Policy-based dynamic negotiations allow more flexible authorization in complex Grid environments, and relieve both users and administrators from up front negotiations and registrations. This paper describes how such negotiations overcome current Grid authorization limitations, and how policy-based

Abstract. Policy-based dynamic negotiations allow more flexible authorization in complex Grid environments, and relieve both users and administrators from up front negotiations and registrations. This paper describes how such negotiations overcome current Grid authorization limitations, and how

Abstract not found

In this paper, we discuss consensus problems for a network of dynamic agents with fixed and switching topologies. We analyze three cases: i) networks with switching topology and no time-delays, ii) networks with fixed topology and communication time-delays, and iii) max-consensus problems (or

in accordance with negotiated Service Level Agreements (SLAs). Our system is based on an economic approach to managing shared server resources, in which services "bid " for resources as a func-tion of delivered performance. The system continuously moni-tors load and plans resource allotments

Abstract We present Tor, a circuit-based low-latency anonymous communication service. This second-generation Onion Routing system addresses limitations in the original design by adding perfect forward secrecy, congestion control, directory servers, integrity checking, configurable exit policies

in industries along with our current work towards realizing market-oriented resource allocation of Clouds as realized in Aneka enterprise Cloud technology. Furthermore, we highlight the difference between High Performance Computing (HPC) workload and Internet-based services workload. We also describe a meta-negotiation

This paper examines a model of dynamic price adjustment based on the assumption that information disseminates slowly throughout the population. Compared with the commonly used sticky-price model, this sticky-information model displays three related properties that are more consistent with accepted

Modern distributed systems contain a large number of objects, and must be capable of evolving, without shutting down the complete system, to cater for changing requirements. There is a need for distributed, automated management agents whose behavior also has to dynamically change to reflect

policy. Large applications of reinforcement learning (RL) require the use of generalizing function approximators such neural networks, decision-trees, or instance-based methods. The dominant approach for the last decade has been the value-function approach, in which all function approximation effort goes