By Ioannis Karydis, Spyros Sioutas, Peter Triantafillou, Dimitrios Tsoumakos
This e-book constitutes the completely refereed post-conference court cases of the 1st overseas Workshop on Algorithmic elements of Cloud Computing, ALGOCLOUD 2015, held in Patras, Greece, in September 2015 together with ALGO 2015.
The thirteen revised complete papers offered including 2 educational papers have been conscientiously reviewed and chosen from 37 preliminary submissions. They disguise quite a lot of subject matters in major tracks: algorithmic elements of large-scale info shops, and software program instruments and disbursed architectures for cloud-based facts management.
Read Online or Download Algorithmic Aspects of Cloud Computing: First International Workshop, ALGOCLOUD 2015, Patras, Greece, September 14-15, 2015. Revised Selected Papers PDF
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Additional resources for Algorithmic Aspects of Cloud Computing: First International Workshop, ALGOCLOUD 2015, Patras, Greece, September 14-15, 2015. Revised Selected Papers
A conﬁguration Zi ∈ K such that j∈J Xj,i πj∗ > 1. t Uj ρj sin(φj ))2 ≤ (C − Uj ρj cos(φj ))2 + ( j∈J j∈J j∈J Uj ∈ N 41 Uj Cj )2 (9) j∈J (10) If the optimal solution of this subproblem has a negative value, then we have identiﬁed a conﬁguration to add to the RMP. On the other hand, if this problem has no solution with negative value, it means that all constraints in the dual of the master problem are satisﬁed with the current solution, which implies that this current solution of the RMP is actually optimal for the master problem.
In our scheme, we use the unary representation for the instruction and data addresses. This type of representation is inappropriate if the clients program is very large because of its redundant bits. In a secret shared form, we have to use n words to represent these n bit which will lead to many operations over Fp . As described in Sect. 2, we can use binary representation as a substitution. Compared with unary representation, binary representation can express exponentially more numbers with the same number of bits.
Tj,Nj , who share the same characteristics in terms of CPU demand. In turn, platform nodes are allowed to run several tasks, provided that at any time, their capacity is not exceeded. We assume that the set of tasks running on a node does not change over time, what is a realistic assumption for dominant Normal Production jobs, and we model the instantaneous demand at time t of task Tj,l , which does not depend on l, as Wj (t) = Cj + ρj sin 2π t + φj P where Cj denotes the average of CPU demand of Task Tj,l , ρj denotes the maximal amplitude of the variation of the demand, φj denotes its phase, and P denotes the common period for all jobs.