In urban areas, the extensive use of Unmanned Aerial Vehicles (UAVs) promises to revolutionize many industries but will increase the number of UAVs inhabiting a given airspace drastically. A necessity for this is the establishment of an Unmanned Aerial Traffic Management (UTM) system that enables the safe and reliable operation of UAVs. One way to establish this is to form an ad-hoc network between UAVs, operators and ground stations and distribute movements and commands throughout the entire network. Recently, Rate Decay Flooding (RDF) was proposed to realize such a network by gradually delaying packets the further they travel and thereby reducing the traffic density. Furthermore, Network Coding (NC) is a novel approach to reduce the traffic as different pieces of information can be encoded into a single transmission. In this work, we present a combination of both approaches. For this we propose a coding policy that determines when to use NC based on the contents of packets waiting to be forwarded. Further we implement a Bayesian online estimator for the current packet loss rate, which is a crucial component of the coding policy and thereby allowing the protocol to adapt to changing network sizes. The protocol is evaluated in an open-source simulator. Here we show that the coding policy successfully determines high-gain coding actions and reacts to larger networks with higher packet loss, by reducing the share of coded transmissions. Using our approach networks 95 % larger than previously possible with RDF are supported by reaching 21.2 % more receivers per transmission.

L-band Digital Aeronautical Communications System (LDACS) is the selected Air-to-Ground (A2G) technology for future aeronautical communications and a proposed candidate for Air-to-Air (A2A) links. Geographic greedy routing in sparse LDACS A2A networks, typical during gradual system deployment, frequently encounters local minima, necessitating backup mechanisms that are inefficient. Previous research has primarily focused on refining backup mechanisms, neglecting the root cause of geographic greedy routing failures. This paper investigates why geographic greedy routing performance deteriorates in sparse network scenarios, where failures occur more frequently than in dense deployments. We introduce a novel metric to quantify the quality of hop-by-hop forwarding decisions in geographic greedy routing. Furthermore, we develop a second-order absorbing Markov chain model to predict the success ratio and hop stretch factor. The model is validated through Monte-Carlo simulations over the French airspace with varying LDACS equipage fractions, achieving an average difference from simulation results of less than 3.4% for the success ratio and 1.5% for the hop stretch factor. The proposed model demonstrates high accuracy and can be generalized to evaluate other geographic routing protocols. Consequently, the outcomes provide valuable insights toward designing optimized geographic greedy routing protocols.

Advances in mechanical capabilities and mass manufacturing of Unmanned Aerial Vehicles (UAVs) are driving their application in various fields from precision agriculture to infrastructure monitoring and on-demand parcel delivery. Especially in urban areas it is projected that large amount of UAVs will inhabit the airspace. To facilitate the safe and reliable operation of large-scale urban UAV deployments, an Unmanned Aerial Traffic Management (UTM) system is required. Such a system needs to be aware of all movements within the airspace to control and monitor urban UAV operations. One way to realize this is the establishment of an ad-hoc network, which UAVs use for network-wide dissemination of their positions. Recently, Rate Decay Flooding (RDF) has been proposed as a tailor-made protocol to realize such a system. Although RDF has been proven to be efficient in supporting UTM applications in larger networks than ordinarily possible, much of its success relies on the proper selection of protocol parameters. In this work, we propose a reinforcement-learning framework that automatically adapts the configuration of RDF to its perceived environment. We utilize deep contextual bandits as a light-weight, but effective method to capture the non-linear relationship between the perceived environment and the achieved performance. We name this extension Dynamic Rate Decay Flooding (dynRDF). In a simulation study, we show that this solution is effective in finding optimal configurations for RDF for varying network sizes. To achieve this, only 2.7 % of all possible configurations had to be explored. Allowing dynRDF to also take the local UAV density into account, a performance gain of more than 12 % is achieved in a relevant composite metric capturing both the timely dissemination of position updates to nearby UAVs and reliable network-wide dissemination.

Replacing traditional wired connections with wireless systems on the aircraft can significantly reduce weight and fuel consumption. Furthermore, complementing existing wired systems with wireless sensors adds redundancy and fault tolerance. Although many applications are already envisioned under the umbrella of Wireless Avionics Intra-Communications (WAIC), finding a suitable communication technology remains challenging due to diverse Quality of Service (QoS) requirements. In this work we discuss challenges associated with the deployment of an in-cabin wireless sensor network (WSN) using different radio bands and propose a solution based on the IPv6 over the TSCH mode of IEEE 802.15.4 (6TiSCH) protocol stack. By extending the latter with cross-layer as well as layer-specific improvements, different challenges in terms of bounded end-to-end delay and high packet delivery ratio are addressed. The solution is validated in simulations using OMNeT++, showing the feasibility of meeting stringent QoS requirements for in-cabin WSNs.

The emergence of the L-band Digital Aeronautical Communications System (LDACS) presents a significant opportunity for enabling Air-to-Air (A2A) communication to accommodate the growing number of aircraft. However, it requires overcoming significant Medium Access Control (MAC) delays and enhancing connectivity in sparse networks. Geographic greedy routing, commonly used in Aeronautical Ad-hoc networks, utilizes position information to eliminate the need for topology discovery. Yet, its efficacy declines as network density decreases. With the gradual introduction of aircraft equipped with LDACS, it becomes crucial to improve greedy forwarding performance. This research investigates Greedy-k, a greedy forwarding variant using k-hop neighborhood information, to boost sparse network performance. We introduce a method to minimize beacon size by transmitting a subset of k-hop neighborhood data that fits within an LDACS time slot. We derived the subset size analytically and evaluated the performance through simulations benchmarked against the conventional Greedy-1. Our results indicate that the proposed approach achieves up to 13% higher Packet Delivery Ratio (PDR) than Greedy-1, while capturing additionally 70.1% and 34.6% of 2ndand 3rdorder neighbors, respectively.

The use of Unmanned Aerial Vehicles (UAVs) has been proposed for numerous applications from recreational photography to commercial deliveries and infrastructure monitoring. But their effective deployment depends on the establishment of an Unmanned Aerial Traffic Management (UTM) which in turn requires reliable communication protocols to ensure safe and efficient operations. Recently, Rate Decay Flooding (RDF) was proposed as a novel protocol to enable position sharing among UAVs, realizing one of the major UTM applications. Another application is the provisioning of a redundant control connection which allows for point-to-point communication between a UAV and its operator in case their proprietary primary connection breaks. Every protocol used for this must harmonize well with RDF so that both applications can be realized at the same time. In this work we propose Spotlight Flooding (SLF) and its enhanced version SLF+, which build on top of RDF to realize a fast and reliable point-to-point connection between any two nodes in the network. These protocols are evaluated in an open-source simulator considering two scenarios. First, we consider a single UAV in distress using SLF/SLF + to explore the performance of our novel protocols for networks of up to 525 UAVs. The results show, that even for large networks, SLF+ achieves a Packet Delivery Ratio (PDR) above 90 % at an end-to-end delay of less than 60 ms. Additionally, we evaluate a scenario of 300 UAVs with an increasing share of UAVs using SLF/SLF+. Again, even if half of the UAVs in the scenario use SLF/SLF+ a PDR above 90 % is achieved at a delay of 142 ms.

Providing reliable and performant information exchange is essential for the success of emerging Networked Control Systems (NCSs) such as vehicular platooning, distributed automation in smart grids or general industry automation. Since control agents have to exchange local measurement data to collectively control the physical system, the timely and frequent dissemination of updates is the main objective for the underlying communication network. However, periodically delivering information from each node to all other nodes in a timely manner is a challenging task, especially in multi-hop networks. In this work we investigate the potential gains of using network coding in terms of Age of Information (AoI). In network coding, intermediate nodes may combine data packets bit-wise and thus achieve higher network capacity. However, to keep decoding delays low, schedules using coded transmissions have to be carefully designed. AoI-optimal transmission schedules are calculated using a novel graph search formulation which allows for efficient solving of the generally NP-hard scheduling problem. Furthermore, a heuristic for calculating network coding schedules for large networks is proposed. Extensive evaluations demonstrate the fitness of the graph search and heuristic formulation and showcase potential AoI gains of up to 38.9%.

While the capabilities of Unmanned Aerial Vehicles (UAVs) lay the foundation for exciting new applications, many communication challenges remain unsolved. To make UAV operation safer and more reliable, the establishment of an Unmanned Aerial Traffic Management (UTM) is necessary. The most important functions of such a system are Airspace Monitoring (AM) and Communication Aided Detect and Avoid (CADA). To realize CADA, UAVs must timely communicate their position to other UAVs nearby to avoid collisions. For AM, positions must be forwarded to a ground station e.g. through an ad-hoc network. In this work, we evaluate whether these two functions can be realized for dense urban UAV networks in a decentralized way by using position-flooding. To measure this, we select three flooding protocols from the literature. Further, we propose Rate Decay Flooding (RDF) as a novel flooding protocol, that leverages the fact, that position updates become less urgent the further they have travelled. RDF reduces the traffic density by lowering the data rate with which traffic is forwarded on every hop. All four protocols are evaluated in an open-source simulator. The results show that RDF can support position-flooding in networks more than twice the size compared to the next best protocol. In doing so, it generates 52% less data traffic and thereby allows for the concurrent use of the ad-hoc network for other use-cases such as remote control. Using RDF improves the position uncertainty of neighbors at a distance of 2500m by 180m.

We propose a novel approach based on deep learning to address the hidden node problem which occurs in the coexistence of aeronautical communication standards. The modern aeronautical communication standard L-band Digital Aeronautical Communications System (LDACS) in Air-Air (A/A) mode needs to share spectrum with the Distance Measuring Equipment (DME), which is a legacy system. As DME is safety-critical, causing interference on it must be avoided for all newly proposed aeronautical systems spectrally coexisting with it. Recently, cognitive radio techniques have been proposed for LDACS A/A to access spectrum dynamically and to overcome the limitations of static approaches. For this, a Recurrent Neural Network (RNN) was trained to predict idle time slots on those frequency bands, where both systems operate. By exploiting patterns in the spectrum access of DME, a promising amount of idle resources could be predicted. However, previous approaches would perform poorly in a real-world deployment, as they did not take the hidden node problem into account.This paper formulates the hidden node problem for the case that an LDACS A/A user is within communication range of a DME ground station, but not within range of all airborne DME users connected to it. Through statistical analysis, we underline the problem’s significance in practical cases. We simulate the coexistence of the two systems from a channel access perspective, taking signal propagation and the behavior of the ground station into account. Further, we present an RNN that is able to predict the channel access of hidden nodes. The key idea of our algorithm is to exploit the fact that while DME request pulses from airborne users may appear as hidden, response pulses from the ground station will be visible. Our results show that by inferring DME request channel activity from the response channel, the hidden node problem can be overcome effectively. By using our approach, nearly the same performance can be achieved as in the idealized case where all nodes are visible.

LCE (Leave Copy Everywhere), as the default caching strategy of CCN (Content-Centric Networking), caches demanded contents in all en route routers. To optimally reduce the resulting redundancy, the dynamic features of contents, clients, and network elements must be entangled with those of the network's topology. Inspired by Quantum Field Theory and Newtonian Mechanics, we developed a model to comprehensively describe the clients' interactions with contents, which generate a “gravitational force” on the latter moving them toward their requesters. The “gravity” is then transformed into a topological metric to confine the replication of contents spatially to an optimum subset of caches. This Interaction-based Caching (IC) uses the couplings of contents and clients to regulate the kinematics of contents in the network deterministically. To maximize the IC's performance, the interaction terms must be adapted to the capacity and betweenness centrality degree of caches and the contents' popularity. The proposed algorithms are extensively analyzed and evaluated in various simulation scenarios showing that the IC significantly outperforms comparable caching strategies in terms of hit ratio.

As the global air-traffic rises, current communication systems for aircraft like satellites and ground based infrastructure will reach their capacity limits. Especially for rural and oceanic regions, the establishment of an Aircraft Adhoc Network (AANET) is a promising solution. In this paper, a tailor-made routing protocol (Link Duration Based AODV) for communication of aircraft on trans-oceanic routes is proposed. It uses an estimation of the expected residual path duration to make informed routing decisions and establish especially long-lasting routes. Two alternative strategies to estimate route durations were designed: In the deterministic strategy (AODV-LD-D), the fact that aircraft mostly exhibit uniform motion is leveraged to estimate link durations from their position and velocity. The stochastic strategy (AODV-LD-S) employs the known and distinct distribution of link durations experienced by oceanic flights. Both strategies were evaluated on real-world aircraft traces over 72 days in simulation. It is shown that both strategies were able to improve the average route lifetime from around 800 s to over 1100 s with the stochastic strategy and even around 1500 s with the deterministic strategy. The increased route lifetime decreases the number of necessary control packets by as much as 44.2 ±8. 5%. Further, it was shown, that AODV-LD achieves the same packet delivery ratio as AODV in all scenarios. Both strategies increase the average hop count of routes by roughly one and therefore increase the average End-to-End delay by around 8ms which is the expected transmission delay for a single hop. Comparing the two strategies, it was observed that AODV-LD-D required a significantly higher amount of control data compared to AODV-LD-S.

In aeronautical communications, legacy systems often only use a small fraction of their historically assigned frequency spectra sparsely over time. Novel systems such as L-band Digital Aeronautical Communications System (LDACS) Air-Air (A/A) need to coexist with legacy systems, and must ensure not to cause excessive interference. The Distance Measuring Equipment (DME) is the most critical legacy system in this case. To analyze the potential number of idle communication resources in LDACS A/A and DME coexistence, we propose a statistical model, which reveals a substantial number of opportunities. Motivated by the statistical properties of the co-existence scenario, we propose a Recurrent Neural Network (RNN) to predict DME patterns reliably. Our architecture is based on a combination of Long Short-Term Memory (LSTM) and dense layers and was found with the help of hyperparameter optimization techniques. The predictor is trained and evaluated on a synthetic data set using realistic DME parameters. Furthermore, we introduce a baseline algorithm for comparison, which makes perfect predictions on a simplified periodic data set but breaks down for realistic scenarios. We argue that our Deep Learning approach can be used in realistic scenarios to detect idle resources given a strict constraint on correctly predicted busy resources.

Going wireless is one of the key industrial trends, which assists the emergence of new manufacturing and maintenance processes by reducing the complexity and cost of physical equipment. However, the adoption of Wireless Sensor Networks (WSNs) in production environments is limited due to the strict Quality of Service (QoS) requirements of industrial applications. In particular, Wireless Avionics Intra-Communication (WAIC) systems operating in 4.3 GHz band are designed for intra-aircraft use cases with considerable restrictions on the transmission power of sensors, which results in multi-hop topologies, complicating a guaranteed QoS. The Internet Engineering Task Force (IETF) has developed the protocol stack IPv6 over the Time Slotted Channel Hopping (TSCH) mode of IEEE 802.15.4 (6TiSCH) based on the IEEE 802.15.4 Standard for Low-Rate Wireless Networks, which combines the TSCH reliability with ubiquitous IPv6 connectivity and with the robust Routing Protocol for Low-Power and Lossy Networks (RPL). The Scheduling Function (SF) is a core IPv6 over the TSCH mode of IEEE 802.15.4 (6TiSCH) component, but the specification of the SF is an open research topic: numerous scientific articles investigated how QoS for a wide range of applications can be met by developing specialized SFs. However, no full-scale information exchange between the layers of the 6TiSCH stack was considered to optimize the SFs and to improve the network performance. In this work, we propose a novel solution named 6TiSCH-CLX to satisfy demanding QoS requirements using cross-layer communication. It is an extension of the 6TiSCH framework at the network and Medium Access Control (MAC) layers, addressing latency and reliability challenges agnostic of the physical layer. 6TiSCH-CLX is evaluated both analytically and in simulations for several safety-critical avionic intra-communication use cases in WAIC. Preliminary results indicate considerable improvements to latency, while maintaining almost 100% Packet Delivery Ratio (PDR) without retransmissions and they highlight the capability of the cross-layer approach compared to existing solutions.

This paper analyses how data dissemination occurs in mobile Opportunistic Networks by evaluating the impact of different parameters such as density of neighbors, communication range, and speed. There exist several analytical models to evaluate the data dissemination time in OppNets. These models were developed based on a very strong assumption of uniform distribution of infected nodes. We prove that this assumption does not work for the whole spectrum of mobile OppNets. This paper shows our simulation results validated with our analytical model and discusses the impact of different parameters on data dissemination.

Modern mobile networks in the era of 5G have ambitious performance goals. One envisioned goal is to have communication that is ultra-reliable and ultra-low latency (uRLLC). To ensure reliability, Automatic Repeat Request (ARQ) processes are usually deployed, sometimes combined with forward error correction. As an evolution of the Long Term Evolution (LTE) system, 5G may be foreseen to use similar methods, and so we assume LTE's Hybrid ARQ on the Medium Access Control (MAC) layer, and a Selective Repeat ARQ on the Radio Link Control (RLC) layer. Simulation of LTE systems is a time-consuming endeavor due to its complexity, and when latency and reliability are the key performance indicators, it may be preferable to isolate the ARQ processes. In this manner, this paper presents a mathematical model of the two stacked ARQ processes that are used in today's LTE system. It is based on the method of Signal Flow Graphs (SFGs) and allows the analysis of either ARQ process in isolation, and of both stacked on top of each other. Analytic results are shown for a realistic set of parameters, and in the spirit of Open Science, the MATLAB implementation files are made available in the conclusion to interested researchers, so that verification and an adaption to similar ARQ processes is easily made.

Next generation mobile systems aim to meet the strict demands of an exponentially increasing number of users. Particularly device-to-device (D2D) communication has attracted a lot of attention during the last years. D2D communication can ofïoad cellular trafïc off the base station. It may reuse radio frequency resources simultaneously used by cellular communication for D2D transmissions, thereby increasing spectral efïciency and system capacity. However, reusing frequency resources can lead to in-cell interference. The expected interference must therefore be actively mitigated as part of the scheduling process. We investigate a novel joint radio resource scheduling and allocation algorithm for D2D communication that makes use of two methods from the ïeld of game theory. It aims to meet the respective user’s Quality of Service requirements and strives for fairness between users by playing a Transferable Utility game. At the same time it actively mitigates in-cell interference from frequency resource reuse and determines an optimal transmission power through Stackelberg gameplays. It is shown through simulation that system performance increases if resource allocation and reuse is done in a coordinated manner. The proposed scheduler scales well due to its polynomial computational complexity and outperforms baseline schedulers and the single-game approach in several simulated scenarios.

Today Wireless Sensor Networks (WSNs) can be found in many application areas, e.g. they are used in smart home systems or in industrial settings in order to monitor and control machinery. The latter usually requires a guaranteed performance of the network. This mainly addresses the real-time capability of the network, i.e. knowledge of possible delays which occur on the multi-hop route between sender and receiver is needed. In this paper, a novel approach to model multi-hop networks with a fixed number of nodes uniformly distributed on a square area is proposed. Accordingly, no explicit knowledge of the routing and the topology is needed. That is, no specific network is reflected, but a class of random networks sharing common properties is modelled. In our model, all nodes generate frames according to a Poisson process with the same rate and send them to a common gateway. Based on this scenario, we deduce a mathematical model for the probability of simultaneous transmissions assuming that a generic CSMA MAC protocol is implemented. We use this result in order to derive an expression for the mean delays arising on the links, i.e. the medium access and queueing delay, of the multi-hop route in the special case of the IEEE 802.15.4 MAC and PHY protocols being used. The model results correspond well to an OMNeT++ simulation if the offered traffic does not exceed a certain limit. Beyond this limit, up to the capacity of the network, the model still captures the behaviour of the simulation but the deviation grows.

Aircraft Ad-hoc Networks (AANETs) are capable not only to allow low-latency Internet connectivity on aircraft but also to transmit safety-critical data. An aircraft in distress could transmit important information to another nearby aircraft in range before it crashes on the ground. In this paper the link probability for aircraft crossing the North Atlantic Corridor is investigated. An analytical model for the nearest neighbor distribution is proposed taking the shape and dynamic position of North Atlantic flight corridors into account. A uniform distribution of nodes is assumed in a bounded model area. Simulation results and empirical aircraft position data captured over 10 weeks are analyzed and used for verification of the analytical model. The link probability is derived from the nearest neighbor distribution and the model performance is evaluated. Aircraft sticking to North Atlantic flight tracks bias the assumed uniform distribution over the area. Therefore the results differ for east-and westbound flights. A link probability of more than 99% can be achieved if the communication range is greater than 250km and at least 40 aircraft are located within the model area. The average error of the model predicting the required communication range for a 99% link probability amounts to 8.94%.

Still today, aircraft disappear and crash without communicating their last position. Looking into details, satellite communications currently seems to be the only reliable way to connect and send data on long-distance flights. However, geostationary satellite systems suffer from high propagation delays making Forward Error Correction (FEC) schemes beneficial compared to error handling by retransmissions. In this paper, Random Linear Network Coding (RLNC) is proposed as a packet level FEC technique for high delay satellite communication. Using emulation, it is shown that correlated losses typical for a satellite channel result in a high variation in the number of redundant symbols required to decode a generation. This can be improved by using interleaving, which comes by the cost of an increased delay. A novel approach is introduced that combines On-the-fly Coding and interleaving. This can significantly reduce the average delay introduced by interleaving and allows to efficiently overcome correlated losses in combination with Network Coding for time-critical applications.

In autonomous platooning of vehicles, robust Cooperative Adaptive Cruise Control (CACC) systems are required for guaranteeing reliable and stable driving performance. Cruise control systems should meet two requirements: prevent collisions between vehicles in any event and prevent amplification of distance errors along the platoon. The absence of one of these requirements causes weak road utilization and fuel efficiency and eventually leads to decreased safety. By usage of suitable control system parameters and deployment of appropriate means of communication between members of a platoon, these risks may be minimized. In this research, an evaluation platform for stability and risk-of-collision of autonomous vehicle platoons is developed. It allows for performance analysis for a large range of controller specifications and network characteristics by extensive simulation based on real-world vehicle parameters. The experiments show platoon performance limits caused by communication constraints and control system specifications. First results suggest that the choice of controller parameters strongly affects communication system requirements. Larger distances and more aggressive controller gains can reduce demands on the radio link to a great extent. The contribution of this work is twofold: firstly, platoon performance of correlated network errors is evaluated broadly and secondly, performance dependencies between communication limitations and the control design are shown.

This paper focuses on modeling the charateristics of opportunistic networks (OppNets). The motivation of this work is to develop a model which is closer to the reality to represent the data dissemination in OppNets. This paper shows our preliminary results validating our model in OppNets scenarios which give an opportunity to exchange data among a group of people.

On-board commercial passenger aircraft Wireless Sensor Networks (WSNs) are anticipated to be used for implementing machine-to-machine communication also referred to as Wireless Avionics Intra-Communications (WAIC). These systems enable safety-related wireless avionics and aim to reduce electrical wiring harness contributing by 5% of the total weight of an aircraft. The globally harmonized frequency band designated for WAIC usage is shared with aeronautical Radio Altimeters (RAs). Literature lacks consideration of the impact of on-board RAs on WAIC systems; thus, we close this gap by performing a detailed study and propose two mitigation techniques based on channel hopping. Our simulations show that harmful RA signals infer doubled to tripled delays as well as packet error rates up to 90% when WAIC systems use the frequency band without applying appropriate techniques for increasing communication robustness. With the developed mitigation techniques, we show delays can be kept at levels comparable to non-interfered performance while increasing the usable spectrum by 50% simultaneously. Our evaluations show that the presented mitigation techniques enable reliable usage of WAIC systems in commercial aircraft allowing increased spectrum usage.

This paper proposes an efficient optimization algorithm to dynamically control the Evolved Packet System (EPS) bearer rates to transport various services between the UE and Evolved Packet Core (EPC) in a LTE Femtocell network scenario. The algorithm is focused on improving the accumulated QoE in the networks and takes joint consideration of limited radio and transport resource so as to leverage the resource management in LTE Radio Access Network (RAN) and transport network. In case of link congestion applications running on TCP tend to share the capacity equally. However, different traffic types have different QoE behaviors and hence sharing the resource equally will lead to a non-optimal aggregated QoE. The proposed algorithm will solve this problem by considering the QoE of individual application flows. We formulate the problem as a convex optimization problem, which maximizes the aggregated QoE, represented by Mean Opinion Score (MOS) value, of all users using different applications, and then solve it using Lagrangian relaxation method. The performance of our algorithms is investigated and evaluated by simulations. The simulations show that our proposed QoE-driven rate shaping algorithm results in a significantly better aggregated QoE compared to the legacy scheme that with fixed rate shaping, especially in heavily congested scenarios. Moreover, a discussion on how often to adjust the shaping rates is given based on the complexity and performance investigations.

In this paper, we study the coordinated QoE-based resource allocation problem for downlink direction in a LTE femtocell cluster, considering the transport network limitation. We first formulate the problem as a convex optimization problem, which maximizes the aggregated QoE of all users and solve it using Lagrangian relaxation method. This approach provides an ideal resource allocation solution but it is not practical, because the allocated bandwidth in the model is assumed to be a real value, while in practice, only an integer amount of Physical Resource Blocks (PRBs) can be assigned to a user. However, it is considered as a benchmark for our new developed algorithms. Afterwards, we propose efficient heuristics, which can be applied in real LTE systems due to their low complexity. The performance of our algorithms is investigated and evaluated by simulations. The simulations show that the coordinated resource allocation scheme considering transport limitation results in a better average QoE compared the scheme that does not take into account the transport network capacity. Furthermore, our proposed heuristics are very close to the theoretical optimal bound.

In this paper, we study the QoE-based resource allocation problem for downlink direction in LTE femtocells, considering the transport network limitation. We first formulate the problem as a convex optimization problem, which maximizes the aggregated QoE of all users and solve it using Lagrangian relaxation method. This approach provides an ideal resource allocation solution but it is not practical, because the allocated bandwidth in the model is assumed to be a real value, while in practice, only an integer amount of Physical Resource Blocks (PRBs) can be assigned to a user. However, it is considered as a benchmark for our new developed algorithm. Then we propose an efficient heuristic, which can be applied in real LTE systems. The heuristic is mathematically proven to provide an optimal solution in case there is no limitation in the transport network. In case of transport network limitation, the simulation results show that it gives almost identical performance (ca. 1%) as the optimal solution in the investigated scenario.

In this paper, we propose a new algorithm to solve the downlink resource allocation problem in LTE networks taking the channel conditions into account. We first formulate the problem as a convex optimization problem, which maximizes the aggregated utility of all users. Different from other papers of the same topic, we construct the utility function based on the Exponential Moving Average (EMA) rate instead of the instantaneous data rate. The advantage of this approach is that it guarantees the users with very bad channel conditions still to be scheduled, even if the number of Physical Resource Blocks (PRBs) is smaller than the number of users. The problem is solved optimally with the Lagrangian decomposition method. Extensive simulations have been carried out to compare our approach to the instantaneous data rate approach and to analyze the influence of the system parameters on the behavior of the algorithm.

Network Virtualization (NV) offers an efficient usage of resource by sharing the infrastructure with different virtual network operators while deploying new services. However, it also raises new challenges for network operators and researchers [1]. One of the main challenges is the efficient resource allocation, known as virtual network (VN) mapping problem. In a dynamic scenario, where VN requests come and leave dynamically, the ability to reallocate the currently-mapped networks allows to enhance the resource utilization. But it also leads to the service disruption of reconfigured virtual networks. In this paper, we study the problem of virtual network reconfiguration taking into account the cost incurred by the disrupted services. Most of the recent research on this topic just focused on the acceptance ratio of the virtual networks but didn't address the possible service disruption during the reconfiguration. This paper proposes a reconfiguration mechanism, which is triggered whenever a new coming virtual network request cannot be mapped on the current network. The mechanism re-allocates the currently-mapped networks to accommodate the new request, provided that the minimized cost of reconfiguration doesn't not exceed the gain from mapping the new request. The approach is mathematically formulated as Integer Linear Programming (ILP) problem that maximizes the net gain of the reconfiguration. Its performance is then evaluated and analysed thoroughly through extensive simulations. Finally, a heuristic is proposed to shorten the solving time of the ILP problem while maintaining its performance.

Content Centric Networking (CCN) has been recently proposed as a potential candidate for the future Internet architecture. It allows users to focus on the data they are interested in, rather than having to connect to a specific physical host where the data locates. CCN is claimed to inherently support mobility. While this is true for content receivers, source mobility as well as handovers still remain a challenging tasks in CCN. This paper proposes a novel handover prediction mechanism based on received signal strength (RSS), delay and handover cost using the nonlinear autoregressive exogenous model (NARX). We first introduce a mathematical model using Integer Linear Programming (ILP) to solve the handover decision problem assuming that the mobility scenario is known. This ILP model minimizes the overall cost over the considered time period including the cost of handover and the cost of using a certain network. The ILP model guarantees an optimal handover solution, which is then used to train the NARX. After the learning phase, the NARX can automatically make the handover decision based on RSS and delay information. The performance evaluation shows that our new mechanism can avoid the ``ping-pong" effect usually seen in threshold-based approaches, and also outperforms the threshold-based handover in terms of delay, which results in a better Quality of Service.

In this paper we present an Open Connectivity Services architecture, which has been conceived such as to cope with the challenges posed by the Future Internet. By relying on currently working solutions and establishing a trustworthy migration strategy, the proposed architecture provides a flexible framework that supports both legacy and enhanced connectivity mechanisms. It is able to dynamically adapt the operation of the involved mechanisms according to the particular requirements of the services and applications. This open architecture is based on three main modules (information gathering, decision taking and decision enforcement) which mimic the basic functionalities of any connectivity mechanism. By having a common way of representing current and future mechanisms, the OConS operation eases the instantiation, launch and interconnection of mechanisms by the specified orchestration procedures. A challenging flash crowd scenario is presented for validation of the architecture, where enhanced connectivity mechanisms support both cloud networking and network of information use cases.

Network Virtualization is claimed to be a key component of the Future Internet, providing the dynamic support of different networks with different paradigms and mechanisms in the same physical infrastructure. A major challenge in the dynamic provision of virtual networks is the efficient embedding of virtual resources into physical ones. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms; most of them either do not consider a simultaneous embedding of virtual nodes and virtual links, or apply link-path formulation, leading to non-optimal solutions. This paper proposes an integer linear programming (ILP) formulation to solve the online virtual network embedding problem as a result of an objective function striving for the minimization of resource consumption and load balancing. To this end 3 different objective functions are proposed and evaluated. This approach applies multi-commodity flow constraint to accomplish a node-link formulation that optimizes the allocation of physical network resources. This proposal is evaluated against state of the art heuristics. The performance of the heuristics related to Virtual Network (VN) request acceptance ratio is, at least, 30% below the one of the Virtual Network Embedding Node-Link Formulation (VNE-NLF) method. From the three cost functions evaluated, the Weighted Shortest Distance Path (WSDP) is the one which embeds more VNs and also requires, on average, less physical resources per embedding.

Multipath transport protocols such as Multipath TCP can concurrently use several subflows to transmit a TCP flow over potentially different paths. Since more than one subflow is used, an efficient multipath scheduling algorithm is needed at the sender. The objective of the scheduler is to identify the subflow over which the current data packet should be sent. This paper compares the most important types of schedulers for multipath transfers. We model their performance analytically and derive key metrics, most notably the resulting end-to-end delay over heterogeneous paths. Our results show that a scheduler minimizing the packet delivery delay yields the best overall performance, but it is complex to realize. An alternative scheduler based on the sender queue size is simpler and has sufficient performance for relatively small asymmetry between the multiple paths. Our model results are confirmed by measurements with a real multipath transport protocol.

Long Term Evolution (LTE) uses Single Carrier Frequency Division Multiple Access (SC-FDMA) as the uplink transmission scheme. The Quality of Service (QoS) provision is one of the primary objectives of the wireless network operators. In this paper, the end-to-end QoS performance of Bandwidth and QoS Aware (BQA) scheduler for LTE uplink is evaluated in heterogeneous traffic environment. The BQA scheduler is designed to provide efficient allocation of radio resources to users according to the QoS requirements of various traffic classes and the instantaneous channel conditions. The user QoS provision is ensured by using dynamic QoS weights. Additionally, the delay sensitive traffic is facilitated by employing delay thresholds. The BQA scheduler algorithm supports multi-bearer users. The end-to-end QoS performance of the scheduler is analyzed in several simulation scenarios. The results show that the proposed scheduler guarantees provision of QoS to users.

Mobile Network Virtualization (NV) is an emerging technique which has drawn increasingly research attention. Network Virtualization enables multiple network operators to share a common infrastructure (including core network, transport network and access network) so as to reduce the investment capital while improving the overall performance at the same time. This is achieved by exploring the multiplexing gain. Similarly, Load Balancing (LB) is a well-known mechanism used in mobile networks to offload excessive traffic from high-load cells (hot spots) to low-load ones within one network operator. This paper aims at investigating the potential gain of applying NV in LTE (Long Term Evolution) networks and compares it with the LB scheme gain. In this paper, we propose an LTE virtualization framework (that enables spectrum sharing) and a dynamic load balancing scheme for multi-eNB and multi-VO (Virtual Operator) systems. We compare the performance gain of both schemes for different applications, e.g. VoIP, video, HTTP and FTP. We also investigate the parameterization of both schemes, e.g. sharing intervals, LB intervals and safety margins, in order to find the optimal parameter settings. The presented results show that the LTE networks can benefit from both NV and LB techniques.

Due to the coexistence of different generations of mobile radio technologies, more and more mobile network operators are keen on deploying multiple radio technologies on a single cell site and carry their traffic over a common transport network. This paper studies such a collocated multiradio system: collocated LTE and HSDPA. Firstly, we investigate the potential gain by using a shared transport network to carry different radio technologies. Furthermore, this paper proposes analytical models to dimension the shared transport network for elastic traffic (TCP-based traffic) from the different radio technologies, by taking traffic characteristics, QoS requirements of each radio technology and the deployed transport QoS function and packet scheduling into considerations. The proposal for modeling the shared transport network is to apply the M/G/R-PS model per QoS class while taking the potential multiplexing gain of bandwidth sharing among the different QoS classes into account. For validating the analytical models, a system simulation model is developed. The analytical results derived from the proposed dimensioning models are validated by comparing with the simulation results for various traffic and network scenarios. Presented results demonstrate that proposed analytical models are well suitable for dimensioning of the shared transport network. With the help of the proposed analytical models, we analyze the potential sharing gain of such a shared transport system under different traffic loads and mix of different radio technologies.

This paper proposes an analytical model for dimensioning transport bandwidths in the Long Term Evolution (LTE) access network. In this work the criterion for dimensioning is the transport network delay QoS (at the packet level). The presented analytical model takes into considerations the key features of the LTE radio interface and the use of Differentiated Service (DiffServ) QoS scheme in the LTE access transport network. Furthermore, the proposed dimensioning approach can be performed for a single transport link as well as for the entire transport network. For validating the analytical dimensioning models, a developed LTE system simulation model is used. The presented results demonstrate that the proposed analytical models can appropriately estimate the transport network delays for different QoS priorities and hence can be used for bandwidth dimensioning for various traffic and network scenarios.

The MAC scheduler is an important and crucial entity of the Long Term Evolution (LTE) and is responsible for efficiently allocating the radio resources among mobile users who have different QoS demands. The scheduler takes different considerations into account such as throughput and fairness when deciding the allocation of the scarce radio resources. LTE is an all IP packet system in which guaranteeing QoS is a real challenge. Therefore the LTE MAC scheduler should consider not only the throughput optimization but also the QoS differentiations in an effective manner. In this paper, we propose a novel LTE downlink MAC scheduling algorithm. The proposed scheduler differentiates between the different QoS classes and their requirements. Two different QoS classifications are considered: Guaranteed Bit Rate (GBR) and non Guaranteed Bit Rate (non-GBR). The proposed scheduler also considers the different users channel conditions and tries to create a balance between the QoS guarantees and the multi-user diversity in a proportional fair manner. The simulation analysis confirms that guaranteeing the different QoS requirements is possible.

As wireless IP-based networks become more popular and larger in size and coverage, simple mobility management protocols cannot deal with the demands. With the growing access to the Internet, mobility can be divided into macro/micro-mobility domains. Macro-mobility can be efficiently handled with Mobile IP and its derivatives but they do not scale that well for the micro-mobility case. An alternative for micro-mobility domains is to use a reactive route discovery mechanism. Ad-hoc routing protocols such as DSR and AODV are the well known protocols that can be used for this purpose. The disadvantage of the reactive approach is that the route discovery process becomes costly in terms of control overhead and latency of the connection setup when done frequently. In this paper, an optimization of the simple AODV route discovery is proposed, introducing a paging extension. The proposed mechanism is somewhat similar to other paging schemes like Cellular IP, but introduces modifications and enhancements for reducing the paging control overhead. Simulation results of AODV and the enhanced route discovery with paging are presented along with the performance evaluation of both schemes. The simulations were performed with the QualNet Network Simulator.

This paper proposes efficient analytical models to dimension the required transport bandwidths for the Long Term Evolution (LTE) access network for the elastic Internet traffic (which is carried by the TCP protocol). The dimensioning models are based on the use of Processor Sharing queuing theory to guarantee a desired end-to-end application QoS target. For validating the analytical dimensioning models, a developed LTE system simulation model is used. Extensive simulations are performed with various traffic and network scenarios. The analytical results derived from the proposed dimensioning models are compared against the simulation results. The presented results demonstrate that the proposed analytical models can appropriately estimate the application performances of different QoS priorities and thus be used for the link dimensioning for various traffic and network scenarios.

Internet access for highly mobile users in high-speed trains or cars, underground walkways and tunnels is often challenged by intermittent connectivity with short and unpredictable connectivity opportunities. In such opportunistic communication scenarios, utilizing these connectivity opportunities to the best potential for the mobile user can be crucial to achieve an acceptable overall perceived service quality. When wireless access networks are shared between mobile and non-mobile TCP users, this objective can be difficult to achieve especially considering the long-term throughput balance. In this paper, we analyze the performance issues with current TCP implementations and propose a new rate control mechanism called RACING (Rate Control for Intermittent Networking) for increasing long-term TCP throughput for Intermittent Connectivity Nodes (ICNs) in such challenged networks. In the proposed algorithm, the sending rate is adjusted based on the expected traffic during the outage to, in a sense, compensate the ICN for the disruption. The algorithm also considers the fairness with other flows by gradually changing its algorithm closer to the original TCP according to the compensated amount. Computer simulation results show that RACING reasonably improves the performance of the ICN.

Wireless Sensor Networks (WSNs) have been used mainly to collect environmental data and send it to a base station. Routing protocols are needed to efficiently direct the information to the base station. Most of the available routing protocols are designed for conventional WSN applications, where small volume data transmission is required and low power consumption is the fundamental. Support to mobility is generally out of interest, since in most scenarios sensor nodes are static after being deployed. However, in fire fighting rescue scenarios, WSN routing protocols are expected to be able to adapt to change of network topology (caused by nodes failure and fire fighters' movement) rapidly. Moreover, routing protocols should be capable to transmit relatively large volume data (e.g. short voice message) without losing efficiency and reliability. In this paper we propose a broadcasting based communication protocol, which is dedicated to the fire fighting rescue scenarios under the framework of a European project wearIT@work. This protocol is applied to building up a virtual lifeline for fire fighters. The protocol is evaluated through experimental tests and simulations using variant scenarios. Performance metrics such as packet transmission time, jitter and packet loss rate are considered. Results show that our broadcasting based communication protocol is able to fulfill the requirements and is more suitable to fire fighting rescue scenarios.

This paper presents dimensioning of an IP-based UMTS Terrestrial Radio Access Network (UTRAN) with multiple Node Bs connected to one RNC, where the applied QoS architecture is based on Differentiated Service (DiffServ) with an integrated Weighted Fair Queue (WFQ) and Strict Priority (SP) scheduling. To provide an appropriate network dimensioning for guaranteeing a desired end-to-end QoS, a general analytical approach is proposed in this paper to dimension the individual links of the Iub interface (between the Node B and the RNC) and furthermore to derive over-booking for the backbone link for elastic traffic. The analytical approach is validated by simulations. Furthermore, based on the proposed analytical approach, important dimensioning rules are summarized.

High Speed Uplink Packet Access (HSUPA) is an extension of the Universal Mobile Telecommunications System (UMTS) technology of 3GPP Rel-99, with the objective increasing the data rate (up to 5.76 Mbps) and reducing the latency of the uplink. 3GPP UMTS standard Rel-6 introduces a new "Enhanced Dedicated Channel" (E-DCH) for the uplink. The main focus of the work presented in this paper is to analyse the effect of TNL congestion control on the HSUPA performance. The congestion control function works together with the scheduler and HARQ functionality in order to control the offered load to the TNL network. In this manner, the data flow over the transport network (TNL) is adequately controlled and limited to the available TNL capacity by avoiding congestion in the transport network. The TNL congestion control consists of two independent parts: congestion detection and congestion control which have been implemented, tested and validated within the focus of this paper. The simulation results presented in this paper confirm that the congestion in the transport network can be controlled in such a way that the available TNL capacity can be effectively utilised and hence the performance of HSUPA network can be significantly improved in all aspects.

HSUPA (High Speed Uplink Packet Access) is introduced by the 3GPP Release 6 to enhance the UMTS uplink with higher data rates, reduced latency and increased capacity. This paper discusses the dimensioning of the backhaul resources on the ATM-based Iub interface in UMTS HSUPA networks. The main focuses of this paper is to (1) analyze the important factors that have influence on the transport network dimensioning and further investigate their impacts; (2) estimate the required backhaul bandwidth as a function of user QoS requirements; (3) discuss the impact when including HSDPA traffic on the downlink. In addition, this paper also provides insights of HSUPA air interface given diverse user applications as well as different number of users within one cell. The investigations and dimensioning are based on simulations.

This paper discusses the use of Carrier Ethernet for the transport of UMTS radio access network as a alternative solution for the gradual migration towards pure IP-based RAN. By means of Pseudo-Wire technique, the ATM service is emulated over the underlying Ethernet network. Within this work, the performance of such Carrier Ethernet based UTRAN is evaluated and compared to the ATM-based UTRAN of UMTS Release 99, in particular the transport efficiency, the delay and packet losses of the Iub. Another contribution of this paper is to investigate the parameter settings to provide a guideline for the optimum configurations.

High speed downlink packet access (HSDPA) is an extension of the universal mobile telecommunication system (UMTS) technology of 3GPP Rel-99, with the objective of increasing the data rate and also reduce the latency in the downlink. The focus of this study is to develop an analytical model for HSDPA congestion control (CC) performance analysis. Often the transport network layer (TNL) is congested in HSDPA networks which degrades the overall HSDPA performance. The congestion control and detection algorithms are implemented in the Node B and RNC in order to minimize system congestions. There are several simulation based investigations carried out so far for the performance analysis of such algorithms. An analytical model which is based on the Embedded Markov chain with multiple departures (EMC-MD) is developed to analyse the effect of CC for the HSDPA performance. This analytical model includes all the important functionalities of the congestion control at TNL level. This paper also shows that the results from the analytical model are in agreement with the simulation results and that the analytical model can be effectively used to analyse the effect of parameters on performance of the HSDPA network and can be used dimensioning of the parameters.

High speed downlink packet access (HSDPA) is an extension of the Universal Mobile Telecommunications System (UMTS) technology of 3GPP Rel-99, with the objective to increase the data rate and reduce the latency in the downlink. The main focus of the work presented is to analyse the effect of congestion at the Iub interface on the HSDPA performance. The data flows should be adequately controlled in order to avoid congestion in the transport network. The 3GPP (3rd Generation Partnership Project) Rel. 5 specifications highlight two congestion detection mechanisms which are based on the frame sequence number (FSN) and the delay reference time (DRT) fields of HSDPA data frame. In addition to these, a third congestion detection mechanism based of Checksum of HSDPA data frame is considered. This paper discusses a congestion control scheme deploying all three congestion detection methods. It is shown, that a congestion control algorithm can effectively work using these congestion detection triggers and can control the offered load to the transport network. The simulation results presented in this paper confirm that the congestion in the transport network can be avoided, and hence the performance of HSDPA network can be significantly improved in all aspects.

In this paper, a novel approach of HSUPA modeling for static simulation is proposed. This approach is based on the simulation results from time-based simulation and combines the well-known snapshot procedure for R99 with corresponding enhancements for the specific features of HSUPA. The detailed simulation structure and required deduction of multi-cell system equation group are described, respectively. The simulation results show that the new static approach can yield significant performance evaluation for a network much faster than the time- based approach and have comparable quality of the results at the same time. The presented approach is as well applicable for detailed system-level simulations as for incorporation in network dimensioning and planning tools.

In this work, we investigate the use of directional antennas and beam steering techniques to improve performance of 802.11 links in the context of communication between amoving vehicle and roadside APs. To this end, we develop a framework called MobiSteer that provides practical approaches to perform beam steering. MobiSteer can operate in two modes - cached mode - where it uses prior radiosurvey data collected during "idle" drives, and online mode, where it uses probing. The goal is to select the best AP and beam combination at each point along the drive given the available information, so that the throughput can be maximized. For the cached mode, an optimal algorithm for AP and beam selection is developed that factors in all overheads.

An ad-hoc network is a network whose particular characteristics include absence of any kind of infrastructure, dynamic topology and limited resources. Up to day, several routing protocols have been proposed to face such a hostile environment. These solutions usually provide to the sources of data flows with single valid paths towards their destinations. However, it has been proven that maintaining multiple paths can be favorable to the network, either using the paths at the same time (for load balancing) or using an alternative path, when the primary one fails. It is also a way to meet the Quality of Service requirements demanded by some particular applications. In this paper, we propose a novel routing mechanism based on Dynamic MANET On-demand (DYMO) routing protocol, in order to enable the establishment of more than one node disjoint routes towards the same destination. Simulation results show that there is a significant gain in end-to-end delay for data packets and a reduction in the number of the transmitted routing packets.

In this paper, a QoS-aware cross-layer scheduler for wireless LANs is introduced which allows the control of a number of data flows according to QoS requirements of the respective applications. It is based on a two-stage concept: The MAC layer scheduler uses an importance function to calculate the priority of a particular flow, whereas the PHY layer scheduler considers the channel conditions of a MIMO-TDMA transmission. It is shown that with the concept presented here, throughput and delay requirements of time-critical applications can be met.

In order to improve the effective utilization of the radio resources, bit rate adaptation (BRA) is applied in the UMTS system, specifically for the best effort and interactive packet traffic. This paper presents investigation results on the optimization of bit rate adaptation (BRA) scheme for an efficient data support in the UMTS radio access network.

This paper presents first results of experiments in vehicular-to-roadside communication using directional antennas. With directional antennas on one side, the duration of connection to a fixed access point or a road side communication unit can be extended and on the other side the interference caused to others can be reduced. In this work results of experiments with electronical steerable directional antennas mounted on a car communicating with stationary access points are presented. The measurements show the benefit of using directional antennas in different environments typical for vehicular communications. The duration of potential 802.11b connections have been compared using directional and omnidirectional antenna patterns when driving through suburban environment. This comparison is based on passive scanning for access points in order to validate the approach in realistic scenarios. The results clearly prove a substantial potential improvement when using directional antennas.

The increasing complexity and dynamics of logistic processes is creating significant new challenges for the management of goods transport. This is leading to increased requirements for the routing of goods and transport vehicles in order to adapt to the dynamics of the changing logistics environment. Current practice of vehicle and goods routing is based on centralised planning and control. This approach is now rapidly becoming too inflexible and complex for maintaining efficient goods transport. In this paper we introduce a novel routing process which implements distributed decision making among transport vehicles, goods items, and other entities in a logistic transport network. The proposed approach enables packages (goods items) and transport vehicles to find their routes autonomously whilst reacting to dynamic changes in their environment.