Person re-identification (re-ID) remains challenging in a real-world scenario, as it requires a trained network to generalise to totally unseen target data in the presence of variations across domains. Recently, generative adversarial models have been widely adopted to enhance the diversity of training data. These approaches, however, often fail to generalise to other domains, as existing generative person re-identification models have a disconnect between the generative component and the discriminative feature learning stage. To address the on-going challenges regarding model generalisation, we propose an end-to-end domain adaptive attention network to jointly translate images between domains and learn discriminative re-id features in a single framework. To address the domain gap challenge, we introduce an attention module for image translation from source to target domains without affecting the identity of a person. More specifically, attention is directed to the background instead of the entire image of the person, ensuring identifying characteristics of the subject are preserved. The proposed joint learning network results in a significant performance improvement over state-of-the-art methods on several benchmark datasets.

The temporal segmentation of events is an essential task and a precursor for the automatic recognition of human actions in the video. Several attempts have been made to capture frame-level salient aspects through attention but they lack the capacity to effectively map the temporal relationships in between the frames as they only capture a limited span of temporal dependencies. To this end we propose a complete end-to-end supervised learning approach that can better learn relationships between actions over time, thus improving the overall segmentation performance. The proposed hierarchical recurrent attention framework analyses the input video at multiple temporal scales, to form embeddings at frame level and segment level, and perform fine-grained action segmentation. This generates a simple, lightweight, yet extremely effective architecture for segmenting continuous video streams and has multiple application domains. We evaluate our system on multiple challenging public benchmark datasets, including MERL Shopping, 50 salads, and Georgia Tech Egocentric datasets, and achieves state-of-the-art performance. The evaluated datasets encompass numerous video capture settings which are inclusive of static overhead camera views and dynamic, ego-centric head-mounted camera views, demonstrating the direct applicability of the proposed framework in a variety of settings.

A Non-terrestrial Network (NTN) comprising Low Earth Orbit (LEO) satellites can enable connectivity to underserved areas, thus complementing existing telecom networks. The high-speed satellite motion poses several challenges at the physical layer such as large Doppler frequency shifts. In this paper, an analytical framework is developed for statistical characterization of Doppler shift in an NTN where LEO satellites provide communication services to terrestrial users. Using tools from stochastic geometry, the users within a cell are grouped into disjoint clusters to limit the differential Doppler across users. Under some simplifying assumptions, the cumulative distribution function (CDF) and the probability density function are derived for the Doppler shift magnitude at a random user within a cluster. The CDFs are also provided for the minimum and the maximum Doppler shift magnitude within a cluster. Leveraging the analytical results, the interplay between key system parameters such as the cluster size and satellite altitude is examined. Numerical results validate the insights obtained from the analysis.

Convolutional neural networks (CNN) have shown promising results for end-to-end speech recognition, albeit still behind other state-of-the-art methods in performance. In this paper, we study how to bridge this gap and go beyond with a novel CNN-RNN-transducer architecture, which we call ContextNet. ContextNet features a fully convolutional encoder that incorporates global context information into convolution layers by adding squeeze-and-excitation modules. In addition, we propose a simple scaling method that scales the widths of ContextNet that achieves good trade-off between computation and accuracy. We demonstrate that on the widely used LibriSpeech benchmark, ContextNet achieves a word error rate (WER) of 2.1\%/4.6\% without external language model (LM), 1.9\%/4.1\% with LM and 2.9\%/7.0\% with only 10M parameters on the clean/noisy LibriSpeech test sets. This compares to the previous best published system of 2.0\%/4.6\% with LM and 3.9\%/11.3\% with 20M parameters. The superiority of the proposed ContextNet model is also verified on a much larger internal dataset.

Most optimization-based community detection approaches formulate the problem in a single or bi-objective framework. In this paper, we propose two variants of a three-objective formulation using a customized non-dominated sorting genetic algorithm III (NSGA-III) to find community structures in a network. In the first variant, named NSGA-III-KRM, we considered Kernel k means, Ratio cut, and Modularity, as the three objectives, whereas the second variant, named NSGA-III-CCM, considers Community score, Community fitness and Modularity, as three objective functions. Experiments are conducted on four benchmark network datasets. Comparison with state-of-the-art approaches along with decomposition-based multi-objective evolutionary algorithm variants (MOEA/D-KRM and MOEA/D-CCM) indicates that the proposed variants yield comparable or better results. This is particularly significant because the addition of the third objective does not worsen the results of the other two objectives. We also propose a simple method to rank the Pareto solutions so obtained by proposing a new measure, namely the ratio of the hyper-volume and inverted generational distance (IGD). The higher the ratio, the better is the Pareto set. This strategy is particularly useful in the absence of empirical attainment function in the multi-objective framework, where the number of objectives is more than two.

Neural networks have opened up many new opportunities to utilize remotely sensed images in meteorology. Common applications include image classification, e.g., to determine whether an image contains a tropical cyclone, and image translation, e.g., to emulate radar imagery for satellites that only have passive channels. However, there are yet many open questions regarding the use of neural networks in meteorology, such as best practices for evaluation, tuning and interpretation. This article highlights several strategies and practical considerations for neural network development that have not yet received much attention in the meteorological community, such as the concept of effective receptive fields, underutilized meteorological performance measures, and methods for NN interpretation, such as synthetic experiments and layer-wise relevance propagation. We also consider the process of neural network interpretation as a whole, recognizing it as an iterative scientist-driven discovery process, and breaking it down into individual steps that researchers can take. Finally, while most work on neural network interpretation in meteorology has so far focused on networks for image classification tasks, we expand the focus to also include networks for image translation.

In this paper, we analyze the symbol error rate (SER) performance of the simultaneous wireless information and power transfer (SWIPT) enabled three-node differential decode-and-forward (DDF) relay networks, which adopt the power splitting (PS) protocol at the relay. The use of non-coherent differential modulation eliminates the need for sending training symbols to estimate the instantaneous channel state informations (CSIs) at all network nodes, and therefore improves the power efficiency, as compared with the coherent modulation. However, performance analysis results are not yet available for the state-of-the-art detectors such as the approximate maximum-likelihood detector. Existing works rely on Monte-Carlo simulation to show that there exists an optimal PS ratio that minimizes the overall SER. In this work, we propose a near-optimal detector with linear complexity with respect to the modulation size. We derive an accurate approximate SER expression, based on which the optimal PS ratio can be accurately estimated without requiring any Monte-Carlo simulation.

Cognitive radio is a promising technology to improve spectral efficiency. However, the secure performance of a secondary network achieved by using physical layer security techniques is limited by its transmit power and channel fading. In order to tackle this issue, a cognitive unmanned aerial vehicle (UAV) communication network is studied by exploiting the high flexibility of a UAV and the possibility of establishing line-of-sight links. The average secrecy rate of the secondary network is maximized by robustly optimizing the UAV's trajectory and transmit power. Our problem formulation takes into account two practical inaccurate location estimation cases, namely, the worst case and the outage-constrained case. In order to solve those challenging non-convex problems, an iterative algorithm based on $mathcal{S}$-Procedure is proposed for the worst case while an iterative algorithm based on Bernstein-type inequalities is proposed for the outage-constrained case. The proposed algorithms can obtain effective suboptimal solutions of the corresponding problems. Our simulation results demonstrate that the algorithm under the outage-constrained case can achieve a higher average secrecy rate with a low computational complexity compared to that of the algorithm under the worst case. Moreover, the proposed schemes can improve the secure communication performance significantly compared to other benchmark schemes.

The increasing ubiquity of low-cost wireless sensors in smart homes and buildings has enabled users to easily deploy systems to remotely monitor and control their environments. However, this raises privacy concerns for third-party occupants, such as a hotel room guest who may be unaware of deployed clandestine sensors. Previous methods focused on specific modalities such as detecting cameras but do not provide a generalizable and comprehensive method to capture arbitrary sensors which may be "spying" on a user. In this work, we seek to determine whether one can walk in a room and detect any wireless sensor monitoring an individual. As such, we propose SnoopDog, a framework to not only detect wireless sensors that are actively monitoring a user, but also classify and localize each device. SnoopDog works by establishing causality between patterns in observable wireless traffic and a trusted sensor in the same space, e.g., an inertial measurement unit (IMU) that captures a user's movement. Once causality is established, SnoopDog performs packet inspection to inform the user about the monitoring device. Finally, SnoopDog localizes the clandestine device in a 2D plane using a novel trial-based localization technique. We evaluated SnoopDog across several devices and various modalities and were able to detect causality 96.6% percent of the time, classify suspicious devices with 100% accuracy, and localize devices to a sufficiently reduced sub-space.

Making changes to a program to optimize its performance is an unscalable task that relies entirely upon human intuition and experience. In addition, companies operating at large scale are at a stage where no single individual understands the code controlling its systems, and for this reason, making changes to improve performance can become intractably difficult. In this paper, a learning system is introduced that provides AI assistance for finding recommended changes to a program. Specifically, it is shown how the evaluative feedback, delayed-reward performance programming domain can be effectively formulated via the Monte Carlo tree search (MCTS) framework. It is then shown that established methods from computational games for using learning to expedite tree-search computation can be adapted to speed up computing recommended program alterations. Estimates of expected utility from MCTS trees built for previous problems are used to learn a sampling policy that remains effective across new problems, thus demonstrating transferability of optimization knowledge. This formulation is applied to the Apache Spark distributed computing environment, and a preliminary result is observed that the time required to build a search tree for finding recommendations is reduced by up to a factor of 10x.

Retired Soccer Star Briana Scurry describes how the computerized baseline test works and how it is used for athletes who have sustained a concussion.

Few people are at this point in time willing to bet their money on .Net Framework, simply because .Net Core is obviously the future. This creates problems for us developers, since a lot of the tools we have grown used to, simply doesn't exist in .Net Core. One example of such a tool is Microsoft Workflow Foundation. According to what I've read, Microsoft is not willing to port Workflow Foundation to .Net Core either, so as you cross the bridge into ".Net Core land", you'll have to leave workflows behind.

What is Microsoft Workflow Foundation?

To find out how to replace Workflow Foundation, we must first ask ourselves what its primary feature is. As in, what makes MWF valuable for developers, and why have so many chosen to use it over the years?

It’s that time of the year again. A new TV season is upon us. With some shows beginning to air this week, I thought it best to post my “to watch” schedule for the fall. Unlike last year, I…

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By Patricia Cohen and Tiffany Hsu The New York Times Company…

New TV ads that started airing on morning shows throughout the Spokane region are aimed at grocery shoppers, but they're not hawking deals on cabbage or Cap'n Crunch.…

A spiking neuron-based working memory device is provided. The spiking neuron-based working memory device includes an input interface configured to convert input spike signals into respective burst signals having predetermined forms, and output a sequence of the burst signals, the burst signals corresponding to the input spike signals in a burst structure, and two or more memory elements (MEs) configured to sequentially store features respectively corresponding to the outputted sequence of the burst signals, each of the MEs continuously outputting spike signals respectively corresponding to the stored features.

Systems and methods are disclosed that may be implemented for network management system (NMS) configuration management support for network devices using a learning and natural language processing application to capture the usage and behavior of the Command Line Interface (CLI) of a network device with the aid of a CLI knowledge model, which in one example may be ontology-based.

Within a radio communication network infrastructure transmitting data organized into a sequence of symbols to a receiving device over a plurality of radio links, data to be transmitted is encoded according to an error correction coding scheme in order to produce a set of systematic symbols and a set of corresponding redundancy symbols; the systematic symbols and a first subset of the corresponding redundancy symbols are transmitted, over a first radio link among said plurality of radio links, in broadcast mode, and a second subset of the corresponding redundancy symbols, distinct from the first one, is transmitted over a second radio link among said plurality of radio links.

The present invention relates to methods for preparing a degradable polymer network. The methods for preparing a degradable polymer network comprise a) preparing a polymer composition comprising monomers of cyclic carbonates and/or cyclic esters and/or linear carbonates and/or linear esters and/or cyclic ethers and/or linear hydroxycarboxylic acids at a temperature between 20° C. and 200° C.; b) adding a cross-linking reagent comprising at least one double or triple C—C bond and/or a cross-linking radical initiator; c) processing the polymer composition (that contains the crosslinking reagent into a desired shape; d) Crosslinking by irradiating the mixture. Further, the present invention relates to a degradable polymer network. Furthermore, the present invention relates to the use of the degradable polymer network.

This disclosure provides a network security architecture that permits installation of different software security products as virtual machines (VMs). By relying on a standardized data format and communication structure, a general architecture can be created and used to dynamically build and reconfigure interaction between both similar and dissimilar security products. Use of an integration scheme having defined message types and specified query response framework provides for real-time response and easy adaptation for cross-vendor communication. Examples are provided where an intrusion detection system (IDS) can be used to detect network threats based on distributed threat analytics, passing detected threats to other security products (e.g., products with different capabilities from different vendors) to trigger automatic, dynamically configured communication and reaction. A network security provider using this infrastructure can provide hosted or managed boundary security to a diverse set of clients, each on a customized basis.

A virtual machine (VM) migration from a source virtual machine monitor (VMM) to a destination VMM on a computer system. Each of the VMMs includes virtualization software, and one or more VMs are executed in each of the VMMs. The virtualization software allocates hardware resources in a form of virtual resources for the concurrent execution of one or more VMs and the virtualization software. A portion of a memory of the hardware resources includes hardware memory segments. A first portion of the memory segments is assigned to a source logical partition and a second portion is assigned to a destination logical partition. The source VMM operates in the source logical partition and the destination VMM operates in the destination logical partition. The first portion of the memory segments is mapped into a source VMM memory, and the second portion of the memory segments is mapped into a destination VMM memory.

A dispersed storage network memory includes a pool of storage nodes, where the pool of storage nodes stores a multitude of encoded data files. A storage node obtains and analyzes data access response performance data for each of the storage nodes to produce a modified data access response plan that includes identity of an undesired performing storage node and an alternative data access response for the undesired performing storage node. The storage nodes receive corresponding portions of a data access request for at least a portion of one of the multitude of encoded data files. The undesired performing storage node or another storage node processes one of the corresponding portions of the data access request in accordance with the alternative data access response.

A system, method and computer-readable media for managing a compute environment are disclosed. The method includes importing identity information from an identity manager into a module performs workload management and scheduling for a compute environment and, unless a conflict exists, modifying the behavior of the workload management and scheduling module to incorporate the imported identity information such that access to and use of the compute environment occurs according to the imported identity information. The compute environment may be a cluster or a grid wherein multiple compute environments communicate with multiple identity managers.

A system and method for detecting, filtering, prioritizing and reporting shared memory hazards are disclosed. The method includes, for a unit of hardware operating on a block of threads, mapping a plurality of shared memory locations assigned to the unit to a tracking table. The tracking table comprises initialization information for each shared memory location. The method also includes, for an instruction of a program within a barrier region, identifying a potential conflict by identifying a second access to a location in shared memory within a block of threads executed by the hardware unit. First information associated with a first access and second information associated with the second access to the location is determined. Filter criteria is applied to the first and second information to determine whether the instruction causes a reportable hazard. The instruction is reported when it causes the reportable hazard.

Methods and systems for statistically eliding fences in a work stealing algorithm are disclosed. A data structure comprising a head pointer, tail pointer, barrier pointer and an advertising flag allows for dynamic load-balancing across processing resources in computer applications.

Some embodiments provide a method for managing a logical switching element that includes several logical ports. The logical switching element receives and sends data packets through the logical ports. The logical switching element is implemented in a set of managed switching elements that forward data packets in a network. The method provides a set of tables for specifying forwarding behaviors of the logical switching element. The method performs a set of database join operations on the tables to specify in the tables that the logical forwarding element drops a data packet received through a first logical port when the data packet is headed to a second logical port different than the first logical port.

A method and circuit arrangement utilize a low latency variable transfer network between the register files of multiple processing cores in a multi-core processor chip to support fine grained parallelism of virtual threads across multiple hardware threads. The communication of a variable over the variable transfer network may be initiated by a move from a local register in a register file of a source processing core to a variable register that is allocated to a destination hardware thread in a destination processing core, so that the destination hardware thread can then move the variable from the variable register to a local register in the destination processing core.

An array of a plurality of processing elements (PEs) are in a data packet-switched network interconnecting the PEs and memory to enable any of the PEs to access the memory. The network connects the PEs and their local memories to a common controller. The common controller may include a shared load/store (SLS) unit and an array control unit. A shared read may be addressed to an external device via the common controller. The SLS unit can continue activity as if a normal shared read operation has taken place, except that the transactions that have been sent externally may take more cycles to complete than the local shared reads. Hence, a number of transaction-enabled flags may not have been deactivated even though there is no more bus activity. The SLS unit can use this state to indicate to the array control unit that a thread switch may now take place.

A framework for implementing multitenant architecture is provided. The framework comprises a framework services module which is configured to provide framework services that facilitate abstraction of Software-as-a-Service (SaaS) services and crosscutting services for a Greenfield application and a non SaaS based web application. Further the abstraction results in a SaaS based multitenant web application. The framework further comprises a runtime module configured to automatically integrate and consume the framework services and APIs to facilitate monitoring and controlling of features associated with the SaaS based multitenant web application. The framework further comprises a metadata services module configured to provide a plurality of metadata services to facilitate abstraction of storage structure of metadata associated with the framework and act as APIs for managing the metadata. The framework further comprises a role based administration module that facilitates management of the metadata through a tenant administrator and a product administrator.

The invention relates to compressed data transmission in wireless data communication. Disclosed are methods and apparatuses for transporting residue of vehicle position data via a wireless network. A disclosed method for transporting residue of vehicle position data via a wireless network, includes the steps of: receiving data for updating residue encoding schema from a monitoring server; constructing a residue encoding schema based on the data, thereby producing a constructed residue encoding schema; and storing the constructed residue encoding schema such that the constructed residue encoding schema will become the current residue encoding schema; where: the constructed residue encoding schema is constructed such that each residue of the constructed residue encoding schema corresponds to a code; and the constructed residue encoding schema is constructed such that a residue having a relatively high probability of occurrence corresponds to a code of relatively short length.

Described herein is a descriptive framework to facilitate large scale demand responsive transit. In accordance with one aspect of the framework, one or more trip requests from one or more commuter devices are received. A trip request indicates at least one start location and at least one end location. In addition, vehicle information is received from one or more available vehicles. The vehicle information indicates at least one current location of a vehicle. An adaptive route for the vehicle may be planned based on the one or more trip requests and the vehicle information. Update information of the adaptive route may be communicated to the vehicle and the one or more commuter devices.

Vehicle event recorder systems are arranged to be in constant communication with remote servers and administrators via mobile wireless cellular networks. Vehicle event recorders equipped with video cameras capture video and other data records of important events relating to vehicle use. These data are then transmitted over special communications networks having very high coverage space but limited bandwidth. A vehicle may be operated over very large region while maintaining continuous communications connections with a remote fixed server. As such, systems of these inventions may be characterized as including a mobile unit having: a video camera; a microprocessor; memory; an event trigger; and mobile wireless transceivers, and a fixed network portion including: mobile wireless cellular network, a protocol translation gateway, the Internet and an application-specific server.

Methods for the design of microwave filters comprises comprising preferably the steps of inputting a first set of filter requirements, inputting a selection of circuit element types, inputting a selection of lossless circuit response variables, calculating normalized circuit element values based on the input parameters, and generate a first circuit, insert parasitic effects to the normalized circuit element values of the first circuit, and output at least the first circuit including the post-parasitic effect circuit values. Additional optional steps include: requirements to a normalized design space, performing an equivalent circuit transformation, unmapping the circuit to a real design space, performing a survey, and element removal optimization. Computer implement software, systems, and microwave filters designed in accordance with the method are included.

In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges, receiving from a first user a voice message comprising one or more commands, receiving location information associated with the first user, identifying edges and nodes in the social graph based on the location information, where each of the identified edges and nodes corresponds to at least one of the commands of the voice message, and generating new nodes or edges in the social graph based on the identified nodes or identified edges.

A method for configuring an interactive platform for monitoring the performance and the quality of a computer network, the monitoring data being suitable to be displayed on a dynamic page of type webpage in a form of graphic components called “displets”; including providing, on the interactive platform a configuration interface in which are defined, for at least one given user, filtering criteria for displaying displets, the criteria being defined in the form of parameters for configuring the rights of the at least one user.

Systems and methods of a 3D mobile user interface with configurable workspace management are disclosed. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of a three-dimensional, multi-layer user interface of a mobile device in a mobile network. User environment may include one or more layers or levels of applications, services, or accounts that are all easily accessible to and navigable by the user. For example, an indicator can be used to access a workspace in 3D representing a category or grouping of services or applications for the user. The user can customize or create a unique, non-mutually exclusive grouping, aggregation, or category of applications, services, accounts, or items. The grouping of indicators can be used to swiftly and efficiently navigate to a desired application, service, account or item, in a 3D-enabled user environment.

A system receives a first request for data associated with a data stream received over a first network from a remote source and then determines when the requested data will be available based on analyzing the data stream. The system communicates a second request for the requested data over a second network to the remote source when the requested data will not be available from the data stream within a threshold time and receives the requested data from the remote source over at least one from the list including the first network and the second network.

In V2V or other networks in which multiple video cameras can share video data, a network participant ordinarily has the option of selecting a particular video data stream (either generated by local cameras or received from other network participants. To facilitate the process of selecting a video data stream for presentation, the user's vehicle (in a V2V network) receives video data streams generated by other network participants along with identifiers indicating the video data stream actually being presented to the sender. The receiving system identifies the received video data stream by the greatest number of network participants and displays the identified video data stream on the user's in-vehicle video display.

A method begins by a router receiving data for storage and interpreting the data to determine whether the data is to be forwarded or error encoded. The method continues with the router obtaining a routing table when the data is to be error encoded. Next, the method continues with the router selecting a routing option from the plurality of routing options and determining error coding dispersal storage function parameters based on the routing option. Next, the method continues with the router encoding the data based on the error coding dispersal storage function parameters to produce a plurality of sets of encoded data slices. Next, the method continues with the router outputting at least some of the encoded data slices of a set of the plurality of sets of encoded data slices to an entry point of the routing option.

A system, method, and computer-readable medium are disclosed for realizing server management functionalities in the absence of a routable Internet Protocol (IP) network address of a remote access controller (RAC). A first device, which is operatively coupled to a link-local network, generates a Multicast Domain Name System (mDNS) IP multicast query message, which it then sends to a second device on the link-local network. In response, the second device, which comprises a RAC, returns its link-local IP address to the first device.

Systems, methods, and computer-readable and executable instructions are provided for providing a simulated network. Providing a simulated network can include collecting a number of network parameters for a plurality of locations and determining an application frequency of an application for the plurality of locations. Furthermore, providing a simulated network can include providing a simulated network with the number of network parameters to a number of testers of the application, wherein the number of network parameters are provided proportionally to the application frequency.

The system and method described herein may leverage passive and active vulnerability discovery to identify network addresses and open ports associated with connections that one or more passive scanners observed in a network and current connections that one or more active scanners enumerated in the network. The observed and enumerated current connections may be used to model trust relationships and identify exploitable weak points in the network, wherein the exploitable weak points may include hosts that have exploitable services, exploitable client software, and/or exploitable trust relationships. Furthermore, an attack that uses the modeled trust relationships to target the exploitable weak points on a selected host in the network may be simulated to enumerate remote network addresses that could compromise the network and determine an exploitation path that the enumerated remote network addresses could use to compromise the network.

Methods and systems for remotely provisioning applications from the cloud in secure environments with robust license control failover options using a hierarchical server topology. Cloud-based servers provide applications and licenses to an organization's local servers, which in turn serve applications and licenses to end user devices. By synchronizing information including license and application provision information among the local and cloud-based servers, an organization's local servers can continue to serve applications and licenses when one or more of the organization's local servers fail.

A network is described for providing estimates of the current time. The network includes multiple computer systems each configured to provide an estimate of the current time in response to a received request. The computer systems are logically arranged to form a hierarchical structure, wherein the hierarchical structure includes multiple levels ranked with respect to one another. Each of the computer systems is assigned one of multiple levels of trust, and occupies one of the levels of the hierarchical structure dependent upon the assigned level of trust. The level of trust assigned to a given computer system is dependent upon a timekeeping dependability of the given computer system. The assigned level of trust may also be dependent upon a timekeeping security of the given computer system, where the timekeeping security is dependent upon a tamper resistance of the time clock of the given computer system. Methods for delegating a level of trust to a new computer system (i.e., a computer system not part of the network) and for adding a new computer system to the network are also described.

Methods and systems for load balancing read/write requests of a virtualized storage system. In one embodiment, a storage system includes a plurality of physical storage devices and a storage module operable within a communication network to present the plurality of physical storage devices as a virtual storage device to a plurality of network computing elements that are coupled to the communication network. The virtual storage device comprises a plurality of virtual storage volumes, wherein each virtual storage volume is communicatively coupled to the physical storage devices via the storage module. The storage module comprises maps that are used to route read/write requests from the network computing elements to the virtual storage volumes. Each map links read/write requests from at least one network computing element to a respective virtual storage volume within the virtual storage device.

A method begins with a processing module obtaining data to store and determining whether substantially similar data to the data is stored. When the substantially similar data is not stored, the method continues with the processing module generating a first encryption key based on the data, encoding the first encryption key into encoded data slices in accordance with an error coding dispersal storage function, and storing the encoded data slices in a dispersed storage network (DSN) memory. The method continues with the processing module encrypting the data using an encryption key of the substantially similar data in accordance with an encryption function to produce encrypted data, compressing the encrypted data in accordance with a compression function to produce compressed data, storing the compressed data when the substantially similar data is stored.

A source device to provide power through a network cable and a user device is to draw power from the network cable. A database is to store a parameter associated with the user device. The source device is to access the stored parameter based on receipt of information related to the user device and is to compare at least one of a current power drawn and an additional power requested by the user device to a power limit of the user device based on the accessed parameters. The source device is to send a power message to the user device based on the comparison, the power message to relate to an amount of the power the user device is to draw.