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1
Weigeng, Shi. "Reconnectable network with limited resources." Journal of Computer Science and Technology 6, no. 3 (July 1991): 243–49. http://dx.doi.org/10.1007/bf02945511.
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Al-Madani, Basem, Anas Al-Roubaiey, and Mohammad F. Al-Hammouri. "Performance Enhancement of Limited-Bandwidth Industrial Control Systems." Advanced Materials Research 739 (August 2013): 608–15. http://dx.doi.org/10.4028/www.scientific.net/amr.739.608.
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Due to its portability, reliability, flexibility, real time and rich set of QoS support, Data Distribution Service (DDs) middleware became one of the best solutions for real time distributed manufacturing systems. Most of these systems are composed of heterogeneous networked devices where network bandwidth represents a very important resource. Those devices include limited-resources devices, such as sensors, actuators and controllers. Thus, controlling such resource will significantly enhance the overall performance of the network in terms of resource utilization, delay, and throughput; moreover, it reduces the cost of using leased network bandwidth by limiting the amount of bandwidth as much as needed. In this paper we propose a solution for controlling the limited-bandwidth networked manufacturing systems by using DDS; and we describe the DDS QoS polices that support manufacturing systems to control network bandwidth. Furthermore, we evaluate DDS middleware performance over Bluetooth channel by measuring latency, throughput and jitter; and examining different QoS parameters to show their effect on improving the existing limited-bandwidth networks.
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Jiang, Xue, Xiaoya Song, Hongyu Zhao, and Haoran Zhang. "Rural Tourism Network Evaluation Based on Resource Control Ability Analysis: A Case Study of Ning’an, China." Land 10, no. 4 (April 16, 2021): 427. http://dx.doi.org/10.3390/land10040427.
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Organization of rural tourism resources is important for optimizing rural land use based on rational resource classification. Quantitative analysis was performed to evaluate the resource control ability of rural tourism networks. This was achieved by determining the resource control relationship and assessing the structure of the rural tourism network. The ability of resource control was analyzed via resource abstraction, which included the extraction of resource nodes and corridors, control scope analysis, and network structure level evaluation. The proposed approach was applied to the Ning’an in Heilongjiang Province, China, and proved to be effective for exploring the network degree and development trends in rural tourism resources. By examining the resource control ability, the spatial characteristics and development trend in rural tourism networks were quantitatively analyzed, especially the connection mode of key tourism resources, network structure analysis, and resource linking ability. The core resources showed a lack of outward ability in the network, and the secondary resource expansion ability was limited. Via resource control ability analysis, this study focused on areas with rich tourism but an unbalanced spatial structure, combining the directional characteristics of the network to provide suggestions for the optimization rural tourism resources network in other regions of the world.
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S. Todd, Margie, and Syed (Shawon) M. Rahman. "Complete Network Security Protection for SME's within Limited Resources." International Journal of Network Security & Its Applications 5, no. 6 (November 30, 2013): 1–13. http://dx.doi.org/10.5121/ijnsa.2013.5601.
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Golenko-Ginzburg, Dimitri, and Aharon Gonik. "Stochastic network project scheduling with non-consumable limited resources." International Journal of Production Economics 48, no. 1 (January 1997): 29–37. http://dx.doi.org/10.1016/s0925-5273(96)00019-9.
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Sarkar, Nurul I. "Enhancing Teaching and Learning Wi-Fi Networking using Limited Resources to Undergraduates." International Journal of Web-Based Learning and Teaching Technologies 8, no. 4 (October 2013): 1–18. http://dx.doi.org/10.4018/ijwltt.2013100101.
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Motivating students to learn Wi-Fi (wireless fidelity) wireless networking to undergraduate students is often difficult because many students find the subject rather technical and abstract when presented in traditional lecture format. This paper focuses on the teaching and learning aspects of Wi-Fi networking using limited hardware resources. It provides a walk-through tutorial on setting up Wi-Fi networks using wireless laptops and access points. Students can easily set up and configure Wi-Fi networks using relatively few computing resources to learn networking concepts more effectively. By measuring the key performance metrics such as network throughput and response times, students are able to gain a deeper understanding of Wi-Fi network performance and related issues. The effectiveness of these Wi-Fi practical learning activities has been evaluated both formally by students and informally in discussion within the teaching team. This paper describes the overall effectiveness of teaching and learning Wi-Fi network fundamentals using limited resources.
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Xu, Zhen, Hailun Zhang, and Rachel Q. Zhang. "Online Demand Fulfillment Under Limited Flexibility." Management Science 66, no. 10 (October 2020): 4667–85. http://dx.doi.org/10.1287/mnsc.2019.3449.
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We study online demand fulfillment in a class of networks with limited flexibility and arbitrary numbers of resources and request types. We show analytically that such a network is both necessary and sufficient to guarantee a performance gap independent of the market size compared with networks with full flexibility, extending the previous literature from the long chains to more general sparse networks. Inspired by the performance bound, we develop simple inventory allocation rules and guidelines for designing such network structures. Numerical experiments including one using some real data from Amazon China are conducted to confirm our findings as well as some of the flexibility principles conjectured in the literature. This paper was accepted by Chung Piaw Teo, optimization.
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Karjalainen, Jesse, Aku Valtakoski, and Ilkka Kauranen. "Interfirm network structure and firm resources: Towards a unifying concept." Journal of Entrepreneurship, Management and Innovation 17, no. 3 (2021): 227–64. http://dx.doi.org/10.7341/20211737.
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PURPOSE: The objective of this paper is to propose a concept of network resource distribution that systematically unifies the resource-based and network-based perspectives on interfirm networks and enables integrated analysis of how firm resources and network structure interact to affect firm performance. METHODOLOGY: This conceptual paper first reviews the extant literature on interfirm networks and then develops the unifying concept of network resource distribution. FINDINGS: The literature review indicates that strategy scholars have long sought to integrate the resource-based view and the social network explanations of firm performance but, thus far, only a partial integration has been achieved. In particular, studies on the resource-level heterogeneity of interfirm networks have largely been limited to the analysis of firm dyads. How firm resources and network structure beyond the immediate network partners interact to affect firm performance has not yet been adequately addressed. The proposed unified concept of network resource distribution systematizes prior research and illuminates how network structure and firm resources interact to affect firm performance beyond the immediate network partners. IMPLICATIONS FOR THEORY AND PRACTICE: For theory, this paper highlights gaps in the extant literature on interfirm networks and proposes a unifying concept that can be utilized to address these gaps and to develop further theory in the area. For practice, this paper encourages managers not to limit their analyses of strategic alliances to immediate partnerships; it is also crucial to consider the partners and their resources, and reflect on how they are related to one another outside of the immediate partnership portfolio. ORIGINALITY AND VALUE: Network resource distribution is a novel concept that ties together and systematizes various strands of research on interfirm networks, thus providing a foundation for future research in the area. The concept is also amenable to detailed operationalization, facilitating subsequent quantitative testing of theoretical arguments combining firm resources and the structure of a network.
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Zahedi, R., and M. Khansari. "Network immunization under limited budget using graph spectra." International Journal of Modern Physics C 27, no. 08 (May 25, 2016): 1650096. http://dx.doi.org/10.1142/s0129183116500960.
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In this paper, we propose a new algorithm that minimizes the worst expected growth of an epidemic by reducing the size of the largest connected component (LCC) of the underlying contact network. The proposed algorithm is applicable to any level of available resources and, despite the greedy approaches of most immunization strategies, selects nodes simultaneously. In each iteration, the proposed method partitions the LCC into two groups. These are the best candidates for communities in that component, and the available resources are sufficient to separate them. Using Laplacian spectral partitioning, the proposed method performs community detection inference with a time complexity that rivals that of the best previous methods. Experiments show that our method outperforms targeted immunization approaches in both real and synthetic networks.
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Belousov, Vadim, Irina Fateeva, and Antonina Deniskina. "Parametrical network models of distribution of limited resources in difficult systems." MATEC Web of Conferences 265 (2019): 07025. http://dx.doi.org/10.1051/matecconf/201926507025.
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In article effective methods of the temporary analysis and calculation of the generalized network models are offered. On their basis the class of parametrical network models is under construction and applications of such models to problems of distribution of limited resources of difficult systems in the conditions of an intensification of works are considered. A number of terms of scheduling is specified. Conditions of consistency and criteria of resource resolvability of some classes of tasks on such models are investigated.
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Nurcahyani, Ida, and Jeong Woo Lee. "Role of Machine Learning in Resource Allocation Strategy over Vehicular Networks: A Survey." Sensors 21, no. 19 (September 30, 2021): 6542. http://dx.doi.org/10.3390/s21196542.
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The increasing demand for smart vehicles with many sensing capabilities will escalate data traffic in vehicular networks. Meanwhile, available network resources are limited. The emergence of AI implementation in vehicular network resource allocation opens the opportunity to improve resource utilization to provide more reliable services. Accordingly, many resource allocation schemes with various machine learning algorithms have been proposed to dynamically manage and allocate network resources. This survey paper presents how machine learning is leveraged in the vehicular network resource allocation strategy. We focus our study on determining its role in the mechanism. First, we provide an analysis of how authors designed their scenarios to orchestrate the resource allocation strategy. Secondly, we classify the mechanisms based on the parameters they chose when designing the algorithms. Finally, we analyze the challenges in designing a resource allocation strategy in vehicular networks using machine learning. Therefore, a thorough understanding of how machine learning algorithms are utilized to offer a dynamic resource allocation in vehicular networks is provided in this study.
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Aveklouris, Angelos, Maria Vlasiou, Jiheng Zhang, and Bert Zwart. "Heavy-traffic approximations for a layered network with limited resources." Probability and Mathematical Statistics 37, no. 2 (May 14, 2018): 498–532. http://dx.doi.org/10.19195/0208-4147.37.2.15.
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HEAVY-TRAFFIC APPROXIMATIONS FOR A LAYERED NETWORK WITH LIMITED RESOURCESMotivated by a web-server model, we present a queueing network consisting of two layers. The first layer incorporates the arrival of customers at a network of two single-server nodes. We assume that the interarrival and the service times have general distributions. Customers are served according to their arrival order at each node and after finishing their service they can re-enter at nodes several times for another service. At the second layer, active servers act as jobs that are served by a single server working at speed one in a processor-sharing fashion. We further assume that the degree of resource sharing is limited by choice, leading to a limited processor-sharing discipline. Our main result is a diffusion approximation for the process describing the number of customers in the system. Assuming a single bottleneck node and studying the system as it approaches heavy traffic, we prove a state-space collapse property.
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Meng, Yun, Yuan Dong, Chunling Wu, and Xinyi Liu. "A Low-Cost Resource Re-Allocation Scheme for Increasing the Number of Guaranteed Services in Resource-Limited Vehicular Networks." Sensors 18, no. 11 (November 9, 2018): 3846. http://dx.doi.org/10.3390/s18113846.
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Vehicular networks are becoming increasingly dense due to expanding wireless services and platooning has been regarded as a promising technology to improve road capacity and on-road safety. Constrained by limited resources, not all communication links in platoons can be allocated to the resources without suffering interference. To guarantee the quality of service, it is required to determine the set of served services at which the scale of demand exceeds the capability of the network. To increase the number of guaranteed services, the resource allocation has to be adjusted to adapt to the dynamic environment of the vehicular network. However, resource re-allocation results in additional costs, including signal overhead and latency. To increase the number of guaranteed services at a low-cost in a resource-limited vehicular network, we propose a time dynamic optimization method that constrains the network re-allocation rate. To decrease the computational complexity, the time dynamic optimization problem is converted into a deterministic optimization problem using the Lyapunov optimization theory. The simulation indicates that the analytical results do approximate the reality, and that the proposed scheme results in a higher number of guaranteed services as compared to the results of a similar algorithm.
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Yoon, Zizung, Walter Frese, and Klaus Briess. "Design and Implementation of a Narrow-Band Intersatellite Network with Limited Onboard Resources for IoT." Sensors 19, no. 19 (September 27, 2019): 4212. http://dx.doi.org/10.3390/s19194212.
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Satellite networks are inevitable for the ubiquitous connectivity of M2M (machine to machine) and IoT (internet of things) devices. Advances in the miniaturization of satellite technology make networks in LEO (Low Earth Orbit) predestined to serve as a backhaul for narrow-band M2M communication. To reduce latency and increase network responsivity, intersatellite link capability among nodes is a key component in satellite design. The miniaturization of nodes to enable the economical deployment of large networks is also crucial. Thus, this article addresses these key issues and presents a design methodology and implementation of an adaptive network architecture considering highly limited resources, as is the case in a nanosatellite (≈10 kg) network. Potentially applicable multiple access techniques are evaluated. The results show that a time division duplex scheme with session-oriented P2P (point to point) protocols in the data link layer is more suitable for limited resources. Furthermore, an applicable layer model is defined and a protocol implementation is outlined. To demonstrate the technical feasibility of a nanosatellite-based communication network, the S-NET (S band network with nanosatellites) mission has been developed, which consists of four nanosatellites, to demonstrate multi-point crosslink with 100 kbps data rates over distances up to 400 km and optimized communication protocols, pushing the technological boundaries of nanosatellites. The flight results of S-NET prove the feasibility of these nanosatellites as a space-based M2M backhaul.
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Wang, Hezhe, Guangsheng Feng, Huiqiang Wang, Hongwu Lv, and Renjie Zhou. "RABP: Delay/disruption tolerant network routing and buffer management algorithm based on weight." International Journal of Distributed Sensor Networks 14, no. 3 (March 2018): 155014771875787. http://dx.doi.org/10.1177/1550147718757874.
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Delay/disruption tolerant network is a novel network architecture, which is mainly used to provide interoperability for many challenging networks such as wireless sensor network, ad hoc networks, and satellite networks. Delay/disruption tolerant network has extremely limited network resources, and there is typically no complete path between the source and destination. To increase the message delivery reliability, several multiple copy routing algorithms have been used. However, only a few can be applied efficiently when there is a resource constraint. In this article, a delay/disruption tolerant network routing and buffer management algorithm based on weight (RABP) is proposed. This algorithm estimates the message delay and hop count to the destination node in order to construct a weight function of the delay and hop count. A node with the least weight value will be selected as the relay node, and the algorithm implements buffer management based on the weight of the message carried by the node, for efficiently utilizing the limited network resources. Simulation results show that the RABP algorithm outperforms the Epidemic, Prophet, and Spray and wait routing algorithms in terms of the message delivery ratio, average delay, network overhead, and average hop count.
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Lopes, Paulo, and Fernando B. Nascimento. "Time Synchronization in Limited Resources Wireless Devices." International Journal for Innovation Education and Research 7, no. 12 (December 31, 2019): 269–88. http://dx.doi.org/10.31686/ijier.vol7.iss12.2046.
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This article deals with implementation of a time distribution protocol among limited resources wireless sensor devices. This type of protocol aims to distribute the same time reference among two or more devices within a network. Timestamps on measures help to relate them on causality studies. The PTP protocol defined at IEEE 1588-2008 is used, with little adaptations, to synchronize and tune software clocks inside the target boards of the Texas Instruments ez430-RF2480ZigBee kit. Initially only synchronization was done, but it was verified the need to implement clock tuning. The devices clocks can be synchronized and tuned, even in heavily limited resources devices.
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Shen, Ling, Muqing Wu, and Min Zhao. "Secure Virtual Network Embedding Algorithms for a Software-Defined Network Considering Differences in Resource Value." Electronics 11, no. 10 (May 23, 2022): 1662. http://dx.doi.org/10.3390/electronics11101662.
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Software-defined networking (SDN) and network virtualization (NV) are key technologies for future networks, which allow telecommunication service providers (TSPs) to share network resources with users in a flexible manner. Since TSPs have limited virtualized network resources, it is critical to develop effective virtual network embedding (VNE) algorithms for an SDN network to improve resource utilization. However, most existing VNE algorithms ignore the security issues of SDN networks, which may be subject to malicious attacks due to their openness feature. Therefore, it is necessary to develop secure VNE (SVNE) for SDN networks. In this paper, we researched the relationship between resource value and node security-level, and we found that there are differences in the resource value of different nodes. Based on this analysis, we define the evaluation indicators considering differences in resource value for the SVNE problem. Then, we present a mixed-integer linear program (MILP) model to minimize the cost of SVNE. As the formulated optimization problem cannot be solved conveniently, we design two node-ranking approaches to rank physical and virtual nodes, respectively, and we propose two novel SVNE algorithms based on the node ranking approaches. Finally, simulation results reveal that our proposed algorithm is superior to other typical algorithms.
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Dai, Xianlong, Guang Cheng, Ziyang Yu, Ruixing Zhu, and Yali Yuan. "MSLCFinder: An Algorithm in Limited Resources Environment for Finding Top-k Elephant Flows." Applied Sciences 13, no. 1 (December 31, 2022): 575. http://dx.doi.org/10.3390/app13010575.
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Encrypted traffic accounts for 95% of the total traffic in the backbone network environment with Tbps bandwidth. As network traffic becomes more and more encrypted and link rates increase in modern networks, the measurement of encrypted traffic relies more on collecting and analyzing massive network traffic data that can be separated from the support of high-speed network traffic measurement technology. Finding top-k elephant flows is a critical task with many applications in congestion control, anomaly detection, and traffic engineering. Owing to this, designing accurate and fast algorithms for online identification of elephant flows becomes more and more challenging. Existing methods either use large-size counters, i.e., 20 bit, to prevent overflows when recording flow sizes or require significant space overhead to measure the sizes of all flows. Thus, we adopt a novel strategy, called count-with-uth-level-sampling, in this paper, to find top-k elephant flows in limited resource environments. Moreover, the proposed algorithm, called MSLCFinder, incurs lightweight counter and uth-level multi-sampling with small, constant processing for millions of flows. Experimental results show that MSLCFinder can achieve more than 97% precision with an extremely limited hardware resource. Compared to the state-of-the-art, our method realizes the statistics and filtering of millions of data streams with less memory.
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Zhang, Yongqiang, Yaming Li, Yi Zhou, and Jinlong Ma. "Optimal link rewiring strategy for transport efficiency on scale-free networks with limited bandwidth." International Journal of Modern Physics C 31, no. 02 (December 26, 2019): 2050033. http://dx.doi.org/10.1142/s0129183120500333.
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The network topology structure has great impact on its traffic capacity. Most of the biological and technological networks have been proved to exhibit scale-free feature. In real networks, the hub links, which usually bear large traffic loads, have restricted transport efficiency of the complex networks. In this paper, we focus on the bandwidth congestion and propose a rewiring link strategy to optimize traffic dynamics on scale-free networks. Two link rewiring strategies are compared and the simulation results on scale-free networks show that our strategy has more advantages, which makes the degree distribution of the network more uniform, reducing the average path length of different nodes, balancing the resources of the network and increasing the traffic capacity of the network. This work will be beneficial for designing network topology and optimizing network performances.
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Hammood, Omar A., Mohd Nizam Mohmad Kahar, Waleed A. Hammood, Raed Abdulkareem Hasan, Mostafa Abdulghfoor Mohammed, Ayoob A. Yoob, and Tole Sutikno. "An effective transmit packet coding with trust-based relay nodes in VANETs." Bulletin of Electrical Engineering and Informatics 9, no. 2 (April 1, 2020): 685–97. http://dx.doi.org/10.11591/eei.v9i2.1653.
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Vehicular ad-hoc networks (VANETs) are characterized by limited network resources such as limited bandwidth and battery capacity. Hence, it is necessary that unnecessary use of network resources (such as unnecessary packet transfers) is reduced in such networks so that the available power can be conserved for efficient multicast communications. In this paper, we have presented a Transmit Packet Coding (TPC) Network Coding in VANET to ensure reliable and efficient multicasting. With network coding, the number of transmitted packets over the network can be reduced, ensuring efficient utilization of network devices and resources. Here, the trust-based graph optimization is performed using Cuckoo search algorithm to select the secure relay nodes. The experimental results showed the superiority of the presented approach compared to the existing techniques in terms of throughput, latency, hop delay, packet delivery ratio, network decoder outage probability, and block error rate.
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Korobkov, I. L. "Method of scheduling channel resources for onboard SpaceWire networks with TDMA." Radio industry (Russia) 29, no. 4 (December 1, 2019): 44–53. http://dx.doi.org/10.21778/2413-9599-2019-29-4-44-53.
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The article presents a new method for scheduling channel resources in SpaceWire onboard networks with support for TDMA technology. The network features based on the SpaceWire network standard and the STP-ISS transport protocol, which provides TDMA technology in the form of the «Scheduling» mechanism, were considered. This mechanism is used in networks with the goal of providing determinism, resolving conflicts and blocks when two or more devices are simultaneously trying to transmit data, occupying a limited channel resource. A comparative analysis of existing methods and algorithms for scheduling channel resources to design a schedule table was conducted. A new method of scheduling channel resources in SpaceWire onboard networks was presented and substantiated. A performance evaluation was carried out using the parameters significant for the space industry. It demonstrates the effectiveness of the developed method.
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Du, Xiu Juan, Ke Jun Huang, Fan Liu, Zhen Xing Feng, and Sheng Lin Lan. "Micro-ANP：A Novel Network Protocol Architecture for Underwater Sensor Network." Applied Mechanics and Materials 303-306 (February 2013): 223–30. http://dx.doi.org/10.4028/www.scientific.net/amm.303-306.223.
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Underwater sensor network (UWSN) adopts acoustic communication and is characterized by high delay, low bandwidth, high error rate, low energy-consumption requirement and sparse topology, which lead to conventional network protocols for terrestrial WSN or other wireless multi-hop networks are unable to satisfy the performance of UWSN. On the other hand, the limited resources of energy, CPU and memory cause that the protocol stack running on the sensor node shouldn’t be much complicated. The paper proposes a novel, green network protocol architecture model tailored for UWSN, referred to as Micro-ANP, which is three layered structure including application, network transport, and physical layer. Furthermore, basing on Micro-ANP we realize the packet size optimization of UWSN through Matlab simulation. Micro-ANP protocol architecture and packet size optimization improve the energy efficiency of UWSN, prolong the network lifetime and achieve green network while meeting the requirement of QoS with the constraints of limited resource.
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Huang, Yu, Wanxing Sheng, Peipei Jin, Baicuan Nie, Meikang Qiu, and Guangquan Xu. "A Node-Oriented Discrete Event Scheduling Algorithm Based on Finite Resource Model." Journal of Organizational and End User Computing 31, no. 3 (July 2019): 67–82. http://dx.doi.org/10.4018/joeuc.2019070104.
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Discrete event simulation is the most important and essential part in network simulation. The node-oriented model of discrete event scheduling is a model that allocates computing resources as nodes and makes the discrete event simulation as a simulation task on nodes. In this article the reason of low performance in large-scale network simulation is analyzed, and an ideal node-oriented model of discrete event scheduling is presented and a resource-limited node-oriented model of discrete event scheduling by adding some restrictions on network resources is proposed. Then, the authors complete contrast experiments of the resource-limited node-oriented model of discrete event scheduling and NS2. Finally, packet loss in resource-limited node-oriented model of discrete event scheduling is examined. Also, NS2 is discussed in this article and the authors have proposed an improved method for the packet loss algorithm in a resource-limited node-oriented model of discrete event scheduling.
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Li, Jun Xia. "Research on Data Compression of WSN Based on Compressed Sensing." Applied Mechanics and Materials 686 (October 2014): 423–28. http://dx.doi.org/10.4028/www.scientific.net/amm.686.423.
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For Wireless Sensor Networks (WSN) is responsible for sensing, collecting, processing and monitoring of environmental data, but it might be limited in resources. This paper describes in detail the compressed sensing theory, study the wireless sensor network data conventional compression and network coding method. The linear network coding scheme based on sparse random projection theory of compressed sensing. Simulation results show that this system satisfies the requirements of the reconstruction error of packets needed to reduce the number of nodes to the total number of 30%, improves the efficiency of data communications in wireless sensor network, reduce the energy consumption of the system. With other wireless sensor network data compression algorithm, the proposed algorithm has the advantages of simple realization, the compression effect is good, especially suitable for resource limited, and the accuracy requirements are not particularly stringent in wireless sensor networks.
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Corso, Alessandra, Lucia Valentina Gambuzza, Pietro De Lellis, and Mattia Frasca. "Synchronizing network systems in the presence of limited resources via edge snapping." Chaos: An Interdisciplinary Journal of Nonlinear Science 33, no. 1 (January 2023): 013123. http://dx.doi.org/10.1063/5.0093560.
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In this work, we propose a multilayer control protocol for the synchronization of network dynamical systems under limited resources. In addition to the layer where the interactions of the system take place, i.e., the backbone network, we propose a second, adaptive layer, where the edges are added or removed according to the edge snapping mechanism. Different from classic edge snapping, the inputs to the edge dynamics are modified to cap the number of edges that can be activated. After studying the local stability of the overall network dynamics, we illustrate the effectiveness of the approach on a network of Rössler oscillators and then show its robustness in a more general setting, exemplified with a model of the Italian high-voltage power grid.
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Sopin, Eduard, and Konstantin Samouylov. "Analysis of the Limited Resources Queuing System with Signals and Multiple Flows of Customers." ITM Web of Conferences 24 (2019): 01007. http://dx.doi.org/10.1051/itmconf/20192401007.
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In the paper, a wireless network is modelled in terms of multiserver queuing system with limited resources, random resource requirements and signals that trigger resource reallocation procedure. For the queuing system, we derive the set of balance equations and propose the solution method. Moreover, the formulas for main performance measures are obtained.
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Trach, Roman, and Sergey Bushuyev. "Analysis communication network of construction project participants." Przegląd Naukowy Inżynieria i Kształtowanie Środowiska 29, no. 3 (October 8, 2020): 388–96. http://dx.doi.org/10.22630/pniks.2020.29.3.33.
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The construction industry is characterized by limited resources and a high level of competition. Limited resources and a competitive environment determine knowledge and information as a particularly important resource for the development of the construction industry. A communication network is one of the elements of a knowledge management system in projects and serves to organize and maintain information links between project participants. We have analysed the communication network between project participants for residential building construction using social network analysis (SNA). The purpose of this work is the calculation and analysis centrality measures for participants in the construction project delivery. Centrality measures can answer the following questions whether the node is influential or central to the network and whether the node is critical for the flow of information in the network.
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Wang, Jing, and ZhongCheng Wu. "Model Lightweighting for Real-time Distraction Detection on Resource-Limited Devices." Computational Intelligence and Neuroscience 2022 (December 23, 2022): 1–13. http://dx.doi.org/10.1155/2022/7360170.
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Detecting distracted driving accurately and quickly with limited resources is an essential yet underexplored problem. Most of the existing works ignore the resource-limited reality. In this work, we aim to achieve accurate and fast distracted driver detection in the context of embedded devices where only limited memory and computing resources are available. Specifically, we propose a novel convolutional neural network (CNN) light-weighting method via adjusting block layers and shrinking network channels without compromising the model’s accuracy. Finally, the model is deployed on multiple devices with real-time detection of driving behaviour. The experimental results for the American University in Cairo (AUC) and StateFarm datasets demonstrate the effectiveness of the proposed method. For instance, for the AUC dataset, the proposed MobileNetV2-tiny model achieves 1.63% higher accuracy with just 78% of the model parameters of the original MobileNetV2 model. The inference speed of the proposed MobileNetV2-tiny model on resource-limited devices is on average 1.5 times that of the original MobileNetV2 model, which can meet real-time requirements.
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Tao, Jiang, Zhen Gao, and Zhaohui Guo. "Training Vision Transformers in Federated Learning with Limited Edge-Device Resources." Electronics 11, no. 17 (August 23, 2022): 2638. http://dx.doi.org/10.3390/electronics11172638.
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Vision transformers (ViTs) demonstrate exceptional performance in numerous computer vision tasks owing to their self-attention modules. Despite improved network performance, transformers frequently require significant computational resources. The increasing need for data privacy has encouraged the development of federated learning (FL). Traditional FL places a computing burden on edge devices. However, ViTs cannot be directly applied through FL on resource-constrained edge devices. To utilize the powerful ViT structure, we reformulated FL as a federated knowledge distillation training algorithm called FedVKD. FedVKD uses an alternating minimization strategy to train small convolutional neural networks on edge nodes and periodically transfers their knowledge to a large server-side transformer encoder via knowledge distillation. FedVKD affords the benefits of reduced edge-computing load and improved performance for vision tasks, while preserving FedGKT-like asynchronous training. We used four datasets and their non-IID variations to test the proposed FedVKD. When utilizing a larger dataset, FedVKD achieved higher accuracy than FedGKT and FedAvg.
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Guan, Xueming, and Yaozhi Ma. "Wireless Network Virtualization Resource Sharing considering Dynamic Resource Allocation Algorithm." Advances in Multimedia 2022 (August 11, 2022): 1–12. http://dx.doi.org/10.1155/2022/7338309.
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In order to improve the efficiency of wireless network virtualization resource processing, this paper combines the dynamic resource allocation algorithm to construct a wireless network virtualization resource sharing model. This paper proposes a task-oriented resource management model and uses the task-oriented TRS model to describe resources and service processes, reducing the complexity of formulating resource allocation strategies. Moreover, this paper comprehensively considers factors such as centralized coordination control cost and limited domain topology visibility to improve the dynamic resource allocation algorithm. Through comparative research, it can be seen that the wireless network virtualization resource sharing method proposed in this paper considering the dynamic resource allocation algorithm can effectively improve the processing efficiency of wireless network virtualization resources.
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Swathi, Gundala, and R. Saravanan. "A Framework for Efficient Routing in MANET using Index Routing Tables-based Algorithms." Defence Science Journal 66, no. 6 (October 31, 2016): 568. http://dx.doi.org/10.14429/dsj.66.10796.
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Conventional network routing protocols rely on predefined numerical network unique node ID or group identifier for packet delivery, independent of semantic applications. This compels incorporation of resource/service discovery approaches in the design itself, at higher layers of network, causing additional overhead. This overhead, though tolerable in high speed wired networks, significantly restricts the performance in the infrastructure-less wireless ad hoc networks expending their limited battery resources, which are already consumed due to assigning unique identifiers to the naturally anonymous and high mobile nodes. This study proposes a single routing approach which facilitates descriptive and semantically-rich identification of network’s resources/services. This fusion of the discovery processes of the resources and the path based on their similarity in a single phase significantly reduces traffic load and latency of communication considering the generality too. Further, a framework capable of exploiting application-specific semantics of messages, adaptable to diverse traffic patterns is proposed. Analytical results amply illustrate the scalability and efficacy of the proposed method.
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Rahmadya Trias Handayanto and Herlawati. "Modification of SqueezeNet for Devices with Limited Computational Resources." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 7, no. 1 (February 3, 2023): 153–60. http://dx.doi.org/10.29207/resti.v7i1.4446.
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In recent years, the computational approach has shifted from a statistical basis to deep neural network architectures which process the input without explicit knowledge that underlies the model. Many models with high accuracy have been proposed by training the datasets using high performance computing devices. However, only a few studies have examined its use on non-high-performance computers. In fact, most users, who are mostly researchers in certain fields (medical, geography, economics, etc.) sometimes need computers with limited computational resources to process datasets, from notebooks, personal computers, to mobile processor-based devices. This study proposes a basic model with good accuracy and can run lightly on the average computer so that it remains lightweight when used as a basis for advanced deep neural networks models, e.g., U-Net, SegNet, PSPNet, DeepLab, etc. Using several well-known basic methods as a baseline (SqueezeNet, ShuffleNet, GoogleNet, MobileNetV2, and ResNet), a model combining SqueezeNet with ResNet, termed Res-SqueezeNet, was formed. Testing results show that the proposed method has accuracy and inference time of 84.59% and 8.46 second, respectively, which has an accuracy of 2% higher than the SqueezeNet (82.53%) and is close to the accuracy of other baseline methods (from 84.93% to 0.88.01%) while still maintaining the inference speed (below nine second). In addition, residual part of the proposed method can be used to avoid vanishing gradient, hence, it can be implemented to solve more advanced problems which need a lot of layers, e.g., semantic segmentation, time-series prediction, etc.
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Parenreng, Jumadi Mabe, and Akio Kitagawa. "A Model of Security Adaptation for Limited Resources in Wireless Sensor Network." Journal of Computer and Communications 05, no. 03 (2017): 10–23. http://dx.doi.org/10.4236/jcc.2017.53002.
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Ahmed, Nehal K., Elsayed E. Hemayed, and Magda B. Fayek. "Hybrid Siamese Network for Unconstrained Face Verification and Clustering under Limited Resources." Big Data and Cognitive Computing 4, no. 3 (August 6, 2020): 19. http://dx.doi.org/10.3390/bdcc4030019.
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In this paper, we propose an unconstrained face verification approach that is dependent on Hybrid Siamese architecture under limited resources. The general face verification trend suggests that larger training datasets and/or complex architectures lead to higher accuracy. The proposed approach tends to achieve high accuracy while using a small dataset and a simple architecture by directly learn face’s similarity/dissimilarity from raw face pixels, which is critical for various applications. The proposed architecture has two branches; the first part of these branches is trained independently, while the other parts shared their parameters. A multi-batch algorithm is utilized for training. The training process takes a few hours on a single GPU. The proposed approach achieves near-human accuracy (98.9%) on the Labeled Faces in the Wild (LFW) benchmark, which is competitive with other techniques that are presented in the literature. It reaches 99.1% on the Arabian faces dataset. Moreover, features learned by the proposed architecture are used in building a face clustering system that is based on an updated version of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN). To handle the cluster quality challenge, a novel post-clustering optimization procedure is proposed. It outperforms popular clustering approaches, like K-Means and spectral by 0.098 and up to 0.344 according to F1-measure.
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Qureshi, Ali Gul, and Eiichi Taniguchi. "A multi-period humanitarian logistics model considering limited resources and network availability." Transportation Research Procedia 46 (2020): 212–19. http://dx.doi.org/10.1016/j.trpro.2020.03.183.
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Kamal, Muhammad Ayoub, Hafiz Wahab Raza, Muhammad Mansoor Alam, Mazliham Mohd Su’ud, and Aznida binti Abu Bakar Sajak. "Resource Allocation Schemes for 5G Network: A Systematic Review." Sensors 21, no. 19 (October 2, 2021): 6588. http://dx.doi.org/10.3390/s21196588.
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Fifth-generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, lower power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising device-to-device networks, macro-cells, and different categories of small cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need for cellular service and the limited resources to provide it, capably handling network traffic and operation has become a problem of resource distribution. One of the utmost serious problems is to alleviate the jamming in the network in support of having a better QoS. However, although a limited number of review papers have been written on resource distribution, no review papers have been written specifically on 5G resource allocation. Hence, this article analyzes the issue of resource allocation by classifying the various resource allocation schemes in 5G that have been reported in the literature and assessing their ability to enhance service quality. This survey bases its discussion on the metrics that are used to evaluate network performance. After consideration of the current evidence on resource allocation methods in 5G, the review hopes to empower scholars by suggesting future research areas on which to focus.
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Plenty, Jackie, Heidi Dix, and Louise Barley. "Practice Education Network for Social Work (PENSW): Evaluation of an online resource." Journal of Practice Teaching and Learning 14, no. 3 (May 4, 2017): 81–96. http://dx.doi.org/10.1921/jpts.v14i3.1016.
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The Practice Education Network for Social Work (PENSW) is an online resource for networking and sharing knowledge and information that is accessed by all the professionals and partner agencies involved in providing social work placements and supervising social work students at the University of Suffolk (UOS) in the United Kingdom (UK). This research explored the ease with which such networks can be set up, and offers an evaluation from network members. Given limited national resources and the need to provide more localised resources; this evaluation demonstrates the importance of providing an easily accessible virtual space for organisations and professionals to access resources, network, and share best practice. The findings suggest that all social work training programmes should consider providing a localised network to support the social work placement process by ensuring that supervisors of social work students have access to necessary documentation, research, and information so that they can effectively fulfil their roles, and stay connected to the programme provider and other professionals involved in social work student practice placements.Keywords: social work placements; supervision; networking; resources; information sharing; practice education.
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Song, Qing Yang, Ming Hong Yue, and Zhao Long Ning. "A Satisfaction-Based Dynamic Bandwidth Allocation Algorithm for Heterogeneous Wireless Network." Applied Mechanics and Materials 220-223 (November 2012): 2004–7. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2004.
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Due to the limited bandwidth resources, traditional networks can not completely guarantee the Quality of Service (QoS) among users with new class, thus how to allocate network resource effectively becomes a very important problem. In this paper, we propose an algorithm for an integrated cellular/WLAN network, namely Satisfaction-based Dynamic Bandwidth Allocation (SDBA) algorithm. The main objective is to guarantee users’ satisfaction through allocating network resource dynamically according to proportional fairness based degradation and one-by-one search based degradation. Numerical results show that our proposed algorithm not only reduces new call blocking probability (NCBP) and handoff call dropping probability (HCDP), but also maintain fairness among users.
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Yan, Yanjun, Huihui Xu, Ning Zhang, Guangjie Han, and Mingliu Liu. "Dynamic Divide Grouping Non-Orthogonal Multiple Access in Terrestrial-Satellite Integrated Network." Sensors 21, no. 18 (September 16, 2021): 6199. http://dx.doi.org/10.3390/s21186199.
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Non-orthogonal multiple access (NOMA) has been extensively studied to improve the performance of the Terrestrial-Satellite Integrated Network (TSIN) on account of the shortage of frequency band resources. In this paper, the terrestrial network and satellite network synergistically provide complete coverage for ground users, and based on the architecture, we first formulate a constrained optimization problem to maximize the sum rate of the TSIN under the limited spectrum resources. As the terrestrial networks and the satellite network will cause interference to each other, we first investigate the capacity performance of the terrestrial networks and the satellite networks separately, in which the optimal power control factor expression is derived. Then, by constructing the relationship model between user elevation angle, beam angle and distance, we develop a dynamic group pairing schemes to ensure the effective pairing of NOMA users. Based on the user pairing, to obtain the optimal resource allocation, a joint optimization algorithm of power allocation, beam channel and base station channel resource is proposed. Finally, simulation results are provided to evaluate the user paring scheme as well as the total system performance, in comparison with the existing works.
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Blommaert, Lieselotte, Roza Meuleman, Stefan Leenheer, and Anete Butkēviča. "The gender gap in job authority: Do social network resources matter?" Acta Sociologica 63, no. 4 (June 12, 2019): 381–99. http://dx.doi.org/10.1177/0001699319847504.
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Women generally have less job authority than men. Previous research has shown that human capital, family features and contextual factors cannot fully explain this gender authority gap. Another popular explanation holds that women’s career opportunities are limited because their social networks comprise less beneficial contacts and resources than men’s. Yet, the role of social networks has received little attention in empirical research seeking to explain the gender gap in job authority. This study examines to what extent gender differences in social networks exist and are related to the gender authority gap. Drawing on two strands of social network theory, we develop hypotheses about the role of network diversity and network status. We test these hypotheses using representative longitudinal data from the NEtherlands Longitudinal Lifecourse Study (2009–2013). Results reveal that women generally had less diverse occupational networks in terms of contacts’ occupations and were less likely to know managers than men, network features which are found to be significantly related to job authority. Controlling for these gender differences in networks leads to a reduction of the observed gender authority gap that is statistically significant but modest in substantive terms.
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Zhang, Chenlin, and Pan Wang. "Fuzzy Logic System Assisted Sensing Resource Allocation for Optical Fiber Sensing and Communication Integrated Network." Sensors 22, no. 20 (October 11, 2022): 7708. http://dx.doi.org/10.3390/s22207708.
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With the development of information transmission, there is an increasing demand for state monitoring of fiber-optic communication networks to improve the security and self-healing ability of the network. Distributed optical fiber sensing is one of the most attractive methods because it can achieve real-time detection of the whole network without additional sensing heads. However, when the sensing network is introduced into the communication network, the failure probability should be efficiently suppressed with limited sensing resources. In this paper, the fuzzy logic system is used to evaluate the impact of different sensing resource allocation on optical cable network quality. The link failure probability and path failure probability under the condition of uniform and non-uniform sensing resource allocation are simulated and analyzed, respectively. As shown in the analysis results, the failure probability under non-uniform allocation is significantly lower than under uniform allocation. In this paper, we discussed and addressed the allocation of the optical fiber sensing and communication integrated (OFSCI) network with the limited sensing resource for the first time. The results are helpful to develop an allocation strategy for optical fiber sensing and a communication integrated network with a higher robustness.
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Tata, Chafika, and Michel Kadoch. "Network Coding-Based D2D Transmission for Public Safety Networks over LTE HetNets and 5G Networks." Wireless Communications and Mobile Computing 2022 (March 14, 2022): 1–15. http://dx.doi.org/10.1155/2022/8889718.
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Device to Device (D2D) communications appear like an emergency solution for the Public Safety Network (PSN) when the LTE cell range is limited. D2D networks can use the unlicensed frequency bands, as this makes their transmissions cheaper and easier to deploy. Therefore, the development of this technology must deal with the security challenge. On the one hand, it is important to know how to design a secure D2D solution within the small cells, and on the other hand, the new scheme needs to deal with the problem of radio resources limit, since it will be used during emergency situations. This paper develops a new algorithm, named Generalized Secure Network Coding-based Data splitting algorithm (G-SNCDS), to ensure a secure data transmission for Public Safety D2D communications over LTE Heterogeneous Networks (HetNets) and 5G networks, without using additional radio resources. Our approach consists of performing Network Coding (NC) data packets transmissions based on a new Data Splitting (DS) technique, which we developed, based on a constructed butterfly effect that uses a new Butterfly network algorithm that we propose. Our solution enhances the security without affecting the level of Quality of Service (QoS). Thus, it is more suitable when network resources are limited. The simulation results show that our approach provides a secure D2D communication without increasing the overhead in the network.
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Kamimura, Atsushi, and Kunihiko Kaneko. "Molecular Diversity and Network Complexity in Growing Protocells." Life 9, no. 2 (June 20, 2019): 53. http://dx.doi.org/10.3390/life9020053.
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A great variety of molecular components is encapsulated in cells. Each of these components is replicated for cell reproduction. To address the essential role of the huge diversity of cellular components, we studied a model of protocells that convert resources into catalysts with the aid of a catalytic reaction network. As the resources were limited, the diversity in the intracellular components was found to be increased to allow the use of diverse resources for cellular growth. A scaling relation was demonstrated between resource abundances and molecular diversity. In the present study, we examined how the molecular species diversify and how complex catalytic reaction networks develop through an evolutionary course. At some generations, molecular species first appear as parasites that do not contribute to the replication of other molecules. Later, the species turn into host species that contribute to the replication of other species, with further diversification of molecular species. Thus, a complex joint network evolves with this successive increase in species. The present study sheds new light on the origin of molecular diversity and complex reaction networks at the primitive stage of a cell.
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Yin, Miaomiao, and Asghar Jahanshahi. "Developing Knowledge-Based Resources: The Role of Entrepreneurs’ Social Network Size and Trust." Sustainability 10, no. 10 (September 21, 2018): 3380. http://dx.doi.org/10.3390/su10103380.
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Entrepreneurs’ social networks play a crucial role in developing knowledge-based resources for their new ventures. Although most studies in an entrepreneurship context find that trust is very important when entrepreneurs develop social networks, limited research examines how trust can explain the variation in the relationship between an entrepreneur’s social networks and a firm’s knowledge-based resources. Therefore, the major objective of the paper is to understand the effects of the size of an entrepreneur’s social network on his or her firm’s knowledge-based resources with high and low levels of trust. Our data were collected from surveys administered to 476 entrepreneurs in China in 2018. Our multiple regression analysis indicates that social networks reinforce knowledge-based resources in a situation where entrepreneurs highly trust their major networks partners in their business environment (e.g., family, close friends, consultants, suppliers, peers, etc.). However, with a low level of trust, the relationship between social network and knowledge-based resources is curvilinear (inverse U-shaped). Our empirical validations showed that the relationship between social network and a firm’s knowledge-based resources is highly contingent to the level of trust among network members.
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Özkan, Ömer, and Ümit Gülçiçek. "A NEURAL NETWORK FOR RESOURCE CONSTRAINED PROJECT SCHEDULING PROGRAMMING." Journal of Civil Engineering and Management 21, no. 2 (January 30, 2015): 193–200. http://dx.doi.org/10.3846/13923730.2013.802723.
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The resource constrained project-scheduling problem (RCPSP) aims to minimize the duration of a project. RCPSP is prevalently used in programming the projects with high number of activities and resources such as construction projects. In this study, 240 projects such as residential, office, school, etc. are designed and programmed under limited resources. The resource amounts of these projects are determined using three priority rules, these are Latest Finish Time, Minimum Slack Time and Maximum Remaining Path Length which have the highest performance according to the literature, in the amounts of 2, 4, 6 and 8. The project times are estimated using artificial neural network (ANN). A correlation coefficient of 0.70 was obtained from the ANN estimation model.
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Zhao, Yong Yi, and Bo Song. "A Wireless Sensor Network Service Management Strategy." Advanced Materials Research 816-817 (September 2013): 1041–44. http://dx.doi.org/10.4028/www.scientific.net/amr.816-817.1041.
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Wireless sensor networks with highly dynamic characteristics and limited resources, this paper presents a simple service management Strategy. It realizes service deployment management across different clusters, the request and the response of wireless sensor is simple that based on the protocol data format of XML WSNXML between the clusters. It provides an effective method for the management of shared resources of wireless sensor network and service expansion and realizes service release and deployment management difficulties between various wireless sensor network management based on different management cluster.
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Manvi, Sunilkumar S. "Resource Monitoring for Wireless Sensor Networks using ANFIS." Journal of Applied Computer Science Methods 8, no. 1 (June 1, 2016): 41–67. http://dx.doi.org/10.1515/jacsm-2016-0004.
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Abstract Wireless sensor networks (WSNs) are usually a resource constrained networks which have limited energy, bandwidth, processing power, memory etc. These networks are now part of Internet by the name Internet of Things (IoT). To get many services from WSNs, we may need to run many applications in the sensor nodes which consumes resources. Ideally, the resources availability of all sensor nodes should be known to the sink before it requests for any further service(s) from the sensor node(s). Hence, continuous monitoring of the resources of the sensor nodes by the sink is essential. The proposed work is a framework for monitoring certain important resources of sensor network using Adaptive-Neuro Fuzzy Inference System (ANFIS) and Constrained Application Protocol (CoAP). The ANFIS is trained with these resources consumption patterns. The input to ANFIS is the resources consumption levels and the output is the resources consumed levels that needs to be sent to the sink which may be individual or combinations of resources. The trained ANFIS generates the output periodically which determines resources consumption levels that needs to be sent to the sink. Also, ANFIS continuously learns using hybrid learning algorithm (which is basically a combination of back propagation and least squares method) and updates its parameters for better results. The CoAP protocol with its observe option is used to transport the resource monitoring data from the sensor nodes to the cluster head, then from the cluster head to the sink. The sensor nodes runs coap server, the cluster head runs both coap client and server and the sink runs coap client. The performance of the proposed work is compared with LoWPAN network management protocol (LNMP) and EmNets Network Management Protocol (EMP) in terms of bandwidth and energy overheads. It is observed that proposed work performs better when compared to the existing works.
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Jimson, Emilia Rosa, Kashif Nisar, and Mohd Hanafi Ahmad Hijazi. "The State of the Art of Software Defined Networking (SDN) Issues in Current Network Architecture and a Solution for Network Management Using the SDN." International Journal of Technology Diffusion 10, no. 3 (July 2019): 33–48. http://dx.doi.org/10.4018/ijtd.2019070103.
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Software defined networking (SDN) architecture has been verified to make the current network architecture management simpler, and flexible. The key idea of SDN is to simplify network management by introducing a centralized control, through which dynamic updates of forwarding rules, simplification of the network devices task, and flow abstractions can be realized. In this article, the researchers discuss the complex design of the current network architecture, which has inevitably resulted in poor network resources management, such as bandwidth management. SDN-based network model has been proposed to simplify the management of the limited bandwidth of a network. The proposed network model utilizes the limited network bandwidth systematically by giving real-time traffics higher priority than non-real-time traffics to access the limited resource. The experimental results showed that the proposed model helped ensure real-time traffics would be given greater priority to access the limited bandwidth, where major portion of the limited bandwidth being allocated to the real-time traffics.
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Ning, Zhaoke, Jinyong Yu, and Tong Wang. "H_/H∞ fault detection filter design for discrete-time stochastic systems with limited communication." Transactions of the Institute of Measurement and Control 41, no. 13 (April 8, 2019): 3808–17. http://dx.doi.org/10.1177/0142331219837327.
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This paper is concerned with the fault detection (FD) problem for discrete-time stochastic systems with limited communication. A filter structure is proposed to construct the residual model for fault detection. For the limited network resources, a novel event-triggered strategy is employed to decrease the amount of data that is transmitted from the sensor to the filter. With the consideration of stochastic model and limited network resources, a novel event-based method is designed to ensure the residual system is stochastically stable and satisfies the desired fault sensitivity level and disturbance attenuation level. Compared with the traditional FD method, the proposed design strategy can not only achieve the desired fault detection performance, but also save the limited network resources. The effectiveness of design strategy is verified by two simulation examples.
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Demirbağ, Orkun, Hale Demir, and Uğur Yozgat. "Political Will, Political Skill, Network Resources and Personal Reputation: A Serial Two-Mediator Model." Central European Management Journal 28, no. 3 (September 15, 2020): 26–56. http://dx.doi.org/10.7206/cemj.2658-0845.26.
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Purpose: Although social capital and positive reputation in organizations are essential for career success, there is a limited perspective in the literature on the political characteristics (motivation and ability) that enable one to acquire and develop the two elements. This study seeks to investigate the sequential role of political skill and network resources as serial mediators of the political will–personal reputation relationship. Methodology: In total, what provided data for the study were 457 sales executives from 13 different sectors in the cities of İstanbul, Kocaeli, and Bursa, which is an economically leading region of western Turkey. Executives rated their political will, political skill network resources, and personal reputation. Based on the complementary theories of political influence, social network, and signaling, we analyzed the relationships between constructs with structural equation modeling. Findings: Political skill mediated the relationship between political will and network resources, network resources mediated the relationship between political skill and personal reputation, while political skill and network resources sequentially mediated the relationship between political will and personal reputation. Implications: The data were collected from a single source. Practical Implications: Political will, political skill training, and social networks may help individuals manage their personal reputation at work, thus benefiting their careers. Originality/Value: This is one of the first studies to sequentially investigate how individuals’ characteristics (motivation and ability) develop their social network and personal reputation at work. Moreover, theories of political influence, social capital, and signaling were jointly used for the first time ever.