Achieving effective resilience for QoS-aware application mapping

Zhang, Xian; Chen, Xiuzhong; Phillips, Chris

doi:10.1016/j.comnet.2012.06.015

Cited by 10 publications

(7 citation statements)

References 25 publications

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“…x(i, u, t ) = 1, if virtual node u is assigned to physical node i at time t 0, otherwise (7) The operation cost of embedding a virtual node u to physical node i at time t consists of a possible baseline energy consumption E base (i) for waking up node i if its status S status (i, t − 1) at time t − 1 is asleep and an operation cost for executing virtual node u's tasks c v (u, t) at time t. S status (i, t ) = 1, if physical node i is asleep at the beginning of time t 0, otherwise (8) On the other hand, link operation cost is determined by traffic volume, b v (u, w, t) on the virtual link (u, w) at time t, and the weight, w p (i, j) of the physical links (i, j) that is different for inter or intra DC links. We use network flow f(i, j, u, w, t) to determine whether a physical link (i, j) is used to embed a virtual link u, w. When f(i, j, u, w, t) is equal to 1, virtual link (u, w) passes through the physical link (i, …”

Section: Operation Energy Consumptionmentioning

confidence: 99%

Energy efficient virtual network embedding for green data centers using data center topology and future migration

Guan

Choi

Song

2015

Computer Communications

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Section: Operation Energy Consumptionmentioning

confidence: 99%

Energy efficient virtual network embedding for green data centers using data center topology and future migration

Guan

Choi

Song

2015

Computer Communications

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“…Survivable virtual network embedding against link failures was addressed in many works [31,33,51,76,91,92,101,102,[115][116][117]. In particular, Shamsi et al [101,102] present QoS-aware resource allocation from the application's perspective.…”

Section: Survivable Virtual Network Embeddingmentioning

confidence: 99%

“…The overlay links requiring high quality were mapped to the direct paths on the substrate networks, and alternative paths were provisioned by indirect paths going through intermediate nodes on the substrate network. Zhang et al [116,117] also considered a QoS-based allocation, where disjoint backup paths on the substrate network were provisioned against link failures and the latency for the requested virtual network was minimized. While allocating the backup paths, the proposed model aimed to minimize the number of the substrate nodes that were selected to support backup paths.…”

Section: Survivable Virtual Network Embeddingmentioning

confidence: 99%

Dynamic virtual network restoration with optimal standby virtual router selection

Medhi

2016

NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

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Network virtualization technologies allow service providers to request partitioned, QoS guaranteed and fault-tolerant virtual networks provisioned by the substrate network provider (i.e., physical infrastructure provider). A virtualized networking environment (VNE) has common features such as partition, flexibility, etc., but fault-tolerance requires additional efforts to provide survivability against failures on either virtual networks or the substrate network.Two common survivability paradigms are protection (proactive) and restoration (reactive). In the protection scheme, the substrate network provider (SNP) allocates redundant resources (e.g., nodes, paths, bandwidths, etc) to protect against potential failures in the VNE. In the restoration scheme, the SNP dynamically allocates resources to restore the networks, and it usually occurs after the failure is detected.iii In this dissertation, we design a restoration scheme that can be dynamically implemented in a centralized manner by an SNP to achieve survivability against node failures in the VNE. The proposed restoration scheme is designed to be integrated with a protection scheme, where the SNP allocates spare virtual routers (VRs) as standbys for the virtual networks (VN) and they are ready to serve in the restoration scheme after a node failure has been identified. These standby virtual routers (S-VR) are reserved as a sharedbackup for any single node failure, and during the restoration procedure, one of the S-VR will be selected to replace the failed VR. In this work, we present an optimal S-VR selection approach to simultaneously restore multiple VNs affected by failed VRs, where these VRs may be affected by failures within themselves or at their substrate host (i.e., power outage, hardware failures, maintenance, etc.). Furthermore, the restoration scheme is embedded into a dynamic reconfiguration scheme (DRS), so that the affected VNs can be dynamically restored by a centralized virtual network manager (VNM).We first introduce a dynamic reconfiguration scheme (DRS) against node failures in a VNE, and then present an experimental study by implementing this DRS over a realistic VNE using GpENI testbed. For this experimental study, we ran the DRS to restore one VN with a single-VR failure, and the results showed that with a proper S-VR selection, the performance of the affected VN could be well restored. Next, we proposed an Mixed-Integer Linear Programming (MILP) model with dual-goals to optimally select S-VRs to restore all VNs affected by VR failures while load balancing. We also present a iv heuristic algorithm based on the model. By considering a number of factors, we present numerical studies to show how the optimal selection is affected. The results show that the proposed heuristic's performance is close to the optimization model when there were sufficient standby virtual routers for each virtual network and the substrate nodes have the capability to support multiple standby virtual routers to be in service simultaneously.Finally, we presen...

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“…However, most make the unrealistic assumption that a substrate network is operational at all times [22]. Some studies deal with providing resilience for VN mapping, but the most frequently proposed protection approaches deal with physical link failure [21], [22], [36], [39], [40], [41]. Only a very few proposals [25], [26], [27], [37], [38] consider backup mechanisms in the event of a physical node failure.…”

Section: Introductionmentioning

confidence: 99%

Cost-Efficient Mapping for Fault-Tolerant Virtual Networks

Jarray

Karmouch

2015

IEEE Trans. Comput.

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Network virtualization provides more flexibility in network provisioning as it offers physical infrastructure providers (PIP) the possibility of smoothly rolling out many separate networks on top of an existing infrastructure. A major challenge is the embedding problem of mapping virtual networks (VNs) onto PIP infrastructure. In the literature, a good deal of research has focused on providing heuristic approaches to this NP-hard problem, usually with the assumption that the PIP infrastructure is operational at all times. In virtualization environment, a single physical node/link failure can result in one or more logical link failures as it effects all VNs with a mapping that spans over. Setting up a dedicated backup for each VN embedding that is not shared with others is an inefficient use of resources. To address these concerns, this paper proposes two classes of periodic VN protection against link and node failures: (a) in the physical layer, by using a path or segment p-cycle technique and a column generation optimization model, and (b) in the VN layer, by augmenting the topology with redundant resources and subsequently applying a column generation mapping model. Our simulations show a clear advantage of our approaches over benchmarks in terms of PIP profit, backup cost/rate and resource use.

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Achieving effective resilience for QoS-aware application mapping

Cited by 10 publications

References 25 publications

Energy efficient virtual network embedding for green data centers using data center topology and future migration

Energy efficient virtual network embedding for green data centers using data center topology and future migration

Dynamic virtual network restoration with optimal standby virtual router selection

Cost-Efficient Mapping for Fault-Tolerant Virtual Networks

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