Abstract
Recently, campuses have been embracing smart digital technologies in order to boost the efficiency of education and creativity. Thus, massive heterogeneous flows are generated as a result of multitude simultaneous access from several heterogeneous devices. This is putting pressure on campuses to make better management of their constrained resources and to ensure the required Quality of Service (QoS). In this paper, we propose a multi-flow management scheme over a software-defined smart digital campus network, named Service and Resource Aware Flow Management (SRAFM). Our approach offers a unified fully-programmable architecture, a distributed end-host-based flow characterization plane, and a centralized software-defined optimization model to efficiently manage heterogeneous flows. Network functionalities, including QoS aware routing and resource allocation optimization, are formulated as a mixed-integer linear programming problem. Due to its NP-hard complexity, we propose an approximation algorithm in a decomposed fashion based on Lagrangian Dual Decomposition (LDD) and subgradient methods to find an optimal solution for flow management. We evaluate our scheme from different aspects, including the number of simultaneous heterogeneous flows, QoS provisioning, characterization impacts, and network scalability. Compared to the well-known benchmarks in QoS aware routing and optimization problem, SWAY and LARAC, our simulation results conducted with a large number of flows over a small-scale network show promising performance. The proposed scheme significantly improves the cost reduction by 51% as compared to LARAC, the end-to-end delay by 21% and 34%, the bandwidth availability by 27% and 36%, and the QoS violation by 11% and 29% as compared to SWAY and LARAC, respectively.
Highlights
Campuses are embracing smart digital technologies (e.g., Industrial Internet, Internet of Things, and Smart Cities) to create intelligent, green, and safe educational environments
Cisco [10] shows that some types of network applications, like video-based applications supplied by providers such as Youtube, Netflix, and Hulu, will grow at a compound annual growth rate (CAGR) of 31%, while online gaming traffic will have a traffic growth rate of 47%, and traffic including web, email, and data will have a CAGR of 18%
In this paper, we propose a multi-flow management scheme over a software-defined smart digital campus network named Service and Resource Aware Flow Management (SRAFM)
Summary
Campuses are embracing smart digital technologies (e.g., Industrial Internet, Internet of Things, and Smart Cities) to create intelligent, green, and safe educational environments. Cisco [10] shows that some types of network applications, like video-based applications supplied by providers such as Youtube, Netflix, and Hulu, will grow at a compound annual growth rate (CAGR) of 31%, while online gaming traffic will have a traffic growth rate of 47%, and traffic including web, email, and data will have a CAGR of 18% These services’ massive data streams are leading to unprecedented challenges for network administrators in terms of advanced solutions development for network flow management and resource allocation control with minimum cost, especially with the constrained campus network resource problems (e.g., limited link capacity, constrained device with limited CPU, memory, and power resources) [11]–[13]. The proposed scheme is different from existing works for two reasons It offers a whole solution in terms of architecture, flow characterization, and QoS aware routing and resource optimization to manage the masses of heterogeneous flows generated from thousands of interconnected devices. Over a unified fully-programmable architecture, SRAFM implements a distributed end-host-based flow characterization solution and a centralized software-defined optimization model for service and resource-aware routing problem.
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