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DQRA: Deep Quantum Routing Agent for Entanglement Routing in Quantum Networks
DQRA: عامل مسیریابی کوانتومی عمیق برای مسیریابی درهم تنیده در شبکه های کوانتومی-2022 Quantum routing plays a key role in the development of the next-generation network system. In
particular, an entangled routing path can be constructed with the help of quantum entanglement and swapping
among particles (e.g., photons) associated with nodes in the network. From another side of computing,
machine learning has achieved numerous breakthrough successes in various application domains, including
networking. Despite its advantages and capabilities, machine learning is not as much utilized in quantum
networking as in other areas. To bridge this gap, in this article, we propose a novel quantum routing model
for quantum networks that employs machine learning architectures to construct the routing path for the
maximum number of demands (source–destination pairs) within a time window. Specifically, we present a
deep reinforcement routing scheme that is called Deep Quantum Routing Agent (DQRA). In short, DQRA
utilizes an empirically designed deep neural network that observes the current network states to accommodate
the network’s demands, which are then connected by a qubit-preserved shortest path algorithm. The training
process of DQRA is guided by a reward function that aims toward maximizing the number of accommodated
requests in each routing window. Our experiment study shows that, on average, DQRA is able to maintain a
rate of successfully routed requests at above 80% in a qubit-limited grid network and approximately 60% in
extreme conditions, i.e., each node can be repeater exactly once in a window. Furthermore, we show that the
model complexity and the computational time of DQRA are polynomial in terms of the sizes of the quantum
networks.
INDEX TERMS: Deep learning | deep reinforcement learning (DRL) | machine learning | next-generation network | quantum network routing | quantum networks. |
مقاله انگلیسی |
2 |
EntangleNetSat: A Satellite-Based Entanglement Resupply Network
-2022 In the practical context of quantum networks, quantum teleportation plays a key role in
transmitting quantum information. In the process of teleportation, a maximally entangled pair is consumed.
Through this paper, an efficient scheme of re-establishing entanglement between different nodes in a
quantum network is explored. A hybrid land-satellite network is considered, where the land-based links
are used for short-range communication, and the satellite links are used for transmissions between distant
nodes. This new scheme explores many different possibilities of resupplying the land nodes with entangled
pairs, depending on: the position of the satellites, the number of pairs available and the distance between
the nodes themselves. As to make the entire process as efficient as possible, we consider the situations of
direct transmissions of entangled photons and also the transmissions making use of entanglement swapping.
An analysis is presented for concrete scenarios, sustained by numerical data.
INDEX TERMS: Quantum communication | entanglement | teleportation | entanglement swapping | routing scheme | satellite. |
مقاله انگلیسی |
3 |
Solving Vehicle Routing Problem Using Quantum Approximate Optimization Algorithm
حل مسئله مسیریابی خودرو با استفاده از الگوریتم بهینه سازی تقریبی کوانتومی-2022 Intelligent transportation systems (ITS) are a critical component of Industry 4.0 and 5.0, particularly having
applications in logistic management. One of their crucial utilization is in supply-chain management and scheduling for
optimally routing transportation of goods by vehicles at a given
set of locations. This paper discusses the broader problem of
vehicle traffic management, more popularly known as the Vehicle
Routing Problem (VRP), and investigates the possible use of
near-term quantum devices for solving it. For this purpose,
we give the Ising formulation for VRP and some of its constrained
variants. Then, we present a detailed procedure to solve VRP
by minimizing its corresponding Ising Hamiltonian using a
hybrid quantum-classical heuristic called Quantum Approximate
Optimization Algorithm (QAOA), implemented on the IBM
Qiskit platform. We compare the performance of QAOA with
classical solvers such as CPLEX on problem instances of up to
15 qubits. We find that performance of QAOA has a multifaceted
dependence on the classical optimization routine used, the depth
of the ansatz parameterized by p, initialization of variational
parameters, and problem instance itself.
Index Terms— Vehicle routing problem | ising model | combinatorial optimization | quantum approximate algorithms | variational quantum algorithms. |
مقاله انگلیسی |
4 |
Timing and Resource-Aware Mapping of Quantum Circuits to Superconducting Processors
نگاشت زمان بندی و آگاهی از منابع مدارهای کوانتومی به پردازنده های ابررسانا-2022 Quantum algorithms need to be compiled to respect
the constraints imposed by quantum processors, which is known
as the mapping problem. The mapping procedure will result in an
increase of the number of gates and of the circuit latency, decreasing the algorithm’s success rate. It is crucial to minimize mapping
overhead, especially for noisy intermediate-scale quantum (NISQ)
processors that have relatively short qubit coherence times and
high gate error rates. Most of prior mapping algorithms have only
considered constraints, such as the primitive gate set and qubit
connectivity, but the actual gate duration and the restrictions
imposed by the use of shared classical control electronics have
not been taken into account. In this article, we present a mapper
called Qmap to make quantum circuits executable on scalable
processors with the objective of achieving the shortest circuit
latency. In particular, we propose an approach to formulate the
classical control restrictions as resource constraints in a conventional list scheduler with polynomial complexity. Furthermore,
we implement a routing heuristic to cope with the connectivity limitation. This router finds a set of movement operations
that minimally extends circuit latency. To analyze the mapping
overhead and evaluate the performance of different mappers, we
map 56 quantum benchmarks onto a superconducting processor named Surface-17. Compared to a prior mapping strategy
that minimizes the number of operations, Qmap can reduce the
latency overhead (LtyOH) up to 47.3% and operation overhead
up to 28.6%, respectively.
Index Terms—Quantum compilation | quantum computing | resource-constrained scheduling | routing. |
مقاله انگلیسی |
5 |
Performance evaluation of Focused Beam Routing for IoT applications in underwater environment
ارزیابی عملکرد مسیریابی پرتو متمرکز برای کاربردهای اینترنت اشیا در محیط زیر آب-2022 Underwater applications are becoming more and more interesting to industry and academy.
They include data gathering for human safety and environment monitoring, control of underwater robots for various tasks and so on. Because of the accessibility limitations in underwater
environment, applications tend to be automated and delay tolerant. In this paper, we consider
IoT applications in underwater environment, while using Delay Tolerant Networking (DTN)
carry–store–forwarding paradigm. DTN routing protocols are used to forward data from the
monitoring mobile sensors to collecting devices at the water surface and vice-versa. One
characteristic of routing protocols for DTN is flooding of messages to increase the delivery
probability. For instance, Epidemic Routing (ER) protocol creates a copy of each message for
each new node that does not already have the message in its memory. This increases the
probability of delivery, but on the other hand, creates overhead in each node’s buffer, and uses
a lot of valuable energy from the forwarding and receiving nodes. This work aims to analyze by
simulations the performance of Focused Beam Routing (FBR) protocol for different FBR angles
and different applications. We use Delivery Probability, Average Number of Hops, Overhead
Ratio and Buffer Occupancy to simulate our scenarios by The ONE simulator. Simulation results
show that for narrow angles of FBR the performance is better. In case of FBR-45, average
hop count and overhead ratio are decreased by 10.9% and 16.6% respectively, compared to
FBR-180. However, delivery probability decreases by only 3.9%.
Keywords: Underwater environment | Delay tolerant network | DTN | Focused Beam Routing | FBR the ONE simulator |
مقاله انگلیسی |
6 |
A jamming attack detection technique for opportunistic networks
یک تکنیک تشخیص حمله پارازیت برای شبکه های فرصت طلب-2022 Opportunistic networks (OppNets) are dispersed in nature, with nodes acting as resource
restrictions, with intermittent connectivity. These nodes are subject to various types of attacks,
posing a security risk in data transmission. One of the most common attacks that cause jamming
among the message forwarding nodes in infrastructure-less networks is Denial of Service (DoS)
attack. Most of the methods addressing this type of attack rely on cryptographic algorithms,
which are too difficult to implement. In this paper, a novel jamming attack detection technique
(JADT) for OppNets, is proposed, which relies on the use of some statistical measures collected
from the relay nodes and a prescribed threshold on the packet delivery ratio (PDR) to discover
a jamming attack while decrypting the acknowledgement, stopping the message transmission
and rebroadcasting the message through a different channel. The proposed JADT is evaluated
using the ONE simulator, showing its superiority against the Fuzzy Geocasting mechanism in
Opportunistic Networks (F-GSAF) scheme in terms of packet delivery ratio and overhead ratio,
under varying TTL and buffer size.
Keywords: Jamming detection | Opportunistic networks | Routing | Statistical information | Energy |
مقاله انگلیسی |
7 |
A new DTN routing strategies ensuring high message delivery ratio while keeping low power consumption
یک استراتژی جدید مسیریابی DTN با تضمین نسبت تحویل پیام بالا و مصرف کم انرژی-2022 This study proposes Delay/Disruption Tolerant Networking (DTN) routing strategies for disaster
information delivery under the existence of obstacles that are based on the message relay
decision (MRD) method. The proposed methods include a new added obstacle detection
procedure to deliver messages to destinations while bypassing the obstacles. Efficient and
precise relief activities are required immediately after disasters, and it is well known that
obstacles appearing after a disaster will degrade message forwarding performance. Hence, the
proposed schemes maintain communication performance by using a node to detect the existence
of obstacles around itself. If there are obstacles, the message strategy is altered to bypass
the obstacle. In this study, human-beings are the main mobile nodes and mobile phones are
the creators and forwarders of messages. A multiple obstacle model is used to evaluate the
schemes in terms of obstacle-resistance. Three routing schemes are proposed: MRD with area
increase (MRDAI), Sub-Relay Station (SRS), and Adapted Predict Obstacle (APO). This model
tests MRDAI and SRS at the macro level and APO under the existence of concave obstacles. The
MRDAI scheme could autonomously perceive the existence of a huge obstacle and intelligently
enlarge the original message relay area. The SRS scheme could re-establish sub-relay areas
based on MRDAI. The APO scheme demonstrated resistance to concave obstacles, stability
(less affected by environmental changes), and a high delivery ratio while ensuring low energy
consumption. These proposed strategies for information delivery in a disaster area can be used
to launch rescue activities more quickly.
Keywords: DTN | Routing strategy | Disaster information | Avoiding obstacles |
مقاله انگلیسی |
8 |
Deep Q learning based secure routing approach for OppIoT networks
رویکرد مسیریابی ایمن مبتنی بر یادگیری Q برای شبکه های OppIoT-2022 Opportunistic IoT (OppIoT) networks are a branch of IoT where the human and machines
collaborate to form a network for sharing data. The broad spectrum of devices and ad-hoc
nature of connections, further alleviate the problem of network and data security. Traditional
approaches like trust based approaches or cryptographic approaches fail to preemptively secure
these networks. Machine learning (ML) approaches, mainly deep reinforcement learning (DRL)
methods can prove to be very effective in ensuring the security of the network as they
are profoundly capable of solving complex and dynamic problems. Deep Q-learning (DQL)
incorporates deep neural network in the Q learning process for dealing with high-dimensional
data. This paper proposes a routing approach for OppIoT, DQNSec, based on DQL for securing the
network against attacks viz. sinkhole, hello flood and distributed denial of service attack. The
actor–critic approach of DQL is utilized and OppIoT is modeled as a Markov decision process
(MDP). Extensive simulations prove the efficiency of DQNSec in comparison to other ML based
routing protocols, viz. RFCSec, RLProph, CAML and MLProph.
Keywords: OppIoT | Reinforcement learning | Deep learning | Deep Q-learning | Markov decision process | Sinkhole attack | Hello flood attack | Distributed denial of service attack |
مقاله انگلیسی |
9 |
FANETs in Agriculture - A routing protocol survey
FANETs در کشاورزی - مرور پروتکل مسیریابی-2022 Breakthrough advances on communication technology, electronics and sensors have led to
integrated commercialized products ready to be deployed in several domains. Agriculture
is and has always been a domain that adopts state of the art technologies in time, in order
to optimize productivity, cost, convenience, and environmental protection. The deployment
of Unmanned Aerial Vehicles (UAVs) in agriculture constitutes a recent example. A timely
topic in UAV deployment is the transition from a single UAV system to a multi-UAV system.
Collaboration and coordination of multiple UAVs can build a system that far exceeds the
capabilities of a single UAV. However, one of the most important design problems multi-
UAV systems face is choosing the right routing protocol which is prerequisite for the co-
operation and collaboration among UAVs. In this study, an extensive review of Flying Ad-
hoc network (FANET) routing protocols is performed, where their different strategies and
routing techniques are thoroughly described. A classification of UAV deployment in agri-
culture is conducted resulting in six (6) different applications: Crop Scouting, Crop Survey-
ing and Mapping, Crop Insurance, Cultivation Planning and Management, Application of
Chemicals,and Geofencing. Finally, a theoretical analysis is performed that suggests which
routing protocol can serve better each agriculture application, depending on the mobility
models and the agricultural-specific application requirements.
keywords: کشاورزی هوشمند | کشاورزی دقیق | وسایل نقلیه هوایی بدون سرنشین (UAV) | شبکه های ادوک پرنده (FANET) | پروتکل های مسیریابی | مدل های تحرک | smart farming | precision agriculture | unmanned aerial vehicles (UAVs) | flying adhoc networks (FANETs) | routing protocols | mobility models |
مقاله انگلیسی |
10 |
A Systematic Literature Review of Quantum Computing for Routing Problems
مروری بر ادبیات سیستماتیک محاسبات کوانتومی برای مسائل مسیریابی-2022 Quantum Computing is drawing a significant attention from the current scientific community.
The potential advantages offered by this revolutionary paradigm has led to an upsurge of scientific production
in different fields such as economics, industry, or logistics. The main purpose of this paper is to collect,
organize and systematically examine the literature published so far on the application of Quantum Computing
to routing problems. To do this, we embrace the well-established procedure named as Systematic Literature
Review. Specifically, we provide a unified, self-contained, and end-to-end review of 18 years of research
(from 2004 to 2021) in the intersection of Quantum Computing and routing problems through the analysis
of 53 different papers. Several interesting conclusions have been drawn from this analysis, which has been
formulated to give a comprehensive summary of the current state of the art by providing answers related to
the most recurrent type of study (practical or theoretical), preferred solving approaches (dedicated or hybrid),
detected open challenges or most used Quantum Computing device, among others.
INDEX TERMS: Quantum computing | quantum annealer | quantum gates | IBM | DWAVE | traveling salesman problem | vehicle routing problem | routing problems. |
مقاله انگلیسی |