The Experts below are selected from a list of 157056 Experts worldwide ranked by ideXlab platform
Gang Sun - One of the best experts on this subject based on the ideXlab platform.
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low latency and resource efficient Service Function chaining orchestration in network Function virtualization
IEEE Internet of Things Journal, 2020Co-Authors: Gang Sun, Victor Chang, Xi Chen, Athanasios V VasilakosAbstract:Recently, network Function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the Service Function chain (SFC) is a key technology that affects the performance of virtual network Function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this article, we propose an SFC deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS-based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing.
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cost efficient Service Function chain orchestration for low latency applications in nfv networks
IEEE Systems Journal, 2019Co-Authors: Gang Sun, Dan Liao, Gungyang Zhu, Mohsen GuizaniAbstract:With the popularization and development of cloud computing, network Function virtualization and Service Function chain (SFC) provisioning have attracted increasing attention from researchers. Excellent and reliable network Service is important for network development. Moreover, as the number of network users increases, network Service construction costs become very high. Therefore, an efficient algorithm is necessary to provide an SFC with excellent performance and low resource costs. In this paper, we re-examine the problem of optimizing the deployment of an SFC to provide users with excellent and resource-saving network Service. We propose a heuristic, closed-loop feedback (CLF) algorithm to find the shortest path to map an SFC. To solve the problem, we introduce and integrate a restricted Boltzmann machine and cross entropy to improve the performance of CLF. Simulation results demonstrate the excellent performance of CLF. The communication delay is reduced by approximately 20%, the accept ratio improves by approximately 15%, and the algorithm running time decreases by approximately 20%. In addition, the resource utilization ratio increases by approximately 15%, and the resource fragmentation ratio decreases by approximately 50%.
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energy efficient and traffic aware Service Function chaining orchestration in multi domain networks
Future Generation Computer Systems, 2019Co-Authors: Gang Sun, Athanasios V Vasilakos, Mohsen GuizaniAbstract:Abstract Service Function chaining (SFC) provisioning is helpful not only for saving the capital expenditure (CAPEX) and operational expenditure (OPEX) of a network provider but also for reducing energy consumption in the substrate network. However, to the best of our knowledge, there has been little research on the problem of energy consumption for orchestrating online SFC requests in multi-domain networks. In this paper, we first formulate the problem of an energy-efficient online SFC request that is orchestrated across multiple clouds as an integer linear programming (ILP) model to find an optimal solution. Then, we analyze the complexity of this ILP model and prove that the problem is NP-hard. Additionally, we propose a low-complexity heuristic algorithm named energy-efficient online SFC request orchestration across multiple domains (EE-SFCO-MD) for near-optimally solving the mentioned problem. Finally, we conduct simulation experiments to evaluate the performance of our algorithm. Simulation results show that EE-SFCO-MD consumes less energy than existing approaches while the online SFC’s requirements are met and the privacy of each cloud is effectively guaranteed. The low computational complexity of the heuristic approach makes it applicable for quickly responding to online SFC requests.
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low latency orchestration for workflow oriented Service Function chain in edge computing
Future Generation Computer Systems, 2018Co-Authors: Gang Sun, Dan Liao, Victor ChangAbstract:Abstract To realize a cost-efficient, affordable, economical, flexible, elastic and innovative network Service, the concepts of Network Function Virtualization (NFV) and Software-Defined Network (SDN) have emerged in edge computing. In the case of NFV deployment, most research regards the deployment of Service Function Chaining (SFC), which is composed of several series-connected Virtual Network Functions (VNFs). Current NFV deployment approaches concern how to efficiently deploy the chaining Service requests. They do not consider the possible form of the Service requests in edge computing. Furthermore, the study regarding response latency in NFV is limited to the chaining Service requests. Most studies consider the deployment of several VNFs in one SFC onto the same substrate node to reduce the total latency and resource consumptions. In this paper, we first propose a novel workflow-like Service request (WFR), which is completely different from the chaining Service request. Then, a Dynamic Minimum Response Time considering Same Level (DMRT_SL) has been proposed to efficiently map the workflow-like requests in edge computing. We use a randomly generated topology as our underlying network. It can be seen from the data obtained from a large number of simulation experiments that DMRT_SL not only is particularly outstanding in terms of response time delay but that blocking rate and deploy time behavior are also particularly surprising.
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Service Function chain orchestration across multiple domains a full mesh aggregation approach
IEEE Transactions on Network and Service Management, 2018Co-Authors: Gang Sun, Dan Liao, Victor ChangAbstract:Generally, a Service request must specify its required virtual network Functions (VNFs) and their specific order, which is known as the Service Function chain (SFC). When mapping SFCs, network providers face many challenges due to the requirements of maintaining the correct order and satisfying other constraints of VNFs. Furthermore, SFC orchestration becomes a more difficult problem when considered in multi-domain networks, because the confidentiality of the topology information of each domain must be considered. In this paper, we study the problem of SFC orchestration across multiple domains. We first use the full mesh aggregation approach to construct an abstracted network to guide the orchestration process, and then propose two efficient methods for SFC partitioning. Based on the SFC partitioning results, we also propose two heuristic algorithms for deploying the sub-chains in multiple domains. Moreover, when the partitioning results cannot be mapped completely, a feedback mechanism is used to repartition the SFC and improve the success ratio of orchestrating the SFC. Finally, to save bandwidth resources, we further improve our heuristic algorithms by migrating the deployment position of VNFs. The simulation results demonstrate that our proposed algorithm achieves better performance compared to existing solutions.
Deval Bhamare - One of the best experts on this subject based on the ideXlab platform.
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on the construction of optimal embedding problems for delay sensitive Service Function chains
International Conference on Computer Communications and Networks, 2019Co-Authors: Andreas Fischer, Deval Bhamare, Andreas KasslerAbstract:Network Function Virtualization (NFV) with minimum-delay Service Function chains will be a key enabling technology for next generation mobile networks, such as 5G. In this paper, we present a new approach to generate problem instances for the cost optimized delay sensitive Virtualized Network Function (VNF) placement and routing problem, where we know by construction the optimal solution for the given objective Function. Our approach produces problem instances, which can be used to test and benchmark heuristic algorithms against. We then implement an Affinity based simulated annealing (ABSA) heuristic approach for cost optimized delay aware placement of VNFs along with a set of greedy approaches. We evaluate the implemented approaches against the optimal solution by generating several problem instances using our proposed method.
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multi objective scheduling of micro Services for optimal Service Function chains
International Conference on Communications, 2017Co-Authors: Deval Bhamare, Lav Gupta, Mohammed Samaka, Aiman Erbad, Raj Jain, Anthony H ChanAbstract:Lately application Service providers (ASPs) and Internet Service providers (ISPs) are being confronted with the unprecedented challenge of accommodating increasing Service and traffic demands from their geographically distributed users. Many ASPs and ISPs, such as Facebook, Netflix, AT&T and others have adopted micro-Service architecture to tackle this problem. Instead of building a single, monolithic application, the idea is to split the application into a set of smaller, interconnected Services, called micro-Services (or simply Services). Such Services are lightweight and perform distinct tasks independent of each other. Hence, they can be deployed quickly and independently as user demands vary. Nevertheless, scheduling of micro-Services is a complex task and is currently under-researched. In this work, we address the problem of scheduling micro-Services across multiple clouds, including micro-clouds. We consider different user-level SLAs, such as latency and cost, while scheduling such Services. Our aim is to reduce overall turnaround time for the complete end-to-end Service in Service Function chains and reduce the total traffic generated. In this work we present a novel fair weighted affinity-based scheduling heuristic to solve this problem. We also compare the results of proposed solution with standard biased greedy scheduling algorithms presented in the literature and observe significant improvements.
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Optimal virtual network Function placement in multi-cloud Service Function chaining architecture
Computer Communications, 2017Co-Authors: Deval Bhamare, Lav Gupta, Mohammed Samaka, Aiman Erbad, Raj Jain, H. Anthony ChanAbstract:Service Function Chaining (SFC) is the problem of deploying various network Service instances over geographically distributed data centers and providing inter-connectivity among them. The goal is to enable the network traffic to flow smoothly through the underlying network, resulting in an optimal quality of experience to the end-users. Proper chaining of network Functions leads to optimal utilization of distributed resources. This has been a de-facto model in the telecom industry with network Functions deployed over underlying hardware. Though this model has served the telecom industry well so far, it has been adapted mostly to suit the static behavior of network Services and Service demands due to the deployment of the Services directly over physical resources. This results in network ossification with larger delays to the end-users, especially with the data-centric model in which the computational resources are moving closer to end users. A novel networking paradigm, Network Function Virtualization (NFV), meets the user demands dynamically and reduces operational expenses (OpEx) and capital expenditures (CapEx), by implementing network Functions in the software layer known as virtual network Functions (VNFs). VNFs are then interconnected to form a complete end-to-end Service, also known as Service Function chains (SFCs). In this work, we study the problem of deploying Service Function chains over network Function virtualized architecture. Specifically, we study virtual network Function placement problem for the optimal SFC formation across geographically distributed clouds. We set up the problem of minimizing inter-cloud traffic and response time in a multi-cloud scenario as an ILP optimization problem, along with important constraints such as total deployment costs and Service level agreements (SLAs). We consider link delays and computational delays in our model. The link queues are modeled as M/D/1 (single server/Poisson arrival/deterministic Service times) and server queues as M/M/1 (single server/Poisson arrival/exponential Service times) based on the statistical analysis. In addition, we present a novel affinity-based approach (ABA) to solve the problem for larger networks. We provide a performance comparison between the proposed heuristic and simple greedy approach (SGA) used in the state-of-the-art systems. Greedy approach has already been widely studied in the literature for the VM placement problem. Especially we compare our proposed heuristic with a greedy approach using first-fit decreasing (FFD) method. By observing the results, we conclude that the affinity-based approach for placing the Service Functions in the network produces better results compared against the simple greedy (FFD) approach in terms of both, total delays and total resource cost. We observe that with a little compromise (gap of less than 10% of the optimal) in the solution quality (total delays and cost), affinity-based heuristic can solve the larger problem more quickly than ILP.
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colap a predictive framework for Service Function chain placement in a multi cloud environment
IEEE Annual Computing and Communication Workshop and Conference, 2017Co-Authors: Lav Gupta, Mohammed Samaka, Deval Bhamare, Aiman Erbad, Raj Jain, C MetzAbstract:Network Function virtualization (NFV) over multi-cloud promises network Service providers amazing flexibility in Service deployment and optimizing cost. Telecommunications applications are, however, sensitive to performance indicators, especially latency, which tend to get degraded by both the virtualization and the multiple cloud requirement for widely distributed coverage. In this work we propose an efficient framework that uses the novel concept of random cloud selection combined with a support vector regression based predictive model for cost optimized latency aware placement (COLAP) of Service Function chains. Extensive empirical analysis has been carried out with training datasets generated using a queuing-theoretic model. The results show good generalization performance of the predictive algorithm. The proposed framework can place thousands of virtual network Functions in less than a minute and has high acceptance ratio.
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A survey on Service Function chaining
Journal of Network and Computer Applications, 2016Co-Authors: Deval Bhamare, Mohammed Samaka, Raj Jain, Aiman ErbadAbstract:Cloud computing is gaining significant attention and virtualized datacenters are becoming popular as a cost-effective infrastructure. The network Services are transitioning from a host-centric to a data-centric model moving the data and the computational resources closer to the end users. To meet the dynamic user demands, network operators have chosen to use elastic virtual resources to implement network Services over static rigid physical model. With the advent of network Function virtualization (NFV), network Services instances are provisioned across multiple clouds for performance and load balancing purposes. Interconnection of these instances to form a complete end-to-end network Service is complex, time consuming and expensive task. Service Function chaining (SFC) is a mechanism that allows various Service Functions to be connected to each to form a Service enabling carriers to benefit from virtualized software defined infrastructure. SFC is an enabler for NFV, providing a flexible and economical alternative to today's static environment for Cloud Service providers (CSPs), Application Service Providers (ASPs) and Internet Service Providers (ISPs). This paper provides a closer look at the current SFC architecture and a survey of the recent developments in SFC including its relevance with NFV to help determine the future research directions and the standardization efforts of SFC. Finally, the paper discusses open research topics in relevance with the SFC architecture and demonstrates a need for an analytical model for the SFC architecture to achieve the optimal performance.
Xiaojun Cao - One of the best experts on this subject based on the ideXlab platform.
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towards latency optimization in hybrid Service Function chain composition and embedding
International Conference on Computer Communications, 2020Co-Authors: Danyang Zheng, Guangchun Luo, Ling Tian, Chengzong Peng, Xueting Liao, Xiaojun CaoAbstract:In Network Function Virtualization (NFV), to satisfy the Service Functions (SFs) requested by a customer, Service providers will composite a Service Function Chain (SFC) and embed it onto the shared Substrate Network (SN). For many latency-sensitive and computing-intensive applications, the customer forwards data to the cloud/server and the cloud/server sends the results/models back, which may require different SFs to handle the forward and backward traffic. The SFC that requires different SFs in the forward and backward directions is referred to as hybrid SFC (h-SFC). In this paper, we, for the first time, comprehensively study how to optimize the latency in Hybrid SFC composition and Embedding (HSFCE). When each substrate node provides only one unique SF, we prove the NP-hardness of HSFCE and propose the first 2-approximation algorithm to jointly optimize the processes of h-SFC construction and embedding, which is called Eulerian Circuit based Hybrid SFP optimization (EC-HSFP). When a substrate node provides various SFs, we extend EC-HSFP and propose the efficient Betweenness Centrality based Hybrid SFP optimization (BC-HSFP) algorithm. Our extensive simulations and analysis show that EC-HSFP can hold the 2-approximation, while BC-HSFP outperforms the algorithms directly extended from the state-of-art techniques by an average of 20%.
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multicast aware Service Function tree embedding
High Performance Switching and Routing, 2019Co-Authors: Evrim Guler, Ling Tian, Swaroop Devaraju, Guanuchun Luo, Xiaojun CaoAbstract:With the technology of Network Function Virtualization (NFV), a multicast Service (e.g., real-time multimedia streaming or event monitoring) may be accommodated with a Service Function Chain (SFC). The SFC consists of an ordered set of network Functions running on generic physical hardware to provide Services from source node to each destination node of the multicast Service. In this paper, we define the problem of Multicast-aware Service Function Tree Embedding (M-SFTE), which allows the multicast flows to traverse through network Service Functions before reaching destination nodes. The M-SFTE maps user's SFC-based multicast requests onto a shared substrate network while considering the constraints of network Functionality, computing demand of each virtual network Function node, and the bandwidth demand of the request. We propose a novel algorithm, called Minimum Cost Multicast Service Function Tree (MC-MSFT) to jointly optimize the process of constructing SFC-based multicast tree and allocating requested resource to embed the tree onto the physical network. The experimental results show that the MC-MSFT algorithm outperforms the traditional greedy-based algorithms as much as by 35% in terms of the total bandwidth consumption.
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Service Function chaining and embedding with spanning closed walk
High Performance Switching and Routing, 2019Co-Authors: Danyang Zheng, Guangchun Luo, Ling Tian, Chengzong Peng, Xueting Liao, Xiaojun CaoAbstract:Network Function Virtualization (NFV) takes advantages of the emerging technologies in virtualization and automation to offer new ways in design, deployment, and management of networking Services. In NFV, the proprietary hardware-based network Functions are replaced by the software-based modules named as Virtual Network Functions (VNFs) or Service Functions (SFs). A network Service request from the customer can be formed by multiple SFs. To satisfy a network Service request, the Service provider has to chain the SFs in the request into a Service Function Chain (SFC) and embed the constructed SFC onto the shared substrate network. In this paper, we comprehensively study how to composite and embed an SFC onto a shared substrate network with unique Service Function. We formulate this problem with the Integer Linear Programming (ILP) technique. We also propose an efficient heuristic algorithm with 2-approximation boundary, namely, Spanning Closed Walk based SFC Embedding (SCW-SFCE). Our extensive simulations and analysis show that the proposed approach can achieve near-optimal performance in a small network and outperform the Nearest Neighbour (NN) algorithm.
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dependence aware Service Function chain embedding in optical networks
International Conference on Communications, 2019Co-Authors: Danyang Zheng, Evrim Guler, Guangchun Luo, Ling Tian, Chengzong Peng, Xiaojun CaoAbstract:Network Function Virtualization (NFV) technology decouples network Functions from proprietary hardware equipments. As a result, Internet Service Providers (ISPs) implement software-based network Functions on generic highvolume substrate network devices. In NFV, a Service Function Chain (SFC) is defined as an ordered set of abstract network Functions running on specific substrate nodes (e.g., servers). A challenging issue in NFV management and orchestration is how to optimize the Dependence-aware SFC Embedding in substrate Optical networks (D_SFCE_O). In this paper, we propose a novel algorithm, namely, Dependence-aware SFC embedding with Least-Used consecutive subcarriers (D_SFC_LU), which jointly optimizes SFC design, SFC mapping and spectrum allocation in optical networks. To minimize resource consumption, D_SFC_LU takes advantages of the proposed techniques: Impact Factor based Node Selection (IFNS), Chain Node Mapping (CNM) and Chain-Fit (CF) spectrum allocation. Our simulation and analysis demonstrate that D_SFC_LU can efficiently embed a network requests while minimizing the required substrate resource in optical networks.
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Embedding dependence-aware Service Function chains
Journal of Optical Communications and Networking, 2018Co-Authors: Maryam Jalalitabar, Danyang Zheng, Evrim Guler, Guangchun Luo, Ling Tian, Xiaojun CaoAbstract:Network Function virtualization (NFV) provides an effective way to decouple network Functions from the proprietary hardware, allowing the network providers to implement network Functions as virtual machines running on standard servers. In the NFV environment, an NFV Service request is provisioned in the form of a Service Function chain (SFC). The SFC defines the exact sequence of actions or virtual network Functions (VNFs) that the data stream from the Service request is subjected to. These actions or VNFs need to bemapped onto specific physical networks to provide network Services for end users. In this paper,we investigate the problem of dependence-aware Service Function chain (D_SFC) design and mapping. We study how to efficiently map users’ Service requests over the physical network while taking into consideration the computing resource demand, Function dependence of the VNFs, and the bandwidth demand for the Service request. We propose an efficient algorithm, namely, Dependence-Aware SFC Embedding With Group Mapping (D_SFC_GM), which integrates the proposed techniques of dependence sorting, independent grouping, adaptive mapping, and tetragon remapping to jointly design and map users’ Service requests. The proposed D_SFC_GM algorithm takes advantage of VNF’s dependence relationships and the available resources in the physical network to efficiently design the chain and reserve the computing/bandwidth in the physical network. The extensive performance analysis in both IP and physical networks shows that the proposed D_SFC_GM significantly outperforms the traditional approach based on topological sorting and sequential embedding.
Mohsen Guizani - One of the best experts on this subject based on the ideXlab platform.
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cost efficient Service Function chain orchestration for low latency applications in nfv networks
IEEE Systems Journal, 2019Co-Authors: Gang Sun, Dan Liao, Gungyang Zhu, Mohsen GuizaniAbstract:With the popularization and development of cloud computing, network Function virtualization and Service Function chain (SFC) provisioning have attracted increasing attention from researchers. Excellent and reliable network Service is important for network development. Moreover, as the number of network users increases, network Service construction costs become very high. Therefore, an efficient algorithm is necessary to provide an SFC with excellent performance and low resource costs. In this paper, we re-examine the problem of optimizing the deployment of an SFC to provide users with excellent and resource-saving network Service. We propose a heuristic, closed-loop feedback (CLF) algorithm to find the shortest path to map an SFC. To solve the problem, we introduce and integrate a restricted Boltzmann machine and cross entropy to improve the performance of CLF. Simulation results demonstrate the excellent performance of CLF. The communication delay is reduced by approximately 20%, the accept ratio improves by approximately 15%, and the algorithm running time decreases by approximately 20%. In addition, the resource utilization ratio increases by approximately 15%, and the resource fragmentation ratio decreases by approximately 50%.
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energy efficient and traffic aware Service Function chaining orchestration in multi domain networks
Future Generation Computer Systems, 2019Co-Authors: Gang Sun, Athanasios V Vasilakos, Mohsen GuizaniAbstract:Abstract Service Function chaining (SFC) provisioning is helpful not only for saving the capital expenditure (CAPEX) and operational expenditure (OPEX) of a network provider but also for reducing energy consumption in the substrate network. However, to the best of our knowledge, there has been little research on the problem of energy consumption for orchestrating online SFC requests in multi-domain networks. In this paper, we first formulate the problem of an energy-efficient online SFC request that is orchestrated across multiple clouds as an integer linear programming (ILP) model to find an optimal solution. Then, we analyze the complexity of this ILP model and prove that the problem is NP-hard. Additionally, we propose a low-complexity heuristic algorithm named energy-efficient online SFC request orchestration across multiple domains (EE-SFCO-MD) for near-optimally solving the mentioned problem. Finally, we conduct simulation experiments to evaluate the performance of our algorithm. Simulation results show that EE-SFCO-MD consumes less energy than existing approaches while the online SFC’s requirements are met and the privacy of each cloud is effectively guaranteed. The low computational complexity of the heuristic approach makes it applicable for quickly responding to online SFC requests.
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reinforcement learning based qos qoe aware Service Function chaining in software driven 5g slices
arXiv: Networking and Internet Architecture, 2018Co-Authors: Yupeng Zhang, Xi Chen, Ruiming Long, Mohsen GuizaniAbstract:With the ever growing diversity of devices and applications that will be connected to 5G networks, flexible and agile Service orchestration with acknowledged QoE that satisfies end-user's Functional and QoS requirements is necessary. SDN (Software-Defined Networking) and NFV (Network Function Virtualization) are considered key enabling technologies for 5G core networks. In this regard, this paper proposes a reinforcement learning based QoS/QoE-aware Service Function Chaining (SFC) in SDN/NFV-enabled 5G slices. First, it implements a lightweight QoS information collector based on LLDP, which works in a piggyback fashion on the southbound interface of the SDN controller, to enable QoS-awareness. Then, a DQN (Deep Q Network) based agent framework is designed to support SFC in the context of NFV. The agent takes into account the QoE and QoS as key aspects to formulate the reward so that it is expected to maximize QoE while respecting QoS constraints. The experiment results show that this framework exhibits good performance in QoE provisioning and QoS requirements maintenance for SFC in dynamic network environments.
Victor Chang - One of the best experts on this subject based on the ideXlab platform.
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low latency and resource efficient Service Function chaining orchestration in network Function virtualization
IEEE Internet of Things Journal, 2020Co-Authors: Gang Sun, Victor Chang, Xi Chen, Athanasios V VasilakosAbstract:Recently, network Function virtualization (NFV) has been proposed to solve the dilemma faced by traditional networks and to improve network performance through hardware and software decoupling. The deployment of the Service Function chain (SFC) is a key technology that affects the performance of virtual network Function (VNF). The key issue in the deployment of SFCs is proposing effective algorithms to achieve efficient use of resources. In this article, we propose an SFC deployment optimization (SFCDO) algorithm based on a breadth-first search (BFS). The algorithm first uses a BFS-based algorithm to find the shortest path between the source node and the destination node. Then, based on the shortest path, the path with the fewest hops is preferentially chosen to implement the SFC deployment. Finally, we compare the performances with the greedy and simulated annealing (G-SA) algorithm. The experiment results show that the proposed algorithm is optimized in terms of end-to-end delay and bandwidth resource consumption. In addition, we also consider the load rate of the nodes to achieve network load balancing.
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low latency orchestration for workflow oriented Service Function chain in edge computing
Future Generation Computer Systems, 2018Co-Authors: Gang Sun, Dan Liao, Victor ChangAbstract:Abstract To realize a cost-efficient, affordable, economical, flexible, elastic and innovative network Service, the concepts of Network Function Virtualization (NFV) and Software-Defined Network (SDN) have emerged in edge computing. In the case of NFV deployment, most research regards the deployment of Service Function Chaining (SFC), which is composed of several series-connected Virtual Network Functions (VNFs). Current NFV deployment approaches concern how to efficiently deploy the chaining Service requests. They do not consider the possible form of the Service requests in edge computing. Furthermore, the study regarding response latency in NFV is limited to the chaining Service requests. Most studies consider the deployment of several VNFs in one SFC onto the same substrate node to reduce the total latency and resource consumptions. In this paper, we first propose a novel workflow-like Service request (WFR), which is completely different from the chaining Service request. Then, a Dynamic Minimum Response Time considering Same Level (DMRT_SL) has been proposed to efficiently map the workflow-like requests in edge computing. We use a randomly generated topology as our underlying network. It can be seen from the data obtained from a large number of simulation experiments that DMRT_SL not only is particularly outstanding in terms of response time delay but that blocking rate and deploy time behavior are also particularly surprising.
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Service Function chain orchestration across multiple domains a full mesh aggregation approach
IEEE Transactions on Network and Service Management, 2018Co-Authors: Gang Sun, Dan Liao, Victor ChangAbstract:Generally, a Service request must specify its required virtual network Functions (VNFs) and their specific order, which is known as the Service Function chain (SFC). When mapping SFCs, network providers face many challenges due to the requirements of maintaining the correct order and satisfying other constraints of VNFs. Furthermore, SFC orchestration becomes a more difficult problem when considered in multi-domain networks, because the confidentiality of the topology information of each domain must be considered. In this paper, we study the problem of SFC orchestration across multiple domains. We first use the full mesh aggregation approach to construct an abstracted network to guide the orchestration process, and then propose two efficient methods for SFC partitioning. Based on the SFC partitioning results, we also propose two heuristic algorithms for deploying the sub-chains in multiple domains. Moreover, when the partitioning results cannot be mapped completely, a feedback mechanism is used to repartition the SFC and improve the success ratio of orchestrating the SFC. Finally, to save bandwidth resources, we further improve our heuristic algorithms by migrating the deployment position of VNFs. The simulation results demonstrate that our proposed algorithm achieves better performance compared to existing solutions.
