Improving Context Interpretation by Using Fuzzy Policies: The Case of Adaptive Video Streaming

Best paper awardInternational audienceAdaptation is an increasingly important requirement for software systems executing in large-scale, heterogeneous, and dynamic environments. A central aspect of the adaptation methodology is management of contextual information needed to support the adaptation process. A major design challenge of managing contextual data lies in the fact that the information is partial, uncertain, and inherently suitable for diverging interpretations. While existing adaptation solutions focus on techniques, methods, and tools, the challenge of managing and interpreting ambiguous contextual information remains largely unresolved. In this paper we present a new adaptation approach that aims to overcome these issues by applying fuzzy set theory and approximate reasoning. We have defined a knowledge management scheme that allows the interpretation of imprecise information and effectively integrated it into the adaptation feedback control loop. To test and evaluate our solution, we implemented it in an adaptation engine to perform rate control for media streaming applications. We show the benefits of our approach in terms of flexibility and performance when compared to more traditional methods, such as TCP-friendly rate control

Exploring resource/performance trade-offs for streaming applications on embedded multiprocessors

Embedded system design is challenged by the gap between the ever-increasing customer demands and the limited resource budgets. The tough competition demands ever-shortening time-to-market and product lifecycles. To solve or, at least to alleviate, the aforementioned issues, designers and manufacturers need model-based quantitative analysis techniques for early design-space exploration to study trade-offs of different implementation candidates. Moreover, modern embedded applications, especially the streaming applications addressed in this thesis, face more and more dynamic input contents, and the platforms that they are running on are more flexible and allow runtime configuration. Quantitative analysis techniques for embedded system design have to be able to handle such dynamic adaptable systems. This thesis has the following contributions: - A resource-aware extension to the Synchronous Dataflow (SDF) model of computation. - Trade-off analysis techniques, both in the time-domain and in the iterationdomain (i.e., on an SDF iteration basis), with support for resource sharing. - Bottleneck-driven design-space exploration techniques for resource-aware SDF. - A game-theoretic approach to controller synthesis, guaranteeing performance under dynamic input. As a first contribution, we propose a new model, as an extension of static synchronous dataflow graphs (SDF) that allows the explicit modeling of resources with consistency checking. The model is called resource-aware SDF (RASDF). The extension enables us to investigate resource sharing and to explore different scheduling options (ways to allocate the resources to the different tasks) using state-space exploration techniques. Consistent SDF and RASDF graphs have the property that an execution occurs in so-called iterations. An iteration typically corresponds to the processing of a meaningful piece of data, and it returns the graph to its initial state. On multiprocessor platforms, iterations may be executed in a pipelined fashion, which makes performance analysis challenging. As the second contribution, this thesis develops trade-off analysis techniques for RASDF, both in the time-domain and in the iteration-domain (i.e., on an SDF iteration basis), to dimension resources on platforms. The time-domain analysis allows interleaving of different iterations, but the size of the explored state space grows quickly. The iteration-based technique trades the potential of interleaving of iterations for a compact size of the iteration state space. An efficient bottleneck-driven designspace exploration technique for streaming applications, the third main contribution in this thesis, is derived from analysis of the critical cycle of the state space, to reveal bottleneck resources that are limiting the throughput. All techniques are based on state-based exploration. They enable system designers to tailor their platform to the required applications, based on their own specific performance requirements. Pruning techniques for efficient exploration of the state space have been developed. Pareto dominance in terms of performance and resource usage is used for exact pruning, and approximation techniques are used for heuristic pruning. Finally, the thesis investigates dynamic scheduling techniques to respond to dynamic changes in input streams. The fourth contribution in this thesis is a game-theoretic approach to tackle controller synthesis to select the appropriate schedules in response to dynamic inputs from the environment. The approach transforms the explored iteration state space of a scenario- and resource-aware SDF (SARA SDF) graph to a bipartite game graph, and maps the controller synthesis problem to the problem of finding a winning positional strategy in a classical mean payoff game. A winning strategy of the game can be used to synthesize the controller of schedules for the system that is guaranteed to satisfy the throughput requirement given by the designer

Stochastic Dynamic Programming and Stochastic Fluid-Flow Models in the Design and Analysis of Web-Server Farms

A Web-server farm is a specialized facility designed specifically for housing Web servers catering to one or more Internet facing Web sites. In this dissertation, stochastic dynamic programming technique is used to obtain the optimal admission control policy with different classes of customers, and stochastic uid- ow models are used to compute the performance measures in the network. The two types of network traffic considered in this research are streaming (guaranteed bandwidth per connection) and elastic (shares available bandwidth equally among connections). We first obtain the optimal admission control policy using stochastic dynamic programming, in which, based on the number of requests of each type being served, a decision is made whether to allow or deny service to an incoming request. In this subproblem, we consider a xed bandwidth capacity server, which allocates the requested bandwidth to the streaming requests and divides all of the remaining bandwidth equally among all of the elastic requests. The performance metric of interest in this case will be the blocking probability of streaming traffic, which will be computed in order to be able to provide Quality of Service (QoS) guarantees. Next, we obtain bounds on the expected waiting time in the system for elastic requests that enter the system. This will be done at the server level in such a way that the total available bandwidth for the requests is constant. Trace data will be converted to an ON-OFF source and fluid- flow models will be used for this analysis. The results are compared with both the mean waiting time obtained by simulating real data, and the expected waiting time obtained using traditional queueing models. Finally, we consider the network of servers and routers within the Web farm where data from servers flows and merges before getting transmitted to the requesting users via the Internet. We compute the waiting time of the elastic requests at intermediate and edge nodes by obtaining the distribution of the out ow of the upstream node. This out ow distribution is obtained by using a methodology based on minimizing the deviations from the constituent in flows. This analysis also helps us to compute waiting times at different bandwidth capacities, and hence obtain a suitable bandwidth to promise or satisfy the QoS guarantees. This research helps in obtaining performance measures for different traffic classes at a Web-server farm so as to be able to promise or provide QoS guarantees; while at the same time helping in utilizing the resources of the server farms efficiently, thereby reducing the operational costs and increasing energy savings

Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications

Communication systems to date primarily aim at reliably communicating bit sequences. Such an approach provides efficient engineering designs that are agnostic to the meanings of the messages or to the goal that the message exchange aims to achieve. Next generation systems, however, can be potentially enriched by folding message semantics and goals of communication into their design. Further, these systems can be made cognizant of the context in which communication exchange takes place, providing avenues for novel design insights. This tutorial summarizes the efforts to date, starting from its early adaptations, semantic-aware and task-oriented communications, covering the foundations, algorithms and potential implementations. The focus is on approaches that utilize information theory to provide the foundations, as well as the significant role of learning in semantics and task-aware communications.Comment: 28 pages, 14 figure

5GAuRA. D3.3: RAN Analytics Mechanisms and Performance Benchmarking of Video, Time Critical, and Social Applications

5GAuRA deliverable D3.3.This is the final deliverable of Work Package 3 (WP3) of the 5GAuRA project, providing a report on the project’s developments on the topics of Radio Access Network (RAN) analytics and application performance benchmarking. The focus of this deliverable is to extend and deepen the methods and results provided in the 5GAuRA deliverable D3.2 in the context of specific use scenarios of video, time critical, and social applications. In this respect, four major topics of WP3 of 5GAuRA – namely edge-cloud enhanced RAN architecture, machine learning assisted Random Access Channel (RACH) approach, Multi-access Edge Computing (MEC) content caching, and active queue management – are put forward. Specifically, this document provides a detailed discussion on the service level agreement between tenant and service provider in the context of network slicing in Fifth Generation (5G) communication networks. Network slicing is considered as a key enabler to 5G communication system. Legacy telecommunication networks have been providing various services to all kinds of customers through a single network infrastructure. In contrast, by deploying network slicing, operators are now able to partition one network into individual slices, each with its own configuration and Quality of Service (QoS) requirements. There are many applications across industry that open new business opportunities with new business models. Every application instance requires an independent slice with its own network functions and features, whereby every single slice needs an individual Service Level Agreement (SLA). In D3.3, we propose a comprehensive end-to-end structure of SLA between the tenant and the service provider of sliced 5G network, which balances the interests of both sides. The proposed SLA defines reliability, availability, and performance of delivered telecommunication services in order to ensure that right information is delivered to the right destination at right time, safely and securely. We also discuss the metrics of slicebased network SLA such as throughput, penalty, cost, revenue, profit, and QoS related metrics, which are, in the view of 5GAuRA, critical features of the agreement.Peer ReviewedPostprint (published version

Beyond Transmitting Bits: Context, Semantics, and Task-Oriented Communications

Communication systems to date primarily aim at reliably communicating bit sequences. Such an approach provides efficient engineering designs that are agnostic to the meanings of the messages or to the goal that the message exchange aims to achieve. Next generation systems, however, can be potentially enriched by folding message semantics and goals of communication into their design. Further, these systems can be made cognizant of the context in which communication exchange takes place, thereby providing avenues for novel design insights. This tutorial summarizes the efforts to date, starting from its early adaptations, semantic-aware and task-oriented communications, covering the foundations, algorithms and potential implementations. The focus is on approaches that utilize information theory to provide the foundations, as well as the significant role of learning in semantics and task-aware communications

Tutorial: Stream processing optimizations

This tutorial starts with a survey of optimizations for streaming applications. The survey is organized as a catalog that introduces uniform terminology and a common categorization of optimizations across disciplines, such as data management, programming languages, and operating systems. After this survey, the tutorial continues with a deep-dive into the fission optimization, which automatically transforms streaming applications for data-parallelism. Fis-sion helps an application improve its throughput by taking advantage of multiple cores in a machine, or, in the case of a distributed streaming engine, multiple machines in a cluster. While the survey of optimizations covers a wide range of work from the literature, the in-depth discussion of ission relies more heavily on the presenters' own research and experience in the area. The tutorial concludes with a discussion of open research challenges in the field of stream processing optimizations. Copyright © 2013 ACM

Mobile Oriented Future Internet (MOFI)

This Special Issue consists of seven papers that discuss how to enhance mobility management and its associated performance in the mobile-oriented future Internet (MOFI) environment. The first two papers deal with the architectural design and experimentation of mobility management schemes, in which new schemes are proposed and real-world testbed experimentations are performed. The subsequent three papers focus on the use of software-defined networks (SDN) for effective service provisioning in the MOFI environment, together with real-world practices and testbed experimentations. The remaining two papers discuss the network engineering issues in newly emerging mobile networks, such as flying ad-hoc networks (FANET) and connected vehicular networks