Network virtualization allows hosting applications with diverse computation and communication requirements on shared edge infrastructure. Given a set of requests for deploying virtualized applications, the edge provider has to deploy a maximum number of them to the underlying physical network, subject to capacity constraints. This challenge is known as the virtual network embedding (VNE) problem: it models applications as virtual networks, where virtual nodes represent functions and virtual links represent communication between the virtual nodes.All variants of VNE are known to be strongly NP-hard. Because of its centrality to network virtualization, VNE has been extensively studied. We focus on the online variant of VNE, in which deployment requests are not known in advance. This reflects the highly skewed and unpredictable demand intrinsic to the edge. Unfortunately, existing solutions to online VNE do not scale well with the number of requests per second and the physical topology size.We propose a novel approach in which our new online algorithm, Olive, leverages a nearly optimal embedding for an aggregated expected demand. This embedding is computed offline. It serves as a plan that Olive uses as a guide for handling actual individual requests while dynamically compensating for deviations from the plan. We demonstrate that our solution can handle a number of requests per second greater by two orders of magnitude than the best results reported in the literature. Thus, it is particularly suitable for realistic edge environments.

Workload traces play a crucial role in the design and evaluation of storage systems. They are used for evaluating system performance and optimizing aspects such as data access speeds, energy consumption, and load balancing. Most publicly available traces were collected in cloud environments, which limits their ability to represent workloads in user-centric and highly disaggregated settings such as edge systems.In this paper, we present WoW-IO, an open-source object trace generator based on the popular video game ‘World of Warcraft’. WoW-IO uses, as input, logs of in-game avatar information from the game’s servers. We describe the principles and assumptions used in the design of WoW-IO, how the generated traces can be used to evaluate various aspects of an edge storage-system design, and how the trace format can be extended to reflect additional details and complex usage scenarios.

Mobile edge computing offers ultra-low latency, high bandwidth, and high reliability. Thus, it can support a plethora of emerging services that can be placed in close proximity to the user. One of the fundamental problems in this context is maximizing the benefit from the placement of networked services, while meeting bandwidth and latency constraints. In this study, we propose an adaptive and predictive resource allocation strategy for virtual-network function placement comprising services at the mobile edge. Our study focuses on maximizing the service provider's benefit under user mobility, i.e., uncertainty. This problem is NP-hard, and thus we propose a heuristic solution: we exploit local knowledge about the likely movements of users to speculatively allocate service functions. We allow the service functions to be allocated at different edge nodes, as long as latency and bandwidth constraints are met. We evaluate our proposal against a theoretically optimal algorithm as well as against recent previous work, using widely used simulation tools. We demonstrate that under realistic scenarios, an adaptive and proactive strategy coupled with flexible placement can achieve close-to-optimal benefit.

Edge systems promise to bring data and computing closer to the users of time-critical applications. Specifically, edge storage systems are emerging as a new system paradigm, where users can retrieve data from small-scale servers inter-operating at the network’s edge. The analysis, design, and optimization of such systems require a tractable model that will reflect their costs and bottlenecks. Alas, most existing mathematical models for edge systems focus on stateless tasks, network performance, or isolated nodes and are inapplicable for evaluating edge-based storage performance. We analyze the capacity-region model–the most promising model proposed so far for edge storage systems. The model addresses the system’s ability to serve a set of user demands. Our analysis reveals five inherent gaps between this model and reality, demonstrating the significant remaining challenges in modeling storage service at the edge.

Erasure codes in large-scale storage systems allow recovery of data from a failed node. A recently developed class of codes, locally repairable codes (LRCs), offers tradeoffs between storage overhead and repair cost. LRCs facilitate efficient recovery scenarios by adding parity blocks to the system. However, these additional blocks may eventually increase the number of blocks that must be reconstructed. Existing LRCs differ in their use of the parity blocks, in their locality semantics, and in their parameter space. Thus, existing theoretical models cannot directly compare different LRCs to determine which code offers the best recovery performance, and at what cost. We perform the first systematic comparison of existing LRC approaches. We analyze Xorbas, Azure’s LRCs, and Optimal-LRCs in light of two new metrics: average degraded read cost and normalized repair cost. We show the tradeoff between these costs and the code’s fault tolerance, and that different approaches offer different choices in this tradeoff. Our experimental evaluation on a Ceph cluster further demonstrates the different effects of realistic system bottlenecks on the benefit from each LRC approach. Despite these differences, the normalized repair cost metric can reliably identify the LRC approach that would achieve the lowest repair cost in each setup.

In this paper, a number of topics on the work of IFETS and IFETS-East-Euro in the system of lifelong learning have been stated. IFETS and IFETS-East-Euro are organizational structures that provide one of the key forms of continuous learning - non-formal learning. Statistics that shows high urgency and importance of IFETS-East-Euro has been given. One of the tools for the virtual development of spaces for learning communities is metadata for educational recourses. The approach of placing "Educational Technology & Society" journal with the corresponding metadata into National E-library has been considered.

Problems of building adaptive, partially integrated learning environments are set out in this paper. The paper is concerned with a standard structure of the electronic textbook included into the environment. The kernel of the environment is an intelligent tutoring system, designed with the aid of software tools of MONAP family. A new, additional adaptation method, integrated into software tools has been described.

We are concerned with a partially integrated environment which supports the main types of teaching and learning activities and provides high-level adaptivity to the learner due to the proposed architecture of the environment, including an intelligent tutoring system (ITS).