Abstract:Advantages of Software Defined Networking are unquestionable and are widely described in numerous scientific papers, business white papers and press articles. However, to achieve full maturity, crucial impediments to this concept and its shortcomings must be overcame. One of the most important issues regards significant setup latency of a new flow. To address this issue we propose PARD: a hybrid proactive and reactive method to manage flow table entries. Additional advantages of the proposed solution are, amon… Show more
“…Additionally, the occurrence of phenomena may be inevitable in some cases and result in link under-utilization, such as the case with TCP incast stemming from uncontrolled TCP behavior and a many-to-one traffic paradigm [13]. Moreover, due to the high cost of ternary content-addressable memory modules, the number of predefined flow entries should be limited [14].…”
With the rapid growth of different massive applications and parallel flow requests in Data Center Networks (DCNs), today's providers are confronting challenges in flow forwarding decisions. Since Software Defined Networking (SDN) provides fine granular control, it can be intelligently programmed to distinguish between flow requirements. The present article proposes a knapsack model in which the link bandwidth and incoming flows are modeled as a knapsack capacity and items, respectively. Furthermore, each flow consists of two size and value aspects, acquired through flow size extraction and the type of service value assigned by the SDN controller decision. Indeed, the current work splits the incoming flow size range into Type of Service (ToS) decimal value numbers. The lower the flow size category, the higher the value dedicated to the flow. Particle Swarm Optimization (PSO) optimizes the knapsack problem and first forwards the selected-flows by KP-PSO, and the non-selectedflows second. To address the shortcomings of these methods in the event of dense parallel flow detection, the present study puts the link under the threshold of a 70% load by simultaneous requests. Experimental results indicate that the proposed method outperforms Sonum, Hedera, and ECMP in terms of flow completion time, packet loss rate, and goodput regarding flow size requirements.
“…Additionally, the occurrence of phenomena may be inevitable in some cases and result in link under-utilization, such as the case with TCP incast stemming from uncontrolled TCP behavior and a many-to-one traffic paradigm [13]. Moreover, due to the high cost of ternary content-addressable memory modules, the number of predefined flow entries should be limited [14].…”
With the rapid growth of different massive applications and parallel flow requests in Data Center Networks (DCNs), today's providers are confronting challenges in flow forwarding decisions. Since Software Defined Networking (SDN) provides fine granular control, it can be intelligently programmed to distinguish between flow requirements. The present article proposes a knapsack model in which the link bandwidth and incoming flows are modeled as a knapsack capacity and items, respectively. Furthermore, each flow consists of two size and value aspects, acquired through flow size extraction and the type of service value assigned by the SDN controller decision. Indeed, the current work splits the incoming flow size range into Type of Service (ToS) decimal value numbers. The lower the flow size category, the higher the value dedicated to the flow. Particle Swarm Optimization (PSO) optimizes the knapsack problem and first forwards the selected-flows by KP-PSO, and the non-selectedflows second. To address the shortcomings of these methods in the event of dense parallel flow detection, the present study puts the link under the threshold of a 70% load by simultaneous requests. Experimental results indicate that the proposed method outperforms Sonum, Hedera, and ECMP in terms of flow completion time, packet loss rate, and goodput regarding flow size requirements.
“…Proactive approaches, e.g., [18][19][20], help reduce packet-forwarding latency with traffic prediction and estimation. However, it limits the controller's ability to dynamically react to changes in the network traffic [21], and it does not alleviate issues related to new entry establishment latency.…”
In software-defined networking (SDN), the traffic forwarding delay highly depends on the latency associated with updating the forwarding rules in flow tables. With the increase in fine-grained flow control requirements, due to the flexible control capabilities of SDN, more rules are being inserted and removed from flow tables. Moreover, the matching fields of these rules might overlap since multiple control domains might generate different rules for similar flows. This overlap implies dependency relationships among the rules, imposing various restrictions on forwarding entries during updates, e.g., by following update orders or storing entries at specified locations, especially in flow tables implemented using ternary content addressable memory (TCAM); otherwise, mismatching or packet dropping will occur. It usually takes a while to resolve and maintain dependencies during updates, which hinders high forwarding efficiency. To reduce the delay associated with updating dependent rules, in this paper, we propose an updating algorithm for TCAM-based flow tables. We formulate the TCAM maintenance process as an NP-hard problem and analyze the inefficiency of existing moving approaches. To solve the problem, we propose an optimal moving chain for single rule updates and provide theoretical proof for its minimum moving steps. For multiple rules arriving at a switch simultaneously, we designed a dynamic approach to update concurrent entries; it is able to update multiple rules heuristically within a restricted TCAM region. As the update efficiency concerns dependencies among rules, we evaluate our flow table by updating algorithms with different dependency complexities. The results show that our approach achieves about 6% fewer moving steps than existing approaches. The advantage is more pronounced when the flow table is heavily utilized and rules have longer dependency chains.
“…The rapid development of online applications, cloud computing, multimedia applications, and big data analytics demands revolutionary steps for flexible, agile, cost-effective, and specific service provisioning related to individuals [1,2]. The concept of virtualization in the network enhances the functionality of the network, such as network function virtualization (NFV) and software-defined networking (SDN) [3,4]. SDN-which is divided into two parts: the control plane and the data plane-is emerging as a key enabler in the networking field, and it aids in packet transmission between network devices and the IoT.…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, the flow-rules are installed into the flow-table in advance in a proactive approach as a network operation begins. The proactive approach can reduce the overhead in the communication between the controllers and switches [4][5][6]. Some more degradation issues related to the SDN performance are (i) topology changes, (ii) network reconfiguration, and iii) re-routing rules creation.…”
Software-defined networking (SDN) is an evolving technology providing proper segregation between the control part and data-forwarding domain of network devices. The expansion of the Internet of Things (IoTs) and embedded mobile devices increases the volume of traffic at the network backbone and causes processing costs in the control plane. This directly affects the Ternary Content Addressable Memory (TCAM) of the switches because insufficient space makes it more challenging to manage the flow-entries. In this situation, providing services to specific users who newly authenticate after the successful handoff from the previous SDN domain is challenging. This paper proposes a method for implanting the users’ primary domain’s flow-rules in the serving SDN domain. As the TCAM is already suffering from a short space, it is hard to handle the flow-tables of multiple SDN domains in limited TCAM storage. The SDN-based Integration of the Interdomain Flow-rule in the SDN (IIF-SDN) scheme maximizes the proficiency of the switches by effectively storing flow-table and flow-entries. The effectiveness of the proposed scheme is benchmarked with proactive and reactive SDN approaches.
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