Logic-based Routing Research Articles

Fuzzy logic-based routing and wavelength assignment with traffic prediction for optical network-on-chip

In Optical Network-on-Chip (ONoC), both routing and wavelength assignment (RWA) have an impact on the Optical Signal-to-Noise Ratio (OSNR), which further influence the power efficiency and scalability. In the state-of-the-art, the consideration of routing is separate with the wavelength assignment, which could not reach a holistic optimization. Also, there is a need of trade-off among multidimensional performance factors in the design of RWA. In this article, we propose a Multidimensional Integrated Predictive RWA (named as MIP-RWA), based on the Fuzzy Logic System (FLS). The MIP-RWA considers routing and wavelength assignment holistically, taking into consideration of multidimensional performance factors at the same time. The predictive scheme is proposed to work with RWA and further reduce the delay in RWA. The evaluation shows that the proposed MIP-RWA can obtain better trade-off of the performance factors. The traffic prediction accuracy of the Fuzzy Neural Network (FNN) improves by 5.29%, 4.79%, and 6.2% respectively under the uniform, transpose, and hotspot traffic, compared with the Long Short-Term Memory (LSTM)-based. Thanks to the traffic predictive scheme, the proposed MIP-RWA reduces the end-to-end delay (ete delay) by 17.77%, 17.39%, and 16.66% respectively under uniform, transpose, and hotspot traffic, compared with the methods without predictive scheme. Also, compared with current RWA methods, the proposed MIP-RWA improves 11.21 dB in OSNR and 21.47% in delay in average.

A novel routing method for dynamic control in distributed computing power networks

Driven by diverse intelligent applications, computing capability is moving from the central cloud to the edge of the network in the form of small cloud nodes, forming a distributed computing power network. Tasked with both packet transmission and data processing, it requires joint optimization of communications and computing. Considering the diverse requirements of applications, we develop a dynamic control policy of routing to determine both paths and computing nodes in a distributed computing power network. Different from traditional routing protocols, additional metrics related to computing are taken into consideration in the proposed policy. Based on the multi-attribute decision theory and the fuzzy logic theory, we propose two routing selection algorithms, the Fuzzy Logic-Based Routing (FLBR) algorithm and the low-complexity Pairwise Multi-Attribute Decision-Making (lPMADM) algorithm. Simulation results show that the proposed policy could achieve better performance in average processing delay, user satisfaction, and load balancing compared with existing works.

A Q-Learning and Fuzzy Logic-Based Hierarchical Routing Scheme in the Intelligent Transportation System for Smart Cities

A vehicular ad hoc network (VANET) is the major element of the intelligent transportation system (ITS). The purpose of ITS is to increase road safety and manage the movement of vehicles. ITS is known as one of the main components of smart cities. As a result, there are critical challenges such as routing in these networks. Recently, many scholars have worked on this challenge in VANET. They have used machine learning techniques to learn the routing proceeding in the networks adaptively and independently. In this paper, a Q-learning and fuzzy logic-based hierarchical routing protocol (QFHR) is proposed for VANETs. This hierarchical routing technique consists of three main phases: identifying traffic conditions, routing algorithm at the intersection level, and routing algorithm at the road level. In the first phase, each roadside unit (RSU) stores a traffic table, which includes information about the traffic conditions related to four road sections connected to the corresponding intersection. Then, RSUs use a Q-learning-based routing method to discover the best path between different intersections. Finally, vehicles in each road section use a fuzzy logic-based routing technique to choose the foremost relay node. The simulation of QFHR has been executed on the network simulator version 2 (NS2), and its results have been presented in comparison with IRQ, IV2XQ, QGrid, and GPSR in two scenarios. The first scenario analyzes the result based on the packet sending rate (PSR). In this scenario, QFHR gets better the packet delivery rate by 2.74%, 6.67%, 22.35%, and 29.98% and decreases delay by 16.19%, 22.82%, 34.15%, and 59.51%, and lowers the number of hops by 6.74%, 20.09%, 2.68%, and 12.22% compared to IRQ, IV2XQ, QGrid, and GPSR, respectively. However, it increases the overhead by approximately 9.36% and 11.34% compared to IRQ and IV2XQ, respectively. Moreover, the second scenario evaluates the results with regard to the signal transmission radius (STR). In this scenario, QFHR increases PDR by 3.45%, 8%, 23.29%, and 26.17% and decreases delay by 19.86%, 34.26%, 44.09%, and 68.39% and reduces the number of hops by 14.13%, 32.58%, 7.71%, and 21.39% compared to IRQ, IV2XQ, QGrid, and GPSR, respectively. However, it has higher overhead than IRQ (11.26%) and IV2XQ (25%).

A cluster-based routing method with authentication capability in Vehicular Ad hoc Networks (VANETs)

Routing is challenging in vehicular ad hoc networks due to their features, such as high mobility of nodes and unstable wireless communication links. Therefore, it is an interesting issue for researchers. In addition, it is very important to design an authentication mechanism between the source node and the destination node because these networks are exposed to many attacks due to their features mentioned above. In this paper, we present a fuzzy logic-based routing method with authentication capability in vehicular ad hoc networks. The proposed routing method has three phases: clustering phase, routing phase between cluster head nodes, and authentication phase. In the first phase, vehicles are clustered using an efficient scheme. In the proposed method, we define two types of data packets: immediate and ordinary. Various data packets have different route discovery processes that are described in Phase 2. Note that any data packet type is divided into two groups: simple and secure. Simple data packets have no authentication mechanism. On the other hand, secure data packets use an authentication mechanism based on message authentication code (MAC) and symmetric key cryptography. We simulate the proposed method using NS2. Simulation results are compared with three routing protocols including, AODV, R2SCDT, and 3VSR. Experiments show that the proposed method outperforms others in terms of end-to-end delay, packet collision, packet delivery rate (PDR), packet loss rate (PLR), and throughput. However, it increases the routing overhead slightly.

OLSR+: A new routing method based on fuzzy logic in flying ad-hoc networks (FANETs)

Flying ad-hoc networks (FANETs) have many applications in military, industrial and agricultural areas. Due to specific features of FANETs, such as high-speed nodes, low density of nodes in the network, and rapid changes in the topology, most routing protocols designed for mobile ad hoc networks (MANETs) or vehicular ad hoc networks (VANETs) are not compatible with FANETs. In this paper, we propose a fuzzy logic-based routing approach called OLSR+ for FANETs. In this scheme, we seek to improve the optimized link state routing protocol (OLSR) so that it can efficiently be used in FANETs. OLSR+ includes four main phases: 1) Discovering neighboring nodes. In this phase, we propose a new and efficient technique for estimating the lifetime of the link between two unmanned ariel vehicles (UAVs) based on the link quality, distance, relative velocity, and movement direction. 2) Selecting multipoint relays (MPRs). In this phase, we present a fuzzy mechanism for selecting a set of MPR nodes. According to this mechanism, when a node has higher residual energy, higher link lifetime, and more neighborhood degree compared to others, it achieves more fitness to be selected as MPR. 3) Discovering the network topology. In this phase, we modify the format of the topology control (TC) message and add two fields, including route energy and route lifetime to this message. 4) Calculating the routing table. In OLSR+, we consider two parameters, including route energy and route lifetime, for establishing stable paths. Finally, we simulate OLSR+ using NS3 and compare its performance with two methods, namely greedy optimized link state routing (G-OLSR) and optimized link state routing (OLSR). The simulation results show that OLSR+ successfully reduces delay compared to G-OLSR and OLSR. In addition, it has higher packet delivery rate and throughput than others. Also, it improves energy consumption in the network. However, OLSR+ has more routing overhead than G-OLSR.

Fuzzy Logic-based Trusted and Power-aware Routing Protocol in Mobile Ad-hoc Networks

Mobile ad-hoc networks (MANETs) have attracted much attention from researchers lately because MANETs are able to provide networks in areas with unavailable fixed network infrastructure. However, some mobile nodes may misbehave by dropping packets to conserve power usage because mobile ad-hoc networks nodes are usually battery operated. In this paper, a fuzzy logic-based routing protocol that considers the battery level of nodes, hop count, and trust among the nodes is proposed. The proposed routing protocol adaptively selects routes that use minimum hop count with the highest level of trust and a sufficient battery level to enhance the reliability of route selection while maintaining the percentage of successfully delivered packets. The result of the simulation shows that the proposed protocol can achieve a high ratio of successfully delivered packets, a lower average end-to-end delay, and a normalized routing load.

An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs)

Today, unmanned aerial vehicles (UAVs), also known as drones, have become very popular in military applications, commercial applications, and academic research. Flying ad hoc network (FANET) is a new type of ad hoc network, which groups small drones into an ad hoc form. These networks have unique characteristics, including moving in a 3D space, high mobility, frequent topological changes, limited resources, low density of nodes, and so on, which impose various challenges when designing a proper and efficient routing scheme. In this paper, we present a fuzzy logic-based routing scheme for flying ad hoc networks. The proposed routing scheme has two phases: route discovery phase and route maintenance phase. In the first phase, we propose a technique for calculating the score of each node in the network to prevent the broadcast storm problem and control the flood of the control messages, which have been broadcast to discover a new route in the network. This score is calculated based on various parameters such as movement direction, residual energy of nodes, link quality, and node stability. Moreover, in the route selection process, we design a fuzzy system to select routes with more fitness, less delay, and fewer hops for data transfer. The second phase includes two steps: preventing route failure in order to detect and modify paths at the failure threshold, and reconstructing failed routes in order to recognize and quickly replace these routes. Finally, the proposed routing scheme is implemented in NS2 to evaluate its performance and determine its efficiency. The simulation results are compared with three routing methods, namely ECaD, LEPR, and AODV. These results show that the proposed routing method outperforms other routing schemes in terms of end to end delay, packet delivery rate, route stability, and energy consumption. However, it has slightly increased the routing overhead.

TRACK: An algorithm for fault-tolerant, dynamic and scalable 2D mesh network-on-chip routing reconfiguration

Network-on-chip (NoC) is a reliable and scalable on-chip interconnect solution particularly used for MPSoCs and CMPs. Increasing susceptibility of NoC to failures is becoming a new research concern. Failures in components such as on-chip link or router may disrupt the underlying routing function. Reconfiguration of routing function is required to sustain network connectivity while maintaining deadlock-freedom in event of failure(s). Existing approaches either use routing tables or meta-data or involve all network nodes for participation in the reconfiguration process. This paper proposes TRACK, an algorithm for fast and scalable routing reconfiguration. It uses logic-based routing instead of tables and identifies affected nodes (i.e., rows/columns of mesh network) by single and double-link failures. In the proposed algorithm, reconfiguration is needed only for the affected nodes and the remaining network can continue to work. TRACK outperforms the existing one and reduces latency up to 42% and improves throughput up to 22% for single and double-link failures in 8 × 8 2D mesh network-on-chip. By employing logic-based routing, hardware cost is also reduced, i.e., 30% in area and 29.5% in power overhead for a 16 × 16 mesh router.

Modified fuzzy-based greedy routing protocol for VANETs

Vehicular Ad Hoc Networks (VANETs) is the most growing research area in wireless communication and has been gaining significant attention over recent years due to its role in designing intelligent transportation systems. Wireless multi-hop forwarding in VANETs is challenging since the data has to be relayed as soon as possible through the intermediate vehicles from the source to destination. This paper proposes a modified fuzzy-based greedy routing protocol (MFGR) which is an enhanced version of fuzzy logic-based greedy routing protocol (FLGR). Our proposed protocol applies fuzzy logic for the selection of the next greedy forwarder to forward the data reliably towards the destination. Five parameters, namely distance, direction, speed, position, and trust have been used to evaluate the node’s stability using fuzzy logic. The simulation results demonstrate that the proposed MFGR scheme can achieve the best performance in terms of the highest packet delivery ratio (PDR) and minimizes the average number of hops among all protocols.

An automated fault-tolerant route discovery with congestion control using TFRF model for 3D network-on-chips

As one of the principle patterns of communication technology for 3D-integrated circuit (ICs), the 3D-networks-on-chips (3D-NoCs) have lot of attention from scientific research community. 3D-NoCs has been provided as a propitious solution merging the high parallelism of network-on-chip (NoCs) interconnect paradigm with the high-performance and lower interconnect-power of three-dimensional integration circuits. For the permanent link faults, the fault-tolerant routing scheme has been regarded as an effective mechanism to ensure the performance of the 2D NoCs. In this paper, we propose a triggered fault-free route forwarding model called TFRF for 3D mesh NoCs without requiring any virtual channels (VCs).TFRF is a deadlock-free scheme by adopting a logic-based routing named TFRF guided by a turn activating rule model. The experimental results show that TFRF possesses better performance, improved reliability and lower overhead compared with the state-of-the-art reliable routing schemes.

S2DIO: an extended scalable 2D mesh network-on-chip routing reconfiguration for efficient bypass of link failures

The paradigm of computing has shifted from computation-centric to communication-centric designs. Network-on-chip has emerged as an alternative interconnect mechanism for future multi-core designs. Transistor integration is approaching its limit, and this increases the susceptibility of the interconnects toward failures. Research efforts are directed toward improving the fault tolerance of these interconnects. Fault-tolerant routing such as segment-based and up*/down* are static by nature and require reconfiguration to circumvent failures. Failures may disrupt the connectivity of the network, and new routing instance needs to be configured in case old routing instance is unable to offer full connectivity. In this paper, we identify nodes affected by the failures and propose an extended scalable routing reconfiguration, called S2DIO. It performs reconfiguration of affected nodes by taking $$N^2$$ cycles for $$N \times N$$ mesh network, whereas state-of-the-art (ARIADNE) consumes $$N^4$$ cycles. Instead of routing tables, we employ logic-based routing and achieve significant improvements, i.e., $$30.7\%$$ in terms of area and $$29\%$$ in terms of power overhead for a $$16\times 16$$ mesh router. A novel algorithm for computation of new logic-based routing bits is also proposed in this paper. Our reconfiguration (S2DIO) improves average flit latency up to $$32\%$$ and throughput up to 19% for single-link failure in $$8\times 8$$ 2D mesh network-on-chip.

An efficient fuzzy logic-based and bio-inspired QoS-compliant routing scheme for VANET

Vehicular ad hoc networks (VANET) are gaining popularity for enabling a wide range of applications for road traffic safety, infotainment and road transportation management. For real-time applications to be successfully deployed in VANET, their quality of service (QoS) requirements need to be met. In this paper, we propose a QoS-based routing protocol named FBQoS-Vanet, which accommodates applications with QoS requirements. This protocol uses a bio-inspired artificial bee colony (ABC) approach for discovering routes complying with QoS criteria. We also use fuzzy logic to identify a feasible path among several available ones discovered by ABC. We rely on the evaluation of a composite fuzzy cost expressed in terms of QoS metrics, where the path must satisfy criteria such as: bandwidth, delay, jitter, and link expiry time. The performance results obtained show the benefits of using our scheme for routing various classes of traffic in VANET with different QoS requirements.

An efficient fuzzy logic-based and bio-inspired QoS-compliant routing scheme for VANET

An efficient fuzzy logic-based and bio-inspired QoS-compliant routing scheme for VANET

Fuzzy Logic-Based Routing Algorithm for Lifetime Enhancement in Heterogeneous Wireless Sensor Networks

Energy consumption of sensor nodes is a key factor affecting the lifetime of wireless sensor networks. Prolonging network lifetime not only requires energy efficient operation, but also even dissipation of energy among sensor nodes. On the other hand, spatial and temporal variations in sensor activities create energy imbalance across the network. Therefore, routing algorithms should make an appropriate tradeoff between energy efficiency and energy consumption balancing to extend the network lifetime. In this paper, we propose a distributed energy-aware fuzzy logic based routing algorithm (DEFL) that simultaneously addresses energy efficiency and energy balancing. Our design captures network status through appropriate energy metrics and maps them into corresponding cost values for the shortest path calculation. We seek fuzzy logic approach for the mapping to incorporate human logic. We compare the network lifetime performance of DEFL with other popular solutions including minimum total energy, minimum drain rate, and flow augmentation. Simulation results demonstrate that the network lifetime achieved by DEFL exceeds the best of all tested solutions under various traffic load conditions. We further numerically compute the upper bound performance and show that DEFL performs near the upper bound.

New Approaches to Routing in Mobile Ad hoc Networks

Worldwide Interoperability for Microwave Access (Wimax) is power station through which mobile network, commonly known as A Mobile Ad-hoc Network (MANET) is used by the people. A MANET can be described as an infrastructure-less and self-configure network with autonomous nodes. Participated nodes in MANETs move through the network constantly causing frequent topology changes. Designing suitable routing protocols to handle the dynamic topology changes in MANETs can enhance the performance of the network. In this regard, this paper proposes four algorithms for the routing problem in MANETs. First, we propose a new method called Classical Logic-based Routing Algorithm for the routing problem in MANETs. Second is a routing algorithm named Fuzzy Logic-based Routing Algorithm (FLRA). Third, a Reinforcement Learning-based Routing Algorithm is proposed to construct optimal paths in MANETs. Finally, a fuzzy logic-based method is accompanied with reinforcement learning to mitigate existing problems in FLRA. This algorithm is called Reinforcement Learning and Fuzzy Logic-based (RLFLRA) Routing Algorithm. Our proposed approaches can be deployed in dynamic environments and take four important fuzzy variables such as available bandwidth, residual energy, mobility speed, and hop-count into consideration. Simulation results depict that learning process has a great impact on network performance and RLFLRA outperforms other proposed algorithms in terms of throughput, route discovery time, packet delivery ratio, network access delay, and hop-count.

The Repetitive Turn Model for Adaptive Routing

For 2D mesh based Network-on-Chip (NoC), the prohibited turns of routing algorithms should be repetitively distributed in order for the routing algorithms to be implemented by logic-based circuit. In this paper, we aim to exploit the designing space for logic-based routing algorithms, and propose new logic-based routing algorithms that outperform the state-of-the-art counterparts. Toward this direction, we firstly construct all routing algorithms for $5 \times 5$ 2D mesh topology. Then we select those routing algorithms which have repetitive prohibited turns across both the network rows and columns. In addition, we chose those routing algorithms that have smaller routing pressures than Odd-Even routing algorithm. Then the routing algorithms for 2D mesh topology ranging from $6 \times 6$ to $15 \times 15$ are respectively constructed according to the prohibited turns distribution of the selected routing algorithms. Two routing algorithms that have smaller routing pressures than Odd-Even routing algorithm are obtained for all considered networks. The obtained logic-based routing algorithms are called as Repetitive Turn Model (RTM). Simulation results show that RTM could achieve up to 51% performance improvement as compared to Odd-Even routing algorithm.

A Fuzzy Logic-Based Fault Tolerance New Routing Protocol in Mobile Ad Hoc Networks

Ad hoc networks are self-organizing and self-configuring networks that do not have fixed infrastructures. Mobile stations in wireless ad hoc networks move around in the network, thus requiring routing to dynamically handle the constant changing of network topologies. In this paper, we propose a fuzzy logic-based on-demand routing protocol (FBRP) for mobile ad hoc networks. The FBRP selects routes based on power of battery and speed of mobile nodes. The results of simulation and a comparison of the proposed method with the well-known ad hoc on-demand distance vector protocol revealed better performance and a higher fault tolerance for our approach, particularly in terms of node failures.

Distributed Fuzzy Logic-Based Cluster Routing for Wireless Sensor Networks

Distributed Fuzzy Logic-Based Cluster Routing for Wireless Sensor Networks

LOFT: A low-overhead fault-tolerant routing scheme for 3D NoCs

As one of the main trends of communication technology for 3D integrated circuits, the 3D networks-on-chip (NoCs) have drawn high concern from the academia. The links are main components of the NoCs. For the permanent link faults, the fault-tolerant routing scheme has been regarded as an effective mechanism to ensure the performance of the 2D NoCs. In this paper, we propose a low-overhead fault-tolerant routing scheme called LOFT for 3D Mesh NoCs without requiring any virtual channels (VCs). LOFT is a deadlock-free scheme by adopting a logic-based routing named LBDRe2 guided by a turn model Complete-OE. The experimental results show that LOFT possesses better performance, improved reliability and lower overhead compared with the state-of-the-art reliable routing schemes.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic.

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.