METHOD AND SYSTEM FOR SCHEDULING INTERFERENCE AWARE OPTIMAL UPLINK FOR DEVICE-TO-DEVICE COMMUNICATION UNDERLYING LTE NETWORKS
    11.
    发明申请
    METHOD AND SYSTEM FOR SCHEDULING INTERFERENCE AWARE OPTIMAL UPLINK FOR DEVICE-TO-DEVICE COMMUNICATION UNDERLYING LTE NETWORKS 有权
    用于调度干扰的方法和系统用于基于LTE网络的设备到设备通信的最佳上行链路

    公开(公告)号:US20160135211A1

    公开(公告)日:2016-05-12

    申请号:US14934831

    申请日:2015-11-06

    Abstract: A method and system is provided for scheduling interference aware optimal uplink for device-to-device communication underlying LTE networks. The present application provides a method and system for scheduling interference aware optimal uplink for device-to-device communication underlying LTE networks, comprises registering a plurality of users equipment (UEs) with a single cell with one Evolved Node B (eNB) over the Long Term Evolution (LTE) network; initiating connection by the plurality of users equipment (UEs) with Evolved Node B (eNB); discovering device-to-device (D2D) communication between the actively connected plurality of users equipment (UEs); segregating the actively connected plurality of users equipment (UEs) in device-to-device and cellular users by the Evolved Node B (eNB); and scheduling the two-phase interference aware optimal uplink for device-to-device communication for segregated actively connected device-to-device (D2d) and cellular users by the Evolved Node B (eNB), underlying the Long Term Evolution (LTE) network.

    Abstract translation: 提供了一种方法和系统,用于调度针对LTE网络的设备到设备通信的干扰感知最佳上行链路。 本申请提供了一种用于调度干扰感知最佳上行链路的方法和系统,用于LTE网络下的设备到设备通信,包括在具有一个演进的节点B(eNB)的单个小区上登记多个用户设备(UE) 术语演进(LTE)网络; 发起由具有演进节点B(eNB)的多个用户设备(UE)的连接; 发现主动连接的多个用户设备(UE)之间的设备到设备(D2D)通信; 通过演进节点B(eNB)将设备到设备和蜂窝用户中的主动连接的多个用户设备(UE)分离; 并且由长期演进(LTE)网络下的演进节点B(eNB)调度分离的主动连接的设备到设备(D2d)和蜂窝用户的设备到设备通信的两相干扰感知最佳上行链路 。

    System and method for assisted link prediction mechanism in robotic communications

    公开(公告)号:US10588033B2

    公开(公告)日:2020-03-10

    申请号:US15912327

    申请日:2018-03-05

    Abstract: Robotic applications are important in both indoor and outdoor environments. Establishing reliable end-to-end communication among robots in such environments are inevitable. Many real-time challenges in robotic communications are mainly due to the dynamic movement of robots, battery constraints, absence of Global Position System (GPS), etc. Systems and methods of the present disclosure provide assisted link prediction (ALP) protocol for communication between robots that resolves real-time challenges link ambiguity, prediction accuracy, improving Packet Reception Ratio (PRR) and reducing energy consumption in-terms of lesser retransmissions by computing link matrix between robots and determining status of a Collaborative Robotic based Link Prediction (CRLP) link prediction based on a comparison of link matrix value with a predefined covariance link matrix threshold. Based on determined status, robots either transmit or receive packet, and the predefined covariance link matrix threshold is dynamically updated. If the link to be predicted is unavailable, the system resolves ambiguity thereby enabling communication between robots.

    Optimal deployment of fog computations in IoT environments

    公开(公告)号:US10439890B2

    公开(公告)日:2019-10-08

    申请号:US15653190

    申请日:2017-07-18

    Abstract: This disclosure relates to managing Fog computations between a coordinating node and Fog nodes. In one embodiment, a method for managing Fog computations includes receiving a task data and a request for allocation of at least a subset of a computational task. The task data includes data subset and task constraints associated with at least the subset of the computational task. The Fog nodes capable of performing the computational task are characterized with node characteristics to obtain resource data associated with the Fog nodes. Based on the task data and the resource data, an optimization model is derived to perform the computational task by the Fog nodes. The optimization model includes node constraints including battery degradation constraint, communication path loss constraint, and heterogeneous computational capacities of Fog nodes. Based on the optimization model, at least the subset of the computational task is offloaded to a set of Fog nodes.

    Framework for provisioning network services in cloud computing environment

    公开(公告)号:US10367701B2

    公开(公告)日:2019-07-30

    申请号:US15253115

    申请日:2016-08-31

    Abstract: This disclosure relates generally to provisioning network services in a cloud computing environment, and more particularly to framework for provisioning network services in a heterogeneous cloud computing environment. In one embodiment, the disclosure includes a network as a service (NaaS) layer under a cloud provisioning platform. The NaaS layer can be interfaced with any cloud provisioning platform. The NaaS layer serves the networking needs of the heterogeneous cloud environment. It provides network services like monitoring, notifications, QoS policies, network topology and other services. For example, the cloud provisioning platform defines a virtual network and attaches a plurality of virtual machines to it. All the communications related to creation/deletion/update of virtual networks, virtual subnets, virtual ports, virtual router, virtual interfaces etc., are sent to the NaaS layer. On receiving the communication, the NaaS layer takes necessary steps to provide the network services as per the needs of the request. Apart from provisioning, the NaaS layer periodically monitors the network elements as well.

    Control plane optimization of communication networks
    17.
    发明授权
    Control plane optimization of communication networks 有权
    通信网络的控制平面优化

    公开(公告)号:US09531633B2

    公开(公告)日:2016-12-27

    申请号:US14663184

    申请日:2015-03-19

    Abstract: Optimization of control plane in a software defined network includes obtaining peer information of at least one neighbouring network controller by a network controller and determining a traffic profile variation. The method further includes computing of a self payoff value indicative of one of optimum utilization, underutilization and overutilization of the network controller. The method further includes initiating a non-zero sum game based network control plane optimization operation based on the self payoff value and the traffic profile of the neighbouring network controllers, and may include one of activating additional network controller(s), transferring control of one or more network devices managed by the network controller(s) to a neighbouring greedy network controller, deactivating the network controller, and transferring control of one or more additional network devices managed by the neighbouring network controller(s) to the greedy network controller.

    Abstract translation: 在软件定义的网络中控制平面的优化包括由网络控制器获取至少一个相邻网络控制器的对等体信息并且确定业务轮廓变化。 该方法还包括计算指示网络控制器的最佳利用率,利用不足和过度利用之一的自我收益值。 该方法还包括基于相邻网络控制器的自身收益值和业务简档来启动基于非零和游戏的网络控制平面优化操作,并且可以包括激活附加网络控制器之一,传送一个 或更多的由网络控制器管理的网络设备连接到相邻的贪婪网络控制器,停用网络控制器,以及将由相邻网络控制器管理的一个或多个附加网络设备的控制传送到贪婪网络控制器。

    Uplink transmission scheduling for wireless communication networks
    18.
    发明授权
    Uplink transmission scheduling for wireless communication networks 有权
    无线通信网络的上行链路传输调度

    公开(公告)号:US09374807B2

    公开(公告)日:2016-06-21

    申请号:US14204933

    申请日:2014-03-11

    CPC classification number: H04W72/0413 H04W72/042 H04W72/12 H04W76/00

    Abstract: A method for uplink scheduling over a communication channel in a communication network including at least one UE and an eNodeB, is described. The method comprises determining whether the UE is associated with at least one of Guaranteed Bit Rate (GBR) bearers and non-Guaranteed Bit Rate (non-GBR) bearers. Based on the determining, for each of the GBR-bearers and the non-GBR-bearers, computing a demand for resources for establishing an uplink communication, wherein the demand is computed based physical layer characteristics and transport layer characteristics associated with the communication channel. The demand computed is communicated as a request message to the eNodeB. In response to the request message, receiving an allocation of the resources for uplink scheduling from the eNodeB.

    Abstract translation: 描述了在包括至少一个UE和eNodeB的通信网络中的通信信道上的上行链路调度的方法。 该方法包括确定UE是否与保证比特率(GBR)承载和非保证比特率(非GBR)承载中的至少一个相关联。 基于对每个GBR承载和非GBR承载的确定,计算用于建立上行链路通信的资源需求,其中基于物理层特性和与通信信道相关联的传输层特性来计算需求。 所计算的需求作为请求消息传送到eNodeB。 响应于该请求消息,从eNodeB接收用于上行链路调度的资源的分配。

    SYSTEM AND METHOD FOR DESIGNING A NETWORK FOR ONE OR MORE ENTITIES IN AN ENTERPRISE
    19.
    发明申请
    SYSTEM AND METHOD FOR DESIGNING A NETWORK FOR ONE OR MORE ENTITIES IN AN ENTERPRISE 审中-公开
    为企业中的一个或多个实体设计网络的系统和方法

    公开(公告)号:US20150188774A1

    公开(公告)日:2015-07-02

    申请号:US14578371

    申请日:2014-12-20

    Abstract: System(s) and method(s) for designing a network of one or more entities in an enterprise is disclosed. A design type along with configurable design parameters is selected from a list of designs. Requirements associated with design of entities are collected from the users. The requirements and configurable design parameters are analyzed to obtain analysis results. Based on at least one of a layer-wise requirement and distribution or a zone-wise requirement and distribution, network devices and modules associated with the entities are determined. One or more designs are generated for the network of entities based on the layer-wise requirement and distribution or the zone-wise requirement and distribution of network devices and modules associated with the entities in the enterprise.

    Abstract translation: 公开了用于设计企业中的一个或多个实体的网络的系统和方法。 从设计列表中选择一种设计类型以及可配置的设计参数。 从用户处收集与设计实体相关的要求。 分析要求和可配置设计参数,以获得分析结果。 基于层次要求和分布或区域要求和分布中的至少一个,确定与实体相关联的网络设备和模块。 基于与企业中的实体相关联的网络设备和模块的分层要求和分布或分区要求和分布,为实体网络生成一个或多个设计。

    Systems and methods for estimating computation times a-priori in fog computing robotics

    公开(公告)号:US10824475B2

    公开(公告)日:2020-11-03

    申请号:US15894322

    申请日:2018-02-12

    Abstract: In order to make use of computational resources available at runtime through fog networked robotics paradigm, it is critical to estimate average performance capacities of deployment hardware that is generally heterogeneous. It is also not feasible to replicate runtime deployment framework, collected sensor data and realistic offloading conditions for robotic environments. In accordance with an embodiment of the present disclosure, computational algorithms are dynamically profiled on a development testbed, combined with benchmarking techniques to estimate compute times over the deployment hardware. Estimation in accordance with the present disclosure is based both on Gustafson's law as well as embedded processor benchmarks. Systems and methods of the present disclosure realistically capture parallel processing, cache capacities and differing processing times across hardware.

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