Abstract:
A system and method are provided. The method includes a base station receiving a plurality of tasks from a plurality of user devices, each of the plurality of tasks involving a respective one of multiple sets of jobs. The method further includes a load balancer generating task allocations for the plurality of tasks, responsive to receiving the plurality of tasks from the base station. A unique task ID is generated for and assigned to each task, from which a task allocation is generated by the load balancer. The task allocations for the plurality of tasks are generated such that all the jobs received from a respective same one of the plurality of user devices are assigned to a same one of the worker entities in the set. The method also includes a set of worker entities performing the plurality of tasks in accordance with the task allocations.
Abstract:
A load balancing device and method are provided. The load balancing device includes a processor. The processor is configured to receive a plurality of tasks from a plurality of user devices, each of the plurality of tasks involving a respective one of multiple sets of sessions. The processor is further configured to generate a task ID for each of the plurality tasks using a randomization function, at least one task ID for at least one of the plurality of tasks changing over time responsive to one or more criterion. The processor is additionally configured to allocate the plurality of tasks amongst a set of worker entities such that all the sessions involved in the plurality of tasks received from a respective same one of the plurality of user devices is assigned to a same one of the worker entities in the set.
Abstract:
Computer-implemented methods and a system are provided for distributing tasks between a plurality of processes in a computer network. A method includes distributing, by a load balancer in the computer network, tasks between the plurality of processes. The method further includes maintaining, by the load balancer, a registry for each of the tasks. For a given task, the registry indicates which of the plurality of processes to which the given task is distributed based on a hash function. The method also includes forming, by the load balancer, a respective set of registries for each of the plurality of processes, based on a set of thresholds. The method additionally includes redefining, by the load balancer, the set of thresholds when one of the plurality of processes ceases or a new process, added to the plurality of processes, commences.
Abstract:
A system and method are provided. The method includes a base station receiving a plurality of tasks from a plurality of user devices, each of the plurality of tasks involving a respective one of multiple sets of jobs. The method further includes a load balancer generating task allocations for the plurality of tasks, responsive to receiving the plurality of tasks from the base station. A unique task ID is generated for and assigned to each task, from which a task allocation is generated by the load balancer. The task allocations for the plurality of tasks are generated such that all the jobs received from a respective same one of the plurality of user devices are assigned to a same one of the worker entities in the set. The method also includes a set of worker entities performing the plurality of tasks in accordance with the task allocations.
Abstract:
Systems and methods for adaptive video delivery over a network, including receiving a plurality of types of data flows from one or more network base stations; separating resource management of the plurality of types of data flows, wherein the data flows include one or more of adaptive video streaming flows, regular video traffic flows, and other traffic flows by resource slicing. A scheduling framework for adaptive video delivery is instantiated; available choices of video bit rates for all users is received as input to an allocator; optimal allocation of resources is computed for all users by determining and selecting an optimal bit rate for each user using the allocator; the optimal bit rate being sent to an enforcer; resources across flows are isolated using the enforcer; and the optimal bit rate for each user is enforced using per-flow traffic shapers to maximize resource utilization without reaching network capacity.
Abstract:
Systems and methods for standards compatible Mobile Edge Computing (MEC), including splitting Serving gateways (SGWs) and Packet Data Network gateways (PDN-GWs) to provision sufficient resources to deploy data-plane entity instances locally at a Radio Access Network (RAN) edge with one or more cloudlets. One or more local controller nodes is deployed in one or more operator clouds, a dedicated bearer is leveraged to route traffic from the one or more cloudlets through the split SGWs and PDN-GWs, and the dedicated bearer is configured with a traffic flow template (TFT) including an Internet Protocol (IP) address of the one or more cloudlets. Efficient access to one or more MEC applications at the RAN edge is provided to one or more user devices using the dedicated bearer.
Abstract:
Systems and methods for managing network resources, including managing a generated virtualized data plane network using a central controller. Virtual machine (VM) resources are assigned to two or more different network functions at a local data center. Traffic is dynamically optimized based on at least one of aggregate traffic demands and quality of service (QoS) goals, and resource allocations and inter-data center (DC) bandwidth resources are determined for VMs for a plurality of services. VMs for each middlebox function and a routing plane for each service are configured based on the determined resource allocation, and flows are routed based on the resource allocation and one or more configured network paths using an overlay-routing framework.
Abstract:
A system for traffic management between a WiFi network and an LTE network that includes a network interface assignment module for determining from an operator side of the WiFi network and the LTE network a set of WiFi Access Points (APs) and LTE base stations for each user that provides a least a highest quality of experience for each of the users using input strength for all users to potential WiFi access points and LTE base stations. The system may further include an interface switching service (ISS) module that includes a control logic and a network HTTP proxy for delivering network switching instructions to devices of users. The control logic receiving instructions from the NIA module and sending signal to the devices of the users to switch from WIFI and LTE networks through the LTE network based upon signal strength of the users.
Abstract:
Systems and methods for standards compatible Mobile Edge Computing (MEC), including splitting Serving gateways (SGWs) and Packet Data Network gateways (PDN-GWs) to provision sufficient resources to deploy data-plane entity instances locally at a Radio Access Network (RAN) edge with one or more cloudlets. One or more local controller nodes is deployed in one or more operator clouds, a dedicated bearer is leveraged to route traffic from the one or more cloudlets through the split SGWs and PDN-GWs, and the dedicated bearer is configured with a traffic flow template (TFT) including an Internet Protocol (IP) address of the one or more cloudlets. Efficient access to one or more MEC applications at the RAN edge is provided to one or more user devices using the dedicated bearer.
Abstract:
Methods and systems for load balancing on a control plane include calculating a hash of a unique identifier using a processor. The unique identifier is associated with a requesting device issuing a control request. The hash is mapped to a control plane processing device. The control request is forwarded to the control plane processing device.