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

Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks.Comment: Extended version of submitted paper - v7 - July 201

Software defined service function chaining with failure consideration for fog computing

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&nbsp;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.</p

CECT: Computationally Efficient Congestion-avoidance and Traffic Engineering in Software-defined Cloud Data Centers

The proliferation of cloud data center applications and network functionvirtualization (NFV) boosts dynamic and QoS dependent traffic into the datacenters network. Currently, lots of network routing protocols are requirementagnostic, while other QoS-aware protocols are computationally complex andinefficient for small flows. In this paper, a computationally efficientcongestion avoidance scheme, called CECT, for software-defined cloud datacenters is proposed. The proposed algorithm, CECT, not only minimizes networkcongestion but also reallocates the resources based on the flow requirements.To this end, we use a routing architecture to reconfigure the network resourcestriggered by two events: 1) the elapsing of a predefined time interval, or, 2)the occurrence of congestion. Moreover, a forwarding table entries compressiontechnique is used to reduce the computational complexity of CECT. In this way,we mathematically formulate an optimization problem and define a geneticalgorithm to solve the proposed optimization problem. We test the proposedalgorithm on real-world network traffic. Our results show that CECT iscomputationally fast and the solution is feasible in all cases. In order toevaluate our algorithm in term of throughput, CECT is compared with ECMP (wherethe shortest path algorithm is used as the cost function). Simulation resultsconfirm that the throughput obtained by running CECT is improved up to 3xcompared to ECMP while packet loss is decreased up to 2x