Network function virtualization (NFV) has drawn significant attention from both industry and academia as an important shift in telecommunication service provisioning. By decoupling network functions (NFs) from the physical devices on which they run, NFV has the potential to lead to significant reductions in operating expenses (OPEX) and capital expenses (CAPEX) and facilitate the deployment of new services with increased agility and faster time-to-value. The NFV paradigm is still in its infancy and there is a large spectrum of opportunities for the research community to develop new architectures, systems and applications, and to evaluate alternatives and trade-offs in developing technologies for its successful deployment. In this paper, after discussing NFV and its relationship with complementary fields of software defined networking (SDN) and cloud computing, we survey the state-of-the-art in NFV, and identify promising research directions in this area. We also overview key NFV projects, standardization efforts, early implementations, use cases, and commercial products.

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Network Function Virtualization: State-of-the-Art and Research Challenges

Multiple applications request data from multiple storage units over a computer network. The data is divided into segments and each segment is distributed randomly on one of several storage units, independent of the storage units on which other segments of the media data are stored. At least one additional copy of each segment also is distributed randomly over the storage units, such that each segment is stored on at least two storage units. This random distribution of multiple copies of segments of data improves both scalability and reliability. When an application requests a selected segment of data, the request is processed by the storage unit with the shortest queue of requests. Random fluctuations in the load applied by multiple applications on multiple storage units are balanced nearly equally over all of the storage units. This combination of techniques results in a system which can transfer multiple, independent high-bandwidth streams of data in a scalable manner in both directions between multiple applications and multiple storage units.

Computer system and process for transferring multiple high bandwidth streams of data between multiple storage units and multiple applications in a scalable and reliable manner

Multiple applications request data from multiple storage units over a computer network. The data is divided into segments and each segment is distributed randomly on one of several storage units, independent of the storage units on which other segments of the media data are stored. Redundancy information corresponding to each segment also is distributed randomly over the storage units. The redundancy information for a segment may be a copy of the segment, such that each segment is stored on at least two storage units. The redundancy information also may be based on two or more segments. This random distribution of segments of data and corresponding redundancy information improves both scalability and reliability. When a storage unit fails, its load is distributed evenly over to remaining storage units and its lost data may be recovered because of the redundancy information. When an application requests a selected segment of data, the request may be processed by the storage unit with the shortest queue of requests. Random fluctuations in the load applied by multiple applications on multiple storage units are balanced nearly equally over all of the storage units. Small data files also may be stored on storage units that combine small files into larger segments of data using a log structured file system. This combination of techniques results in a system which can transfer both multiple, independent high-bandwidth streams of data and small data files in a scalable manner in both directions between multiple applications and multiple storage units.

Computer system and process for transferring streams of data between multiple storage units and multiple applications in a scalable and reliable manner

From the Publisher:
This work covers all aspects of physical design. The book is a core reference for graduate students and CAD professionals. For students, concept and algorithms are presented in an intuitive manner. For CAD professionals, the material presents a balance of theory and practice. An extensive bibliography is provided which is useful for finding advanced material on a topic. At the end of each chapter, exercises are provided, which range in complexity from simple to research level.

Algorithms for VLSI Physical Design Automation

Network lifetime has become the key characteristic for evaluating sensor networks in an application-specific way. Especially the availability of nodes, the sensor coverage, and the connectivity have been included in discussions on network lifetime. Even quality of service measures can be reduced to lifetime considerations. A great number of algorithms and methods were proposed to increase the lifetime of a sensor network—while their evaluations were always based on a particular definition of network lifetime. Motivated by the great differences in existing definitions of sensor network lifetime that are used in relevant publications, we reviewed the state of the art in lifetime definitions, their differences, advantages, and limitations. This survey was the starting point for our work towards a generic definition of sensor network lifetime for use in analytic evaluations as well as in simulation models—focusing on a formal and concise definition of accumulated network lifetime and total network lifetime. Our definition incorporates the components of existing lifetime definitions, and introduces some additional measures. One new concept is the ability to express the service disruption tolerance of a network. Another new concept is the notion of time-integration: in many cases, it is sufficient if a requirement is fulfilled over a certain period of time, instead of at every point in time. In addition, we combine coverage and connectivity to form a single requirement called connected coverage. We show that connected coverage is different from requiring noncombined coverage and connectivity. Finally, our definition also supports the concept of graceful degradation by providing means of estimating the degree of compliance with the application requirements. We demonstrate the applicability of our definition based on the surveyed lifetime definitions as well as using some example scenarios to explain the various aspects influencing sensor network lifetime.

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On the lifetime of wireless sensor networks

Since the delay of a circuit is determined by the delay of its longest sensitizable paths (such paths are called critical paths), the problem of estimating the delay of a circuit is called critical path problem One important aspect of the critical path problem is to decide whether a path is sensitizable A framework which allows various previously proposed path sensitization criteria to be compared with each other in a unified way is presented An exact path sensitization criterion and a looser path sensitization criterion based on the framework are also proposed >

Path sensitization in critical path problem

The bloom filter is a probabilistic data structure that provides a compact representation of a set of elements. To keep false positive probabilities low, the size of the bloom filter must be dimensioned a priori to be linear in the maximum number of keys inserted, with the linearity constant ranging typically from one to few bytes. A bloom filter is most commonly used as an in memory data structure, hence its size is limited by the availability of RAM space on the machine. As datasets have grown over time to Internet scale, so have the RAM space requirements of bloom filters. If sufficient RAM space is not available, we advocate that flash memory may serve as a suitable medium for storing bloom filters, since it is about one-tenth the cost of RAM per GB while still providing access times orders of magnitude faster than hard disk. We present BLOOMFLASH, a bloom filter designed for flash memory based storage, that provides a new dimension of trade off with bloom filter access times to reduce RAM space usage (and hence system cost). The simple design of a single flat bloom filter on flash suffers from many performance bottlenecks, including in-place bit updates that are inefficient on flash and multiple reads and random writes spread out across many flash pages for a single lookup or insert operation. To mitigate these performance bottlenecks, BLOOMFLASH leverages two key design innovations: (i) buffering bit updates in RAM and applying them in bulk to flash that helps to reduce random writes to flash, and (ii) a hierarchical bloom filter design consisting of component bloom filters, stored one per flash page, that helps to localize reads and writes on flash. We use two real-world data traces taken from representative bloom filter applications to drive and evaluate our design. BLOOMFLASH achieves bloom filter access times in the range of few tens of microseconds, thus allowing up to order of tens of thousands operations per sec.

BloomFlash: Bloom Filter on Flash-Based Storage

Real-time distribution of stored video over wide-area networks (WANs) is a crucial component of many emerging distributed multimedia applications. The heterogeneity in the underlying network environments is an important factor that must be taken into consideration when designing an end-to-end video delivery system. We present a novel approach to the problem of end-to-end video delivery over WANs using proxy servers situated between local-area networks (LANs) and a backbone WAN. A major objective of our approach is to reduce the backbone WAN bandwidth requirement. Toward this end, we develop an effective video delivery technique called video staging via intelligent utilization of the disk bandwidth and storage space available at proxy servers. Using this video staging technique, only part of a video stream is retrieved directly from the central video server across the backbone WAN whereas the rest of the video stream is delivered to users locally from proxy servers attached to the LANs. In this manner, the WAN bandwidth requirement can be significantly reduced, particularly when a large number of users from the same LAN access the video data. We design several video staging methods and evaluate their effectiveness in trading the disk bandwidth of a proxy server for the backbone WAN bandwidth. We also develop two heuristic algorithms to solve the problem of designing a multiple video staging scheme for a proxy server with a given video access profile of a LAN. Our results demonstrate that the proposed proxy-server-based approach provides an effective and scalable solution to the problem of the end-to-end video delivery over WANs.

Video staging: a proxy-server-based approach to end-to-end video delivery over wide-area networks

Persistent key-value stores are widely used as building blocks in today’s IT infrastructure for managing and storing large amounts of data. However, studies of characterizing real-world workloads for key-value stores are limited due to the lack of tracing/analyzing tools and the difficulty of collecting traces in operational environments. In this paper, we first present a detailed characterization of workloads from three typical RocksDB production use cases at Facebook: UDB (a MySQL storage layer for social graph data), ZippyDB (a distributed key-value store), and UP2X (a distributed key-value store for AI/ML services). These characterizations reveal several interesting findings: first, that the distribution of key and value sizes are highly related to the use cases/applications; second, that the accesses to key-value pairs have a good locality and follow certain special patterns; and third, that the collected performance metrics show a strong diurnal pattern in the UDB, but not the other two. We further discover that although the widely used key-value benchmark YCSB provides various workload configurations and key-value pair access distribution models, the YCSBtriggered workloads for underlying storage systems are still not close enough to the workloads we collected due to ignorance of key-space localities. To address this issue, we propose a key-range based modeling and develop a benchmark that can better emulate the workloads of real-world key-value stores. This benchmark can synthetically generate more precise key-value queries that represent the reads and writes of key-value stores to the underlying storage system.

https://www.usenix.org/system/files/fast20-cao_zhichao.pdf

Characterizing, Modeling, and Benchmarking RocksDB Key-Value Workloads at Facebook

A central problem in sensor network security is that sensors are susceptible to physical capture attacks Once a sensor is compromised, the adversary can easily launch clone attacks by replicating the compromised node, distributing the clones throughout the network, and starting a variety of insider attacks Previous works against clone attacks suffer from either a high communication/storage overhead or a poor detection accuracy In this paper, we propose a novel scheme for detecting clone attacks in sensor networks, which computes for each sensor a social fingerprint by extracting the neighborhood characteristics, and verifies the legitimacy of the originator for each message by checking the enclosed fingerprint The fingerprint generation is based on the superimposed s-disjunct code, which incurs a very light communication and computation overhead The fingerprint verification is conducted at both the base station and the neighboring sensors, which ensures a high detection probability The security and performance analysis indicate that our algorithm can identify clone attacks with a high detection probability at the cost of a low computation/communication/storage overhead To our best knowledge, our scheme is the first to provide realtime detection of clone attacks in an effective and efficient way

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David H. C. Du

Papers

Path sensitization in critical path problem

BloomFlash: Bloom Filter on Flash-Based Storage

Video staging: a proxy-server-based approach to end-to-end video delivery over wide-area networks

Characterizing, Modeling, and Benchmarking RocksDB Key-Value Workloads at Facebook

Real-Time Detection of Clone Attacks in Wireless Sensor Networks