This article proposes context-aware integrated scheme for mobile cloud service allocation, which can provide desirable cloud services to mobile cloud clients according to the mobile cloud contexts. The article makes use of various contexts information in the mobile cloud environment, such as the mobile cloud user's preferences, the battery levels and the parameters of cloud datacenter servers to improve the performance of mobile cloud. Interplay coupling of the mobile cloud users and the cloud datacenter supplier is used to achieve global optimization of the mobile cloud system. The article integrates energy-based service provisioning, cloud virtual resource allocation and dynamic load balancing. The integrated scheme can adapt to dynamic context information changes of the mobile cloud system such as device energy consumption, bandwidth and server load without compromising mobile application's quality of service. Based on the proposed model, the context-aware integrated mobile cloud service allocation algorithm is proposed, it uses the mobile cloud service profile to select the services among the available service suppliers to enhance the mobile cloud user's quality of experience. The efficiency of the context-aware integrated mobile cloud service allocation algorithm is tested by the experiments.

In the paper, we consider the hybrid cloud model used for cloud bursting, when the computational capacity of the private cloud provider is insufficient to deal with the peak number of customers’ applications, the private cloud will rely on the resources leased from public cloud providers for the execution of private cloud applications. The paper proposes the model and algorithm of hybrid cloud scheduling optimization for cloud bursting. Public cloud providers and private cloud users communicate by the hybrid cloud marketplace. The hybrid cloud scheduling optimization is conducted at different levels. According to the model formulation and mathematic solutions of hybrid cloud scheduling, hybrid cloud scheduling algorithms for cloud bursting are proposed, which includes the routines of public cloud optimization, private cloud application optimization and private cloud job optimization. In the simulations, compared with other related algorithm, our proposed hybrid cloud scheduling algorithms achieve the better performance.

Energy consumption is the main obstacle to the green cloud computing, particularly with the global climate warming and data center scale expanding. The green computing is gaining more and more attention because energy consumption increased rapidly. We propose a cloud computing management framework in order to ensure energy consumption of cloud computing to be a minimum. The framework uses virtual date center instead of virtual machine service mode of traditional service providers, and partition the virtual data center used in the management framework is based on the network communications of virtual machines. Then the virtual data center partition is placed into corresponding green data center in order to maximize revenue of providers and minimize the carbon emissions.

This article improves on the energy-consuming equation and nodes 'energy states in the old energy model of ad hoc networks, which concerned of the nodes' energy consumption in listening and idle period, and enhances the comprehensive of solving energy problem in this area. In the communication range of a node, where include the nodes could reach the nodes' signal, setting the highest energy-state node as an Agent will reduce the number of Agent in old save-energy model, and for improving the surviving time of the net, we added a new conception: edge-agent. The experiment indicates that the new energy-saving model cut down the idle nodes' energy consumption, declines the probability for nodes becoming agent-nodes, and increase the whole net's surviving time and the stability of communication because of using edge-agents.

Abstract This paper presents an optimization approach for decentralized Quality of Service (QoS)‐based scheduling based on utility and pricing in Grid computing. The paper assumes that the quality dimensions can be easily formulated as utility functions to express quality preferences for each task agent. The utility values are calculated by the user‐supplied utility function that can be formulated with the task parameters. The QoS constraint Grid resource scheduling problem is formulated into a utility optimization problem. The QoS‐based Grid resource scheduling optimization is decomposed into two subproblems by applying the Lagrangian method. In the Grid, a Grid task agent acts as a consumer paying for the Grid resource and the resource providers receive profits from task agents. A pricing‐based QoS scheduling algorithm is used to perform optimally decentralized QoS‐based resource scheduling. The experiments investigate the effect of the QoS metrics on the global utility and compare the performance of the proposed algorithm with other economical Grid resource scheduling algorithms. Copyright © 2006 John Wiley & Sons, Ltd.

This paper presents multiple QoS-bsed Grid resource scheduling models and solves the scheduling problems using optimization techniques. Each of grid task agent’s diverse requirements is modeled as a quality of service (QoS) dimension, associated with each QoS dimension is a utility function that defines the benefit that is perceived by a user with respect to QoS choices in that dimension. The paper proposes the idea of decomposing a global optimization problem in multiple QoS based resource scheduling into two subproblems: task agent optimization and resource agent optimization. It simplifies the problem and makes it mathematically tractable.The experiments show that optimal multiple QoS based resource scheduling involves less overhead and leads to more efficient resource allocation than no optimal resource allocation.

The paper presents a market oriented resource allocation strategy for grid resource. The proposed model uses the utility functions for calculating the utility of a resource allocation. This allows the integration of different optimization objectives into allocation process. This paper is target to solve above issues by using utility-based optimization scheme. We decompose the optimization problem into two levels of subproblems so that the computational complexity is reduced. Two market levels converge to its optimal points; a globally optimal point is achieved. Total user benefit of the computational grid is maximized when the equilibrium prices are obtained through the service market level optimization and resource market level optimization. The economic model is the basis of an iterative algorithm that, given a finite set of requests, is used to perform optimal resource allocation. The experiments show that scheduling based on pricing directed resource allocation involves less overhead and leads to more efficient resource allocation than conventional round robin scheduling.

In this paper, we apply market mechanism and agent to build grid resource management, where grid resource consumers and providers can buy and sell computing resource based on an underlying economic architecture. All market participants in the grid environment including computing resources and services can be represented as agents. Market participant is registered with a Grid Market Manager. A grid market participant can be a service agent that provides the actual grid service to the other market participants. Grid market participants communicate with each other by communication space that is an implementation of tuple space. In this paper, Grid agent model description is given. Then, the structure of Grid Market is described in detail. The design and implementation of agent oriented and market oriented grid resource management are presented in this paper.

A formal method for communication protocol specification is presented in which the best features of approaches using finite-state machines, communication sequential processes, and abstracting data types are combined. First, the formal techniques of the communication protocol are briefly described. Then, the hybrid method of protocol specification is presented. Finally, an example, i.e IEEE 802.3 MAC protocol for a LAN described by the proposed formal method is given.>