By David Abramson (auth.), Yang Xiang, Alfredo Cuzzocrea, Michael Hobbs, Wanlei Zhou (eds.)
This quantity set LNCS 7016 and LNCS 7017 constitutes the refereed lawsuits of the eleventh foreign convention on Algorithms and Architectures for Parallel Processing, ICA3PP 2011, held in Melbourne, Australia, in October 2011.
The first quantity offers 24 revised commonplace papers and 17 revised brief papers including the summary of the keynote lecture - all rigorously reviewed and chosen from eighty five preliminary submissions. The papers disguise the various dimensions of parallel algorithms and architectures, encompassing basic theoretical methods, sensible experimental effects, and advertisement parts and structures and concentrate on extensive components of parallel and dispensed computing, i.e., architectures, algorithms and networks, and structures and applications.
Read or Download Algorithms and Architectures for Parallel Processing: 11th International Conference, ICA3PP, Melbourne, Australia, October 24-26, 2011, Proceedings, Part I PDF
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Extra resources for Algorithms and Architectures for Parallel Processing: 11th International Conference, ICA3PP, Melbourne, Australia, October 24-26, 2011, Proceedings, Part I
In particular, we could have deﬁned Lu to consist of all locks that are held from the very beginning to the very end of u. However, this deﬁnition would yield many false positives, since excl1 (u) and excl2 (u) do not need to be protected by locks. 3 Calculating a Computational Unit’s Lockset In the previous section, we assumed that we are endowed with suﬃcient a priori knowledge to compute Lu . That is, knowledge about which memory accesses constitute shared(u). In dynamic program analysis, however, shared(u) can repeatedly change for various reasons: 1.
Now, since all exclusive parts solely operate on exclusive variables and do not interfere with parallel computations, the ﬁrst case is always equivalent to the left side while the second is always equivalent to the right side: excl1 (u1 ) excl1 (u2 ) shared(u2 ) shared(u1 ) excl2 (u1 ) excl1 (u1 ) shared(u1 ) excl2 (u1 ) excl1 (u2 ) excl2 (u2 ) shared(u2 ) excl2 (u2 ) Therefore, our initial assumption implies that all possible interleavings of u1 and u2 must be equivalent to either u2 → u1 or u1 → u2 and are thus serializable.
6 Conclusions In this paper, we propose a secure and energy-efficient data aggregation scheme with malicious aggregator identification in wireless sensor networks. The goal of our proposed scheme is to make sure that not only the BS does not accept forged aggregation results, but also the malicious aggregators tampering with the intermediate results can be identified. The adversarial aggregators, after detected, can be evicted from the network, hence reducing the damage of malicious aggregators.