Digital twin is a transformative technology with the power to reshape the future of industries, which enables accurate simulation and optimization of the production process by creating virtual copies of physical entit...
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Digital twin is a transformative technology with the power to reshape the future of industries, which enables accurate simulation and optimization of the production process by creating virtual copies of physical entities. Industrial wireless network such as ISA100.11a, as an indispensable communication bridge in digital twin, provides a stable and reliable data transmission pathway for all-element connectivity. However, the access of a large number of nodes increases the risk of network congestion and poses a challenge to the real-time network transmission. Therefore, the intention of our research is to deal with network congestion by establishing a load balancing routing algorithm. First, considering the time-triggered characteristic of industrial scenarios, a directed acyclic graph model is established for multi-periodic communication streams. We analyze the causes of load imbalance in multi-source single-sink topology, and prove that choosing optimal path scheme is an NP- hard problem by generalizing to the multidimensional bin packing problem. Then, we theoretically derive the average load of the hierarchy, establish a loss function characterizing the degree of hierarchical load balancing, and propose a hierarchical load balancing strategy based on the black-winged kite algorithm by establishing a mapping relationship. Finally, a scheduling constraint model is introduced to evaluate the superiority of the proposed algorithm. Experimental validation shows that the proposed algorithm reduces 70.80%, 27.15%, 15.57%, 14.01% in terms of loss function value and 23.52%, 4.71%, 5.19%, 4.64% in terms of total delay as compared to Dijkstra algorithm, Greedy algorithm, Bat algorithm and Deep Q-Networks respectively.
Energy harvesting (EH) wireless sensor networks (WSNs) have wide applications in various fields due to their ability to sense and transmit environmental information, while current routing algorithms on EH-WSN generall...
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Energy harvesting (EH) wireless sensor networks (WSNs) have wide applications in various fields due to their ability to sense and transmit environmental information, while current routing algorithms on EH-WSN generally rely on a single EH method, such as solar or wind. Due to the uncertainty of EH efficiency, a single-type EH technique may not be able to meet the energy demand of WSNs. In light of this, we propose an energy-efficient dual EH routing algorithm based on whale optimization (WO) strategy (DEHRA-WO). In the modeling process, we firstly propose a dual EH (including solar EH and radio frequency charging (RFC) techniques) switching mechanism. Namely, if the collected solar energy is not enough to maintain the operation of WSNs, RFC is employed to harvest additional energy, in which the collected solar energy is predicted using Kalman filter theory. With this, a residual energy model is constructed to measure the energy status of nodes. Secondly, we provide a communication range model to confirm the transmission area of nodes, where the wireless fading environment is considered. After that, a data link layer model is established to reflect the node blocking state. Based on the above models, we define the evaluation function to indicate the possibility of a node to be selected as the next hop and then propose the overall path selection scheme using WO strategy. Moreover, we also prove the convergence of DEHRA-WO and analyze its complexity. Through extensive simulation experiments, we demonstrate the superior performance of DEHRA-WO in terms of packet loss rate and energy utilization.
Three-dimensional Network-on-Chip (3D-NoC) is an efficient solution to overcome communication limitations in complex System-on-Chip (SoC) architectures. However, challenges such as increased temperature, traffic conge...
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Three-dimensional Network-on-Chip (3D-NoC) is an efficient solution to overcome communication limitations in complex System-on-Chip (SoC) architectures. However, challenges such as increased temperature, traffic congestion, and link wear-out significantly impact network performance and lifespan. In this study, we propose an adaptive routing algorithm named CTWR (Congestion, Temperature and Wear-aware routing), which simultaneously considers temperature, congestion, and wear-out while utilizing both intra-layer and inter-layer routing approaches to enhance network performance. The algorithm employs a dynamic approach to assess the realtime status of vertical links to control and reduce wear-out, selecting paths that mitigate thermal hotspots, balance traffic distribution, and extend the lifespan of interconnects. Extensive assessments and simulations performed under diverse traffic scenarios and multiple vertical link or elevator layout configurations indicate that the CTWR algorithm outperforms ETW, EF, HE, and Nezarat routing methods in reducing average packet delay by 92.71 %, 67.84 %, 56.33 %, and 26.91 %, respectively. Furthermore, our proposed approach enhances average network throughput by 9.88 %, 4.38 %, 2.64 %, and 1.66 % compared to these methods. Thermal analysis of the chip surface also reveals a lower overall temperature and a more balanced heat distribution than competing techniques.
In opportunistic networks, the lack of a stable route between nodes necessitates the use of relay nodes for message transmission. In social attribute-based routing, the selection of relay nodes is mainly done accordin...
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In opportunistic networks, the lack of a stable route between nodes necessitates the use of relay nodes for message transmission. In social attribute-based routing, the selection of relay nodes is mainly done according to historical encounter information among nodes. This historical information is used to compute utility values between nodes, which are then used to select relay nodes. However, when there is insufficient historical encounter information between source and destination nodes, the utility value between nodes may not be accurately calculated by traditional social routing strategies. This results in difficulties in selecting appropriate relay nodes and hence a low delivery ratio. To address this shortcoming, a routing algorithm based on social relationships and location information (SRLI) is proposed. Initially, historical encounter information among nodes is used to identify social relationships among nodes. Messages are forwarded to the relay nodes possessing higher social relationships with the destination nodes. To enhance the coverage of messages, the geographic cosine similarity between nodes is calculated. Messages are preferentially transmitted to adjacent nodes with lower similarity to the current node. In addition, a dynamic buffer management strategy is utilized to facilitate the appropriate discarding of messages. Lower priority messages are prioritized for deletion when a node buffer is full. Experimental results demonstrate that the proposed routing algorithm significantly outperforms the Epidemic, Prophet, and CHOP-NET algorithms in terms of message delivery ratio, average message forwarding latency and routing overhead. Our proposed SRLI is superior to CHOP-NET, Prophet and Epidemic by at least 16.9% in terms of average message forwarding latency and 7.7% in terms of message delivery ratio, while still being able to achieve 1.5% lower routing overhead.
Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing *** satisfy qual...
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Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing *** satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite *** paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite *** auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing *** results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.
The new Path Length Control (PLC) algorithm establishes and maintains multicast trees which maximize the bandwidth to be shared by multiple receivers and which satisfy the maximum path length bounds for each receiver....
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The new Path Length Control (PLC) algorithm establishes and maintains multicast trees which maximize the bandwidth to be shared by multiple receivers and which satisfy the maximum path length bounds for each receiver. The PLC algorithm can be implemented as a distributed algorithm, can tradeoff end-to-end delay and bandwidth consumption, and can be implemented for polynomial time execution. Analysis and simulation show that (a) the PLC algorithm generates multicast trees which consume less bandwidth than chose generated by the SPT algorithm while guaranteeing the same shortest path length and (b) consume less bandwidth than trees generated by the Greedy algorithm with only a moderate increase in path length. The PLC algorithm is more flexible and has a lower cost than a combined SPT and Greedy algorithm. (C) 2000 Elsevier Science B.V. All rights reserved.
With the popularization of wireless sensor networks (WSN) and the concept of IoT (Internet-of-things), several applications have emerged in the industrial, scientific and engineering sectors. However, energy consumpti...
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With the popularization of wireless sensor networks (WSN) and the concept of IoT (Internet-of-things), several applications have emerged in the industrial, scientific and engineering sectors. However, energy consumption is a challenge, because the demands for improvement in transmission rates and latency limitations. In particular, increasing the lifetime of wireless sensor networks has been a common goal in recent research. A viable alternative to solve this problem consists in reducing the data traffic defined by the routing protocol, which optimizes the number of messages that travel through the network. These protocols can also be optimized using evolutive algorithms, such as genetic algorithms. In the present work, is proposed a routing algorithm for WSN based on genetic algorithms, with the purpose of minimizing the total distance from the sensor node to the sink, which would allow optimized use of energy by sensor nodes and extend the lifetime of the WSN. The proposed algorithm includes a form of chromosome coding that had not yet been used in the context of routing and a new multi-objective fitness function. Performance analyzes were carried out establishing exhaustive search (ES) and opportunistic routing (OR) algorithms as comparison references and considering two scenarios: an open field and the other in a closed residential area. Proposed algorithm revealed superior performance when compared to reference algorithms. In open space and in the residential scenario, the lifetime provided by the proposed algorithm was 7320 and transmissions greater than that provided by OR. It was also observed that, with the increase in the number of transmissions, the standard deviation of the nodes ' residual energy is smaller when GAEA-RP is applied, which means the predictability of the energy consumed by them. After 1.8x10(5) transmissions, it was 0.105 J for GAEA-RP versus 0.188 J for OR in the first scenario. In the second scenario, in addition to the smaller standard
SDN network is a dynamic, controllable, cost-effective and adaptable system. It is suitable for communication networks with high bandwidth and high dynamic characteristics. Therefore, combining SDN ideas with the new ...
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SDN network is a dynamic, controllable, cost-effective and adaptable system. It is suitable for communication networks with high bandwidth and high dynamic characteristics. Therefore, combining SDN ideas with the new generation of LEO satellite networks can achieve more flexible monitoring and management of the network, and can make the network expansion more convenient. Joint the Depth-First-Search (DFS) idea and Dijkstra algorithm for the huge numbers of LEO mobile satellite network based on SDN is proposed to improve the computational efficiency and the reliability of calculation result. Moreover, the communication performance of space-based network based on SDN and traditional space-based network is compared and analyzed. The simulation results show that the huge numbers of LEO mobile satellite network based on SDN breaks through the performance limitations of the traditional network architecture, and it can achieve better performance of the network.
As regular topology networks, grid networks are widely adopted in network deployment. Link congestion and routing path length are two critical factors that affect the delay and throughput of a network. In this paper, ...
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As regular topology networks, grid networks are widely adopted in network deployment. Link congestion and routing path length are two critical factors that affect the delay and throughput of a network. In this paper, we study the routing problem in grid networks concerning these two factors. The main objective of our routing algorithms is to minimize the maximum link congestion. The shortest path minimum maximum (SPMM) link congestion and non-shortest path minimum maximum (NSPMM) link congestion routing problems are studied. The two problems are first formulated as integer optimization problems. Then, corresponding routing algorithms (SPMM and NSPMM routing algorithms) are proposed. For SPMM routing algorithm, the path length is optimal, while for NSPMM routing algorithm, the path is limited in a submesh. Thus, the path length can be bounded. At last, we compare the proposed routing algorithms under different scenarios with other popular routing algorithms (RowColumn, ZigZag, Greedy, Random routing algorithms). The performances are evaluated through different metrics including link congestion, path length, path congestion, path congestion to path length ratio, delay and throughput.
A row-based Field Programmable Gate Array (FPGA) consists of rows of identical processing modules separated by segmented tracks that are used for routing nets between specified module pins. The problem of finding a fe...
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A row-based Field Programmable Gate Array (FPGA) consists of rows of identical processing modules separated by segmented tracks that are used for routing nets between specified module pins. The problem of finding a feasible routing of a given set of nets onto a set of segmented tracks is NP-complete. We present an enumeration algorithm for the problem that uses matching arguments to improve the time complexity while requiring polynomial space. The algorithm serves as the basis of powerful practical heuristics and its additional advantage is that it is directly parallelizable.
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