As cloud-based services become more numerous and dynamic, resource provisioning becomes more and more challenging. A QoS constrained resource allocation problem is considered in this paper, in which service demanders intend to solve sophisticated parallel computing problem by requesting the usage of resources across a cloud-based network, and a cost of each computational service depends on the amount of computation. Game theory is used to solve the problem of resource allocation. A practical approximated solution with the following two steps is proposed. First, each participant solves its optimal problem independently, without consideration of the multiplexing of resource assignments. A Binary Integer Programming method is proposed to solve the independent optimization. Second, an evolutionary mechanism is designed, which changes multiplexed strategies of the initial optimal solutions of different participants with minimizing their efficiency losses. The algorithms in the evolutionary mechanism take both optimization and fairness into account. It is demonstrated that Nash equilibrium always exists if the resource allocation game has feasible solutions.A game-theoretic method of fair resource allocation for cloud 253
In this paper, we propose an efficient Two-Phase geographic Greedy Forwarding (TPGF) routing algorithm for WMSNs. TPGF takes into account both the requirements of real time multimedia transmission and the realistic characteristics of WMSNs. It finds one shortest (near-shortest) path per execution and can be executed repeatedly to find more on-demand shortest (near-shortest) node-disjoint routing paths. TPGF supports three features: (1) hole-bypassing, (2) the shortest path transmission, and (3) multipath transmission, at the same time. TPGF is a pure geographic greedy forwarding routing algorithm, which does not include the face routing, e.g., right/left hand rules, and does not use planarization algorithms, e.g., GG or RNG. This point allows more links to be available for TPGF to explore more routing paths, and enables TPGF to be different from many existing geographic routing algorithms. Both theoretical analysis and simulation comparison in this paper indicate that TPGF is highly suitable for multimedia transmission in WMSNs.
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