Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing clusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

Replicas are selected in a large distributed network, and the roles for these replicas are identified. In one example, a leader is selected from among candidate computing clusters. To make this selection, an activity monitor predicts or monitors the workload of one or more clients. Different activities of the workload are given corresponding weights. The delay in performing requested activities, modified by these weights is found, and the candidate leader with the lowest weighted delay is selected as the leader.

Methods, systems, and apparatus, including computer program products, for managing resources in virtualization systems, including multi-cloud systems. The use of supply chain economics alone and in combination with other techniques offers a unified platform to integrate, optimize or improve, and automate resource management in a virtualization system. These techniques may be used to monitor and control the delivery of service level agreements and software licenses. They may also be used to monitor and control contention of computing resources in a virtualization system, and to suspend or terminate computing resources.

Systems, methods and apparatus, including computer program products, are disclosed for regulating access of consumers (e.g., applications, containers, or VMs) to resources and services (e.g., storage). In one embodiment, this regulation occurs through the movement of consumers between different providers of a resource or service, such as a cloud service provider. Moving consumers includes, for example, determining the cost of moving the consumer from a first provider to a second provider. According to various embodiments, the cost of moving the consumer is compared to cost and performance criteria associated with moving the consumer from the first provider to the second provider. Cloud-based services may be priced as templates, reserved instances, or a combination.

Systems, methods and apparatus, including computer program products, are disclosed for regulating access of consumers (e.g., applications, containers, or VMs) to resources and services (e.g., storage). In one embodiment, this regulation occurs through the movement of consumers between different providers of a resource or service, such as a cloud service provider. Moving consumers includes, for example, determining the cost of moving the consumer from a first provider to a second provider. According to various embodiments, the cost of moving the consumer is compared to cost and performance criteria associated with moving the consumer from the first provider to the second provider. Cloud-based services may be priced as templates, reserved instances, or a combination.

A communication protocol includes one or more messages passed between Web routers over a reliable transmission protocol used for inter-Web router communication. These messages include information that allows the Web routers to dynamically update mappings of client addresses or address ranges to information object repository addresses based on client-to-server distance and server load. The mappings are preferably optimal mappings of the client addresses or address ranges to the information object repository addresses and the messages report updated distances from these information object repository addresses to the client addresses or address ranges. For example, the messages may report, for each updated distance, an associated client address or address range and/or an associated anchor address of a Web router co-located with an information object repository that is the subject of the message.

Load balancing and overload control techniques are disclosed for use in a SIP-based network or other type of network comprising a plurality of servers. In a load balancing technique, a first server receives feedback information from at least first and second downstream servers associated with respective first and second paths between the first server and a target server, the feedback information comprising congestion measures for the respective downstream servers. The first server dynamically adjusts a message routing process based on the received feedback information to compensate for imbalance among the congestion measures of the downstream servers. In an overload control technique, the first server utilizes feedback information received from at least one downstream server to generate a blocking message for delivery to a user agent.

A distributed computation offloading method based on computation-network collaboration in a stochastic network is provided. The distributed computation offloading method includes: building a device revenue maximization problem model and a MEC server revenue maximization problem model based on a local computing model and an edge cloud computing model; building composite sets of scenarios for dwell time and waiting latency based on a random movement of a user and burst computation demands; compensating for a game strategy by using a posteriori recourse action and building a game-based stochastic programming model between the device and the MEC server; transforming a multi-stage stochastic regularization problem for both the device and the MEC server into a DEP problem by constructing a scenario tree, and solving the DEP problem to obtain an optimal task strategy for the offloading from the MEC server and an optimal offering strategy of the MEC server to the device.

A distributed computation offloading method based on computation-network collaboration in a stochastic network is provided. The distributed computation offloading method includes: building a device revenue maximization problem model and a MEC server revenue maximization problem model based on a local computing model and an edge cloud computing model; building composite sets of scenarios for dwell time and waiting latency based on a random movement of a user and burst computation demands; compensating for a game strategy by using a posteriori recourse action and building a game-based stochastic programming model between the device and the MEC server; transforming a multi-stage stochastic regularization problem for both the device and the MEC server into a DEP problem by constructing a scenario tree, and solving the DEP problem to obtain an optimal task strategy for the offloading from the MEC server and an optimal offering strategy of the MEC server to the device.

A system designed for increasing network communication speed for users, while lowering network congestion for content owners and ISPs. The system employs network elements including an acceleration server, clients, agents, and peers, where communication requests generated by applications are intercepted by the client on the same machine. The IP address of the server in the communication request is transmitted to the acceleration server, which provides a list of agents to use for this IP address. The communication request is sent to the agents. One or more of the agents respond with a list of peers that have previously seen some or all of the content which is the response to this request (after checking whether this data is still valid). The client then downloads the data from these peers in parts and in parallel, thereby speeding up the Web transfer, releasing congestion from the Web by fetching the information from multiple sources, and relieving traffic from Web servers by offloading the data transfers from them to nearby peers.