Vizing's theorem asserts the existence of a (∆ + 1)-edge coloring for any graph G, where ∆ = ∆(G) denotes the maximum degree of G. Several polynomial time (∆ + 1)-edge coloring algorithms are known, and the state-...
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In this paper, we present Ray-shooting Quickhull, which is a simple, randomized, output-sensitive version of the Quickhull algorithm for constructing the convex hull of a set of n points in the plane. We show that the...
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We address the problem of learning-augmented online caching in the scenario when each request is accompanied by a prediction of the next occurrence of the requested page. We improve currently known bounds on the compe...
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We show that global exponential convergence for the augmented primal-dual gradient algorithms can be achieved for partially strongly convex functions. In particular, the objective function only needs to be strongly co...
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This paper investigates the job flow control problem for a network of buffers in a job-shop manufacturing system, where jobs are stored in buffers in order to supply a job demand to the job shop. For each buffer, a jo...
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ISBN:
(数字)9798350354409
ISBN:
(纸本)9798350354416
This paper investigates the job flow control problem for a network of buffers in a job-shop manufacturing system, where jobs are stored in buffers in order to supply a job demand to the job shop. For each buffer, a job flow control law is proposed, which requires that each buffer has access to the average total number of jobs stored in all buffers. It is shown that the control objectives of balancing the stock levels of the buffers and delivering the desired total job demand are both achieved if the proposed job flow control law is implemented for each buffer. Moreover, to relax the requirement of each buffer having access to the average total number of jobs among all buffers, two types of dynamic average consensus algorithms acting as distributed estimators are constructed for each buffer, each of which can provide an estimate of the average total number of stored jobs. By leveraging either type of distributed estimators, the proposed job flow control law is implemented in a distributed fashion. Simulation studies are provided to verify the effectiveness of the proposed control law.
The graph invariant EPT-sum has cropped up in several unrelated fields in later years: As an objective function for hierarchical clustering, as a more fine-grained version of the classical edge ranking problem, and, s...
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A natural variant of the classical online k-server problem is the weighted k-server problem, where the cost of moving a server is its weight times the distance through which it moves. Despite its apparent simplicity, ...
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A digital emergency rescue system is an effective means to achieve accurate rescue, minimize casualties and property losses. When large emergencies occur, medical institutions need to jointly participate in the emerge...
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A digital emergency rescue system is an effective means to achieve accurate rescue, minimize casualties and property losses. When large emergencies occur, medical institutions need to jointly participate in the emergency rescue coordination. But it is hard to share medical resource and injured information,which reduces the efficiency of recue and affects the treatment of injured ***, this paper proposes a rescue information sharing architecture based on blockchain and distributed storage, which shares data for many medical institutions. Moreover, we propose a new consensus algorithm ERBFT based on reputation models and Verifiable Random Function(VRF) to reduce communication complexity, and maintain the security of blockchain information sharing system.
In this paper, we establish the global convergence of the actor-critic algorithm with a significantly improved sample complexity of O(ǫ−3), advancing beyond the existing local convergence results. Previous works provi...
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Cloud computing has become an important technology for the processing of large computationally expensive programs and data from real-world. IT organizations are en-trusting the cloud vendors for the security of their ...
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ISBN:
(纸本)9781665429528
Cloud computing has become an important technology for the processing of large computationally expensive programs and data from real-world. IT organizations are en-trusting the cloud vendors for the security of their computational infrastructures including the data. Thus, there is a need for better provenance assurance for the data present in the cloud for better security and to establish trust between the cloud vendors and customers. Blockchain technology operates in a decentralized way for building trust between the entities in the system using immutable ledger. In this work, we propose the decentralized and trusted cloud data provenance mechanism using Ethereum blockchain platform, IPFS and scalable consensus mechanism. PoW is the consensus algorithm currently used in Ethereum Blockchain. PoW consensus mechanism needs lot of computational power for the processing of data in the Blockchain. Thus, we implement Proof of Stake (POS) consensus algorithm in Ethereum to improve the efficiency of the proposed data provenance mechanism. We demonstrate the performance of PoS-enabled provenance framework in a multi-node testbed. The results reveal that POS performs better than PoW for cloud data provenance.
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