Joint Energy Efficient and QoS-Aware Path Allocation and VNF Placement for Service Function Chaining

Tajiki, Mohammad Mahdi; Salsano, Stefano; Chiaraviglio, Luca; Shojafar, Mohammad; Akbari, Behzad

doi:10.1109/tnsm.2018.2873225

Cited by 167 publications

(102 citation statements)

References 43 publications

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“…It takes into consideration the propagation delay of physical links, the processing Binary variable such that y c k,l,i,j,u,v = 1 iff physical link (k, l) ∈ E belongs to the path between nodes i and j to which u, v ∈ U c are mapped delay of VSNFs and the queuing delay through network devices. Note that the minimum bandwidth requirement is verified against the bandwidth resource Constraint (10).…”

Section: B Constraintsmentioning

confidence: 99%

Dynamic and Application-Aware Provisioning of Chained Virtual Security Network Functions

Doriguzzi-Corin

Scott-Hayward

Siracusa

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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A promising area of application for Network Function Virtualization is in network security, where chains of Virtual Security Network Functions (VSNFs), i.e., security-specific virtual functions such as firewalls or Intrusion Prevention Systems, can be dynamically created and configured to inspect, filter or monitor the network traffic. However, the traffic handled by VSNFs could be sensitive to specific network requirements, such as minimum bandwidth or maximum end-to-end latency. Therefore, the decision on which VSNFs should apply for a given application, where to place them and how to connect them, should take such requirements into consideration. Otherwise, security services could affect the quality of service experienced by customers.In this paper we propose PESS (Progressive Embedding of Security Services), a solution to efficiently deploy chains of virtualised security functions based on the security requirements of individual applications and operators' policies, while optimizing resource utilization. We provide the PESS mathematical model and heuristic solution.Simulation results show that, compared to state-of-the-art application-agnostic VSNF provisioning models, PESS reduces computational resource utilization by up to 50%, in different network scenarios. This result ultimately leads to a higher number of provisioned security services and to up to a 40% reduction in end-to-end latency of application traffic.

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Section: B Constraintsmentioning

confidence: 99%

Dynamic and Application-Aware Provisioning of Chained Virtual Security Network Functions

Doriguzzi-Corin

Scott-Hayward

Siracusa

et al. 2020

IEEE Trans. Netw. Serv. Manage.

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“…Focusing on Fog computing appliances in SDNs/NFVs, there are limited works that target the routing in fogsupported SDNs/NFVs, such as [34,35,36,37]. In particular, the authors in [34] address Fog computing over SDNs structures that preserve safety and non-safety services and are validated across two use cases: Data streaming and lanechange assistance services.…”

Section: Energy-aware Fog-supported Solutions In Sdns/nfvsmentioning

confidence: 99%

Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN

et al. 2019

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Middleboxes have become a vital part of modern networks by providing services such as load balancing, optimization of network traffic, and content filtering. A sequence of middleboxes comprising a logical service is called a Service Function Chain (SFC). In this context, the main issues are to maintain an acceptable level of network path survivability and a fair allocation of the resource between different demands in the event of faults or failures. In this paper, we focus on the problems of traffic engineering, failure recovery, fault prevention, and SFC with reliability and energy consumption constraints in Software Defined Networks (SDN). These types of deployments use Fog computing as an emerging paradigm to manage the distributed small-size traffic flows passing through the SDN-enabled switches (possibly Fog Nodes). The main aim of this integration is to support service delivery in real-time, failure recovery, and fault-awareness in an SFC context. Firstly, we present an architecture for Failure Recovery and Fault Prevention called FRFP; this is a multi-tier structure in which the real-time traffic flows pass through SDN-enabled switches to jointly decrease the network side-effects of flow rerouting and energy consumption of the Fog Nodes. We then mathematically formulate an optimization problem called the Optimal Fog-Supported Energy-Aware SFC rerouting algorithm (OFES) and propose a near-optimal heuristic called Heuristic OFES (HFES) to solve the corresponding problem in polynomial time. In this way, the energy consumption and the reliability of the selected paths are optimized, while the Quality of Service (QoS) constraints are met and the network congestion is minimized. In a reliability context, the focus of this work is on fault prevention; however, since we use a reallocation technique, the proposed scheme can be used as a failure recovery scheme. We compare the performance of HFES and OFES in terms of power consumption, average path length, fault probability, network side-effects, link utilization, and Fog Node utilization. Additionally, we analyze the computational complexity of HFES. We use a real-world network topology to evaluate our algorithm. The simulation results show that the heuristic algorithm is applicable to large-scale networks.

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“…We categorized the existing solution into two parts, in which, at first, we address the SFC algorithms, [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and then in the second part, we describe the solutions and handle the failures and faults in SDNs/NFVs. We categorized the existing solution into two parts, in which, at first, we address the SFC algorithms, [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and then in the second part, we describe the solutions and handle the failures and faults in SDNs/NFVs.…”

Section: Related Workmentioning

confidence: 99%

“…In the following, we briefly discuss the main literature on NFVs/SDNs and service function changing related to our work. We categorized the existing solution into two parts, in which, at first, we address the SFC algorithms, [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] and then in the second part, we describe the solutions and handle the failures and faults in SDNs/NFVs. [24][25][26][27][28][29][30][31][32][33][34][35]…”

Section: Related Workmentioning

confidence: 99%

Software defined service function chaining with failure consideration for fog computing

Tajiki

Shojafar

Akbari

et al. 2018

Concurrency and Computation

Self Cite

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Middleboxes have become a vital part of modern networks by providing services such as load balancing, optimization of network traffic, and content filtering. A sequence of middleboxes comprising a logical service is called a Service Function Chain (SFC). In this context, the main issues are to maintain an acceptable level of network path survivability and a fair allocation of the resource between different demands in the event of faults or failures. In this paper, we focus on the problems of traffic engineering, failure recovery, fault prevention, and SFC with reliability and energy consumption constraints in Software Defined Networks (SDN). These types of deployments use Fog computing as an emerging paradigm to manage the distributed small-size traffic flows passing through the SDN-enabled switches (possibly Fog Nodes). The main aim of this integration is to support service delivery in real-time failure recovery in an SFC context. First, we present an architecture for Failure Recovery called FRFP; this is a multi-tier structure in which the real-time traffic flows pass through SDN-enabled switches to jointly decrease the network side-effects of flow rerouting and energy consumption of the Fog Nodes. We then mathematically formulate an optimization problem called the Optimal Fast Failure Recovery algorithm (OFFR) and propose a near-optimal heuristic called Heuristic HFFR to solve the corresponding problem in polynomial time. In this way, the reliability of the selected paths are optimized, while the network congestion is minimized. KEYWORDS failure recovery, fog computing (FC), network function virtualization (NFV), resource reallocation, service function chaining (SFC), software defined network (SDN) 1 INTRODUCTION Network Function Virtualization (NFV) paradigm decouples network functions (NFs) from dedicated hardware equipment and provides more flexibility to the owner of an IT infrastructure. NFV consists in a set of different services running on generic hardware (eg, IDS, proxy, deep packet inspection, and firewall) that are chained using the so called Service Function Chaining (SFC) concept. This concept can be applied to industrial environments; in particular, NFV is used in industrial network design in order to reduce exposure to risks, reduce CAPEX/OPEX costs, and minimize future performance issues by basing the infrastructure upon commodity servers and switches. 1 NFV and SFCs offer a great flexibility in the chaining and placement of NFs. The European Telecommunications Standards Institute (ETSI) is driving the standardization of NFV. Software Defined Networking (SDN) complements NFV and is concerned with the decoupling of control plane functionality from packet forwarding devices, allowing a controller to flexibly configure the networking operations in the infrastructure. NFV and SDN require attention to avoid cascading threats as well ascontroller protections, especially for the software applications across the SDN switches that interoperate with the server virtualization and virtual machines (VMs). 2...

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Joint Energy Efficient and QoS-Aware Path Allocation and VNF Placement for Service Function Chaining

Cited by 167 publications

References 43 publications

Dynamic and Application-Aware Provisioning of Chained Virtual Security Network Functions

Dynamic and Application-Aware Provisioning of Chained Virtual Security Network Functions

Joint failure recovery, fault prevention, and energy-efficient resource management for real-time SFC in fog-supported SDN

Software defined service function chaining with failure consideration for fog computing

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