Cornet

In the context of team Cornet’s seminars, Mandar Datar (LIA) will present his research work on Fisher market model-based resource allocation for 5G network slicing, on June 6, 2022, at 11:35 in the meeting room. Abstract: Network slicing is one of the potential technologies to support a higher degree of heterogeneity and flexibility required by next-generation services in 5G networks. In a 5G network, slicing is a specific form of virtualization that allows multiple logical networks (e.g., Mobile Virtual Network Operators (MVNOs)) to run on top of shared physical infrastructure. In the multi-resource allocation scheme, a set of heterogeneous resources (e.g., radio resource, CPU, memory, bandwidth) is shared among Slice tenants or MVNOs, and a portion of them is allocated to each MVNO to support dedicated service to their customers. We consider a scenario where service providers or slice tenants need heterogeneous resources at geographically distributed locations to support the service for their end-users. We propose a resource sharing scheme based on the Fisher market model and the Trading post mechanism. In the proposed scheme, each slice owns the budget representing its infrastructure share or purchasing power in the market. The slices acquire different resources by spending their budgets to Plus d'infos

In the context of team Cornet’s seminars, Naresh Modina (LIA) will present his research work on Multi Resource Allocation (MRA) for network slices with Multi-Level Fairness, on May 5, 2022, at 11:35 in the meeting room. Abstract: Network slicing is becoming the platform of choice for several applications and services. Nowadays most applications are virtualized to gain flexibility and portability. With network slicing, operators can create multiple network slices or tenants, which can be used for certain applications with specific requirements. Behind the network slicing, a slice expresses the need to access a precise service type, under a fully qualified set of computing and network requirements. Resource allocation decision encompasses a combination of different resource types (e.g., radio resource, CPU, memory, bandwidth). In this paper, we explore a differential pricing scheme that maximizes social welfare among slices as well as among end-users. To do so, we propose a pricing mechanism that makes fairness at multiple levels: fairness among slices and fairness among slice locations supported by each slice. Therefore, the proposed scheme is beneficial for both the slices and the end-users independent of their location. Additionally, we study the case where slices can manipulate their preferences to improve their utility. Plus d'infos

In the context of team Cornet’s seminars, Jannis Kurtz (University of Amsterdam) will present his research work on April 29, 2022, at 11:35 in the room S5.

In the context of team Cornet’s seminars, Lucas Potin (LIA) will present his research work on Anomaly Detection on Attributed Networks with GCN and autoencoder, on April 15, 2022, at 11:35 in the meeting room.

In the context of team Cornet’s seminars, Francesco De Pellegrini (LIA) will present his research work on Coflow Fair Scheduling via Dynamic Progress, on April 1, 2022, at 11:35 in the meeting room. Abstract : The average coflow completion time (CCT) is the standard performance metric in coflow scheduling. However, standard CCT minimization may introduce unfairness between the data transfer phase of different computing jobs. Static progress guarantees have been introduced in the literature to mitigate this fairness issue, but the trade-off between fairness and efficiency of data transfer seems hard to control. In this paper we introduce a new fairness framework for coflow scheduling based on the concept of slowdown to measure the performance degradation experienced by a coflow compared to isolation. This framework provides more flexible means to control the progress of coflows while minimizing the average CCT. We design an algorithmic solution chosen in the class of the sigma-order schedulers to solve the fair coflow scheduling problem in polynomial time. The algorithm is proved to be a 4-approximation w.r.t. an optimal scheduler. Our numerical results validate the proposed scheme and demonstrate that this approach can trade off average CCT for per-coflow slowdown.

In the context of team Cornet’s seminars, Rachid Elazouzi (LIA) will present his research work on Deadline-aware scheduling algorithm for coflows in datacenters, on March 3, 2022, at 11:35 in the meeting room.

In the context of team Cornet’s seminars, Julio Cesar (LIA) will present his research work on March 4, 2022, at 11:35 in the meeting room.