Software Defined Network’s Garbage Collection With Clean-Up Packets

Huque, Tanvir Ishtaique ul; Jourjon, Guillaume; Russell, Craig; Gramoli, Vincent

doi:10.1109/tnsm.2019.2944523

Cited by 2 publications

(3 citation statements)

References 25 publications

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“…A heuristic algorithm using relaxation and rounding techniques was presented, and feasible solutions were obtained by invoking the proposed PathSearch, PathRulePlacement, and SessionRulePlacement algorithms, respectively. Under the constraint of the maximum transmission delay in the network, [29] jointly considers the problem of flow forwarding and rule update, and introduces a garbage collection technique to minimize the space occupation of the switches.…”

Section: Joint Rule Caching and Flow Forwarding Algorithms Of Sdnmentioning

confidence: 99%

“…While the authors in [28]- [31] considered rule caching and flow forwarding issues, they mainly assumed that flow forwarding strategy was given, and designed the optimal rule caching strategy in order to minimize caching space occupation [28], [29] or maximize the utilization of caching space [30], [31]. In this article, we investigate the problem of joint rule caching and flow forwarding for multiple user flows in SDN, and formulate the joint optimization problem as an end-to-end delay minimization problem.…”

Section: Joint Rule Caching and Flow Forwarding Algorithms Of Sdnmentioning

confidence: 99%

“…2) While rule caching and flow forwarding schemes have been studied for SDN in previous work independently [9]- [27], it can be demonstrated that the two issues are closely related and the joint design is highly desired. Although the authors in [28]- [31] stressed both the rule caching and flow forwarding issues, they mainly assumed that flow forwarding strategy was given, and designed the optimal rule caching strategy in order to minimize caching space occupation [28], [29] or maximize the utilization of caching space [30], [31], and failed to consider extensively the overall network performance, especially the end-to-end delay of user flows. Unlike previous work, to emphasize the importance of the end-to-end delay caused by the transmission and processing delay of user flows in both data plane and control plane, we take into account flow forwarding requirements, rule caching and resource allocation constraints, and formulate the joint rule caching and flow forwarding problem as an end-to-end delay minimization problem.…”

Section: Introductionmentioning

confidence: 99%

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End-to-End Delay Minimization-Based Joint Rule Caching and Flow Forwarding Algorithm for SDN

et al. 2020

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Software-defined networking (SDN) technology is expected to offer higher flexibility and programmability and enhanced transmission performance by decoupling control plane from data plane and enabling centralized network management. In SDN, switches may cache a certain number of flow forwarding rules, so that user flows can be forwarded accordingly. In this article, stressing the limited caching space of switches and the heterogeneous transmission performance of switches and links, we jointly design rule caching and flow forwarding strategy for multiple user flows in SDN. To emphasize the importance of the end-to-end delay caused by the transmission and processing of user flows in both the data plane and control plane, we formulate the joint optimization problem as an end-to-end delay minimization problem. As the original optimization problem is a non-deterministic polynomial hard (NP-hard) problem, which cannot be solved directly, we propose a heuristic algorithm which successively solves three subproblems, i.e., flow forwarding subproblem, rule caching and candidate path selection subproblem, and resource sharing subproblem. By applying the K-shortest path algorithm, a priority-based rule caching algorithm, and Lagrangian dual method, respectively, the three subproblems are solved and the joint rule caching and flow forwarding strategy is obtained. Simulation experiments are conducted to examine the effectiveness of the proposed algorithm, and the results indicate that our proposed algorithm is capable of improving system performance by about 20% compared with the previous solutions.INDEX TERMS Software-defined networking, end-to-end delay, rule caching, flow forwarding, resource sharing.

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Section: Joint Rule Caching and Flow Forwarding Algorithms Of Sdnmentioning

confidence: 99%