanks to the availability of network infrastructure and the presence of a network coordinator that efficiently allocates the available radio resources. In this work, we consider a WSN that simultaneously transmits measurements of Networked Control Systems' (NCSs) dynamics to remote state estimators over a shared packet-erasure channel. We develop a minimum transmission power control (TPC) policy for the coordination of the wireless medium by formulating an infinite horizon Markov decision process (MDP) optimization problem. We compute the policy using an approximate value iteration algorithm and provide an extensive evaluation of its parameters in different interference scenarios and NCSs dynamics. The evaluation results present a comprehensive characterization of the algorithm's performance, proving that it can flexibly adapt to arbitrary use cases.

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Design of a Networked Controller for a Two-Wheeled Inverted Pendulum Robot

The topic of this paper is to use an intuitive model-based approach to design a networked controller for a recent benchmark scenario. The benchmark problem is to remotely control a two-wheeled inverted pendulum robot via W-LAN communication. The robot has to keep a vertical upright position. Incorporating wireless communication in the control loop introduces multiple uncertainties and affects system performance and stability. The proposed networked control scheme employs model predictive techniques and deliberately extends delays in order to make them constant and deterministic. The performance of the resulting networked control system is evaluated experimentally with a predefined benchmarking experiment and is compared to local control involving no delays.

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Mobility-Aware Joint Service Placement and Routing in Space-Air-Ground Integrated Networks

People desire to be connected, no matter where they are. Recently, providing Internet access to on-board passengers has received a lot of attention from both industry and academia. However, in order to guarantee an acceptable Quality of Service (QoS) for the passenger services with low incurred cost, the path to route the services, as well as the datacenter (DC) to deploy the services should be carefully determined. This problem is challenging, due to different types of Air-to-Ground (A2G) connections, i.e., satellites and Direct-Air-to-Ground (DA2G) links. These A2G connection types differ in terms of cost, bandwidth, and latency. Furthermore, due to the flights' movements, it is important to consider adapting the service location accordingly. In this work, we formulate two Mixed Integer Linear Programs (MILPs) for the problem of Joint Service Placement and Routing (JSPR): i) Static (S-JSPR), and ii) Mobility-Aware~(MA-JSPR) in Space-Air-Ground Integrated Networks (SAGIN), with the objective of minimizing the total cost. We compare S-JSPR and MA-JSPR using comprehensive evaluations in a realistic European-based SAGIN. The obtained results show that the MA-JSPR model, by considering the future flight positions and using a service migration control, reduces the long-term total cost notably. Also, we show S-JSPR benefits from a low time-complexity and it achieves lower end-to-end delays comparing to MA-JSPR model.

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Dynamic Binary Countdown for Massive IoT Random Access in Dense 5G Networks

Massive connectivity for Internet of Things applications is expected to challenge the way access reservation protocols are designed in 5G networks. Since the number of devices and their density are envisioned to be orders of magnitude larger, state-of-the-art access reservation, Random Access (RA) procedure, might be a bottleneck for end-to-end delay. This would be especially challenging for burst arrival scenarios: Semi-synchronous triggering of a large number of devices due to a common event (blackout, emergency alarm, etc.). In this article, to improve RA procedure scalability, we propose to combine Binary Countdown Contention Resolution (BCCR) with the state-of-the-art Access Class Barring (ACB). We present a joint analysis of ACB and BCCR and apply a framework for treating RA as a bi-objective optimization, minimizing the resource consumption and maximizing the throughput of the procedure in every contention round. We use this framework to devise dynamic load-adaptive algorithm and simulatively illustrate that the proposed algorithm reduces the burst resolution delay while consuming less resources compared to the state-of-the-art techniques.

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Admission Control based Traffic-Agnostic Delay-Constrained Random Access (AC/DC-RA) for M2M Communication

The problem of wireless M2M communication is twofold: the reliability aspect and the scalability aspect. The solution of this problem demands a delay constrained random access protocol. To this end we propose Admission Control based Traffic Agnostic Delay Constrained Random Access (AC/DC-RA) protocol. Our main contribution is enabling the stochastic delay constraints agnostic to the traffic, such that the stochastic delay constraint is valid with respect to varying number of arrivals. We achieve this with an admission control decision that uses a novel collision estimation algorithm for active number of arrivals per contention resource. We use an adaptive contention resolution algorithm to react to the varying number of arrivals. Using these tools, the admission control solves the stability problem. We show with simulations that AC/DC-RA provide stochastic delay constrained random access in a traffic agnostic way to sustain a stable performance against Poisson and Beta arrivals without any modification to the protocol.

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Age-of-Information vs. Value-of-Information Scheduling for Cellular Networked Control Systems

Age-of-Information (AoI) is a recently introduced metric for network operation with sensor applications which quantifies the freshness of data. In the context of networked control systems (NCSs), we compare the worth of the AoI metric with the value-of-information (VoI) metric, which is related to the uncertainty reduction in stochastic processes. First, we show that the uncertainty propagates non-linearly over time depending on system dynamics. Next, we define the value of a new update of the process of interest as a function of AoI and system parameters of the NCSs. We use the aggregated update value as a utility for the centralized scheduling problem in a cellular NCS composed of multiple heterogeneous control loops. By conducting a simulative analysis, we show that prioritizing transmissions with higher VoI improves performance of the NCSs compared with providing fair data freshness to all sub-systems equally.

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Bounded Dijkstra (BD): Search Space Reduction for Expediting Shortest Path Subroutines

The shortest path (SP) and shortest paths tree (SPT) problems arise both as direct applications and as subroutines of overlay algorithms solving more complex problems such as the constrained shortest path (CSP) or the constrained minimum Steiner tree (CMST) problems. Often, such algorithms do not use the result of an SP subroutine if its total cost is greater than a given bound. For example, for delay-constrained problems, paths resulting from a least-delay SP run and whose delay is greater than the delay constraint of the original problem are not used by the overlay algorithm to construct its solution. As a result of the existence of these bounds, and because the Dijkstra SP algorithm discovers paths in increasing order of cost, we can terminate the SP search earlier, i.e., once it is known that paths with a greater total cost will not be considered by the overlay algorithm. This early termination allows to reduce the runtime of the SP subroutine, thereby reducing the runtime of the overlay algorithm without impacting its final result. We refer to this adaptation of Dijkstra for centralized implementations as bounded Dijkstra (BD). On the example of CSP algorithms, we confirm the usefulness of BD by showing that it can reduce the runtime of some algorithms by 75% on average.

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BFT Protocols for Heterogeneous Resource Allocations in Distributed SDN Control Plane

Distributed Software Defined Networking (SDN) controllers aim to solve the issue of single-point-of-failure and improve the scalability of the control plane. Byzantine and faulty controllers, however, may enforce incorrect configurations and thus endanger the control plane correctness. Multiple Byzantine Fault Tolerance (BFT) approaches relying on Replicated State Machine (RSM) execution have been proposed in the past to cater for this issue. The scalability of such solutions is, however, limited. Additionally, the interplay between progressing the state of the distributed controllers and the consistency of the external reconfigurations of the forwarding devices has not been thoroughly investigated. In this work, we propose an agreement-and-execution group-based approach to increase the overall throughput of a BFT-enabled distributed SDN control plane. We adapt a proven sequencing-based BFT protocol, and introduce two optimized BFT protocols that preserve the uniform agreement, causality and liveness properties. A state-hashing approach which ensures causally ordered switch reconfigurations is proposed, that enables an opportunistic RSM execution without relying on strict sequencing. The proposed designs are implemented and validated for two realistic topologies, a path computation application and a set of KPIs: switch reconfiguration (response) time, signaling overhead, and acceptance rates. We show a clear decrease in the system response time and communication overhead with the proposed models, compared to a state-of-the-art approach.

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On Throughput Maximization of Grant-Free Access with Reliability-Latency Constraints

Enabling autonomous driving and industrial automation with wireless networks poses many challenges, which are typically abstracted through reliability and latency requirements. One of the main contributors to latency in cellular networks is the reservation-based access, which involves lengthy and resource-inefficient signaling exchanges. An alternative is to use grant-free access, in which there is no resource reservation. A handful of recent works investigated how to fulfill reliability and latency requirements with different flavors of grant-free solutions. However, the resource efficiency, i.e., the throughput, has been only the secondary focus. In this work, we formulate the throughput of grant-free access under reliability-latency constraints, when the actual number of arrived users or only the arrival distribution are known. We investigate how these different levels of knowledge about the arrival process influence throughput performance of framed slotted ALOHA with $K$-multipacket reception, for the Poisson and Beta arrivals. We show that the throughput under reliability-latency requirements can be significantly improved for the higher expected load of the access network, if the actual number of arrived users is known. This insight motivates the use of techniques for the estimation of the number of arrived users, as this knowledge is not readily available in grant-free access. We also asses the impact of estimation error, showing that for high reliability-latency requirements the gains in throughput are still considerable.

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Hard Latency-Constraints for High-Throughput Random Access: SICQTA

Enabling closed control loops via wireless communication has attracted a lot of interest recently and is investigated under the name cyber-physical systems. Under cyber-physical systems one challenging scenario is multiple loops sharing a wireless medium, and the age of the control information has to be minimized without sacrificing reliability to guarantee the control stability. The number of transmitting devices depends on the control parameters thus, it is stochastic. Wireless uplink resource allocation given low latency constraints for unknown number of devices is a hard problem. For this problem, random access is the most prominent way to minimize latency, but reliability is sacrificed. However, as reliability is also critical for such applications, improved random access algorithms with hard latency guarantees are needed. Currently available random access algorithms with hard latency guarantees have low throughput and some of them are limited to low number of active devices. In this work, we provide a high-throughput random access algorithm with hard latency-constraints (SICQTA) that scales to any number of active devices. This algorithm, making use of feedback, has a varying throughput between $0.69$ and $1$ depending on the number of devices, which is unprecedented in the state of the art up to our best knowledge.

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HNLB: Utilizing Hardware Matching Capabilities of NICs for Offloading Stateful Load Balancers

In order to scale web or other services, the load on single instances of the respective service has to be balanced. Many services are stateful such that packets belonging to the same connection must be delivered to the same instance. This requires stateful load balancers which are mostly implemented in software. On the one hand, modern packet processing frameworks supporting software load balancers, such as the Data Plane Development Kit (DPDK), deliver high performance compared to older approaches. On the other hand, common Network Interface Cards (NICs) provide additional matching capabilities that can be utilized for increasing the performance even further and in turn reduce the necessary server resources. In fact, offloading the packet matching to hardware can free up CPU cycles of the servers. Therefore, in this work, we propose the Hybrid NIC-offloading Load Balancer (HNLB), a high performance hybrid hardware-software load balancer, utilizing the NIC-offloading hardware matching capabilities. The results of our performance evaluations show that the throughput using NIC offloading can be increased by up to 50%, compared to a high performance software-only implementation. Furthermore, we investigated the limitations of our proposed approach, e.g., the limited number of possible concurrent connections.

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Towards adaptive state consistency in distributed SDN control plane

State synchronisation in clustered Software Defined Networking controller deployments ensures that all instances of the controller have the same state information in order to provide redundancy. Current implementations of controllers use a strong consistency model, where configuration changes must be synchronised across a number of instances before they are applied on the network infrastructure. For large deployments, this blocking process increases the delay of state synchronisation across cluster members and consequently has a detrimental effect on network operations that require rapid response, such as fast failover and Quality of Service applications. In this paper, we introduce an adaptive consistency model for SDN Controllers that employs concepts of eventual consistency models along with a novel `cost-based' approach where strict synchronisation is employed for critical operations that affect a large portion of the network resources while less critical changes are periodically propagated across cluster nodes. We use simulation to evaluate our model and demonstrate the potential gains in performance.

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MORPH: An Adaptive Framework for Efficient and Byzantine Fault-Tolerant SDN Control Plane

Current approaches to tackle the single point of failure in SDN entail a distributed operation of SDN controller instances. Their state synchronization process is reliant on the assumption of a correct decision-making in the controllers. Successful introduction of SDN in the critical infrastructure networks also requires catering to the issue of unavailable, unreliable (e.g. buggy), and malicious controller failures. We propose MORPH, a framework tolerant to unavailability and Byzantine failures, which distinguishes and localizes faulty controller instances and appropriately reconfigures the control plane. Our controller-switch connection assignment leverages the awareness of the source of failure to optimize the number of active controllers and minimize the controller and switch reconfiguration delays. The proposed re-assignment executes dynamically after each successful failure identification. We require 2FM + FA +1 controllers to tolerate FM malicious and FA availability-induced failures. After a successful detection of FM malicious controllers, MORPH reconfigures the control plane to require a single controller message to forward the system state. Moreover, we outline and present a solution to the practical correctness issues related to the statefulness of the distributed SDN controller applications, previously ignored in the literature. We base our performance analysis on a resource-aware routing application, deployed in an emulated testbed comprising up to 16 controllers and up to 34 switches, so to tolerate up to 5 unique Byzantine and additional 5 availability-induced controller failures (a total of 10 unique controller failures). We quantify and highlight the dynamic decrease in the packet and CPU load and the response time after each successful failure detection.

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Impact of Adaptive Consistency on Distributed SDN Applications: An Empirical Study

Scalability of the control plane in a software-defined network (SDN) is enabled by means of decentralization of the decision-making logic, i.e., by replication of controller functions to physically or virtually dislocated controller replicas. Replication of a centralized controller state also enables the protection against controller failures by means of primary and backup replicas responsible for managing the underlying SDN data plane devices. In this paper, we investigate the effect of the deployed consistency model on scalability and correctness metrics of the SDN control plane. In particular, we compare the strong and eventual consistency, and make a case for a novel adaptive consistency approach. The existing controller platforms rely on either strong or eventual consistency mechanisms in their state distribution. We show how an adaptive consistency model offers the scalability benefits in terms of the total request-handling throughput and response time, in contrast to the strong consistency model. We also outline how the adaptive consistency approach can provide for correctness semantics that are unachievable with the eventual consistency paradigm in practice. The adaptability of our approach provides a balanced and tunable tradeoff of scalability and correctness for the SDN application implemented on top of the adaptive framework. To validate our assumptions, we evaluate and compare the different approaches in an emulated testbed with an example of a load balancer controller application. The experimental setup comprises up to five extended OpenDaylight controller instances and two network topologies from the area of service provider and data center networks.

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Response Time and Availability Study of RAFT Consensus in Distributed SDN Control Plane

Software defined networking (SDN) promises unprecedented flexibility and ease of network operations. While flexibility is an important factor when leveraging advantages of a new technology, critical infrastructure networks also have stringent requirements on network robustness and control plane delays. Robustness in the SDN control plane is realized by deploying multiple distributed controllers, formed into clusters for durability and fast-failover purposes. However, the effect of the controller clustering on the total system response time is not well investigated in current literature. Hence, in this work we provide a detailed analytical study of the distributed consensus algorithm RAFT, implemented in OpenDaylight and ONOS SDN controller platforms. In those controllers, RAFT implements the data-store replication, leader election after controller failures and controller state recovery on successful repairs. To evaluate its performance, we introduce a framework for numerical analysis of various SDN cluster organizations w.r.t. their response time and availability metrics. We use Stochastic Activity Networks for modeling the RAFT operations, failure injection and cluster recovery processes, and using real-world experiments, we collect the rate parameters to provide realistic inputs for a representative cluster recovery model. We also show how a fast rejuvenation mechanism for the treatment of failures induced by software errors can minimize the total response time experienced by the controller clients, while guaranteeing a higher system availability in the long-term.

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