Multiple Source-destination Pairs Research Articles

High-fidelity entanglement routing in quantum networks

Quantum networks, endowed with their distinct quantum properties, are poised to emerge as indispensable platforms for the implementation of quantum information technology applications in the near future. Within the realm of quantum networks, the transmission of remote quantum information presents a pivotal and intricate challenge, commonly referred to as the entanglement routing problem. While previous efforts have delved into the intricacies of entanglement routing, there has been a notable oversight concerning the crucial parameter of entanglement fidelity. Hence, this paper introduces a novel Purification-enabled Entanglement Routing Algorithm (PERA). Initially, PERA utilizes the network throughput as the routing metric and ensures fidelity guarantees on all nodes in the link through a hop-by-hop purification process. Subsequently, acknowledging the probabilistic nature of entanglement purification, a strategy involving multiple attempts at purification is employed. Finally, a comprehensive utility function is deployed to address the path selection problem for multiple source–destination pairs. Numerical simulations confirm that PERA establishes entanglement connections with outstanding fidelity guarantees. Concurrently, PERA outperforms the baseline algorithm in terms of network throughput and resource utilization.

A Multi-Objective Optimization-Based Transmission Design for V2V Communication Networks

Data delivery in vehicular networks confronts unique challenges due to vehicle movement and stringent quality-of-service (QoS) demands. This paper investigates the efficient transmission design problem in a typical vehicle-to-vehicle (V2V) communication network, where multiple source-destination pairs with different types of message transmission requirements coexist and the network environment dynamically changes. A sequential transmission decision framework based on the multi-objective optimization (MOO) theory is proposed to maximize the performance of each link, while ensuring the QoS of different messages. We integrate the Lyapunov optimization theory with the weighted Tchebycheff method, as well as other mathematical optimization tools, to transform the original problem into a solvable MOO problem at each time slot. Transmission actions can be determined continuously according to the environment change and time-related design goals. The effectiveness and efficiency of the proposed method are demonstrated through extensive simulation experiments.

Generation of Homotopy Classes for Unconstrained 3D Wire Routing from Characteristic Loops

Routing of wire harnesses in complex machinery is a complicated problem. In this paper, we present an approach for computing all non-homotopic paths characteristic of all the homotopy classes associated with a pair of source–destination points embedded on the surface of the product. We introduce the notion of routing graphs, which are generated from specific non-trivial loops in the first homology group associated with the surface of the product. The routing graph, which is constructed only once, encodes the homotopy of the routing environment and is, therefore, used to find all the non-homotopic paths between multiple source–destination pairs. Based on the path embedding requirements, we classify the routing process into (1) On-Surface Routing, when the paths are constrained to the surface of the product, and (2) In-Air Routing, when the paths are allowed to venture into the product ambiance space. In the former case, the routing graph is defined by both the handle and tunnel loops in the first homology group, whereas in the latter case, it is defined by only the handle loops. We propose a linking number-based strategy for computing the handle and tunnel loops for a given closed surface. The methods are extended for routing in assemblies using the so-called shell structures associated with them. The results obtained demonstrate the efficacy of the proposed approach. The results show that the computation of the routing graph is very efficient, and the homotopy classes can be generated in very little time using the proposed approach.

Memory-Occupied Routing Algorithms for Quantum Relay Networks

Quantum transmission experiments have shown that the successful transmission rate of entangled quanta in optical fibers decreases exponentially. Although current quantum networks deploy quantum relays to establish long-distance connections, the increase in transmission distance and entanglement switching costs still need to be considered when selecting the next hop. However, most of the existing quantum network models prefer to consider the parameters of the physical layer, which ignore the influence factors of the network layer. In this paper, we propose a meshy quantum network model based on quantum teleportation, which considers both network layer and physical layer parameters. The proposed model can reflect the realistic transmission characteristics and morphological characteristics of the quantum relay network. Then, we study the network throughput of different routing algorithms with the same given parameters when multiple source-destination pairs are interconnected simultaneously. To solve the challenges of routing competition caused by the simultaneous transmission, we present greedy memory-occupied algorithm Q-GMOA and random memory-occupied algorithm Q-RMOA. The proposed meshy quantum network model and the memory-occupied routing algorithms can improve the utilization rate of resources and the transmission performance of the quantum network. And the evaluation results indicate that the proposed methods embrace a higher transmission rate than the previous methods with repeater occupation.

Fidelity-Guaranteed Entanglement Routing in Quantum Networks

Entanglement routing establishes remote entanglement connection between two arbitrary nodes, which is one of the most important functions in quantum networks. The existing routing mechanisms mainly improve the robustness and throughput facing the failure of entanglement generations, which, however, rarely include the considerations on the most important metric to evaluate the quality of connection, entanglement fidelity. To solve this problem, we propose purification-enabled entanglement routing designs to provide fidelity guarantee for multiple Source-Destination (S-D) pairs in quantum networks. In our proposal, we first consider the single S-D pair scenario and design an iterative routing algorithm, Q-PATH, to find the optimal purification decisions along the routing path with minimum entangled pair cost. Further, a low-complexity routing algorithm using an extended Dijkstra algorithm, Q-LEAP, is designed to reduce the computational complexity by using a simple but effective purification decision method. Finally, we consider the common scenario with multiple S-D pairs and design a greedy-based algorithm considering resource allocation and re-routing process for multiple routing requests. Simulation results show that the proposed algorithms not only can provide fidelity-guaranteed routing solutions, but also has superior performance in terms of throughput, fidelity of end-to-end entanglement connection, and resource utilization ratio, compared with the existing routing scheme.

Feasibility of Joint Power Optimization of Multiple Source-Destinations in an AF Relay Network

Joint power optimization of sources and relay in cooperative networks, while multiple source-destination (SD) pairs are utilizing a relay and also have direct transmission links, is addressed in this letter. In the assumed network each SD pair requires a minimum quality of service (QoS) in terms of its received SINR. We have shown that the resulted power control equations are quadratic due to coexistence of direct and relay links. The feasibility analysis of the resulted non-convex optimization problems is complicated. The necessary condition for the optimization problem feasibility is studied and two upper bounds for the achievable SINR of the users are derived. Computer simulations are used to study the achievable SINRs and the results are compared with the obtained upper bounds.

Full-Duplex UAV Relaying for Multiple User Pairs

Based on the advantages of small size, lightweight, as well as flexible deployment and recycling, unmanned aerial vehicle (UAV) has been more and more widely used in military and civilian. As flying relays, UAVs can quickly set up relay communication links for different missions, to enhance the receiving signal power, increase the system capacity, and expand the communication coverage. In this article, we investigate full-duplex (FD) UAV relaying for multiple source–destination pairs. To fully exploit the flying flexibility of the UAV in serving multiple source–destination pairs, we propose a scheduling protocol that exploits time-division multiple access (TDMA) to serve different source–destination pairs in turns when flying along an optimized trajectory. Then, we further formulate a joint optimization problem of the TDMA-based user scheduling, the dynamic UAV trajectory, and the UAV transmit power to maximize the system throughput. The formulated problem is nonconvex that makes it difficult to solve directly, hence we propose an iterative algorithm to obtain an approximate optimal solution based on block coordinate descent and successive convex optimization techniques. Simulation results demonstrate that our proposed FD-based UAV relaying network achieves significant throughput gains compared with the half-duplex (HD) baseline, and the TDMA-based protocol outperforms the OFDMA-based ones with fixed UAV position/trajectory when the UAV helps relay information for multiple source–destination pairs.

Multihop Wireless Networks With Quality-of-Service: Fluid and Diffusion Approximations

We consider a multihop wireless network. There are multiple source destination pairs. We propose a scheduling algorithm to provide end-to-end mean delay guarantees to the flows. We demonstrate that the algorithm is also throughput optimal. Under heavy traffic, we obtain a Brownian approximation of the network. Furthermore, we also show that the stationary distribution of the scaled process of the network converges to that of the Brownian limit, providing an approximation to the stationary distribution under heavy traffic. Finally simulations further verify our claims.

Routing for Traffic Networks With Mixed Autonomy

In this article, we propose a macroscopic model for studying routing on networks shared between human-driven and autonomous vehicles that captures the effects of autonomous vehicles forming platoons. We use this to study inefficiency due to selfish routing and bound the price of anarchy (PoA), the maximum ratio between total delay experienced by selfish users and the minimum possible total delay. To do so, we establish two road capacity models, each corresponding to an assumption regarding the platooning capabilities of autonomous vehicles. Using these, we develop a class of road delay functions, parameterized by the road capacity, that are polynomial with respect to vehicle flow. We then bound the PoA and the bicriteria, another measure of the inefficiency due to selfish routing, for general networks with multiple source-destination pairs. We find these bounds depend on: the degree of the polynomial in the road delay function; and the degree of asymmetry, the difference in how human-driven and autonomous traffic affect road delay. We demonstrate that these bounds recover the classical bounds when no asymmetry exists. We show the bounds are tight in certain cases and that the PoA bound is order optimal with respect to the degree of asymmetry.

Techniques for extending unicast CR networks to multi‐source multi‐destination over Rayleigh fading channels

In this work, the authors propose a novel technique to extend the scope of cognitive radio (CR) networks to multiple source–destination pairs. To accomplish this, a simplified feasible path set is formed and then three types of criteria or methods are employed to reach a solution for the best path for each pair. This set is defined by non-intersecting paths which do not share any relay nodes. This not only solves the problem at hand but also greatly reduces the complexity which leads to a fast solution. The first method uses the maximum probability of success as a means for selecting the best path. In the second method, a fast and simple technique is used by choosing the minimum number of overall hops for path selection. The element with the minimum overall transmission time is selected for data transmission in the third technique. Finally, the proposed methods are compared through simulation to a unicast single user case in terms of throughput and packet delivery rate. The simulation results show that the first method has the best performance while the second method is slightly worse but faster.

Tracking routes in communication networks

The minimum tracking set problem is an optimization problem that deals with monitoring communication paths that can be used for exchanging point-to-point messages using as few tracking devices as possible. More precisely, a tracking set of a given graph G and a set of source-destination pairs of vertices is a subset T of vertices of G such that the vertices in T traversed by any source-destination shortest path P uniquely identify P. The minimum tracking set problem has been introduced in Banik et al., CIAC (2017) [1] for the case of a single source-destination pair. There, the authors show that the problem is APX-hard and that it can be 2-approximated for the class of planar graphs, even though no hardness result is known for this case. In this paper we focus on the case of multiple source-destination pairs and we present the first O˜(n)-approximation algorithm for general graphs. Moreover, we prove that the problem remains NP-hard even for cubic planar graphs and all pairs S×D, where S and D are the sets of sources and destinations, respectively. Finally, for the case of a single source-destination pair, we design an (exact) FPT algorithm w.r.t. the maximum number of vertices at the same distance from the source.

Secrecy Outage and Diversity Analysis of Multiple Cooperating Source-Destination Pairs

We study the physical-layer security of multiple source-destination (SD) pairs communicating within a wireless network in the face of an eavesdropper attacking the SD pairs. In order to protect the wireless transmission against eavesdropping, we propose a cooperation framework relying on two stages. Specifically, an SD pair is selected to access the total allocated spectrum using an appropriately designed scheme at the beginning of the first stage. The other source nodes (SNs) simultaneously transmit their data to the SN of the above-mentioned SD pair relying on orthogonal resources during the first stage. Then, the SN of the chosen SD pair transmits the data packets containing its own messages and the other SNs’ messages to its dedicated destination node (DN) in the second stage. Finally, this dedicated DN will forward all the other DNs’ data to the application center via the core network. We conceive a specific SD pair selection scheme, termed as the transmit antenna selection aided source-destination pair selection (TAS-SDPS). We continue by deriving the secrecy outage probability (SOP) expressions of both the TAS-SDPS conceived, as well as of the conventional round-robin source-destination pair selection (RSDPS) and of the conventional non-cooperative (Non-coop) schemes for comparison. Furthermore, we carry out the secrecy diversity gain analysis in the high main-to-eavesdropper ratio (MER) region, showing that the TAS-SDPS scheme is capable of achieving the maximum attainable secrecy diversity order. Additionally, we show that increasing the number of transmitting pairs will reduce the SOP, whilst increasing the secrecy diversity order of the TAS-SDPS scheme. It is demonstrated that the SOP of the TAS-SDPS scheme is better than that of the RSDPS and of the conventional Non-coop schemes. We also demonstrate that the secrecy diversity gain of the proposed TAS-SDPS scheme is $M$ times that of the RSDPS scheme in the high-MER region, where $M$ is the number of the SD pairs.

P4Consist: Toward Consistent P4 SDNs

The prevailing wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Unfortunately, bugs, misconfigurations, faults or attacks can introduce inconsistencies between the network control and the data plane that can undermine the correct operation at runtime. Through our experiments, we realize that P4 SDNs are no exception, and are prone to similar problems. With the aim to verify the control-data plane inconsistency, we present the design and implementation of P4Consist, a system to detect the inconsistency between control and data plane in P4 SDNs. P4Consist generates active probe-based traffic continuously or periodically as an input to the P4 SDNs to check whether the actual behavior on the data plane corresponds to the expected control plane behavior. In P4Consist, the control plane and the data plane generate independent reports which are later, compared to verify the control-data plane consistency. The previous works in the field of monitoring and verification mostly aim to test the P4 programs through static analysis and thus, are insufficient to verify the network consistency at runtime. Experiments with our prototype implementation of P4Consist are promising and show that P4Consist can verify the control-data plane consistency in the complex datacenter 4-ary fat-tree (20 switches) and multipath grid (4, 9 and 16 switches) topologies with 60k rules per switch within a minimum time of 4 minutes. At the same time, P4Consist scales to multiple source-destination pairs to detect control-data plane inconsistency.

Entanglement Distribution in a Quantum Network: A Multicommodity Flow-Based Approach

We consider the problem of optimising the achievable EPR-pair distribution rate between multiple source-destination pairs in a quantum internet, where the repeaters may perform a probabilistic bell-state measurement and we may impose a minimum end-to-end fidelity as a requirement. We construct an efficient linear programming formulation that computes the maximum total achievable entanglement distribution rate, satisfying the end-to-end fidelity constraint in polynomial time (in the number of nodes in the network). We also propose an efficient algorithm that takes the output of the linear programming solver as an input and runs in polynomial time (in the number of nodes) to produce the set of paths to be used to achieve the entanglement distribution rate. Moreover, we point out a practical entanglement generation protocol which can achieve those rates.

Deep Reinforcement Learning-Based Access Control for Buffer-Aided Relaying Systems With Energy Harvesting

This paper considered a buffer-aided relaying system with multiple source-destination pairs and a relay node (RN) with energy harvesting (EH) capability. The RN harvests energy from the ambient environment and uses the harvested energy to forward the sources' information packet to the corresponding destinations. It is assumed that information on the EH and channel gain processes is unavailable. Thus, the model free deep reinforcement learning (DRL) method, specifically the deep Q-learning, is applied to learn an optimal link selection policy directly from historical experience to maximize the system utility. In addition, by taking advantage of the structural features of the considered system, a pretraining scheme is proposed to accelerate the training convergence of the deep Q-network. Experiment results show that the proposed pretraining method can significantly reduce the training time required. Moreover, the performance of the transmission policy obtained by using deep Q-learning is compared with that of several conventional transmission schemes. It is shown that the transmission policy obtained by using our proposed model can achieve better performance.

Minimizing end-to-end delay in multi-hop wireless networks with optimized transmission scheduling

The problem of transmission scheduling in single hop and multi-hop wireless networks has been extensively studied. The focus has been on optimizing the efficiency of transmission parallelization, through a minimum-length schedule that meets a given set of traffic demands using the smallest possible number of time slots. Each time slot is associated with a set of transmissions that are compatible with each other according to the considered interference model. The minimum-length approach maximizes the resource reuse, but it does not ensure minimum end-to-end packet delay for multiple source-destination pairs, due to its inherent assumption of frame periodicity. In the paper we study the problem of transmission scheduling and routing aiming at minimizing the end-to-end delay under the signal-to-interference-and-noise-ratio (SINR) model for multi-hop networks. Two schemes are investigated. The first scheme departs from the conventional scheduling approach, by addressing explicitly end-to-end delay and removing the restriction of frame periodicity. The second scheme extends the first one by featuring cooperative forwarding and forward interference cancellation. We study the properties of the two schemes, and propose novel mixed-integer programming models and solution algorithms. Extensive results are provided to gain insights on how the schemes perform in end-to-end delay.

Physical-Layer Security in Full-Duplex Multi-Hop Multi-User Wireless Network With Relay Selection

This paper investigates the relay selection (RS) problem for multi-hop full-duplex relay networks where multiple source-destination (SD) pairs compete for the same pool of relays, under the attack of multiple eavesdroppers. To enhance the physical-layer security, within a given coherence time, our objective is to jointly assign the available relays at each hop to different SD pairs to maximize the minimum secrecy rate among all pairs. Two RS schemes, optimal RS and suboptimal RS (SRS), are proposed for two-hop networks based on global channel state information (CSI) and only SD pairs CSI, respectively. Since all users can communicate within the same coherence time, our joint RS schemes are important for the user-fairness and ultra-reliable low-latency communications. To evaluate the performance, the exact secrecy outage probability of the SRS scheme is derived under two residual self-interference models. The asymptotic analysis shows that the SRS scheme achieves full diversity. A relay-based jamming scheme is also proposed by using unassigned relays for user communications. Finally, the two-hop RS schemes and the analysis are extended to the general multi-hop network with multiple eavesdroppers. The numerical results reveal interesting fundamental trends where the proposed schemes can significantly enhance the secrecy performance.

A Physical-Layer Scheduling Approach in Large-Scale Cooperative Networks

In a sensor, mesh, or ad hoc network, different transmissions take place between multiple source-destination pairs, which is referred to as data flows. In this paper, each data flow is associated with a certain duty cycle schedule to avoid collisions of multiple flows in an energy-efficient manner. Cooperative routes in the network are assumed to be linear and strip-shaped, where each hop or a level contains multiple nodes, and the distance between the nodes is kept constant. We assume all nodes in a cooperative route, which corresponds to one source-destination pair, follow the same duty cycle schedule, while schedules of different routes are orthogonal in time to avoid interference between routes. Therefore, when a new route is formed, it is important to select a duty cycle schedule that is not already in use by the nodes participating in the new route. As part of route set-up, an orthogonal frequency division multiplexing packet travels from the source to the destination, identifying the schedules in use by the nodes along the path. Our objective in this paper is to analyze the probabilities of detection for this method of detecting schedules, which is useful to gain insights into duty cycling-based medium access protocol design in the presence of multiple data flows. To this end, the successive transmissions in a linear network are modeled using an irreducible discrete time Markov chain. Also, three different approaches to detect a certain schedule are investigated, which are distinguished by the binary integration process with multiple sub-carriers corresponding to the schedule. We derive the probability transition matrix for the Markov chain based on different distributions of the received signal energy, the left eigenvector of which yields the probability of detection.

Charge-Then-Forward: Wireless-Powered Communication for Multiuser Relay Networks

This paper studies a relay-assisted wireless-powered communication network consisting of multiple source-destination pairs and a hybrid relay node (HRN). We consider a “charge-then-forward” protocol at the HRN, in which the HRN with constant energy supply first acts as an energy transmitter to charge the sources, and then forwards the information from the sources to their destinations through time division multiple access (TDMA) or frequency division multiple access (FDMA). Processing costs at the wireless-powered sources are taken into account. Our goal is to maximize the sum rate of all transmission pairs by jointly optimizing the time, frequency, and power resources. The formulated optimization problems for both TDMA and FDMA are non-convex. For the TDMA scheme, by appropriate transformation, the problem is reformulated as a convex problem and be optimally solved. For the FDMA case, we find the asymptotically optimal solution in the dual domain. Furthermore, suboptimal algorithms are proposed for both schemes to tradeoff the complexity and performance. Finally, the simulation results validate the effectiveness of the proposed schemes.

Optimal Multicommodity Spectrum-Efficient Routing in Multihop Wireless Networks

Finding the route with maximum end-to-end spectral efficiency in multihop wireless networks has been subject to interest in the recent literature. All previous studies, however, focused on finding one route from a given source to a given destination under the constraint of equal bandwidth sharing. To the best of our knowledge, for the first time, this paper provides extensions to the multicommodity flow case, i.e., the case of multiple simultaneous source-destination (s-d) pairs. In particular, given an arbitrary number of s-d pairs, we address the problem of finding a route for every s-d pair such that the minimum spectral efficiency across all routes is maximized. We provide two alternative approaches, where one is based on fixed-sized time slots and the other is based on variable-sized time slots. For each approach, we derive the provably optimal routing algorithm. We also shed the light on the arising tradeoff between the complexity of network-layer route computation and the complexity of medium access control (MAC) layer scheduling of time slots, as well as the amenability to distributed implementation of our proposed algorithms. Our numerical results further illustrate the efficiency of the proposed approaches and their tradeoffs.