Presentacio sobre l'Oficina de Proteccio de Dades Personals de la UAB i la politica Open Science. Va formar part de la conferencia "Les politiques d'Open Data / Open Acces: Implicacions a la recerca" orientada a investigadors i gestors de projectes europeus que va tenir lloc el 20 de setembre de 2018 a la Universitat Autonoma de Barcelona

/pdf/general-data-protection-regulation-2z11cloyp7.pdf

General data protection regulation

As opposed to the decentralized control logic underpinning the devising of the Internet as a complex bundle of box-centric protocols and vertically integrated solutions, the software-defined networking (SDN) paradigm advocates the separation of the control logic from hardware and its centralization in software-based controllers. These key tenets offer new opportunities to introduce innovative applications and incorporate automatic and adaptive control aspects, thereby, easing network management and guaranteeing the user’s quality of experience. Despite the excitement, SDN adoption raises many challenges including the scalability and reliability issues of centralized designs that can be addressed with the physical decentralization of the control plane. However, such physically distributed, but logically centralized systems bring an additional set of challenges. This paper presents a survey on SDN with a special focus on the distributed SDN control. Besides reviewing the SDN concept and studying the SDN architecture as compared to the classical one, the main contribution of this survey is a detailed analysis of state-of-the-art distributed SDN controller platforms which assesses their advantages and drawbacks and classifies them in novel ways (physical and logical classifications) in order to provide useful guidelines for SDN research and deployment initiatives. A thorough discussion on the major challenges of distributed SDN control is also provided along with some insights into emerging and future trends in that area.

Distributed SDN Control: Survey, Taxonomy, and Challenges

Having gained momentum from its promise of centralized control over distributed network architectures at bargain costs, software-defined Networking (SDN) is an ever-increasing topic of research. SDN offers a simplified means to dynamically control multiple simple switches via a single controller program, which contrasts with current network infrastructures where individual network operators manage network devices individually. Already, SDN has realized some extraordinary use cases outside of academia with companies, such as Google, AT&T, Microsoft, and many others. However, SDN still presents many research and operational challenges for government, industry, and campus networks. Because of these challenges, many SDN solutions have developed in an ad hoc manner that are not easily adopted by other organizations. Hence, this paper seeks to identify some of the many challenges where new and current researchers can still contribute to the advancement of SDN and further hasten its broadening adoption by network operators.

Advancing Software-Defined Networks: A Survey

We present the design of Espresso, Google's SDN-based Internet peering edge routing infrastructure. This architecture grew out of a need to exponentially scale the Internet edge cost-effectively and to enable application-aware routing at Internet-peering scale. Espresso utilizes commodity switches and host-based routing/packet processing to implement a novel fine-grained traffic engineering capability. Overall, Espresso provides Google a scalable peering edge that is programmable, reliable, and integrated with global traffic systems. Espresso also greatly accelerated deployment of new networking features at our peering edge. Espresso has been in production for two years and serves over 22% of Google's total traffic to the Internet.

https://dl.acm.org/doi/pdf/10.1145/3098822.3098854

Taking the Edge off with Espresso: Scale, Reliability and Programmability for Global Internet Peering

Large content providers build points of presence around the world, each connected to tens or hundreds of networks. Ideally, this connectivity lets providers better serve users, but providers cannot obtain enough capacity on some preferred peering paths to handle peak traffic demands. These capacity constraints, coupled with volatile traffic and performance and the limitations of the 20 year old BGP protocol, make it difficult to best use this connectivity.We present Edge Fabric, an SDN-based system we built and deployed to tackle these challenges for Facebook, which serves over two billion users from dozens of points of presence on six continents. We provide the first public details on the connectivity of a provider of this scale, including opportunities and challenges. We describe how Edge Fabric operates in near real-time to avoid congesting links at the edge of Facebook's network. Our evaluation on production traffic worldwide demonstrates that Edge Fabric efficiently uses interconnections without congesting them and degrading performance. We also present real-time performance measurements of available routes and investigate incorporating them into routing decisions. We relate challenges, solutions, and lessons from four years of operating and evolving Edge Fabric.

https://dl.acm.org/doi/pdf/10.1145/3098822.3098853

Engineering Egress with Edge Fabric: Steering Oceans of Content to the World

The demands on mobile networks are constantly evolving, but designing and integrating new high-speed packet processing remains a challenge due to the complexity of requirements and opacity of protocol specifications. 5G data planes should be implemented in programmable hardware for both speed and flexibility, and extending or replacing these data planes should be painless. In this paper we implement the 5G data plane using two P4 programs: one that acts as a open-source model data plane to simplify the interface with the control plane, and one to run efficiently on hardware switches to minimize latency and maximize bandwidth. The model data plane enables testing changes made to the control plane before integrating with a performant data plane, and vice versa. The hardware data plane implements the fast path for device traffic, and makes use of microservices to implement functions that highspeed switch hardware cannot do. Our data plane implementation is currently in limited deployment on three university campuses where it is enabling new research on mobile networks.

https://dl.acm.org/doi/pdf/10.1145/3482898.3483358

A P4-based 5G User Plane Function

Network devices such as routers and switches forward traffic based on entries in their local forwarding tables. Although these forwarding tables conventionally make decisions based on a packet header field such as a destination address, tagging flows with sets or sequences of attributes and making forwarding decisions based on these attributes can enable richer network policies. For example, devices at the edge of a network could add a tag to each packet that encodes a set of egress locations, a set of host permissions, or a sequence of middleboxes to traverse; simpler devices in the core of the network could then forward packets based on this tag.Unfortunately, naive construction of these tags can create forwarding tables that grow quadratically with the number of elements in the set or sequence---prohibitive for commodity network devices. In this paper, we present PathSets, a compression algorithm that makes such encodings practical. The algorithm encodes sets or sequences (e.g., middlebox service chains, lists of next-hop network devices) in a compact tag that fits in a small packet-header field. Our evaluation shows that PathSets can encode attribute sets and sequences for large networks using tag widths competitive with existing approaches and that the number of forwarding rules grows linearly with the number of attributes encoded.

Concise Encoding of Flow Attributes in SDN Switches

Incident routing is critical for maintaining service level objectives in the cloud: the time-to-diagnosis can increase by 10x due to mis-routings. Properly routing incidents is challenging because of the complexity of today's data center (DC) applications and their dependencies. For instance, an application running on a VM might rely on a functioning host-server, remote-storage service, and virtual and physical network components. It is hard for any one team, rule-based system, or even machine learning solution to fully learn the complexity and solve the incident routing problem. We propose a different approach using per-team Scouts. Each teams' Scout acts as its gate-keeper --- it routes relevant incidents to the team and routes-away unrelated ones. We solve the problem through a collection of these Scouts. Our PhyNet Scout alone --- currently deployed in production --- reduces the time-to-mitigation of 65% of mis-routed incidents in our dataset.

Scouts: Improving the Diagnosis Process Through Domain-customized Incident Routing

—Network operators want to enforce fair bandwidth sharing between users without solely relying on congestion control running on end-user devices. However, in edge networks (e.g., 5G), the number of user devices sharing a bottleneck link far exceeds the number of queues supported by today’s switch hardware; even accurately tracking per-user sending rates may become too resource-intensive. Meanwhile, traditional software- based queuing on CPUs struggles to meet the high throughput and low latency demanded by 5G users. We propose Approximate Hierarchical Allocation of Bandwidth (AHAB), a per-user bandwidth limit enforcer that runs fully in the data plane of commodity switches. AHAB tracks each user’s approximate traffic rate and compares it against a bandwidth limit, which is iteratively updated via a real-time feedback loop to achieve max-min fairness across users. Using a novel sketch data structure, AHAB avoids storing per-user state, and therefore scales to thousands of slices and millions of users. Furthermore, AHAB supports network slicing, where each slice has a guaranteed share of the bandwidth that can be scavenged by other slices when under-utilized. Evaluation shows AHAB can achieve fair bandwidth allocation within 3.1ms, 13x faster than prior data-plane hierarchical schedulers.

Scalable Real-Time Bandwidth Fairness in Switches

Network applications often define policies to manage network traffic based on its attributes (e.g., a service chain, valid next-hops, permission flags). These policies match against packets' attributes in switches before being applied. However, the prior works of identifying attributes all incur a high memory cost in the data plane. This paper presents MEME, a scheme that clusters the attributes in packets to reduce the memory usage. MEME also leverages match-action tables and reconfigurable parsers on modern hardware switches to achieve 87.7% lower memory usage, and applies a graph algorithm to achieve 1-2 orders of magnitude faster compilation time than the prior state of the art [12]. These performance gains pave the way for deployment of a real system desired by the world's largest Internet Exchange Points.

Memory-Efficient Membership Encoding in Switches

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